channel:@VeevaSystems
24 videos
Season 1 Episode 1: Building the Right Data and Technology Foundation for Safety
Veeva Systems Inc
@VeevaSystems
Aug 29, 2025
This video, from the Veeva podcast "Safety Revolution," features David Kološić (Veeva) and Aniket Agarwal (Director for Data Operations and Analytics in Patient Safety at Sandoz), discussing the critical role of a robust data and technology foundation in pharmacovigilance (PV). The conversation centers on how Sandoz, as a large generic and biosimilar company, is navigating its growth while enhancing operational efficiency and speed in patient safety through strategic technology adoption. The discussion highlights Sandoz's deliberate shift from a historical landscape of "best-in-class" siloed systems to a platform-based approach. This transformation is driven by the need to overcome challenges associated with maintaining complex integrations between disparate systems and to ensure sustainable growth without a proportional increase in operational teams. Aniket explains that while other domains like clinical and regulatory have adopted platforms earlier, PV's slower pace is due to stringent regulations, frequent inspections, and the necessity of maintaining data compatibility for products with long market lifecycles (30-40 years). The core idea is to harmonize data and technology across global development (clinical, regulatory, safety) to establish a single source of truth, reducing manual reconciliation and improving data quality. A significant portion of the conversation is dedicated to the strategic application of automation and AI in PV. Aniket advocates for a "grounded approach," emphasizing that organizations should first identify specific problems and leverage simpler automation for quick efficiencies before deploying more complex AI solutions. He identifies high-impact AI use cases, particularly in the Individual Case Safety Report (ICSR) space, such as ingesting unstructured data (e.g., non-E2B reports which constitute a significant portion of incoming data) and generating human-readable narratives. Beyond ICSRs, AI is seen as transformative for moving from traditional to predictive signal detection, enhancing the quality of detected signals. The speakers also touch upon the balance between making reporting easy for healthcare professionals and patients (e.g., supporting regional languages) and the need for technology to structure this diverse intake downstream. The ultimate vision for 2030 is "no-touch" end-to-end case processing, with AI solving the remaining 40% of complex scenarios, contingent on evolving regulatory frameworks and building confidence in AI-generated data. Key Takeaways: * **Shift to Platform-Based PV:** Sandoz is moving from siloed, "best-in-class" systems to a unified platform approach to achieve sustainable operations, reduce integration complexities, and ensure systems evolve at a consistent pace. This is crucial for long-term efficiency and growth in pharmacovigilance. * **Drivers for PV Platform Adoption:** The need for harmonization of data and technology across global development (clinical, regulatory, safety) is a prime driver. A platform approach simplifies data flow, reduces maintenance, and supports cross-functional collaboration. * **Challenges in PV Technology Evolution:** PV has been slower to adopt platform solutions due to strict regulations, frequent inspections, the need for data compatibility for products with decades-long market presence, and the inherent risk associated with system changes. * **Importance of Data Standardization:** Standardizing data across regulatory, clinical, and safety domains is critical for establishing a "one source of truth," reducing manual reconciliation efforts, and improving the efficiency and quality of reporting (e.g., for PSURs/DSURs). * **Overcoming Data Silos and Mindset Shifts:** Achieving data standardization requires breaking down historical departmental silos and fostering a mindset shift towards common organizational goals, even if it involves an iterative process and governance to align definitions. * **Grounded Approach to Automation and AI:** Prioritize solving specific problems with simpler automation for quick wins and agility. Reserve AI for more complex, high-impact use cases where traditional automation is insufficient, adopting a phased approach if necessary. * **High-Impact AI Use Cases in PV:** Key areas where AI can drive significant value include ingesting and structuring unstructured incoming data (e.g., non-E2B reports), generating advanced, human-readable narratives for ICSRs, and transitioning from traditional to predictive signal detection. * **Balancing Reporting Ease and Data Structure:** To encourage higher reporting rates, it's essential to make the reporting process as simple as possible for users (e.g., supporting regional languages, flexible input formats). Technology, particularly AI, can then be leveraged downstream to decipher and structure this diverse information. * **Benefits of Cross-System Analytics:** A platform approach enables efficient, real-time cross-system analytics for periodic reports, reducing manual data extraction and reconciliation, and ensuring consistent information for regulatory submissions and inspections. * **Regulatory Harmonization and Frameworks:** Organizations like ICH, EMA, and FDA are actively working on frameworks and guidance to support the adoption of automation and AI in PV, indicating a growing openness and a shared goal with the industry towards safer and more efficient processes. * **Vision for "No-Touch" PV:** The aspirational goal for 2030 is end-to-end automated (no-touch) case processing, where systems can consistently handle a vast majority of scenarios, driving both quality and efficiency, and freeing up resources for more complex tasks. * **Building Regulator Confidence in AI:** As AI technologies advance, it's crucial to collaborate with regulators to understand their expectations, address concerns like hallucination, and ensure AI-generated data remains usable and fit for purpose within a compliant framework. **Tools/Resources Mentioned:** * **Veeva:** A leading platform provider in the pharmaceutical industry, hosting the podcast. * **E2B:** An international standard for the electronic transmission of individual case safety reports (ICSRs). * **ICH (International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use):** Mentioned as an organization striving for harmonization. * **EMA (European Medicines Agency):** Referenced for its efforts in standardization (e.g., through UdraVigilance) and guidance on AI. * **FDA (U.S. Food and Drug Administration):** Referenced for its guidance on AI. * **CIOMS (Council for International Organizations of Medical Sciences):** Mentioned as producing material on AI. **Key Concepts:** * **Pharmacovigilance (PV):** The science and activities relating to the detection, assessment, understanding and prevention of adverse effects or any other drug-related problem. * **Individual Case Safety Report (ICSR):** A report detailing a single suspected adverse drug reaction in a patient. * **Periodic Safety Update Report (PSUR):** A periodic report providing an update on the worldwide safety experience of a medicinal product. * **Development Safety Update Report (DSUR):** A periodic report providing an update on the worldwide safety experience of an investigational medicinal product. * **Signal Detection:** The process of identifying and assessing potential safety signals from various data sources. * **Generics and Biosimilars:** Types of pharmaceutical products Sandoz specializes in. * **GxP (Good x Practice):** A collection of quality guidelines and regulations created to ensure that products are safe and meet their intended use. * **21 CFR Part 11:** Regulations issued by the FDA that set forth the criteria under which electronic records and electronic signatures are considered trustworthy, reliable, and equivalent to paper records.
Season 1 Episode 5: Turning Content into Memorable Customer Experiences
Veeva Systems Inc
@VeevaSystems
Jun 6, 2025
This video, featuring marketing leaders from Genentech and hosted by Veeva, explores the critical transformation from content creation to delivering memorable customer experiences within the life sciences industry. The discussion highlights the strategic shift required for pharmaceutical companies to move beyond product-centric marketing to a more holistic, personalized, and data-driven approach. Key themes include the necessity of organizational change, the pivotal role of real-time data in shaping and optimizing customer interactions, and the imperative to foster a culture of continuous experimentation and rapid content iteration to meet evolving customer demands and competitive pressures. Key Takeaways: * **Evolution of Pharma Marketing:** The industry is moving from a product-first, brand-oriented approach to a holistic, experience-driven marketing discipline that unifies content and customer experience, driven by increasing competition and customer demands for better healthcare experiences. * **Content vs. Experience:** Content is necessary but not sufficient; true customer experience is built on deep customer understanding and personalization, akin to transforming a "house" (content) into a "home" (experience). This requires breaking down silos between content creation, experience delivery, and measurement. * **Organizational Transformation Drivers:** Successful change requires full senior leadership commitment, a clear vision, addressing discomfort with the status quo, and crucially, aligning incentive structures to support new ways of working and moving away from outdated processes. Leaders must be prepared to "blow up the old bridge" to fully embrace new methodologies. * **Data as the Core Enabler:** Real-time data from every customer engagement (or lack thereof) is fundamental for crafting effective messages, optimizing content, and informing strategic adjustments. This necessitates integrated MarTech platforms and a robust content supply chain to provide a holistic view of performance. * **Embrace Experimentation and Speed:** The industry must stop "planning to perfection" and instead embrace continuous experimentation, rapid iteration, and a willingness to put out "90% right" content, measuring and optimizing constantly to adapt to fast-changing technology and consumer behavior. * **Redefining Customer Engagement:** The traditional view of the sales representative as the sole "quarterback" of the customer relationship is evolving. A multi-channel approach is needed, recognizing a diverse web of decision-makers (including patients and caregivers) beyond just the prescriber. * **Future of Content:** The goal is to create significantly more engaging, personalized content (e.g., "20x the content") at scale, faster, and more affordably, with integrated, real-time measurement feeding back into content generation.
Season 1 Episode 6: Improving the Customer Experience through Medical-Commercial Collaboration
Veeva Systems Inc
@VeevaSystems
Oct 3, 2025
This video explores the critical importance of medical-commercial collaboration within the pharmaceutical industry to enhance the customer (HCP) experience and drive better patient outcomes. Industry leaders from UCB and Takeda discuss the challenges of traditional silos, the strategic imperative for integrated efforts in product launches, and the pivotal role of technology, data, and AI in fostering a more unified and effective future for healthcare engagement. Key Takeaways: * **Essential Cross-Functional Collaboration:** Effective medical-commercial-clinical collaboration is paramount for successful product launches, optimizing HCP engagement, and ultimately improving patient outcomes. A lack of coordination leads to inefficiencies, missed opportunities, and confusion among healthcare providers. * **Technology as an Integration Enabler:** Platforms like Veeva CRM, Veeva Vault, Veeva Link Key People, and Veeva Link Workflow are crucial for creating transparency around HCP engagements, centralizing approved medical content, and facilitating coordinated cross-functional planning. * **AI Augments, Data Foundations Enable:** While AI, particularly Generative AI, is recognized as a powerful tool to augment medical affairs by optimizing tasks and enhancing insight detection, a robust data foundation (including data governance, standards, and management) is critical for its successful implementation and for deriving actionable insights. * **Change Management is Key to Adoption:** Successful implementation of integrated processes and technologies requires strong senior leadership buy-in, early and continuous engagement with all stakeholders (including compliance and legal), and a phased approach to manage change fatigue and ensure end-user adoption. * **Measuring Impact through Data:** Increased adoption of integrated systems provides the necessary data to measure operational effectiveness, engagement quality, and insights gathering, which are foundational steps towards ultimately assessing and improving medical affairs' impact on patient outcomes and clinical practice.
Season 3 Episode 1: Against All Odds: Finding a Treatment for SPG50
Veeva Systems Inc
@VeevaSystems
Sep 25, 2024
This video features a deeply personal account from two patient advocates, Terry Pirovolakis and Samuela Bellini, who embarked on a relentless journey to find a gene therapy for children diagnosed with SPG50, an ultrarare neurodegenerative disease. Terry recounts his son Michael's diagnosis and his subsequent immersion into the world of genetics and gene therapy, leading him to collaborate with leading scientists and establish Aleda Therapeutics. Samuela shares her efforts to bring this therapy to children in Italy, highlighting the regulatory complexities and the need for local advocacy. Both speakers emphasize the critical need for urgency in the pharmaceutical industry, particularly for rare diseases, and challenge existing barriers to accelerate treatment development and access. The discussion underscores the profound impact of gene therapy on treated children, the vital role of community support and funding, and the ambitious vision to expand these efforts to eradicate numerous other rare conditions. Key Takeaways: * **Patient-Driven Innovation & Urgency:** The narrative powerfully illustrates how patient advocacy can catalyze the development of life-saving gene therapies for ultra-rare diseases, emphasizing the critical need for urgency and challenging traditional pharmaceutical development timelines. * **Navigating Complex Regulatory Landscapes:** The speakers highlight significant hurdles in securing regulatory approvals (e.g., Health Canada, FDA, Italian regulatory bodies), underscoring the call for streamlined processes to accelerate access to treatments. * **Specialized Biotech & Funding for Rare Diseases:** The formation of mission-driven biotech firms like Aleda Therapeutics demonstrates a model for addressing diseases deemed "non-commercially viable," emphasizing the constant need for funding and strategic partnerships to scale these efforts. * **Community & Cross-Functional Collaboration:** The video stresses the indispensable role of a supportive community, dedicated individuals across the supply chain (from scientists to logistics personnel), and collaborative efforts in overcoming obstacles in drug development and delivery. * **Impact and Potential of Gene Therapy:** Tangible positive outcomes, such as improved cognition and motor skills, are observed in children treated with gene therapy, showcasing its potential to not only halt disease progression but also to offer significant quality of life improvements, especially with early intervention. * **Enterprise Software & Data Management in R&D:** Terry's professional background in "Salesforce integration" and "CMS which is very similar to an EDC" implicitly highlights the foundational role of robust enterprise software and data management systems in supporting complex clinical and commercial operations within the life sciences, even in patient-driven initiatives.
Why a Site-centric Approach is Key to Your Remote Monitoring Strategy
Veeva Systems Inc
@VeevaSystems
Apr 14, 2021
This video provides an in-depth exploration of the critical importance of adopting a site-centric approach to remote monitoring strategies in clinical trials. The speaker, Bree Burks from Veeva Systems, draws on her extensive background working within research sites, particularly academic medical centers, to emphasize shifting the perspective from sponsors and Contract Research Organizations (CROs) to the operational realities and challenges faced by clinical research sites. The core message revolves around the need to understand site values, operational models, and technological burdens to build effective, sustainable remote monitoring solutions that truly empower sites. Burks outlines a comprehensive framework for a site-centric approach, beginning with fundamental values such as acknowledging sites' continued critical role in decentralized and virtual trials due due to their unique patient relationships and specialized expertise. She challenges the audience to think beyond individual trial needs, urging them to consider a site's broader operational model across multiple studies and sponsors. A novel idea proposed is for sites to operate on their own technology rather than solely relying on sponsor-provided systems, fostering greater control and standardization. The presentation highlights unique challenges faced by diverse site types—including private, complex network, outpatient clinic-connected, and hospital-affiliated sites—and the pervasive issue of limited, fixed resources, especially concerning staff and budget for technology adoption and digitization efforts. A significant portion of the discussion focuses on the "double-edged sword" of technology for sites. While past surveys (e.g., 2019) indicated site frustration with "too many systems, too many logins, too much training, and data duplication," more recent data (from the Society for Clinical Research Sites) shows a strong desire for specific technologies like e-consent, telemedicine, and e-source to enable virtual operations and reduce administrative burden. The speaker traces the evolution of site technology from early Electronic Data Capture (EDC) systems to internal business management tools, illustrating how the proliferation of disconnected systems has created significant tension. This historical context leads to the vision of a "connected and unified clinical trial ecosystem," where technology solutions are standardized, flexible, affordable, patient-centric, and supported by dedicated technology partners. The video further delves into the practical system components of remote monitoring, stressing the need for purpose-built solutions over ad-hoc tools. Key considerations include affordability, robust security (managing logins, audit trails, handling unredacted Protected Health Information, or PHI), and the ability to provide certified copies of source documents to avoid redundant monitoring. Beyond mere access, a truly site-centric system should facilitate collaborative review, track document stages, prevent re-monitoring, and integrate seamlessly into a site's workflow. The speaker also underscores the importance of change management, including guidance on global regulations, onboarding, training, templates, and Standard Operating Procedures (SOPs), alongside community and networking support from technology providers. The future vision emphasizes unified internal systems (e.g., Clinical Trial Management Systems or CTMS, e-consent, clinical systems) and connected external systems through digital exchange mechanisms, moving towards real-time collaboration across all stakeholders, with technology partners bearing the burden of efficient data and document exchange. Key Takeaways: * **Embrace a Site-Centric Mindset:** Successful remote monitoring strategies must originate from understanding and addressing the unique perspectives, challenges, and operational realities of clinical research sites, rather than solely from sponsor/CRO needs. This foundational shift is crucial for developing effective and sustainable solutions. * **Sites Remain Critical in Decentralized Trials:** Despite the rise of virtual and hybrid trials, sites provide invaluable expertise and are a critical link to patients, offering unique relationships and skills. Their continued integration and empowerment with appropriate technology are essential for the future of clinical research. * **Acknowledge Sites' Multi-Trial Operations:** Clinical research sites manage numerous trials concurrently, often for different sponsors and CROs. Solutions should aim for standardization and flexibility across studies, rather than imposing unique, disparate processes for each trial, to significantly reduce operational burden and improve efficiency. * **Consider Site-Owned Technology:** Exploring models where sites own and control their remote monitoring technology can allow for greater standardization across their entire portfolio of studies and reduce reliance on a multitude of disparate sponsor-provided systems. This approach, however, requires careful consideration of affordability and the maintenance burden on sites. * **Address the "Technology Overload" Paradox:** While sites express frustration with "too many systems" (leading to excessive logins, training, and data duplication), they simultaneously demand specific technologies (e-consent, telemedicine, e-source) that enable virtual operations and reduce administrative tasks. Solutions must strike a delicate balance, providing needed functionality without adding to the existing system sprawl. * **Prioritize Unified and Connected Ecosystems:** The future of clinical trials lies in a unified and connected ecosystem where site-level systems (e.g., CTMS, e-consent, clinical systems) are integrated internally and seamlessly connected with sponsor/CRO systems through digital exchange mechanisms. This minimizes manual data transfer, reduces duplication, and enables real-time collaboration. * **Purpose-Built Systems are Superior:** Ad-hoc tools are insufficient for robust remote monitoring. Purpose-built systems offer critical features like auto-notifications, dashboards for workflow prioritization, secure audit trails, and the ability to track collaborative review processes, which prevent re-monitoring and significantly improve overall efficiency and data integrity. * **Ensure Security and Regulatory Compliance:** Remote monitoring solutions must prioritize robust security, especially when handling unredacted Protected Health Information (PHI). They must also support the provision of certified copies of source documents to satisfy regulatory requirements and avoid the need for redundant on-site monitoring, streamlining the inspection process. * **Beyond Technology: Focus on Change Management:** Implementing remote monitoring solutions at sites involves significant change management. Technology providers must offer comprehensive support, including guidance on global regulations, thorough onboarding, effective training, standardized templates, and clear Standard Operating Procedures (SOPs), alongside fostering community and networking opportunities. * **Affordability and Resource Burden are Key:** When considering site-owned technology or new systems, the cost and resource burden (e.g., staff time, validation efforts) on sites must be a primary consideration. Solutions should be designed to be affordable and minimize ongoing maintenance for sites, which often operate with limited fixed resources. * **Prioritize Patient Centricity:** Technology solutions, such as e-consent, must be designed to ensure a positive and intuitive patient experience, as sites are directly responsible for managing these patient relationships. A poor patient experience directly impacts site workload, patient retention, and overall satisfaction. * **Seek Strategic Technology Partners:** Sites need technology partners who offer a clear long-term vision, provide opportunities for input on product roadmaps, and are actively engaged in professional organizations that support sites. This ensures that the solutions evolve in alignment with their strategic needs and industry best practices. Key Concepts: * **Site-Centricity:** An approach to clinical trial design and technology implementation that prioritizes the operational needs, challenges, and perspectives of clinical research sites. * **Remote Monitoring:** The process of reviewing clinical trial data and documents from a remote location, reducing the need for on-site visits by monitors. * **Unified Clinical Trial Ecosystem:** A future state where all systems used by sites, sponsors, and CROs are seamlessly integrated and connected, allowing for efficient, real-time data and document exchange across the entire trial lifecycle. * **Digital Exchange Mechanism:** A technological framework or platform that facilitates the secure and efficient sharing of information and documents between different stakeholders (e.g., sites, sponsors, CROs) without manual intervention. * **Certified Copies:** Electronically generated copies of original source documents that are verified as true and accurate representations of the original, meeting regulatory requirements for inspectable records. * **E-consent:** Electronic informed consent, allowing patients to review and sign consent forms digitally. * **E-source:** Electronic source data, where patient data is captured directly into an electronic system at the source, eliminating paper records. * **CTMS (Clinical Trial Management System):** A software system used by clinical research organizations and sponsors to manage and track various aspects of clinical trials, from planning and startup to closeout. Tools/Resources Mentioned: * **Veeva Systems:** The speaker's employer, a technology company providing solutions for the life sciences industry. * **EDCs (Electronic Data Capture systems):** Early technology introduced to sites for data collection. * **Society for Clinical Research Sites (SCRS):** An organization that conducted a survey mentioned in the presentation regarding sites' technology needs and desires.
Season 3 Episode 2: Special Episode: Boehringer Ingelheim’s One Medicine Platform
Veeva Systems Inc
@VeevaSystems
Oct 7, 2024
This video provides an in-depth exploration of Boehringer Ingelheim's "One Medicine Platform" project, a transformative initiative aimed at reimagining drug development through advanced data utilization and a connected technology ecosystem. Hosted by Nicole Raleigh, the discussion features Andrea Kloeble and Daniel Schwenk, Product Owners in Clinical Data Engineering at Boehringer Ingelheim, alongside Richard Young, Veeva's VP of Clinical Data Strategy. The conversation takes place on-site at Boehringer Ingelheim's Human Pharmacology Center in Biberach, Germany, highlighting the real-world context of Phase I clinical trials. The central theme revolves around Boehringer Ingelheim's "Medicine Excellence initiative," which seeks to unify development processes and data within a centralized platform to address unmet medical needs and accelerate the innovation of new medicines. The speakers emphasize the exponential growth in study data volumes and sources, necessitating a robust and integrated technology landscape. This transformation focuses on reducing complexity, fostering an innovative digital culture, and moving away from the historical reliance on paper-based data capture towards fully digital and integrated solutions, including the consideration of direct integration of electronic health record (EHR) data into clinical trials. A significant milestone discussed is the go-live of the Veeva Vault Clinical Data Management Suite (CDMS) at Boehringer Ingelheim, marking a pivotal step in their digital journey. This implementation is part of a broader, holistic ecosystem that includes Veeva Clinical for operations, Veeva Quality, and Veeva RIM (Regulatory Information Management), ensuring data is automatically available across different vaults for various functions like patient recruitment, data visualization, and dashboards. The collaboration with Veeva is highlighted as a true partnership, with a shared commitment to leveraging technology to free up scientists for core research and accelerate the delivery of breakthrough therapies, particularly in challenging areas like personalized medicine, cell and gene therapy, and rare diseases, while maintaining regulatory compliance. Key Takeaways: * **Holistic Digital Transformation in Pharma:** Boehringer Ingelheim's "One Medicine Platform" is a comprehensive initiative to unify development processes and data across a connected technology ecosystem, moving beyond incremental changes to achieve full digital transformation in drug development. * **Connected Technology Ecosystem:** The project leverages the Veeva Development Cloud, integrating Veeva Vault CDMS, Clinical, Quality, and RIM to create a seamless flow of data and processes, reducing redundancies and handovers. * **Data-Driven Decision Making:** The core objective is to accelerate access to data for faster, more informed decisions, ultimately bringing new medications to patients more quickly, especially for diseases with unmet needs. * **Transition from Paper to Integrated Digital Data:** The industry has moved from 90% paper-based data capture to less than 10%, with a strong push towards integrating diverse data sources, including electronic health records (EHRs) directly into clinical trials. * **Multi-Dimensional Clinical Trials:** Modern trials are no longer "one-dimensional" (does it hurt, does it work) but involve multiple questions and data points, including real-world data from wearables and everyday actions, creating pressure for more complex data management. * **Addressing Data Complexity and Risk:** The influx of more data creates potential for "noise" and greater risk, necessitating robust systems to pull data into an intelligible format for good decision-making. * **FAIR Data Principles:** The future of clinical data management will increasingly focus on making data Findable, Accessible, Interoperable, and Reusable (FAIR) to maximize its value and support advanced analytics. * **Strategic Partnership for Innovation:** The collaboration between Boehringer Ingelheim and Veeva exemplifies a strong partnership where technology providers deliver tools that enable pharmaceutical companies to focus on scientific innovation and accelerate their drug pipeline. * **Focus on Patient, Site, and Sponsor Experience:** The initiative prioritizes improving the experience for patients (faster access to medication), sites (easier processes for investigators), and sponsors (efficient data access for confident decisions). * **Regulator Engagement:** Regulatory bodies play a crucial role, and the complexity of varying country-specific regulations adds another layer to data management challenges, requiring flexible and compliant solutions. * **Beyond Traditional EDC:** While Electronic Data Capture (EDC) systems are fundamental, the future involves integrating data from a rapidly increasing variety of sources and data types, such as biomarkers, and utilizing cutting-edge tools for analysis. * **Role of Data Curators:** With the growing volume and variety of data, there will be an increasing need for "data curators" to extract maximum value and ensure data quality and usability. * **Future Expansion with CTMS:** The next major step for Boehringer Ingelheim is the release of Veeva CTMS (Clinical Trial Management System) for clinical operations, which will further expand the ecosystem to manage protocol deviations, payments, and other operational aspects. **Tools/Resources Mentioned:** * **Veeva Development Cloud:** A comprehensive suite of cloud software for the life sciences industry. * **Veeva Vault Clinical Data Management Suite (CDMS):** A specific component for managing clinical trial data. * **Veeva Vault Clinical:** For clinical operations. * **Veeva Vault Quality:** For quality management. * **Veeva Vault RIM (Regulatory Information Management):** For managing regulatory submissions and information. * **Veeva Vault CTMS (Clinical Trial Management System):** For managing clinical trial operations. * **EDC Systems (Electronic Data Capture):** General term for systems used to collect clinical trial data. * **Electronic Healthcare Records (EHRs):** Digital versions of patients' paper charts. * **Fitbits/Wearables:** Mentioned as sources of real-world data. **Key Concepts:** * **One Medicine Platform:** Boehringer Ingelheim's initiative to create a unified digital platform for drug development, integrating processes and data. * **Medicine Excellence Initiative:** Boehringer Ingelheim's internal drive to optimize and innovate its medical development processes. * **Remote Data Capture:** The process of collecting clinical trial data electronically from sites. * **Data-Enabled Clinical Trials:** Trials that leverage digital data collection, integration, and analysis to improve efficiency and outcomes. * **Rubik's Cube Analogy:** Used to describe the multi-faceted challenge of clinical trial optimization, considering patients, sites, data managers, clinical teams, and regulators as different sides of a complex problem that requires constant movement and perspective shifts to solve. * **Single-Use Data:** The outdated concept of data being collected for one specific purpose and not being easily reusable or interoperable, which the industry is moving away from. * **FAIR Data (Findable, Accessible, Interoperable, Reusable):** A set of guiding principles to enhance the reusability of scientific data. **Examples/Case Studies:** * **Boehringer Ingelheim's Digital Transformation:** The entire discussion serves as a case study of a major biopharmaceutical company undertaking a significant digital transformation, moving from paper to remote data capture, and now implementing a holistic Veeva ecosystem. * **Go-live of Veeva Vault CDMS:** The specific example of Boehringer Ingelheim releasing its first clinical study to production using Veeva Vault CDMS highlights a concrete milestone in their platform journey. * **COVID-19 Pandemic Impact:** The pandemic is cited as a catalyst that brought clinical trials into public gaze, demonstrating the industry's ability to accelerate trials (8-10 years to 8-10 months) and the importance of common goals and patient volunteering.
Season 2 Episode 5: SPECIAL EPISODE The State of Clinical Trials in the U.K. and Europe
Veeva Systems Inc
@VeevaSystems
Dec 13, 2023
This video provides an in-depth exploration of the state of clinical trials in the UK and Europe, featuring Nicole Raleigh of Pharmaphorum interviewing Chris Moore, President of Europe at Veeva. The discussion begins by establishing the global landscape of clinical trials, highlighting key trends such as a growing focus on specialty diseases, the critical need for efficient patient identification and diversity, and the industry's demand for predictability in regulatory conditions. Moore emphasizes that these macro factors significantly influence geographical decisions for trial execution. The conversation then tunnels into the specifics of UK clinical trials, addressing a concerning 41% decline in new trial initiations between 2017 and 2021. Moore attributes this decline to the uncertainty caused by Brexit, the overstretched NHS, and a lack of supporting capabilities like scanning infrastructure. He notes that while COVID-19 initially impacted trials globally, it also showcased the UK's strength in executing large-scale studies when its structural benefits, such as a unified healthcare system, were leveraged effectively. The discussion transitions to recent positive developments, including the UK government's £650 million investment in life sciences research and the Lord O’Shaughnessy report, which advocates for regulatory reform, speedier study setup, and improved data access. Moore views these as positive first steps, signaling a renewed political consensus on the importance of the life sciences sector. Shifting focus to Europe, the interview examines the European Commission's proposal for a single market for medicines and the impact of the European Clinical Trials Regulation (EU CTR). Moore acknowledges the positive intent behind harmonizing clinical studies across the EU to rival North America's population access. However, he points out "teething problems," such as discrepancies in national interpretations of rules (e.g., Germany's privacy laws) and the largely manual upload process for approvals. These issues undermine predictability and efficiency, particularly for rare disease treatments and cell and gene therapies, where accessing small, dispersed patient populations is crucial. Finally, the conversation delves into the pervasive topic of Artificial Intelligence (AI). Moore, drawing on his past experience with IBM Watson, expresses confidence in AI's coming of age. He outlines Veeva's role in providing better data to feed AI and highlights tangible applications within life sciences, such as automated document categorization, CRM chatbots for sales reps, and enhanced safety signal detection. Crucially, Moore stresses the unique challenge in a regulated industry: the imperative for confidence in AI-generated data and answers, distinguishing it from general AI applications where "convincing but wrong" is unacceptable. He suggests a future where AI operates on both a mass data corpus and "within the firewall" data, where quality and harmonization are paramount for reliable decision-making. Key Takeaways: * **Global Clinical Trial Trends:** The industry is increasingly focused on specialty diseases, necessitating efficient and diverse patient recruitment, predictability in regulatory environments, and high-quality data. * **UK Clinical Trial Decline & Recovery:** The UK experienced a 41% decline in new trial initiations (2017-2021) due to Brexit uncertainty, NHS strain, and infrastructure deficits. However, recent government investment (£650M) and policy shifts (Lord O’Shaughnessy report) indicate a positive reversal, with a renewed focus on valuing the life sciences industry. * **Impact of Policy Reform:** The UK's new national approach to costing and contracting for commercial research has already reduced study setup times by 45% (from 213 to 118 days), demonstrating the immediate positive impact of streamlined processes. * **UK's Structural Advantages:** The UK possesses a unified healthcare system and a traditionally positive attitude towards digital solutions, which, if leveraged, could restore its leadership position in digital access, approvals, and overall speed of trial delivery. * **European Harmonization Challenges:** While the EU CTR and the push for a single market for medicines are positive steps towards harmonizing clinical trials, national discrepancies in rule interpretation and manual approval processes hinder predictability and efficiency, especially for rare disease treatments. * **Veeva's Role in Friction Reduction:** Veeva aims to reduce friction in clinical trials by providing a unified platform connecting pharmaceutical companies, CROs, sites, and patients. They offer free life sciences quality systems to sites and patient-facing tools to reduce site visits and ensure consistent data flow. * **Efficiency and Speed Goals:** Through these integrated solutions, Veeva projects a potential for 25% cheaper and 25% faster clinical studies across the industry, alongside improved patient enrollment and engagement. * **AI's Emergence in Life Sciences:** AI is "coming of age" with significant potential for applications like automated document categorization, intelligent CRM chatbots for healthcare professionals, and enhanced safety signal detection. * **Data Confidence is Paramount for Regulated AI:** Unlike general AI, life sciences cannot tolerate "convincing but wrong" answers. There is a critical need for high confidence in the data feeding AI and the outputs it generates, necessitating robust data quality and governance. * **"Within the Firewall" AI:** A distinction is made between AI applied to general public information and AI operating "within the firewall" of a company, where data quality is assured, enabling more reliable decision-making for specific business processes. * **Importance of Data Harmonization for AI:** To fully leverage AI, data must be in a harmonized form, accounting for subtleties and context (e.g., conditions under which medical measurements are taken) to ensure accurate and actionable insights. **Tools/Resources Mentioned:** * Veeva platform * ChatGPT * IBM Watson **Key Concepts:** * **EU CTR (European Clinical Trials Regulation):** A regulation aimed at harmonizing the assessment and supervision processes for clinical trials throughout the European Union. * **Lord O’Shaughnessy Report:** An independent review advising on making the UK an attractive destination for industry clinical trials, recommending regulatory reform, speedier study setup, and improved data access. * **Clinical Trial Acceleration Networks (CTAENs):** Proposed networks to be funded and equipped to deliver "best in world" clinical trial services in the UK. * **Single Contracting:** A streamlined approach to contracting for clinical studies, replacing the fragmented system where each care commissioning group required its own contracts. * **Within-the-firewall AI:** AI applications that operate on a company's internal, curated, and high-quality data, distinct from AI trained on a general corpus of information, to ensure greater confidence and reliability in regulated environments.
Season 3 Episode 4: AI and Clinical Transformation: High-Value or Hype?
Veeva Systems Inc
@VeevaSystems
Oct 11, 2024
This video provides an in-depth exploration of the role of AI in clinical transformation, featuring Ibrahim Kamstrup-Akkaoui, Vice President for Clinical Data Operations and Insights at Novo Nordisk. The discussion, hosted by Veeva Systems, highlights the accelerating pace of innovation in clinical development and the challenges posed by the exponential growth of data. Kamstrup-Akkaoui shares Novo Nordisk's journey from a historically conservative industry to one embracing digital transformation, emphasizing the critical need for sustainable scaling through technology, particularly AI. The conversation delves into the evolution of technology adoption in pharmaceuticals, contrasting the slow uptake of early systems like EDC with the current imperative for advanced solutions. A central theme is the shift towards a user-centric approach, acknowledging the burden placed on clinical sites and patients by disparate systems. Kamstrup-Akkaoui advocates for a platform strategy to streamline operations and improve data quality, moving away from the current model where sites may interact with dozens of different systems across multiple sponsors. This foundational change is seen as essential for managing the sheer volume of data, which has grown from millions to billions of data points annually. Kamstrup-Akkaoui distinguishes between automation and AI, asserting that while automation has its place, AI is indispensable for breaking the traditional proportionality between data volume and the human resources required to manage it. He champions a "think big, start small" philosophy for AI implementation, encouraging experimentation and creative application of technology to solve significant industry challenges. Concrete examples from Novo Nordisk illustrate the practical value of AI, including the generation of meaningful test data for system validation and the development of a "Study Builder" application that digitizes protocol development, standardizes processes, and automates system setup, ultimately aiming for submission-ready data sets even before a study begins. The discussion concludes with a forward-looking vision for a fully automated clinical trial setup, driven by AI and a collaborative industry approach. Key Takeaways: * **Pharma's Digital Catch-Up:** The pharmaceutical industry, historically conservative, is now undergoing a rapid digital transformation to catch up with other sectors. Initial technology adoption, like EDC, was slow due to lack of knowledge and a conservative mindset, but current insights into processes and technology applications are game-changers. * **Exponential Data Growth:** Clinical development faces an overwhelming increase in data, with Novo Nordisk experiencing a jump from 5-7 million data points annually to approximately 2 billion. This exponential growth necessitates a fundamental shift in how data is managed and leveraged. * **AI for Sustainable Scaling:** To manage this data explosion sustainably, AI is crucial for breaking the traditional proportionality between the volume of data and the number of people required to process it. Automation alone is insufficient for future scaling needs. * **User-Centric Platform Approach:** Clinical sites and patients are burdened by interacting with numerous disparate systems (up to 20 per sponsor, potentially 30-40 across multiple sponsors). A platform approach that consolidates systems and prioritizes user experience is vital for improving data quality and efficiency. * **AI is Not Hype:** Concrete examples demonstrate that AI is already delivering tangible value in clinical operations, moving beyond mere hype. Organizations should embrace AI as a practical tool for innovation. * **"Think Big, Start Small" with AI:** The recommended strategy for AI adoption involves starting with small, creative experiments to understand the technology's potential, then scaling successful initiatives to address larger challenges. * **AI for Test Data Generation:** Novo Nordisk successfully implemented an AI algorithm that learns from past studies to generate meaningful test data for system setup, testing, and validation, significantly saving time and improving quality. * **Automated Study Build with Metadata:** The "Study Builder" application digitizes protocol development, allowing stakeholders to collaborate in a standardized environment. This process generates rich metadata, enabling the automation of clinical system setup and the creation of submission-ready data sets (including SDTM annotations) early in the trial lifecycle. * **Transforming UAT:** Automating the setup and testing processes, particularly through AI-generated test data, allows UAT (User Acceptance Testing) to focus on complex study configurations rather than tedious, repetitive tasks, thereby enhancing overall quality. * **Elevated Role of Data Management:** Data management has evolved from a supporting discipline to a key strategic player, gaining recognition for its technical understanding and critical role in digitizing and digitalizing clinical operations. * **Vision for Full Automation:** The ultimate goal is a "magic button" that automates the entire setup of clinical trials, allowing teams to focus solely on operating and improving the core functionality. * **Industry Collaboration:** Sharing historical data and collaborating across sponsors, organizations, and authorities is essential for gaining deeper insights and accelerating the development of new treatments. * **Prioritizing Patient and Site Perspective:** Technology solutions must be built with the patient and site perspective at the forefront, ensuring they genuinely support daily life and processes rather than adding complexity. Key Concepts: * **EDC (Electronic Data Capture):** Early technology for digital data collection in clinical trials. * **UAT (User Acceptance Testing):** The process of verifying that a system meets user requirements, often a time-consuming manual task. * **MDR (Metadata Repository):** A centralized system for storing and managing metadata, crucial for standardizing and automating system setup. * **SDTM (Study Data Tabulation Model):** A standard for organizing and formatting clinical trial data for submission to regulatory authorities like the FDA. * **Clinical Transformation:** The comprehensive overhaul of processes, technologies, and organizational structures within clinical development. * **Sustainable Growth:** Scaling operations in a way that is efficient, cost-effective, and environmentally/socially responsible, particularly in the face of exponential data growth. Examples/Case Studies: * **Novo Nordisk's AI for Test Data Generation:** A small team developed an algorithm that learns from past study data to generate realistic and meaningful test data for setting up and validating new clinical systems, significantly reducing manual effort and improving quality. * **Novo Nordisk's Study Builder Application:** This application facilitates digital protocol development by standardizing language, leveraging catalogs, and enabling collaboration among stakeholders. It generates digital specifications and metadata that can then be used to automate the setup of clinical systems and prepare submission-ready data sets.
Season 4 Episode 2: Patient vs Process Bridging the Gap for a Better Trial Experience
Veeva Systems Inc
@VeevaSystems
Oct 1, 2025
This video provides an in-depth exploration of bridging the gap between patient experience and clinical trial processes, emphasizing a patient-centric approach. Hosted by Manny Vazquez, Senior Director of Clinical Data Strategy at Veeva, the episode features Joyce Moore, a leading voice in patient recruitment with 25 years of industry experience, most recently at Allucent. The discussion highlights the critical shift from viewing patients merely as subjects to seeing them as collaborators, underscoring the importance of understanding their lives and challenges outside the clinical setting. The conversation delves into how patient engagement and site engagement are intrinsically linked, asserting that one cannot truly thrive without the other. Joyce Moore shares her journey from traditional patient recruitment to embracing decentralized trials (DCTs) and Electronic Clinical Outcome Assessment (eCOA) technologies, all driven by the goal of making trial participation easier for patients. She explains her team's role at Allucent in defining sponsor problems, developing patient-resonant materials, conducting digital outreach, and working with patient advocacy groups. A significant portion of the discussion focuses on the burden placed on both patients and sites by increasingly complex protocols, advocating for technology solutions that seamlessly integrate into existing workflows without adding undue stress. The speakers also explore the ethical implications of data collection, questioning the necessity of extensive exploratory endpoints and advocating for an "endpoint-driven design" that focuses on critical data. They discuss the potential of digital endpoints as exploratory measures to pave the way for more patient-centric trials in the future, while acknowledging the need for regulatory acceptance and clear communication with patients. The concept of "immemorable" technology for sites is introduced, suggesting that the best technology is one that is so intuitive and integrated that site staff barely notice they are using it. The episode concludes with a powerful call to action for the industry to engage patients earlier, simplify protocols, and prioritize sharing data and trial progress back with participants. Key Takeaways: * **Patient-Centricity is Paramount:** Patients should be viewed as collaborators, not just subjects. Understanding their daily lives, challenges, and motivations is crucial for successful engagement and retention in clinical trials. * **Interconnectedness of Patient and Site Engagement:** Effective patient engagement cannot occur without robust site engagement. Supporting sites and reducing their burden directly translates to a better experience for patients. * **Technology for Seamless Integration:** Clinical trial technology, such as eCOA, must be designed to integrate smoothly into existing site workflows and SOPs. The goal is for technology to be "immemorable," meaning it's so intuitive that site staff don't even notice they're using it, allowing them to focus on patient care. * **Addressing Trial Complexity and Burden:** The increasing complexity of clinical trial protocols places significant burden on both sites and patients. This includes long site visits, extensive travel, and the impact on patients' families, which can turn a short appointment into an all-day event. * **Protocol Optimization is Essential:** There is a critical need for protocol optimization to reduce unnecessary data collection. Focusing on "endpoint-driven design" ensures that only data essential for proving the hypothesis is collected, potentially reducing patient and site burden. * **Ethical Data Collection:** The ethics of collecting extensive exploratory endpoints, especially if their future use is uncertain, should be carefully considered. Every data point collected from a patient should have a clear purpose and value. * **The Value of Digital Endpoints:** Digital endpoints, even when initially exploratory, are vital for gathering data that can lead to more patient-centric clinical trials and monitoring in the future, potentially replacing traditional, burdensome assessments. * **Transparent Communication with Patients:** Explaining the "why" behind data collection and trial procedures to patients can significantly improve compliance and engagement. Treating patients like adults who understand the purpose of their participation fosters trust. * **Strategic Decentralized Trial (DCT) Implementation:** While DCTs aim to reduce patient burden, the specific implementation (e.g., centralized home health vs. site-led home visits) needs to consider patient and site preferences. Patients, especially in pediatric or elderly populations, may prefer familiar site staff visiting their homes. * **Early Patient Community Engagement:** Engaging patient communities as early as possible in the protocol design phase allows for true input, leading to lighter, more patient-friendly protocols that better reflect their needs and realities. * **Returning Data to Patients:** The industry has a responsibility to give patients their data back, both personal health information and updates on trial progress. This reciprocates their significant contribution and provides valuable insights into their own health and the study's impact. * **Just-in-Time Training for Sites:** Overburdening sites with extensive training should be avoided. "Just-in-time" training, delivered precisely when needed, is a more effective and less burdensome approach for site staff who are primarily focused on patient care. * **Cost-Benefit Analysis of Data Points:** Attaching a value or cost to each data point can serve as ammunition for sponsors to critically evaluate the necessity of collecting certain information, potentially streamlining protocols and reducing overall trial costs. **Key Concepts:** * **eCOA (Electronic Clinical Outcome Assessment):** Technology used to collect patient-reported outcomes, clinician-reported outcomes, or observer-reported outcomes electronically, often via devices like tablets or smartphones. * **DCT (Decentralized Clinical Trials):** Clinical trials where some or all trial-related activities occur at locations other than traditional clinical sites, such as a patient's home, using technology for remote monitoring and data collection. * **Endpoint-Driven Design:** A methodology for designing clinical trial protocols that prioritizes the collection of only the data necessary to prove the primary and critical secondary endpoints, thereby reducing unnecessary data points and associated burden. * **Patient Burden vs. Site Burden:** The cumulative physical, emotional, and logistical challenges faced by patients participating in a trial versus the operational and administrative challenges faced by clinical trial sites. * **Digital Endpoints:** Objective, quantifiable physiological and behavioral measures collected by connected digital health technologies (e.g., wearables, sensors) that are relevant to a patient's health status. **Examples/Case Studies:** * **Father of a child with a rare disease:** A personal anecdote illustrating how a two-hour site appointment could translate into an 8-10 hour day for a patient and their family due to travel, preparation, and logistical challenges, highlighting the significant patient burden. * **Elderly patient population and home health:** An example where sites expressed concern about centralized nurses visiting their elderly patients, preferring to send their own known staff. This underscores the importance of trust and established relationships in home health settings within DCTs.
Season 1, Episode 3: Strengthening Safety Oversight for CRO-Sponsor Partnerships
Veeva Systems Inc
@VeevaSystems
Nov 3, 2025
This video provides an in-depth exploration of strengthening safety oversight in CRO-Sponsor partnerships within pharmacovigilance (PV), hosted by David Kološić of Veeva Systems Inc. The discussion features Martijn van de Leur (Chief Commercial Officer) and Olga Asimaki (Head of International QPPV Office and Global Medical Information) from Biomapas, a Contract Research Organization (CRO). The conversation delves into the evolving landscape of PV outsourcing, the critical role of technology like Veeva Volt Safety, the challenges and opportunities presented by automation and Artificial Intelligence (AI), and how Qualified Persons for Pharmacovigilance (QPPVs) are adapting to these shifts while maintaining regulatory compliance. The discussion begins by establishing the importance of CROs in the pharmaceutical industry, particularly in PV, regulatory affairs, medical information, and clinical research. Martijn and Olga share their extensive backgrounds in PV, highlighting the historical context of outsourcing, from early "massive outsourcing projects" with control challenges to the current trend of increased trust and integrated partnerships. They identify key drivers for outsourcing, including cost efficiency, access to specialized expertise, talent attraction and retention, and the need for scalability to adapt to fluctuating resource demands. A significant shift is noted from purely transactional relationships to strategic partnerships where CROs act as an extension of the sponsor's team, offering advisory roles and sharing best practices gleaned from working with diverse clients. A central theme is the adoption of advanced technology to facilitate these partnerships and enhance PV operations. Biomapas's early adoption of Veeva Volt Safety is presented as a case study, driven by the need to replace outdated systems and provide greater transparency and control to sponsors. The speakers emphasize how cloud-based systems like Volt Safety enable real-time visibility, collaborative workflows (e.g., medical review, unblinding in clinical trials), and standardized processes, which are crucial for building trust and ensuring inspection readiness. The conversation then transitions to the QPPV perspective on technology, with Olga stressing that patient safety and regulatory compliance are paramount. She distinguishes between basic automation (like RPAs) and true AI, advocating for a strong foundation of trusted processes and clear oversight before embracing advanced digital transformation, ensuring compliance is not compromised. The latter part of the podcast critically examines the hype surrounding AI in PV. Martijn, with 20 years in the industry, reflects on the slow but significant evolution from paper-based systems to paperless, then to cloud technology, and now to automation. While automation is seen as a tangible "next stage of the revolution," he expresses skepticism about the current state of AI for end-to-end PV automation, citing challenges like data privacy (not being able to mix customer data for training) and the limited data available for smaller clients to train robust AI systems. Olga suggests that current practical AI applications are more likely to be supportive tools, such as in document authoring, content summarization, and generating text based on references, rather than fully autonomous decision-making. Both speakers envision a future (by 2030) where AI-driven signal detection and case processing are seamlessly integrated with real-time data sources, leading to predictive analytics, proactive compliance, and a sustainable, scalable PV system that can manage exponentially growing data volumes. Key Takeaways: * **Evolution of PV Outsourcing:** Outsourcing in pharmacovigilance has evolved from cost-driven, often challenging, large-scale projects to more integrated, trust-based partnerships. This shift is driven by the need for specialized expertise, talent management, and scalable solutions that CROs can provide. * **Strategic CRO-Sponsor Partnerships:** The relationship between CROs and sponsors is moving beyond transactional service provision to a collaborative partnership model. CROs are increasingly seen as an extension of the sponsor's team, offering advisory insights and implementing best practices across multiple clients. * **Transparency and Oversight through Technology:** Modern cloud-based PV systems, such as Veeva Volt Safety, are crucial for fostering trust and transparency in outsourced operations. They provide sponsors with real-time visibility into cases, data, and workflows, allowing for direct involvement in critical steps like medical review and unblinding. * **Standardization as a Key Driver:** The industry is increasingly moving towards standardization in PV processes and system configurations. Utilizing default configurations of validated systems like Veeva Volt Safety simplifies operations, reduces customization costs, and enhances inspection readiness by aligning with health authority expectations. * **QPPV Perspective on Technology Adoption:** For QPPVs, patient safety and regulatory compliance remain the highest priorities. Digital transformation, including automation and AI, must be built upon a strong foundation of trusted processes, data visibility, and clear oversight to ensure compliance is never compromised. * **Distinguishing Automation from AI:** It's important to differentiate between basic automation (e.g., RPAs) and advanced AI in PV. While automation is already delivering practical benefits, true AI for end-to-end PV processes is still in its early stages and requires careful validation and quality control. * **AI's Current Practical Applications:** Currently, AI is more realistically implemented as a supportive tool in PV, particularly for tasks like document authoring, generating content summaries from references, and assisting with text creation, rather than fully replacing human decision-making. Human review and approval remain essential. * **Challenges for AI in PV:** Significant hurdles for widespread AI adoption include data privacy concerns (inability to pool data from multiple clients for training) and the lack of sufficient, diverse data from individual small clients to effectively train robust AI models. * **Regulatory Lag and Uncertainty:** The pace of technological advancement often outstrips regulatory evolution, creating uncertainty for QPPVs. Clear, concrete guidance from regulatory authorities is needed to enable the industry to confidently lean into innovation without compromising compliance. * **Continuous Validation and Proactive Change Management:** Validation of PV systems and tools should not be a one-time event but a continuous process, adapting to evolving needs and configurations. Proactive change management is vital to ensure successful implementation and adoption of new technologies. * **Future Vision for PV (2030):** The future of PV is envisioned as a seamless integration of AI-driven signal detection and case processing with trusted, real-time data sources. This will lead to connected, intelligent safety systems capable of predictive analytics, anticipating compliance needs, and supporting data-driven decisions. * **Technology as a Necessity for Scalability:** With increasing case volumes and pressure to control costs, technology is no longer a "nice-to-have" but a "must" for PV departments. It is essential for achieving scalability, sustainability, and operational efficiency without exponential cost increases. Tools/Resources Mentioned: * **Veeva Volt Safety:** A cloud-based safety database system used by CROs and pharmaceutical companies for pharmacovigilance operations. Key Concepts: * **Pharmacovigilance (PV):** The science and activities relating to the detection, assessment, understanding and prevention of adverse effects or any other drug-related problem. * **CRO-Sponsor Partnerships:** Collaborative relationships between Contract Research Organizations (CROs) and pharmaceutical/biotech sponsors, particularly in outsourcing specialized services like pharmacovigilance. * **QPPV (Qualified Person for Pharmacovigilance):** A designated individual within a marketing authorization holder (or CRO acting on their behalf) responsible for the establishment and maintenance of the pharmacovigilance system. * **Automation (RPA):** The use of technology to perform tasks with minimal human intervention, often referring to Robotic Process Automation (RPA) for repetitive, rule-based tasks. * **Artificial Intelligence (AI) / Large Language Models (LLMs):** Advanced computational systems designed to simulate human intelligence, including learning, reasoning, and problem-solving. In PV, this includes potential applications for data analysis, signal detection, and document generation.
Episode 10: Why We Need to Expand Patient Choice in Clinical Trials
Veeva Systems Inc
@VeevaSystems
Aug 23, 2023
This video provides an in-depth exploration of the evolution of clinical trials, focusing on data management, patient and site centricity, and the future of digital solutions. Richard Young interviews Tim Davis, Vice President of Strategy for MyVeeva for Patients, who offers a historical perspective on clinical data management, from the early days of paper Case Report Forms (CRFs) to the advent of electronic data capture (EDC) and electronic patient-reported outcomes (e-PRO). Davis highlights the initial challenges of integrating e-PRO data, which was often treated as an afterthought or "another source of pain" by data managers, primarily due to its non-traditional nature compared to typical EDC source data. The discussion underscores the significant lag (often 8-14 weeks) between data collection and its visualization or integration in paper-based systems, contrasting it with the real-time insights offered by electronic methods. The conversation delves into the role of regulators, with Davis asserting that regulatory bodies have been largely supportive of technological advancements, particularly regarding the use of patients' own devices, provided fundamental requirements like audit trails and data security are met. He notes that the industry's hesitancy, rather than regulatory barriers, often impedes innovation. A significant portion of the discussion critiques buzzwords like "patient centricity," "site centricity," and "decentralized clinical trials" (DCTs). Davis redefines "patient centricity" as offering "choice" and convenience, rather than aiming to "delight" patients who are often struggling with illness. For sites, centricity means providing convenience through integrated, intuitive solutions under a single login. He expresses a strong dislike for the term "decentralized clinical trials," arguing that many of its components have existed for decades and that the term itself has become a barrier to a clear path forward. The speakers reflect on the impact of the COVID-19 pandemic, which forced a rapid adoption of digital tools but often resulted in a fragmented "layered tech" approach, overwhelming sites and patients with disparate systems. This experience, while challenging, underscored the need for scalable, repeatable models for digital trials. Davis envisions the future of digital trials as being driven by flexible, consistent underlying platforms that can adapt to various operating models—whether remote, in-person, or a hybrid—to truly offer patient choice. He emphasizes focusing on "how" patients participate rather than "where." The interview concludes with practical advice for data managers, urging them to "think about the end at the beginning" by involving themselves in the design phase of e-PRO solutions and ensuring consistent patient identifiers across all systems to avoid downstream issues. Davis also shares his "magic wand" wishes: to shed the historical baggage of e-PRO/eCOA development, enhance patient recognition and transparency by sharing study outcomes, and eliminate the costly and often unnecessary practice of provisioning devices to every patient. Key Takeaways: * **Evolution of Data Management:** Clinical data management has progressed from manual, paper-based systems (CRFs, validated rulers for pain scales) with significant data lag (8-14 weeks) to electronic data capture (EDC) and e-PRO, offering real-time insights. * **e-PRO Integration Challenges:** Historically, e-PRO data was often an afterthought, not fully integrated into clinical data management processes, and seen as a separate "source of pain" due to its non-traditional, non-queryable nature compared to typical EDC data. * **Regulator Support vs. Industry Hesitancy:** Regulators (e.g., FDA) are generally supportive of new technologies like patient-owned devices for data collection, provided core requirements like audit trails and data security are met. The primary barrier to innovation is often internal industry hesitancy and a reluctance to be "first." * **Redefining Patient Centricity:** True patient centricity is about offering "choice" and convenience, not "delight." This includes providing flexible participation options (remote, in-person, hybrid), accessible educational information, and timely support tailored to a patient's journey. * **Site Centricity for Efficiency:** Site centricity involves providing convenience through integrated technology solutions (e.g., single username/password, intuitive apps) that reduce burden and offer tangible benefits back to the sites, acknowledging their critical role as the "window to patients." * **Critique of "Decentralized Clinical Trials" (DCT):** The term "decentralized clinical trials" is often overused and can hinder progress. Many elements of DCTs, such as patient diaries on devices, have existed for decades. The focus should be on enabling flexible participation models rather than adhering to a rigid definition of "decentralized." * **COVID-19's Impact on Tech Adoption:** The pandemic accelerated the adoption of digital tools in clinical trials, but often led to a fragmented approach with "layered tech" and disparate vendor systems, creating stress for sites and patients. This highlighted the need for scalable and repeatable digital trial models. * **Future of Digital Trials:** Digital trials require flexible, consistent, underlying platforms that can support a mix of remote and in-person activities, adapting to patient needs and locations. The emphasis should be on "how" patients wish to participate (e.g., day-by-day choice) rather than prescriptive "where" decisions. * **Proactive Data Management:** Data managers should be involved from the very beginning of e-PRO design, considering the end-state data tables and how e-PRO data will fit into the overall data asset. This includes planning for data frequency and integration. * **Importance of Consistent Identifiers:** Ensuring consistent patient identifiers (screening ID, randomized ID) across all clinical trial systems (RTSM, EDC, e-PRO) is crucial to avoid significant data management headaches and improve data integrity. * **Overcoming Historical Baggage:** The industry needs to move past historical limitations and assumptions in e-PRO/eCOA (e.g., the necessity of providing specific, validated devices to all patients) to foster true innovation. * **Enhancing Patient Recognition and Transparency:** Improve patient engagement and participation rates by being more transparent: sharing study outcomes, providing high-level summaries of results, and informing patients if a drug they participated in gets approved. * **Eliminating Universal Device Provisioning:** The practice of provisioning a device to every patient, regardless of need, is expensive, disliked by sites, and often unnecessary, as many patients already possess better personal devices. This practice should be largely phased out in favor of patient choice. Key Concepts: * **e-PRO (Electronic Patient-Reported Outcomes):** Data reported directly by patients about their health status, symptoms, or treatment effects, collected electronically. * **eCOA (Electronic Clinical Outcome Assessment):** A broader term encompassing e-PRO, e-ClinRO (clinician-reported outcomes), e-ObsRO (observer-reported outcomes), and e-PerfO (performance outcomes), all collected electronically. * **EDC (Electronic Data Capture):** Software systems used to collect clinical trial data in electronic format, replacing paper CRFs. * **Patient Centricity:** An approach to clinical trial design and execution that prioritizes the needs, preferences, and experiences of patients, often by offering choice and convenience. * **Site Centricity:** An approach that focuses on making clinical trials easier and more efficient for investigative sites, recognizing their vital role in patient recruitment and data collection. * **Decentralized Clinical Trials (DCTs) / Digital Trials:** Clinical trials that incorporate digital technologies and remote methodologies to reduce the need for in-person site visits, offering flexibility in how and where patients participate. The video advocates for "digital trials" or "distributed" over "decentralized." * **Veeva CRM:** A leading cloud-based customer relationship management platform specifically designed for the pharmaceutical and life sciences industries, used for commercial operations and engagement. The speaker's role at MyVeeva for Patients indicates a focus on patient-facing technologies within the Veeva ecosystem.
Mallinckrodt Shares Digital Asset Management Best Practices
Veeva Systems Inc
@VeevaSystems
Mar 29, 2021
This video provides an in-depth exploration of digital asset management (DAM) best practices, specifically tailored for emerging and mid-sized pharmaceutical companies. Presented by Joyce Pearl, Director of Marketing Services, and Tom Zito, Marketing Materials Specialist and DAM SME, from Mallinckrodt, the session outlines their journey from a chaotic, costly content management situation to a streamlined, efficient DAM program. The speakers share practical insights and lessons learned from building their DAM system from scratch, emphasizing the challenges and triumphs of implementing such a system within a resource-constrained environment. The presentation begins by illustrating the severe pain points Mallinckrodt faced prior to DAM implementation, including exorbitant costs for retrieving or recreating lost files (e.g., $40,000 for a single file package), difficulty locating original files and licensed images, and reliance on expensive agencies for simple updates. This context sets the stage for their decision to adopt a DAM system, integrating it with their transition from Zinc to Veeva PromoMats. A significant challenge was not just getting internal buy-in due to cost and legal concerns, but also ensuring user adoption, particularly from agencies responsible for uploading content. This led to the creation of custom training materials and the establishment of a dedicated DAM librarian role. A core component of their methodology is the "TASK" acronym, which encapsulates their key learnings and criteria for setting DAM expectations. "Taxonomy" stresses the critical importance of consistent classification, naming conventions, and metadata for discoverability. "Accept when it's not working" highlights the necessity of flexibility and willingness to iterate on processes, even if it means admitting initial approaches were flawed. "Set expectations and train everyone" underscores the continuous effort required for onboarding agencies and internal teams, providing clear guidelines and support. Finally, "Know your image rights" emphasizes the often-overlooked legal complexities of content usage, advocating for a deep understanding of licensing terms like royalty-free and rights-managed. The speakers detail how they integrated their printing process with Veeva to ensure file integrity and developed fields within the DAM to track image permissions and expiration dates, significantly mitigating previous issues. Key Takeaways: * **Address Costly Inefficiencies:** Prior to DAM, Mallinckrodt faced significant financial burdens, including paying up to $40,000 to retrieve or recreate lost files for a single brand, highlighting the critical need for centralized asset management to reduce operational costs. * **Strategic DAM Implementation with Veeva:** The company strategically integrated its DAM implementation with a broader transition from Zinc to Veeva PromoMats, leveraging the platform's capabilities for promotional review and asset storage. Agencies were required to be Veeva certified. * **The Crucial Role of a Dedicated DAM Librarian:** Establishing a dedicated Digital Asset Management Subject Matter Expert (SME) or "Librarian" is vital for day-to-day operations, ensuring consistent content classification, metadata application, and overall system integrity. * **The "TASK" Framework for Success:** Mallinckrodt developed the "TASK" acronym to guide their DAM strategy: Taxonomy, Accept when not working, Set expectations and train, and Know your image rights. This framework provides a structured approach to managing digital assets. * **Taxonomy is Paramount for Discoverability:** Effective taxonomy, including clear classification, consistent naming conventions, and robust metadata, is essential for users to find and reuse assets efficiently. Without it, the DAM becomes a costly storage solution rather than a functional library. * **Embrace Flexibility and Iteration:** Be prepared to "Accept when it's not working" and adjust processes. Mallinckrodt initially required source files too early, leading to corrupt or incomplete packages, and later shifted this requirement, integrating their printing process with Veeva to pull files directly from the DAM, significantly improving file integrity. * **Continuous Training and Communication:** "Set expectations and train everyone" is an ongoing effort. This includes virtual onboarding sessions for agencies and marketers, custom quick guides, and additional sessions like "ask the librarian" to ensure consistent understanding and adoption of DAM guidelines. * **Deep Understanding of Image Rights is Non-Negotiable:** Companies must "Know your image rights," understanding terms like royalty-free and rights-managed. The video highlights that agencies often lack this deep understanding, making it incumbent on the client to educate and enforce proper licensing documentation. * **Leverage System Features for Compliance:** The DAM system can be configured with custom fields to document image permissions, expiration dates, and automatically alert users about upcoming expirations, streamlining compliance and reducing legal risks associated with content usage. * **Overcoming Agency Resistance:** Agencies may not prioritize taxonomy and metadata as much as the client. The DAM librarian must be hands-on in verifying and editing incoming content to maintain consistency and quality within the library. * **Internal Buy-in and Cross-Functional Support:** Gaining initial buy-in from marketing and legal teams was easier due to existing frustrations and costs. However, active user adoption required more convincing and work, emphasizing the need for continuous advocacy and support. * **Building Processes from the Ground Up:** Mallinckrodt's team, initially without direct DAM experience, successfully built their operational model and processes from scratch, demonstrating that a base knowledge of the creative process and a willingness to learn can lead to effective solutions. Tools/Resources Mentioned: * Veeva PromoMats (Digital Asset Management and Promotional Review platform) * Zinc (Previous promotional review system) Key Concepts: * **Digital Asset Management (DAM):** A system for organizing, storing, and retrieving digital assets. * **Taxonomy:** The classification and categorization of content, crucial for search and discoverability within a DAM. * **Image Rights:** Legal permissions governing the use of images, including concepts like royalty-free (one-time fee for broad usage) and rights-managed (specific usage rights with limitations). * **Promotional Review Process (PRC):** The internal review and approval process for marketing and promotional materials in regulated industries, often involving medical, legal, and regulatory teams. * **DAM Librarian/SME:** A dedicated role responsible for the day-to-day operations, governance, and quality control of the digital asset management system. Examples/Case Studies: * **Mallinckrodt's DAM Journey:** The entire presentation serves as a case study of Mallinckrodt, an emerging/mid-sized pharma company, and their experience implementing and optimizing a DAM system, including their initial challenges, strategic decisions, and the development of the "TASK" framework. Specific examples include paying $40,000 for file retrieval and integrating their printing process with Veeva PromoMats.
Season 1 Episode 2: The Problem of Plenty in Commercial Life Sciences
Veeva Systems Inc
@VeevaSystems
May 6, 2024
This video provides an in-depth exploration of the evolving landscape of commercial excellence in the life sciences industry, particularly focusing on the challenges and opportunities presented by the "problem of plenty" in data and technology. Hosted by Florian Schnappauf, the episode features Rakesh Vashishta, Global Head of Customer Facing Execution Excellence at Boehringer Ingelheim, who shares his three decades of experience in commercial pharmaceutical roles. The discussion centers on the dramatic shifts in customer engagement, the growing expectations placed on field teams, and the critical role of technology, data, and compliance in shaping the future of interactions with healthcare professionals (HCPs) and patients. Rakesh emphasizes that commercial excellence has transformed dramatically over the last 15 years, moving from primarily face-to-face, paper-based detailing to an omnichannel approach driven by technology like Veeva CRM and iPads. This shift necessitates a change in mindset from being internally focused on customer-facing teams to externally focused on creating exceptional customer and patient experiences. He outlines three fundamental building blocks for commercial excellence: understanding your customers, respecting their preferences through customer-centric engagement planning, and achieving execution excellence. A significant challenge highlighted is the difficulty in achieving a true 360-degree view of the customer due to fragmented platforms and issues with data accuracy and completeness, despite the abundance of available data. The conversation further delves into the nuances of understanding customer preferences, distinguishing between "stated" preferences (what customers say) and "observed" preferences (what they do). Rakesh argues that observed behavior, such as engagement with digital channels or non-face-to-face interactions, is a more reliable indicator of true preference. He notes a significant increase in digital engagements post-pandemic, though face-to-face interactions remain foundational. This evolution redefines the role of the sales representative from a mere channel to a "strategic asset" and "orchestrator of the omnichannel experience," requiring new competencies, tools, and continuous learning. The discussion also touches upon the growing importance of inbound communication channels like chat, acknowledging the challenge of ensuring compliance while offering flexibility and speed. Looking ahead, Rakesh envisions "next-gen commercial" as being synonymous with simplicity, driven by intelligent CRM systems powered by Artificial Intelligence (AI). He believes AI will simplify cross-functional customer engagement planning, provide live, prospective recommendations, and offer actionable insights to enhance effectiveness, moving beyond rule-based or retrospective approaches. He stresses the importance of a "one-team mindset" across medical, commercial, IT, finance, and compliance departments to achieve these transformations, especially as portfolios shift towards specialty care and require closer collaboration between commercial and clinical functions. Finally, he advocates for stopping the creation of unused content and starting to prioritize user experience by actively involving users in the development and evaluation of tools and technologies. Key Takeaways: * **Evolution of Commercial Excellence:** The pharmaceutical industry has undergone a seismic shift from traditional face-to-face engagements to a complex omnichannel approach, driven by technology and changing customer expectations. This demands a mindset change from internal team focus to external customer and patient experience focus. * **Three Pillars of Commercial Excellence:** The core principles involve deeply understanding customers, designing engagements that respect customer preferences (customer-centricity), and achieving excellence in execution. * **The "Problem of Plenty" in Data:** While there's an abundance of data and platforms, achieving a 360-degree customer view remains challenging due to poor integration, data incompleteness, and accuracy issues. The industry needs "lesser but highly valuable, highly accurate actionable insights" rather than overwhelming data. * **Observed vs. Stated Customer Preferences:** True customer preferences are best understood by observing their actual behavior (e.g., channel engagement, digital interactions) rather than solely relying on what they state they prefer. There's often a significant gap between the two. * **Rise of Digital Engagement:** Post-pandemic, non-face-to-face interactions have dramatically increased, indicating a shift in HCP preferences towards digital channels, though face-to-face remains a critical component of engagement. * **Reps as Strategic Orchestrators:** The role of the customer-facing team has evolved from a simple channel to a "strategic asset" and "orchestrator of the omnichannel experience," requiring new competencies, agility, and continuous growth. * **Importance of Inbound Channels:** Inbound communication, facilitated by instant messaging platforms, is growing in importance as HCPs seek quick, convenient answers. The challenge lies in making these channels compliant while maintaining user-friendliness. * **Non-Negotiable Compliance:** Compliance is paramount and non-negotiable in the pharmaceutical industry. New technologies and engagement models must be built with 100% compliance in mind, even if it initially impacts user experience. * **AI for Simplicity and Effectiveness:** Artificial Intelligence is expected to simplify future commercial operations by enabling intelligent CRM systems to provide live, prospective recommendations and actionable insights for effective cross-functional customer engagement planning. * **Cross-Functional Collaboration:** Achieving commercial transformation requires a "one-team mindset" and strong collaboration across medical, commercial, IT, finance, and compliance departments, recognizing that all functions are equally vital. * **Prioritizing User Experience:** A critical area for improvement is actively involving users (e.g., sales reps, first-line managers) in the design and evaluation of tools and technologies to ensure they are user-friendly and truly enhance their work. * **Eliminate Content Waste:** The industry should stop creating content that is never used, focusing instead on producing valuable, utilized content to reduce waste of money, time, and effort. Tools/Resources Mentioned: * **Veeva CRM system:** A leading customer relationship management platform in the life sciences industry. * **Veeva Engage:** A platform for remote engagement with HCPs. * **Veeva Engage Connect:** A platform for compliant instant messaging and engagement. * **Veeva Pulse data:** Data and insights provided by Veeva Systems. * **iPad:** A tablet computer used for digital detailing and other field activities. * **WhatsApp, Viber, KakaoTalk:** Instant messaging platforms. * **Concur, Outlook:** General enterprise tools mentioned in the context of user experience. * **iPhone 15:** Mentioned as a recent example of a product with initial imperfections but strong user loyalty. Key Concepts: * **Commercial Excellence:** The strategic and operational initiatives aimed at optimizing commercial operations, sales performance, and customer engagement within a pharmaceutical company. * **Omnichannel Experience:** A seamless and integrated customer experience across all available channels (face-to-face, digital, phone, email, etc.), orchestrated to meet customer preferences. * **Closed-Loop Marketing:** A marketing approach where customer interactions and feedback are continuously captured, analyzed, and used to refine future marketing efforts and content. * **360-Degree View of the Customer:** A comprehensive understanding of a customer derived from integrating all available data points and interactions across various platforms and touchpoints. * **Customer-Centricity:** Designing and executing strategies with the customer's needs, preferences, and experience at the absolute center. * **Inbound Traffic/Engagement:** Customer-initiated interactions or requests, where the customer reaches out to the company (e.g., via chat, email, phone). * **Next-Gen Commercial:** Refers to the future state of commercial operations in life sciences, characterized by advanced technology, AI, data-driven insights, and highly personalized customer experiences. Examples/Case Studies: * **Boehringer Ingelheim:** Rakesh Vashishta's company, where he is implementing strategies for customer-facing execution excellence and fostering a "one-team mindset" across departments. * **Tablet PC-based detailing (2008):** An early example of technology adoption in the industry before iPads and Veeva, highlighting the rapid pace of technological change. * **Henry Ford's "faster horses" analogy:** Used to illustrate that customers may not always know what they truly need or what innovative solutions are possible. * **Apple vs. Android:** Used to discuss the balance between flexibility (Android) and stability/security/predictability (Apple) in technology, and how users might prioritize different aspects, drawing a parallel to compliant vs. flexible communication platforms.
Season 4 Episode 3: Innovation from the Inside: How Sites Are Redefining Clinical Research
Veeva Systems Inc
@VeevaSystems
Nov 6, 2025
This video provides an in-depth exploration of innovation in clinical research, focusing on how research sites are redefining their operations through technology and collaboration. Hosted by Manny Vasquez from Veeva, the discussion features Denali Rose (Veeva, Site Solution Strategy) and Joe Lengfellner (Memorial Sloan Kettering Cancer Center - MSKCC, Clinical Research Informatics and Innovation Consortium Lead). The conversation delves into the daily challenges faced by clinical trial coordinators, the inefficiencies of current data management practices, and the transformative potential of advanced technologies like EHR-to-EDC integration and Large Language Models (LLMs) in areas such as patient recruitment and health equity. The discussion begins by highlighting the often-underappreciated and chaotic role of clinical research coordinators, who juggle patient management, data curation, regulatory tasks, and financial coordination. Joe Lengfellner from MSKCC describes how coordinators spend a significant portion of their time on data management, often manually transferring information from electronic health records (EHRs) to electronic data capture (EDC) systems. This manual process is identified as a major bottleneck, leading to inefficiencies, potential errors, and high turnover rates among coordinators. The speakers emphasize the need for technological solutions to alleviate this burden, particularly through direct data capture and integration. A significant portion of the conversation focuses on the shift towards sites taking ownership of their technological infrastructure. MSKCC's initiative to implement EHR-to-EDC integration using FHIR resources and APIs with a vendor like Ignite Data is presented as a prime example of a large academic center digitizing its workflows to improve scalability and data accuracy. For smaller sites, the focus shifts to eSource solutions and the challenge of duplicate data entry between eSource systems and sponsor-provided EDCs. The speakers advocate for a "Bring Your Own Technology" (BYOT) approach, where sponsors support sites in using their preferred and established tools, rather than imposing new, disruptive systems for each trial. The podcast also explores the evolving relationship between sites, sponsors, and CROs, noting a positive trend towards more open dialogue and genuine site-centricity, moving beyond mere buzzwords. Finally, the discussion ventures into cutting-edge innovations, particularly the application of LLMs and AI in clinical research. Joe Lengfellner introduces MSKCC's Clinical Research Innovation Consortium (CRIC), a collaborative initiative involving sites, sponsors, technology providers, and regulators to identify and test industry-wide solutions. A key project within CRIC involves evaluating LLMs for clinical trial matching and patient recruitment. An example is shared where an LLM successfully identified all patients manually matched by coordinators, plus additional eligible patients who were previously missed, demonstrating the technology's potential to enhance patient access, improve diversity in trials, and address health equity challenges. The speakers conclude with a call to action for the industry to embrace risk-taking in technology adoption and foster greater inter-stakeholder communication and collaboration. Key Takeaways: * **Undervalued Role of Clinical Trial Coordinators:** Clinical research coordinators perform a wide array of tasks, from patient recruitment and management to regulatory and financial duties, often in chaotic environments, making it one of the most challenging and underappreciated roles in the industry. * **Data Curation as a Major Bottleneck:** A significant portion of a coordinator's day, sometimes up to 100% for specialized roles, is spent on manual data curation, involving copying and pasting data from clinical records (EHRs) into EDC systems and responding to queries. * **Critical Need for EHR-to-EDC Integration:** Direct integration between EHRs and EDCs is essential for improving the efficiency, scalability, and data quality of clinical trials, reducing manual effort, and enabling more trials to be conducted. * **Challenges with Protocol Amendments:** Managing protocol amendments is highly complex and duplicative, requiring multiple teams to update different representations of the trial across various systems (EDC, CTMS, EHR treatment plans, eConsent), leading to delays and potential errors. * **Site-Driven Technology Adoption (Esource & BYOT):** Research sites are increasingly adopting their own electronic source (eSource) and eConsent tools, and there's a growing need for sponsors to support a "Bring Your Own Technology" (BYOT) approach to avoid disrupting established site workflows. * **Duplication in Digital Workflows:** Even with eSource, sites often face the challenge of entering the same data twice – once into their eSource system and again into the sponsor's EDC, highlighting the need for direct data capture or unified systems. * **Evolving Site-Sponsor Relationship:** There's a positive shift towards genuine site-centricity, with sponsors showing more willingness to listen to sites' challenges and collaborate on solutions, moving beyond superficial engagement. * **LLMs for Patient Recruitment and Health Equity:** Large Language Models (LLMs) and AI hold immense potential for revolutionizing clinical trial matching, patient identification, and recruitment, helping to find previously missed eligible patients and improve diversity and health equity in trials. * **Clinical Research Innovation Consortium (CRIC):** Collaborative initiatives like MSKCC's CRIC, which brings together sites, sponsors, tech providers, and regulators, are crucial for vetting and scaling innovative technologies in a metrics-driven manner. * **Data Access for AI Solutions:** A significant hurdle for effective AI-powered patient recruitment is gaining access to comprehensive patient data, especially for the large population of patients outside of major academic centers (e.g., 80% of oncology patients in the community). * **Risk Aversion Hinders Innovation:** The industry's risk-averse culture, particularly among sponsors, often leads to prolonged pilot programs for new technologies, causing promising solutions to "die on the vine" instead of being widely adopted. * **Standardization of Site Workflows:** Sites benefit greatly from standardizing their internal workflows and technology across their portfolio of studies; disparate sponsor-mandated systems (e.g., multiple e-consent platforms) can be highly disruptive and lead to a reversion to paper-based processes. * **Call for Inter-Stakeholder Communication:** There is a strong call for increased and more open dialogue between different stakeholders—sites, sponsors, and CROs—to understand each other's challenges and collaboratively drive industry improvement. Tools/Resources Mentioned: * Veeva (Clinical Data Strategy, Site Solution Strategy) * Ignite Data (Vendor for EHR-to-EDC integration) * FHIR resources/APIs (Technical standard for data exchange in EHRs) * Epic (EHR system mentioned for treatment plans) * EDC (Electronic Data Capture systems) * EHR (Electronic Health Records) * eSource (Electronic Source documentation systems) * CTMS (Clinical Trial Management Systems) * eConsent (Electronic Consent platforms) * Large Language Models (LLMs) * AI (Artificial Intelligence) Key Concepts: * **Site Centricity:** A philosophy and approach in clinical trials that prioritizes the needs and workflows of research sites, aiming to make their participation more efficient and less burdensome. * **EHR-to-EDC Integration:** The automated transfer of clinical data from a hospital's Electronic Health Record system directly into a sponsor's Electronic Data Capture system, reducing manual data entry. * **Esource:** Electronic capture of source data directly at the point of care or data generation, eliminating the need for paper source documents. * **Direct Data Capture:** A method of collecting clinical trial data directly into an electronic system, bypassing paper records and often integrating with other systems. * **Clinical Research Innovation Consortium (CRIC):** A collaborative group (started at MSKCC) focused on identifying, evaluating, and implementing innovative technologies to solve industry-wide problems in clinical research. * **Health Equity / Patient Diversity:** Efforts to ensure that clinical trials are accessible to and representative of diverse patient populations, addressing disparities in healthcare access and outcomes. * **BYOT (Bring Your Own Technology):** A concept where research sites are allowed or encouraged to use their existing, preferred, and integrated technologies for clinical trial activities, rather than being forced to adopt sponsor-specific tools. Examples/Case Studies: * **Memorial Sloan Kettering's EHR-to-EDC Initiative:** MSKCC is actively working with Ignite Data to leverage FHIR resources and APIs to pull clinical data directly from their EHR (Epic) into EDC systems, aiming to eliminate manual data entry for coordinators. * **CRIC's LLM-based Patient Recruitment Project:** The Clinical Research Innovation Consortium conducted a metrics-driven evaluation of LLMs for clinical trial matching. By providing a vendor with a month's worth of patient data and three trials, the LLM not only identified all patients manually matched by coordinators but also found additional eligible patients who had been previously missed, demonstrating its potential to expand patient access to trials.
Challenges with Clinical Data Management: Findings by Tufts
Veeva Systems Inc
@VeevaSystems
Oct 24, 2017
This video provides an in-depth exploration of the challenges and opportunities in clinical data management, drawing upon findings from a recent Tufts University study commissioned by Veeva Systems. Richard Young, Vice President of Vault EDC at Veeva Systems, discusses the evolving landscape of electronic data capture (EDC) and the increasing complexity of clinical trials. The core purpose of the study was to examine current and evolving EDC and clinical data usage practices across drug development, specifically questioning whether traditional systems are still fit for purpose given the growing demands of data collection, management, and reporting. The study surveyed over 250 senior industry professionals with an average of 20 years of experience, aiming to surface current and future challenges in the field. Young highlights a critical issue with the term "EDC" itself, noting that traditional EDC systems, often built in the 1990s, primarily function as electronic case report forms (eCRFs), capturing only 20-30% of the total study data. This leaves a vast amount of diverse data—such as lab data, biomarkers, PK data, and increasingly, millions of data points from mobile health devices like Fitbits and Garmins—unmanaged by these systems. He introduces a four-stage framework for data management: "design, collect, decide, and act." The challenges users face stem from the inability of outdated systems to support designing the trial one truly wants to run, collecting all necessary data types, making confident and timely decisions based on comprehensive data, and acting effectively on those decisions amidst growing project complexity. A key finding from the Tufts research reveals a strong correlation between the initial stages of a clinical trial and subsequent delays. The study demonstrated that delays in building the study database directly lead to longer data entry times and slower database lock times. This insight underscores the principle that "if you start behind, you never catch up," emphasizing the critical need for upfront efficiency and robust preparation. Young further discusses the "four V's" of clinical data management—Volume, Variety, Velocity, and Veracity—which collectively lead to the "fifth V," Value. He stresses that the sheer volume of data, its diverse formats, the demand for real-time access, and the understanding that not every data point requires absolute perfection (veracity, focusing resources on critical data) are paramount considerations for modern data management strategies. Veeva's proposed solution is a unified, "true platform" that seamlessly consolidates data, content, and workflows, addressing the industry's current reliance on over 160 disparate systems. Key Takeaways: * **Outdated EDC Systems:** Traditional Electronic Data Capture (EDC) systems, often developed in the 1990s, are no longer fit for purpose. They primarily function as electronic forms, capturing only 20-30% of total clinical study data and failing to manage the growing volume and variety of modern data sources. * **Expanding Data Landscape:** Clinical trials now involve a vast array of data beyond traditional eCRFs, including lab data, biomarkers, PK data, and millions of data points from mobile health devices (e.g., Fitbits, Garmins). Current systems struggle to integrate and manage this diverse and high-volume data. * **The "Design, Collect, Decide, Act" Framework:** Effective data management can be broken down into four critical stages: designing the trial without technological limitations, collecting all types of relevant data, making confident and timely decisions based on comprehensive data, and acting decisively on those insights. * **Correlation of Early Delays to Later Inefficiencies:** The Tufts study revealed a direct and perfect correlation: delays in building the study database significantly prolong data entry times and slow down database lock. This highlights the critical importance of upfront planning and efficient setup. * **"If You Start Behind, You Never Catch Up":** This powerful insight from the research emphasizes that initial project delays create a cascading effect, leading to persistent inefficiencies throughout the clinical trial lifecycle. Proactive and timely execution in early phases is crucial. * **The Four V's of Clinical Data:** Modern clinical data management must contend with: **Volume** (exponential growth, e.g., billions of data points per patient from mobile health), **Variety** (diverse data types and formats), **Velocity** (demand for real-time access and processing), and **Veracity** (strategic focus on the most important data points, acknowledging that not all data requires absolute perfection). * **Achieving Data Value:** By effectively managing the four V's, organizations can unlock the "fifth V"—Value. The goal is to ensure systems help identify the true value of data to drive better decisions, primarily concerning patient safety and efficacy. * **Industry's System Fragmentation:** A major challenge in pharma is the use of numerous disparate systems (some companies use over 160 systems for data management, clinical, and statistical work), leading to inefficiencies, data silos, and integration complexities. * **Need for a Unified Platform:** The vision for the future of clinical data management involves a unified, "true platform" capable of managing all data, content, and workflows concurrently and seamlessly. Such a platform would enable data flow to all consumers and contributors without delay, driving actions and informing decisions. * **Seamless Consolidation:** A unified platform should facilitate the seamless consolidation not just of structured data, but also unstructured data (e.g., Twitter feeds), content (documentation), and workflows. This integration is essential for comprehensive oversight and operational efficiency. Tools/Resources Mentioned: * **Veeva Systems Inc:** The company that commissioned the Tufts study and whose Vice President of Vault EDC was the speaker. Veeva is presented as a leader in cloud-based software for the global life sciences industry, advocating for a unified platform approach. * **Tufts University:** Specifically, Tufts Center for the Study of Drug Development (CSDD), which conducted the research study on clinical data management and EDC practices. * **EDC (Electronic Data Capture):** The primary technology discussed, though the video highlights its limitations in its traditional form. * **Mobile Health Devices (Fitbits, Garmins):** Mentioned as examples of sources generating massive volumes of new clinical data. Key Concepts: * **eClinical Landscape:** Refers to the ecosystem of electronic systems and processes used in clinical trials, including EDC, clinical trial management systems (CTMS), and other data management tools. * **Database Build Delays:** The time taken to set up and validate the study database before patient enrollment, identified as a critical factor impacting subsequent trial timelines. * **Data Entry Cycle Times:** The duration from patient visit to the transcription of data into the EDC system. * **Database Lock:** The final stage of data management where the clinical database is finalized and locked for analysis, a key milestone in trial completion. * **Four V's of Data (Volume, Variety, Velocity, Veracity):** A framework used to characterize the challenges and requirements of managing big data, applied here specifically to clinical data. * **Volume:** The sheer amount of data being generated. * **Variety:** The different types and formats of data. * **Velocity:** The speed at which data is generated, processed, and accessed. * **Veracity:** The quality, accuracy, and trustworthiness of the data, with an emphasis on strategically focusing resources on the most critical data points rather than striving for absolute perfection across all. * **Unified Platform:** A single, integrated software solution designed to manage all aspects of data, content, and workflows across an enterprise, contrasting with fragmented, bolted-together systems.
Season 1 Episode 3: Preparing for a Launch Pharma's High Stakes Gamble
Veeva Systems Inc
@VeevaSystems
Aug 6, 2024
This video provides an in-depth exploration of the high-stakes challenge of preparing for and ensuring launch success in the pharmaceutical industry, with a particular focus on rare diseases. Featuring Florian Schnappauf from Veeva Systems and Andy Eeckhout, Commercial Excellence Lead at ADVANZ PHARMA, the discussion delves into ADVANZ PHARMA's unique journey from a generics company to an innovator in specialized medicines, biosimilars, and rare diseases. Eeckhout shares his extensive experience, emphasizing the critical role of commercial excellence, cross-functional collaboration, data utilization, and technology in navigating complex market landscapes and optimizing patient and customer experiences. The conversation progresses from Eeckhout's personal journey into pharma to defining commercial excellence as the comprehensive effort required to prepare for and sustain product promotion, particularly highlighting the importance of a strong launch pipeline. A significant portion of the discussion is dedicated to the unique complexities of launching products in the rare disease space, where market knowledge, stakeholder identification, and patient journeys are often less defined. Eeckhout elaborates on how ADVANZ PHARMA leverages data, including insights from platforms like Veeva Link, for targeting and segmentation, and adapts its multi-channel strategies based on direct feedback from healthcare professionals (HCPs). The dialogue further explores the crucial interplay between commercial and medical teams, noting ADVANZ PHARMA's lean structure and open communication channels as key enablers for effective pre-launch activities and strategy definition. Eeckhout candidly discusses challenges such as balancing new launch preparations with ongoing business demands and resource limitations. He underscores the importance of data in measuring KPIs and maintaining flexibility to adapt strategies post-launch. The discussion culminates in a forward-looking perspective on enhancing customer experience through continuous feedback and a shift from traditional, volume-based engagement models to more personalized, customer-centric approaches, especially vital in the nuanced rare disease landscape. Key Takeaways: * **Commercial Excellence is Foundational for Launch Success:** Commercial excellence encompasses all preparatory and ongoing support activities required to effectively promote a product, involving cross-functional strategy definition from market access to marketing and medical affairs. * **Technology is Pivotal, Especially Post-COVID:** CRM systems are crucial for tracking information and managing customer interactions. The COVID-19 pandemic accelerated the adoption of technology to enable alternative engagement channels when face-to-face interactions were limited, highlighting the need for robust digital solutions. * **Rare Disease Launches Present Unique Complexities:** Preparing for a rare disease launch is significantly more challenging due to unknown markets, difficulty identifying key stakeholders, and less established patient journeys, necessitating extensive exploratory work and cross-functional collaboration. * **Cross-Functional Collaboration is Essential:** A lean organizational structure and open communication between departments, particularly medical and commercial, are vital for sharing pre-launch insights, defining strategies, and ensuring alignment, overcoming traditional "silo" challenges. * **Data Drives Targeting, Segmentation, and Strategy Adaptation:** Data is crucial for defining physician targets, segmentation, and call planning. Platforms like Veeva Link provide valuable intelligence for identifying key stakeholders, while internal CRM data allows for continuous measurement of KPIs and flexible adaptation of strategies based on field insights. * **Balancing New Launches with Ongoing Business is a Key Challenge:** Managing a robust launch pipeline while sustaining focus and investment in existing products and channels requires careful prioritization and resource allocation, often leading to demanding workloads for specialized teams like CRM and digital. * **Customer Experience is a Critical Differentiator:** In competitive markets, especially rare diseases, an optimal customer experience is paramount. This involves actively seeking feedback from stakeholders on preferred channels and discussion topics, continuous training for field teams, and tailoring engagement strategies to meet specific needs. * **Comprehensive Patient Journey Analysis is Indispensable:** Understanding the patient journey from diagnosis through treatment, including experiences across multiple specialties often involved in rare diseases, is crucial for developing effective tactics and key messages for stakeholders. * **High-Quality Field Data Enhances Strategic Decision-Making:** Capturing crucial information from the field in a compliant and easily analyzable manner (e.g., through CRM pre-launch modules for MSLs and KAMs) ensures that insights on leading physicians, prescribers, influencers, and barriers are leveraged effectively. * **Diverse Stakeholder Engagement Requires Tailored CRM:** Field teams interact with various stakeholders beyond physicians, including nurses, payers, and pharmacists. CRM systems must be configured to capture interactions with these diverse groups and enable multi-channel engagement for all relevant customer types. * **Shift from Classical to Customer-Centric Engagement:** The industry must move away from classical, prescriptive engagement models (e.g., fixed interaction counts or key messages) towards a more customer-centric approach that prioritizes stakeholder feedback on preferred channels and communication content. * **Artificial Intelligence Holds Promise for Data Integration:** AI could significantly enhance the analysis of both external (vendor, market research) and internal (CRM) data sources, helping to match and synthesize information to provide deeper insights and support better decision-making. * **Global Guidance with Local Flexibility is Key for Multi-Country Operations:** In companies with a commercial presence across multiple countries, global strategies and guidance must allow for local adaptation, recognizing that each country may have different market dynamics, commercial models, and stakeholder approaches. **Tools/Resources Mentioned:** * **Veeva CRM:** A customer relationship management system specifically designed for the pharmaceutical industry, used for tracking interactions, managing customer data, and supporting commercial operations. * **Veeva Link:** A platform mentioned for gathering intelligence on key opinion leaders (KOLs) and stakeholders, particularly useful for identifying experts in new or rare disease areas. **Key Concepts:** * **Commercial Excellence:** A strategic approach focused on optimizing all commercial activities, from strategy definition to execution and support, to achieve superior market performance and launch success. * **Rare Disease Launch:** The complex process of introducing a new pharmaceutical product for a rare disease, characterized by unique challenges such as limited patient populations, specialized medical communities, and often undefined market landscapes. * **Customer Journey:** The entire experience a customer (e.g., a healthcare professional or patient) has with a company or product, from initial awareness through engagement, treatment, and ongoing support. * **Multi-channel/Omni-channel Strategy:** An approach to customer engagement that utilizes multiple communication channels (e.g., face-to-face, email, digital platforms, events) to provide a seamless and integrated experience, tailored to customer preferences. * **Targeting & Segmentation:** The process of identifying and categorizing specific groups of customers (e.g., physicians) based on their characteristics, needs, and potential influence, to focus commercial efforts more effectively. * **Adoption Ladders:** A framework used to track the progression of a customer's engagement and acceptance of a product or message, often used by field teams to guide interactions. **Examples/Case Studies:** * **ADVANZ PHARMA's Transformation:** The company's strategic shift from a generics focus to innovative medicines, specialized generics, biosimilars, and rare diseases, highlighting the complexities and opportunities of such a transition. * **Veeva Link for KOL Identification:** ADVANZ PHARMA's use of Veeva Link to identify key stakeholders and gather information on rare diseases, aiding in targeting and segmentation efforts. * **CRM Pre-Launch Module:** The implementation of a specific module within Veeva CRM to capture crucial pre-launch information from MSLs in the field, such as leading physicians, prescribers, and influencers in key accounts, ensuring compliant and useful data collection.
Season 3 Episode 6: The State of Patient Engagement: From a Patient Advocate
Veeva Systems Inc
@VeevaSystems
Dec 4, 2024
This video provides an in-depth exploration of the critical role of patient engagement in clinical trials and pharmaceutical development, featuring a discussion between Manny Vazquez, Director of Strategy for Clinical Data at Veeva Systems, and Trishna Bharadia, a patient engagement consultant and advocate. The conversation is anchored by Trishna's personal journey, stemming from a life-changing multiple sclerosis diagnosis in 2008, which fueled her mission to champion patient-centered healthcare. The discussion highlights the increasing regulatory pressure from bodies like the FDA and EMA for sponsors to demonstrate patient preference integration into clinical research, underscoring the shift towards a more patient-centric paradigm in the life sciences. The podcast delves into key themes such as good patient engagement practices, diversity, equity, and inclusion (DEI) in healthcare and research, and patient involvement in scientific publications. Trishna emphasizes that patient centricity, while a buzzword, holds immense value when implemented correctly. Effective patient engagement leads to better shared decision-making, accelerates medicines to market, makes clinical trials more suitable for participation, and improves adherence rates—a significant challenge in chronic illness management. She argues that the investment in patient engagement is minimal compared to the overall cost and time of drug development, yielding substantial returns in trial recruitment, retention, and ultimately, successful product development. Throughout the discussion, Trishna provides compelling real-world examples to illustrate the profound impact of early and consistent patient involvement. She recounts the failure of an inhaled insulin product that, despite strong scientific backing, was withdrawn due to poor patient acceptance, primarily because practical patient needs (e.g., bulky inhaler, trust in administration) were not considered during design. Another example highlights a spasticity medication that, while effective in trials, failed in real-world use because patients with motor skill challenges could not self-administer it effectively. These cases underscore that patients, living with their conditions daily, identify critical factors that sponsors often overlook, from trial logistics (like icy car parks affecting site visits) to the practicalities of medication disposal in diverse geographic settings. The conversation also touches on the challenges of contracting, ensuring diversity of patient voices, and integrating patients into the publication process, advocating for a shift in mindset from "can't" to "how can we." Key Takeaways: * **Regulatory Imperative for Patient Engagement:** The FDA and EMA are increasingly demanding evidence of patient involvement and consideration of patient preferences in drug development and clinical research, making patient engagement a regulatory necessity, not just a best practice. * **Strategic Value of Early Patient Involvement:** Engaging patients early and consistently throughout the product lifecycle (from research priorities and target product profiles to clinical trial design and technology selection) significantly improves trial recruitment, retention, and the likelihood of successful market adoption. * **Patient Engagement as an Investment:** The time and financial resources required for effective patient engagement are a "drop in the ocean" compared to the overall cost of drug development, with returns far outweighing the investment through more efficient trials and better-accepted products. * **Define Objectives for Engagement Methods:** Sponsors should clearly define their objectives before engaging patients, then select the most appropriate method (e.g., surveys for broad views, advisory boards for in-depth discussion, 1-on-1 interviews for specific insights) rather than defaulting to a single approach. * **Overcoming the "Can't" Mindset:** A fundamental shift in organizational mindset from immediately thinking "we can't" (due to time, resources, legal, or compliance concerns) to "how can we make this happen" is crucial for fostering patient engagement. * **Addressing Challenges in R&D Engagement:** Key challenges include streamlining contracting processes (using plain language templates), ensuring diversity of patient voices (through flexible working, training, language support, and considerate scheduling), and integrating patient input into scientific publications. * **Pragmatic Trial Design:** Clinical trial design, particularly inclusion/exclusion criteria, should be more pragmatic and aligned with real-world patient populations, considering comorbidities, varying BMIs, and practical daily living challenges that can impact participation and adherence. * **Real-World Usability is Paramount:** Drug efficacy proven in controlled trial settings does not guarantee real-world effectiveness if practical aspects of administration or daily use are not considered with patient input, as demonstrated by the spasticity medication example. * **Importance of Localization and International Representation:** Designing trials and products with an understanding of diverse international patient circumstances, including environmental factors, infrastructure, and cultural nuances, is essential for global accessibility and success. * **Expanding Clinical Trial Awareness:** Awareness of clinical trials remains a significant issue, often limited by HCP knowledge. Patient groups, educational initiatives (like the Fuse project), and accessible online resources are vital for empowering patients with information beyond traditional channels. * **Patient Involvement in Scientific Publications:** Patients who contribute to the concept or design of clinical research should be considered for authorship on scientific publications, aligning with ICMJE criteria, though internal company processes often create barriers to this. * **Ethical Imperative for Patient-Centered Design:** Beyond regulatory and commercial benefits, there is an ethical obligation to involve patients in the development of treatments that directly impact their lives, ensuring solutions are truly beneficial and usable. * **Equitable Access to Healthcare:** The ultimate goal should be equitable access to healthcare and treatment, ensuring patient outcomes are not dictated by socio-economic factors, geography, language, or health literacy, thereby unlocking the full potential of modern medicine. **Tools/Resources Mentioned:** * **Veeva Systems:** The host's company, a leading platform in the pharmaceutical industry, particularly for CRM and clinical data. * **MRCT (Multi-Regional Clinical Trials Center):** Mentioned for providing a brilliant glossary of clinical trial terms with lay language definitions and explanations. * **Fuse (Pistoia Alliance):** A nonprofit organization focused on health and data science, involved in a project to raise awareness about clinical trial data transparency through infographics and videos. * **International Council of Medical Journal Editors (ICMJE):** Their criteria for authorship are referenced in the context of patient involvement in scientific publications. **Key Concepts:** * **Patient Centricity:** A philosophy of designing healthcare around the patient's needs, preferences, and values. * **Patient Engagement:** The active involvement of patients in various stages of healthcare, research, and drug development. * **Good Patient Engagement Practice:** Methodologies and strategies for effectively and ethically involving patients, ensuring their input is meaningful and impactful. * **DEI in Healthcare and Research:** Ensuring diversity, equity, and inclusion in patient engagement practices to represent a broad spectrum of patient experiences and needs. * **Pragmatic Trial Design:** Designing clinical trials to better reflect real-world clinical practice and patient populations, often involving broader inclusion criteria and fewer rigid procedures. * **Site Centricity:** A focus on optimizing the experience and efficiency for clinical trial sites, often seen as complementary to patient centricity. * **Health Literacy:** The degree to which individuals have the capacity to obtain, process, and understand basic health information and services needed to make appropriate health decisions. **Examples/Case Studies:** * **Inhaled Insulin Failure:** A science-driven development program for inhaled insulin failed commercially despite FDA approval because patient preferences regarding the bulky inhaler, difficulty in dismantling, inconvenience, and distrust in the administration route were not considered early enough. * **Spasticity Medication Usability Issue:** A medication for spasticity, effective in clinical trials when administered by a nurse, failed in real-world use because patients with motor skill issues could not effectively self-administer it with the puffer device at home, leading to its withdrawal and redesign. * **Winter Site Visit Drop-offs:** A clinical trial experienced a drop in patient attendance during winter months because patients with mobility issues were afraid of falling on iced-over car parks when trying to reach the site entrance, a practical concern overlooked in trial design. * **Rural Medication Disposal:** An example of a patient advocate in rural India highlighting the challenge of disposing of medical waste like syringes due to the lack of appropriate infrastructure, emphasizing the need for localization in product and trial design.
Why We Need to Expand Patient Choice in Clinical Trials
Veeva Systems Inc
@VeevaSystems
Apr 13, 2023
This video provides an in-depth exploration of the evolution and future of clinical trials, emphasizing the critical need to expand patient choice and streamline site operations through technology. Featuring Tim Davis, VP of Strategy for MyVeeva for Patients, and Richard Young, the discussion aims to cut through the industry buzzwords like "decentralized clinical trials," "patient centricity," and "site centricity" to focus on practical, impactful strategies. The conversation traces the journey from archaic paper-based data collection to the promise of integrated digital platforms, highlighting the challenges and opportunities in managing clinical data, engaging patients, and navigating regulatory landscapes. The speakers delve into their early experiences in clinical data management, recalling the days of red and green pens, paper CRFs, and the initial skepticism surrounding electronic patient-reported outcomes (e-PRO) on devices like Palm Pilots. This historical context sets the stage for understanding the persistent challenges in data integration, where e-PRO data was often an "afterthought" and disconnected from the main clinical data management systems. Tim Davis argues that while regulators have become more supportive of digital solutions and patient-owned devices, the industry's own hesitancy and legacy practices often hinder innovation. He redefines patient centricity as simply "choice" and site centricity as "convenience," advocating for flexible, mixed-model approaches to trials rather than rigid adherence to the "decentralized" label. The discussion progresses to envisioning the future of "digital trials," emphasizing the necessity of a consistent, underlying platform that can flex to accommodate diverse patient needs and participation models, regardless of location. The COVID-19 pandemic is cited as a catalyst that exposed the shortcomings of disparate technology "islands" but also demonstrated the industry's capacity for rapid digital adoption. The podcast concludes with a "magic wand" thought experiment, where Tim Davis expresses a desire to overcome the historical baggage of e-PRO/e-COA, enhance patient recognition and transparency by sharing study outcomes, and eliminate the costly and often unnecessary practice of provisioning devices to every patient. The overarching message is to embrace the learnings from recent years and bravely move forward with integrated, patient-focused technological solutions. Key Takeaways: * **Evolution of Clinical Data Management:** Early clinical trials were heavily reliant on manual, paper-based data collection, leading to significant delays (often 8-14 weeks) between data recording and its availability for analysis, hindering timely insights. * **E-PRO Data as an Afterthought:** Historically, e-PRO/e-COA data was frequently treated as secondary to EDC data, often falling outside the primary purview of clinical data management teams, leading to integration challenges and being perceived as an additional burden. * **Bridging Real-time Data Gaps:** While early electronic methods (e.g., pain scales on rudimentary touchscreens) offered real-time patient data, the critical challenge lay in seamlessly integrating this data into the broader study database for comprehensive analysis and regulatory submission. * **Regulators are More Supportive:** Regulators are generally open to and supportive of digital solutions and the use of patient-owned devices in clinical trials, provided fundamental requirements like audit trails and data security are met. Industry hesitancy often stems from internal regulatory interpretations and a reluctance to be "first." * **Patient Centricity is Choice:** True patient centricity should be understood as providing patients with genuine "choice" in their participation, including flexibility in how and where they engage (e.g., remote visits, local pharmacies) and access to digestible educational information about their disease and trial. * **Site Centricity is Convenience:** Site centricity focuses on offering convenience to clinical sites through integrated technology solutions that operate "under one roof" with a single login, intuitive interfaces, and reduced administrative burden, especially when balancing multiple stakeholder demands. * **Rethinking "Decentralized Clinical Trials":** The term "decentralized clinical trials" is viewed as potentially restrictive, advocating instead for "digital trials" that offer inherent flexibility—a mix of remote, in-person, and hybrid approaches—tailored to patient needs and study design, rather than a rigid, all-or-nothing model. * **Integrated Data Strategy:** Data managers should adopt an "end-to-beginning" approach, considering how e-PRO data will integrate into the final data warehouse and statistical tables from the initial design phase. Consistent patient identification across all systems (EDC, RTSM, e-PRO) is paramount to avoid transcription errors and ensure data integrity. * **Overcoming E-PRO Legacy:** The industry must move past outdated e-PRO/e-COA practices, such as the historical necessity of providing every patient with a company-issued device (e.g., Palm Pilots), which is now an expensive and often unnecessary barrier to innovation. * **Enhancing Patient Recognition:** A significant improvement would be to "switch on" greater patient recognition and transparency by providing participants with high-level summaries of study outcomes, information on drug publication, and ongoing engagement, fostering trust and encouraging future participation. * **Eliminate Mandatory Device Provisioning:** The practice of mandatorily provisioning devices to all patients is costly, logistically complex, often disliked by sites, and frequently unnecessary, as most patients possess their own, often superior, mobile devices. A choice-based model is preferred. * **Leveraging COVID-19 Learnings:** The pandemic demonstrated the industry's ability to rapidly adopt digital technologies and maintain trial continuity under extreme pressure. These learnings about technology's potential and the need for adaptable operating models should inform future trial design and not be abandoned. * **Platform-Based Approach:** Moving away from disparate "islands" of technology vendors towards a unified, integrated platform approach (like Veeva's ecosystem) can significantly reduce timelines, improve data flow, and streamline the management of diverse data sources. **Tools/Resources Mentioned:** * **Palm Pilots:** Mentioned as an early, rudimentary device used for e-PRO data collection. * **EDC (Electronic Data Capture):** A standard system for collecting clinical trial data. * **e-PRO (Electronic Patient-Reported Outcomes):** Electronic methods for patients to report their own health status. * **e-COA (Electronic Clinical Outcome Assessment):** A broader term encompassing e-PRO and other electronic assessments. * **MyVeeva for Patients:** A patient-facing technology platform from Veeva Systems. **Key Concepts:** * **Patient Centricity:** Redefined as providing patients with "choice" and options in their clinical trial participation, focusing on convenience and accessibility. * **Site Centricity:** Defined as providing "convenience" to clinical sites through integrated and intuitive technology solutions that simplify workflows and reduce burden. * **Digital Trials:** A preferred term over "decentralized clinical trials," emphasizing the use of technology to enable flexible, mixed-model patient participation (remote, in-person, hybrid) based on individual needs and study requirements. * **Data Islands:** Refers to the common problem of disparate, unintegrated technology systems used across different aspects of clinical trials, leading to inefficiencies and data management challenges. **Examples/Case Studies:** * **Early Osteoarthritis Studies:** Use of rudimentary touchscreen devices in the early 2000s to collect pain scales from osteoarthritis patients, highlighting early efforts in e-PRO. * **Photocopied CRF Pages:** An anecdote about monitors photocopying paper CRF pages for visual analog scales, which resulted in incorrect measurements (e.g., 9.7cm instead of 10cm), underscoring the critical importance of data integrity and the flaws of paper-based methods for primary endpoints. * **COVID-19 Pandemic Impact:** The pandemic forced clinical trials to rapidly adopt layered technologies and adapt operating models, exposing both the challenges of disparate systems and the potential for technology to maintain trial continuity and accelerate drug development.
Season 3 Episode 3: Does Data Science Require Data Perfection?
Veeva Systems Inc
@VeevaSystems
Oct 9, 2024
This video provides an in-depth exploration of the evolution of data science, the practical application of artificial intelligence, and the concept of "data perfection" within the pharmaceutical and life sciences industries. Hosted by Richard Young, VP of Clinical Data Strategy at Veeva, the episode features Demetris Zambas, Global Head of Data Monitoring and Management at Pfizer. Zambas shares his extensive 33-year journey in the industry, from laboratory roles to pioneering clinical data management, and discusses how his early experiences shaped his focus on organized, outcome-driven data. The conversation emphasizes the critical role of data in proving hypotheses and supporting regulatory submissions, highlighting that the entire investment in a clinical trial hinges on generating "fit for purpose" data. A significant portion of the discussion centers on the transformation of data management into data science. Zambas argues that a good data manager has always been a data scientist, characterized by critical thinking and the ability to ensure data is trustworthy and adequate for its intended purpose, rather than merely adhering to checklists. He recounts the period when data management was commoditized, focusing on output metrics like "queries per day," which obscured its true value. The video also delves into the strategic use of AI, likening it to a specialized tool rather than a universal solution. Zambas advocates for AI as an "assistant" or "co-pilot" to data scientists, capable of automating routine checks and flagging critical insights, thereby accelerating processes and allowing human experts to focus on higher-value tasks. The conversation further explores the importance of industry collaboration and regulatory engagement. Zambas details his significant contributions to the Society for Clinical Data Management (SCDM), including making the Global Clinical Data Management Plan (GCDMP) publicly accessible to facilitate regulatory referencing and broader industry benefit. He stresses the ethical imperative for companies to collaborate on non-competitive issues like fraud and anomaly detection, citing the unprecedented cross-company data management calls during the COVID-19 vaccine development as a prime example. The video concludes by addressing the convergence of central monitoring and data science roles, the growing recognition of data management's value in areas like Real-World Evidence (RWE), and Zambas's personal aspirations for overcoming resistance to change and improving global access to medicines. Key Takeaways: * **Evolution of Data Management to Data Science:** The role of a data manager has evolved from a commoditized function focused on output metrics (e.g., queries per day) to a critical data science discipline requiring deep critical thinking and an outcome-oriented approach to ensure data fitness for regulatory consumption. * **"Fit for Purpose" Data Over Absolute Perfection:** The standard for data quality should be "fit for purpose" – adequate for proving a hypothesis and supporting regulatory submissions – rather than striving for an unattainable "perfection." Effort should be tiered, with significant focus on endpoints and safety data. * **AI as a Strategic Assistant/Co-pilot:** AI should be viewed as a specialized tool, not a "Swiss army knife." Its most impactful application in data science is as an assistant or co-pilot, automating routine validation checks and highlighting critical data patterns for human data scientists, thereby accelerating insights and efficiency. * **Outcome-Driven Focus:** It is crucial to focus on meaningful outcomes (e.g., earlier market access for therapies) rather than solely on output metrics. Data professionals must articulate how seemingly "boring" operational improvements, potentially driven by AI, can lead to significant strategic advantages. * **Importance of Industry Collaboration:** For non-competitive areas like fraud detection, anomaly detection, and navigating shared challenges (e.g., regulatory communication during a pandemic), industry-wide collaboration among data management leaders is vital for collective success and patient benefit. * **SCDM's Role in Discipline Advancement:** Organizations like SCDM are crucial for enabling data professionals to impact their discipline, establish best practices (e.g., GCDMP), and engage directly with regulators (FDA, EMA, PMDA) to shape industry standards. * **Public Accessibility of Guidelines:** Making industry guidelines, such as the GCDMP, publicly available is essential for regulators to reference them and for fostering broader adoption and understanding across the community. * **Convergence of Central Monitoring and Data Science:** The roles, technologies, and processes of central monitoring and data science are increasingly converging, suggesting a future where data management and monitoring plans are integrated to drive more detailed, signal-driven data dives. * **Increased Recognition of Data Management's Value:** The discipline has transitioned from being considered non-core and outsourced to being recognized as a critical function, now actively invited to contribute to new areas like Real-World Evidence (RWE) data structuring and management. * **Overcoming Resistance to Change:** A significant impediment to progress is resistance to change. Professionals are encouraged to at least "try" new approaches in a controlled manner, even if not fully convinced, to foster innovation and efficiency. * **Data Quality for Regulatory Trust:** The ultimate goal of clinical data management is to deliver data that is robust enough to convince regulators and stakeholders that it is trustworthy for proving hypotheses and validating endpoints, thereby justifying the significant investment in clinical trials. * **Global Access to Medicines:** Beyond the technical aspects, the broader mission of data management and clinical trials is to facilitate the timely and equitable access to life-saving medicines for patients worldwide, a deeply motivating factor for industry professionals. Tools/Resources Mentioned: * **Veeva:** The host, Richard Young, is VP of Clinical Data Strategy at Veeva. * **Face Forward:** An older EDC (Electronic Data Capture) system mentioned in the context of a tech transfer. * **SCDM (Society for Clinical Data Management):** A key industry organization discussed for its role in advancing the data management discipline. * **GCDMP (Global Clinical Data Management Plan):** A set of guidelines developed by SCDM, made public to aid regulatory referencing and industry best practices. * **Python/R:** Mentioned as utilities that a data scientist would use, rather than being the definition of data science itself. Key Concepts: * **Fit for Purpose:** The primary definition of quality in clinical data, meaning the data is adequate and trustworthy for its intended use, particularly for regulatory submissions and proving hypotheses. * **Data Commoditization:** A historical period where data management was viewed as a low-value, outsourceable function, often measured by simple output metrics like "dollars per page" or "queries per day." * **Central Monitoring:** The process of remotely reviewing aggregated data to identify potential risks, trends, or issues across clinical trial sites, distinct from traditional on-site field monitoring. * **Risk-Based Monitoring (RBM):** An approach to clinical trial oversight that focuses monitoring activities on the most critical data and processes, based on identified risks, to ensure patient safety and data quality. * **Real-World Evidence (RWE):** Data derived from real-world settings (e.g., electronic health records, claims data) used to make inferences about the usage and potential benefits or risks of a medical product. * **AI as Co-pilot/Assistant:** A concept where AI systems augment human capabilities by automating routine tasks, analyzing large datasets, and flagging critical information, allowing human experts to focus on complex problem-solving and decision-making. Examples/Case Studies: * **Pfizer's COVID Vaccine Development:** Demetris Zambas described regular, senior-leader-blessed calls between heads of data management across competing companies (e.g., J&J, AstraZeneca) during the COVID vaccine studies to share challenges and best practices, demonstrating industry collaboration for public good. * **CAR T-cell Therapy Success:** Zambas recounted the story of the first young girl cured of leukemia using CAR T-cell therapy, highlighting how a data manager at UPenn identified a critical pattern of increasing cytokine levels, prompting medical intervention and saving the patient's life. This example underscores the direct patient impact of meticulous data management. * **Challenges with RWE Data:** The discussion touched on how Real-World Evidence data, when initially received, is often unstructured and "a mess" compared to carefully designed clinical trial data, leading to invitations for data management experts to help structure, control, and manage it.
AstraZeneca: The CTMS CRA Experience
Veeva Systems Inc
@VeevaSystems
Feb 22, 2021
This video provides an in-depth exploration of AstraZeneca's strategy for achieving high end-user adoption during the implementation of a cloud-based Clinical Trial Management System (CTMS), specifically utilizing the Veeva Clinical Vault platform. The discussion centers on how the pharmaceutical giant proactively engaged Clinical Research Associates (CRAs) and site-facing personnel—the primary users—throughout the entire project lifecycle, from initial evaluation to post-go-live optimization. The core philosophy driving this approach was the commitment to "doing this with them and for them," rather than imposing change "to them," recognizing that poor user experience can turn intended benefits into burdens for clinical staff. This focus on user-centric design and change management is critical for regulated systems where adoption directly impacts data quality and compliance. AstraZeneca employed a highly structured methodology for user engagement, beginning well before vendor selection. During the evaluation process, they established focus groups composed of CRAs and global study management teams. These groups actively participated in vendor demos and, crucially, were given access to a dedicated sandbox environment for the competing CTMS platforms. This allowed end-users to gain hands-on experience, identify potential challenges, and provide scored feedback on usability and functionality. Following the selection of Veeva, these users remained involved throughout the deployment phase, helping to define and refine processes by articulating the pain points of the legacy systems and specifying desired changes, ensuring that the final configuration addressed real-world operational needs in clinical operations. Six months post-go-live (which occurred in June of the previous year), the company reported mixed but generally positive reviews, acknowledging that managing the "change curve" is an ongoing process. While some users immediately embraced the streamlined system, others required more time to transition from established habits. To manage this transition and ensure continuous improvement, AstraZeneca established a rapid feedback loop. Three months after launch, they deployed a comprehensive survey to their site monitoring community across 38 countries, achieving an impressive response rate of 60% or more. This feedback was immediately channeled back into the development cycle, demonstrating a commitment to agile iteration even within a regulated environment. The feedback highlighted several areas of significant improvement for CRAs. One key enhancement was the introduction of the "user tasks" functionality, a new feature that helps track activities directly within the platform, moving task management away from external tools like email. Users also appreciated the single, unified interface provided by the Vault platform, which offers single sign-on across applications and allows for seamless navigation between milestones, documents, and other tracking elements. Importantly, the feedback often centered on minor configuration changes—such as converting a "yes/no" dropdown to a radio button—which, despite their simplicity, had a major positive impact on user efficiency. AstraZeneca’s dedicated platform team, consisting of both business and IT staff, has established a rapid cadence of internal releases (three major and eight minor releases in the post-go-live period) to quickly incorporate these small but impactful user-suggested improvements into the platform. ### Key Takeaways: * **Prioritize User-Centric Implementation:** Successful CTMS deployment requires engaging end-users (CRAs, monitors, study managers) early and often, treating the implementation as a collaborative effort ("with them and for them") rather than a mandate imposed upon them. * **Utilize Sandbox Environments for Evaluation:** Providing end-users with hands-on access to sandbox environments during the vendor evaluation phase allows them to test usability and functionality in a low-stakes setting, resulting in more informed selection decisions and better initial buy-in. * **Integrate User Feedback into Configuration:** Involve key user groups in defining the "to-be" processes by identifying pain points in legacy systems and specifying desired changes, ensuring the new system configuration directly addresses operational inefficiencies. * **Expect and Manage the Change Curve:** Acknowledge that user adoption will be mixed initially; while some users will immediately find the new system streamlined, others will require time and guidance to transition from old ways of working, particularly those who have used the previous system for a long time. * **Establish a Rapid Feedback Cadence:** Deploying a comprehensive user survey shortly after go-live (AstraZeneca achieved a 60%+ response rate three months post-launch across 38 countries) provides actionable data for immediate system optimization. * **Small Changes Yield Big Impact:** User feedback often focuses on minor configuration tweaks (e.g., changing input methods like dropdowns to radio buttons); these small, quality-of-life improvements can significantly enhance user experience and efficiency. * **Leverage Platform Features for Task Management:** The "user tasks" functionality within the CTMS is a critical feature for streamlining operations, helping to move tracking activities and communications away from unmanaged external channels like email. * **Value a Single, Unified Interface:** Users highly appreciate the benefits of a single sign-on and unified interface (like the Veeva Vault platform), which allows seamless navigation between core functionalities (milestones, documents, tasks) without clicking between multiple disparate applications. * **Maintain a Dedicated Platform Team:** Having a dedicated internal team (comprising both business and IT expertise) is essential for maintaining a rapid release cadence (AstraZeneca reported three major and eight minor releases post-go-live) necessary to quickly implement user-suggested changes. * **Consult with the Vendor on Configuration:** Utilize the vendor (e.g., Veeva) as a resource to bounce ideas off and seek advice on the best configuration approach for specific user requirements, ensuring changes are implemented in the most effective and streamlined manner. ### Tools/Resources Mentioned: * **Veeva Clinic Vault Platform:** The overarching cloud platform used for clinical operations. * **Veeva CTMS (Clinical Trial Management System):** The specific application within the Vault platform being implemented. ### Key Concepts: * **CRA (Clinical Research Associate) / Monitor:** Site-facing personnel responsible for monitoring clinical trials, ensuring compliance, and managing data quality at investigative sites. They are the primary end-users of the CTMS. * **CTMS (Clinical Trial Management System):** Software designed to manage and track the planning, execution, and reporting of clinical trials, including site information, milestones, and monitoring activities. * **Sandbox Environment:** A testing or development environment that isolates changes from the live production system, used here to allow end-users to safely "play around" with the system during the evaluation phase. * **Change Curve:** The psychological process individuals go through when adapting to significant organizational change, often involving initial resistance followed by exploration and eventual commitment.
Season 2 Episode 7: Sites Are Voicing Their Concerns, But Are We Listening?
Veeva Systems Inc
@VeevaSystems
Jan 31, 2024
This podcast episode, hosted by Veeva Systems Inc, provides a critical examination of the challenges faced by clinical trial sites, emphasizing the detrimental effects of inconsistent technology and poor industry communication on site operations and patient care. Featuring Vivienne van de Walle, a medical director and research site founder, and Bree Burks, Veeva's VP of Strategy for Site Solutions, the discussion centers on the urgent need for sponsors, CROs, and vendors to genuinely listen to sites, simplify processes, and integrate technology more effectively to support, rather than hinder, clinical research. The conversation is framed around the idea that research happens *at the site*, making site feedback paramount for industry improvement. A major theme explored is the overwhelming technological burden placed on sites, which Dr. van de Walle vividly describes as an "escape room" due to the multitude of vendors, codes, URLs, and activation processes required for a single trial. This complexity takes time away from patient care, which sites view as their primary pain point. Beyond technology, universal challenges include staffing shortages—often because young professionals are unaware of clinical research as a viable career path—and persistent issues with budgeting, finances, and timely payments. The speakers stress that technology should be a supportive tool, not the focus of the trial itself, and criticize the current practice of providing training without allowing sites hands-on experience until the first patient is present. The discussion pivots to the critical need for consistency and interoperability. Sites often deal with different activation methods (e.g., e-diaries, iPads, portals) even within trials run by the same service provider, highlighting a lack of internal coordination among project teams. A key procedural flaw identified is the lack of transparent issue tracking; site deviations are often logged for problems caused by vendors, couriers, or malfunctioning technology, leading to unfair negative evaluations of the site's performance. Dr. van de Walle shared a crucial insight: vendors often assume they are delivering good service if sites resolve issues internally without calling the help desk, reinforcing the need for a transparent, industry-wide issue log that tracks problems back to the responsible party (vendor, courier, or sponsor). Looking toward the future, the speakers advocate for significant procedural and technological shifts. Bree Burks emphasizes embedding clinical trials into routine healthcare to increase patient access and reduce the variation in how trials are conducted. Dr. van de Walle introduced a successful operational model at her site where staff are assigned specialized roles (e.g., e-diaries, data entry) based on their aptitude, rather than forcing one coordinator to handle all technologies from A to Z. The ultimate hope is to move away from a "tick box" compliance culture toward sensible, quality-focused evaluations and to achieve true system communication, allowing seamless data flow across different applications and stakeholders, similar to consumer technology standards. Key Takeaways: * **Technology Overload is a Major Pain Point:** Clinical trial sites face an overwhelming "escape room" scenario due to managing a multitude of disconnected vendor systems, requiring excessive time spent on logins, codes, and activations that detracts from patient care. * **Lack of Standardization and Consistency:** Even within the same vendor or sponsor, trials often use different methods for activating patient technology (e.g., e-diaries via iPad vs. portal), creating unnecessary complexity and friction for site staff. * **Need for System Interoperability:** The industry must move beyond siloed systems and enable technology platforms to communicate seamlessly, allowing for a "one entry, read many times" data flow, which is crucial for efficient data engineering and site operations. * **The Deviation Log Problem:** Current regulatory processes unfairly penalize sites by logging deviations for issues caused by external factors like vendor software bugs, late drug delivery, or courier errors, masking the true source of operational failures. * **Mandate Transparent Issue Tracking:** The industry needs a transparent, shared issue log (or deviation log) that tracks problems back to the responsible party (sponsor, CRO, vendor, or courier) to ensure accountability and drive necessary software or process improvements. * **Technology Training Must Be Hands-On:** Sites often receive training but lack practical, hands-on experience with new systems until the first patient visit, turning the initial patient into a "trial in the trial" and weakening the patient-caregiver relationship. * **Shift Staffing Models:** Sites can optimize efficiency and staff satisfaction by moving away from the traditional model of one coordinator handling all aspects (A-to-Z) of a trial, instead assigning specialized roles based on staff aptitude (e.g., one person excels at e-diaries, another at data entry). * **Address Patient Access and Centricity:** Current technology fails patients by making it nearly impossible to easily find and screen for clinical trials; true patient centricity requires designing technology that prioritizes simple access and communication. * **Avoid Assumptions about Technology Literacy:** Sponsors and vendors must avoid assuming technology access (e.g., internet, computers) or literacy based on patient demographics (e.g., age), as this creates diversity barriers and complicates trial participation. * **Eliminate the "Tick Box" Culture:** The industry must move away from simply ticking boxes for training completion and compliance, focusing instead on the quality and sensible application of training and procedures to ensure actual preparedness and quality outcomes. * **Clinical Trials Must Be Embedded in Routine Care:** To increase patient access and physician participation, clinical research needs to be simplified and integrated into the standard healthcare system, rather than remaining a specialized, separate activity. * **Acknowledge Site as the Hub:** Sponsors and CROs must recognize that the site is the central "Lynch pin" and the hub of all information exchange (sponsor to site, site to patient, data return), requiring robust support and communication infrastructure. Tools/Resources Mentioned: * **Veeva ID:** A Veeva product announced at the summit, designed to improve the site experience for logging into various systems. * **Veeva Study Portal:** A Veeva product announced at the summit, aimed at streamlining site operations. * **EDC (Electronic Data Capture):** Mentioned as a historical technological shift 20 years ago that failed to account for increased site workload. * **eDiaries:** Electronic patient diaries used in trials. * **IVRS (Interactive Voice Response System):** Mentioned as a historical technology used for randomization. Key Concepts: * **Patient Centricity:** The concept of designing trials and technology around the needs and experiences of the patient, which the speakers argue is currently lacking in technology implementation. * **Site Solutions:** A strategy area within Veeva focused on improving the tools and processes used by clinical trial sites. * **GxP / 21 CFR Part 11 (Implied):** The regulatory environment is referenced through the discussion of protocol rigidity, deviations, and the need for audit trails and transparency in issue logging.
Season 2 Episode 6: Transforming Clinical Operations: What Comes Next?
Veeva Systems Inc
@VeevaSystems
Jan 31, 2024
This podcast episode, hosted by Veeva Systems, features an in-depth conversation with Emma Earl, Bayer’s Head of Clinical Trial Management Services and Solutions, focusing on the dramatic transformation of clinical operations over the last two decades and the challenges and opportunities that lie ahead. The discussion centers on the shift from legacy paper-based systems to modern digital platforms, emphasizing the critical balance between people, process, and technology required to deliver efficient and patient-centric clinical trials. Emma Earl, drawing on over 20 years of industry experience, provides a perspective rooted in operational history, having transitioned from a Clinical Research Associate (CRA) role into defining and implementing clinical trial technologies, including a significant focus on Veeva Vault clinical implementations. A major theme explored is the industry's evolution from completely paper-based processes—including paper CRFs, manual data entry, and physical document handling—to the current digital landscape utilizing Electronic Data Capture (EDC) and modern Clinical Trial Management Systems (CTMS). This transition, while initially met with skepticism, has provided crucial visibility and transparency, enabling organizations like Bayer to look across studies, identify trends, and assess overall performance metrics. Earl highlights that the complexity of modern protocols, including those for advanced research like gene and cell therapies, necessitates flexible systems and processes that can accommodate "edge cases" without creating 25 different workflows, driving the need for a simplified, consolidated technology landscape. The speakers dedicate significant time to the perennial challenge of balancing people, process, and technology. While technology enables efficiency and reduces errors, the human element remains paramount, especially since clinical research fundamentally occurs when people (site staff, patients) interact. Earl argues that technology should serve to enable people, making processes better and easier. She stresses that the ultimate goal is not just adding new functionality but fixing existing problems, exemplified by the energy derived from successful process simplification, such as reducing the number of system roles. Furthermore, the conversation addresses the evolving definition of "monitoring," which has broadened beyond the traditional CRA role to include collaborative data review between clinical operations and data management, necessitating clear role definitions to avoid inefficiency and duplication of work. ### Detailed Key Takeaways * **Consolidating the System Landscape is a Key Priority:** Bayer's current focus is streamlining its technology environment by minimizing the need for complex integrations and leveraging platform features (like Veeva Vault) where possible. The goal is to achieve a simpler, more efficient landscape, with the ultimate win being the ability to retire legacy systems (e.g., a final Legacy CTMS). * **Process Re-evaluation Must Accompany Technology Implementation:** Implementation projects should be used as opportunities to critically revisit and question existing processes, rather than simply "lifting and shifting" old workflows onto new technology. This ensures that new systems are utilized to their full potential for optimization. * **Inefficiency is the Primary Target for Elimination:** The greatest wish for transformation is the elimination of inefficiency—getting rid of unnecessary steps and processes that exist only because of historical incidents or inertia. Organizations must be willing to stop and rethink whether long-standing processes are still required. * **Scientific Complexity Drives Operational Challenges:** The increasing complexity of clinical protocols, especially in advanced therapies, demands systems and processes that can accommodate numerous "edge cases" without sacrificing standardization or creating overly fragmented workflows. * **People are the Most Important Element in the Triad:** While technology and process are critical, clinical trials cannot function without people. Technology's role is to enable staff to perform better, recognizing that success hinges on people's willingness and mindset to leverage new processes and systems. * **Site Centricity is a Catalyst for Overall Success:** Solving the problem of making sites happy is identified as the single most impactful change an organization can make. Site satisfaction has a huge knock-on effect on patient experience and the sponsor's ability to run trials quickly. * **Avoid Disproportionate Prioritization of Users:** The industry often vacillates between focusing heavily on sites or heavily on patients. True success requires a balancing act—solving the "Rubik's Cube" by addressing the needs of all six sides (all stakeholders) simultaneously. * **The Definition of Monitoring Has Evolved:** The term "monitoring" is now much broader than traditional CRA site visits. Clarity is needed between clinical operations and data management regarding their respective roles in data review and oversight to ensure efficient collaboration and prevent duplication of effort. * **Early, Broad Exposure is Formative for Leaders:** Starting in a small biotech or CRO, where individuals are exposed to a wide range of tasks (e.g., data management, monitoring, closeout visits), provides a critical foundation and broad experience that shapes future technology and process definition roles. * **Learning Comes from Problem Solving:** As an industry lesson, it is crucial to remember that "you never learn anything from something that goes well." Troubleshooting and problem-solving exercises, often triggered by new scientific or operational scenarios, generate energy and lead to innovation. ### Key Concepts * **Veeva Vault Clinical Implementations:** The use of Veeva's suite of clinical applications (e.g., CTMS, eTMF) to manage and execute clinical trials, a core technology focus for Bayer's clinical operations team. * **Incompetence Intolerance:** A personality trait described as a strength, where individuals are driven by a desire to fix inefficient or poorly designed processes, often leading them toward technology and process optimization roles. * **Site Centricity:** The strategy of designing clinical trial processes and technology solutions with the needs and pain points of the investigative sites (hospitals, clinics) as a primary focus, recognizing their crucial role in patient interaction and data collection. * **Legacy CTMS:** Older, often fragmented or non-integrated Clinical Trial Management Systems that modern organizations are actively trying to replace or consolidate into unified platforms. ### Examples/Case Studies * **The Shift from Paper-Based Monitoring:** The speaker recalls the early days of monitoring, involving paper CRFs, DCFs, green pens, Post-it notes, and physically bundling documents in cars—a stark contrast to current digital access via websites and EDC systems. * **EDC Adoption Skepticism:** The initial rollout of laptops for Electronic Data Capture (EDC) was met with widespread industry skepticism that "this is never going to work," highlighting the initial resistance to digital transformation. * **Collaboration-Driven Process Change:** Bayer recently had to re-evaluate how they number their studies due to a new collaboration, demonstrating how external factors force internal process adjustments and problem-solving exercises within the team.
COVID-19’s Impact on Scientific Engagement interview
Veeva Systems Inc
@VeevaSystems
May 26, 2020
This video provides an in-depth exploration of the profound and sudden impact of the COVID-19 pandemic on scientific engagement within the pharmaceutical industry, focusing specifically on the role of Medical Science Liaisons (MSLs) and Medical Affairs organizations. The discussion, featuring Brian Harper, VP of Medical Content Strategy at Veeva Systems, frames the pandemic as the "ultimate digital restructure," forcing immediate and long-term changes in how pharmaceutical companies disseminate scientific data and interact with Healthcare Professionals (HCPs). The immediate effects included the near-total cessation of face-to-face engagements, canceled conferences and congresses, and a rapid pivot to virtual platforms like Zoom and Skype for scientific exchange. The analysis highlights that this shift necessitated MSLs to quickly adopt new skills to ensure virtual interactions remained effective, efficient, and maintained continuity with previous field discussions. A key insight derived from an MSL Society study validated the rapid uptake of virtual platforms and revealed significant shifts in MSL activities. With reduced travel and in-office visits, MSLs dedicated more time to reviewing scientific literature to strengthen their therapeutic knowledge and supported other functions within Global Medical Affairs (GMA). Notably, Medical Information teams experienced a spike in activity and requests, particularly those related to COVID-19, leading to MSLs being redeployed to support these functions and manage increased demand. A critical finding regarding virtual engagement was the duration of these interactions. MSLs were able to carry on conversations with HCPs ranging from five to thirty minutes. This finding has significant implications for content strategy, requiring organizations to fuel these engagements with highly effective, compliant, and correctly versioned content tailored for shorter, focused virtual interactions. Furthermore, the speakers noted that scientific experts (HCPs) demonstrated a newfound receptivity to virtual engagements, likely influenced by their own shift to telemedicine with patients. This suggests that virtual engagement is not a temporary fix but will become a permanent, strategic component of scientific and thought leader engagement plans moving forward, requiring companies to optimize their business processes accordingly. The video also addresses the challenge of data dissemination in the absence of traditional medical conferences. The cancellation of these large-scale events forces organizations to develop non-traditional methods to get their data out to a broad audience in a meaningful way. This environment elevates the value of Medical Information teams, which remain the primary conduit for fielding specific medical requests. The need to staff and flex Medical Information teams—potentially by integrating MSLs or other GMA experts—to meet increased demand underscores the necessity for robust, scalable systems and processes to manage the influx of scientific inquiries and ensure timely, compliant responses. Key Takeaways: • **Digital Restructure Acceleration:** The pandemic acted as the "ultimate digital restructure," immediately eliminating traditional face-to-face MSL engagements and forcing a rapid, industry-wide pivot to virtual platforms (Zoom, Skype) for scientific exchange. • **New MSL Skill Requirements:** MSLs must acquire and refine new skills specifically for delivering engaging and effective virtual interactions to maintain business continuity and ensure discussions with HCPs are efficient and productive. • **Shift in MSL Focus:** With reduced travel, MSLs are spending more time on internal activities, including deeper dives into scientific literature to strengthen therapeutic knowledge and supporting other Global Medical Affairs (GMA) functions. • **Spike in Medical Information Demand:** Medical Information teams saw a significant increase in call volume and requests, particularly those related to COVID-19, necessitating organizations to assess and potentially flex staffing models by leveraging MSLs to support the increased demand. • **Optimizing Content for Virtual Engagement:** The duration of virtual conversations (5 to 30 minutes) requires organizations to rethink content strategy, ensuring MSLs have access to compliant, high-quality, and appropriately versioned content tailored for shorter, highly focused digital interactions. • **HCP Receptivity to Virtual:** Scientific experts are now generally receptive to virtual engagements, suggesting a permanent shift in interaction preference, likely influenced by their own adoption of telemedicine. • **Permanent Component of Strategy:** Virtual engagement is not a temporary measure but will become a fixed, strategic component of future scientific engagement and thought leader plans, requiring long-term optimization of business processes. • **Non-Traditional Data Dissemination:** The cancellation of major congresses forces companies to explore and implement non-traditional, digital methods for disseminating critical scientific data to a broad audience effectively. • **Value of Medical Information:** The Medical Information function is critical in the new environment, serving as the primary channel for fielding specific medical requests and demonstrating its value by ensuring customers receive necessary information despite disruptions to traditional channels. • **Systemic Optimization Required:** Companies must look beyond immediate fixes and focus on optimizing their core business processes to integrate virtual engagement seamlessly, ensuring long-term efficiency and compliance in the new hybrid environment. Tools/Resources Mentioned: * Veeva Systems (Host and context provider) * Zoom (Virtual engagement platform) * Skype (Virtual engagement platform) * MSL Society (Source of the study quantifying the impact on MSL activities) * Veeva Commercial & Medical Summit Online (Upcoming industry event focused on medical affairs strategy) Key Concepts: * **Scientific Engagement:** The interaction between pharmaceutical company representatives (like MSLs) and Healthcare Professionals (HCPs) to exchange scientific and medical information. * **MSL (Medical Science Liaison):** Field-based professionals within Medical Affairs who engage with key opinion leaders (KOLs) and HCPs to discuss scientific data and therapeutic areas. * **Global Medical Affairs (GMA):** The department responsible for ensuring the scientific and medical integrity of a company's products, including managing MSLs and Medical Information. * **Medical Information:** The team responsible for receiving, documenting, and responding to unsolicited requests for medical information from HCPs and consumers. * **Digital Restructure:** The forced, rapid transformation of business models and processes toward digital methods, catalyzed by external events like the pandemic.
Season 2 Episode 9: Are We Too Risk Averse in Clinical Research?
Veeva Systems Inc
@VeevaSystems
May 29, 2024
This episode of the State of Digital Clinical Trials podcast features a discussion between Richard Young and Ken Getz, Executive Director of the Tufts Center for the Study of Drug Development (CSDD), exploring the evolution of clinical research, the industry’s pervasive risk aversion, and the transformative role of data and patient engagement. Getz provides a historical perspective spanning 35 years, categorizing industry shifts from the privatization of research in the late 80s/early 90s to the focus on operational feasibility and efficiency in the 2000s, culminating in the current era defined by personalized medicine and patient engagement. A central theme is the industry's conservatism, which Getz argues is reinforced by historically low success rates and worsening phase transition probabilities, creating inertia against adopting novel trial designs and executional models. The discussion heavily emphasizes the changing role of data management, transitioning from siloed, reactive, paper-based data to centralized Electronic Data Capture (EDC) systems, and now moving toward integrated, cloud-based, and synchronized data environments leveraging data science and AI enablement for predictive qualities. A critical insight shared by Getz is the quantitative evidence demonstrating the increasing complexity and inefficiency of trials; his research shows that the average number of protocol amendments has increased significantly, often leading sites to bundle necessary scientific changes until they reach a threshold deemed worth the administrative burden, resulting in suboptimal study execution in the interim. The speakers agree that if clinical trials were redesigned today, they would look fundamentally different, driven by novel, decentralized models and greater site autonomy in technology selection (e.g., telemedicine solutions). Furthermore, the conversation addresses the crucial need for improved collaboration and trust across the ecosystem—between sponsors, CROs, investigative sites, and patients. Getz, who also founded CISCRP (Center for Information and Study on Clinical Research Participation), highlights the industry's failure to establish sustainable public trust and perceived value in clinical research, noting that the awareness boost from the COVID-19 pandemic was temporary. He stresses that while the intent for patient centricity is widespread, execution is lacking, often resulting in decentralized patient engagement functions focused on short-term recruitment goals rather than long-term partnership. The ultimate aspirational goal is to remove the separation between clinical care and clinical research, moving toward a "learning health model" that leverages existing infrastructure and data within the clinical care environment to accelerate research and elevate public health. Key Takeaways: • **Rising Protocol Complexity and Amendments:** Research confirms that protocol complexity is a persistent issue, with a significant increase in the number of protocol amendments over the last seven years. This inefficiency is compounded by the practice of delaying necessary scientific amendments until enough changes accumulate, leading to periods of suboptimal study execution. • **Data Transition to Predictive AI:** The evolution of data in clinical research has moved from siloed, reactive data to strategic assets. The current phase is defined by the promise of AI and machine learning, requiring greater focus on data compatibility, interoperability, harmonization, and centralized, synchronized, cloud-based access to leverage predictive analytics. • **Risk Aversion Hinders Innovation:** The industry remains fundamentally risk-averse, a mindset reinforced by historically low success rates in phase transitions. Overcoming this conservatism requires a cultural shift and a willingness to embrace entrepreneurial approaches—succeeding quickly but failing early—without compromising patient safety. • **Site Enablement and Autonomy:** The current "sponsor-flows-downstream" model is inefficient. Innovation should be sourced from investigative sites, which often solve problems locally (e.g., telemedicine). Sponsors and CROs should accommodate site-preferred technologies rather than imposing proprietary systems, fostering better efficiency and automation. • **The Need for a Learning Health Model:** A major transformative goal is to eliminate the separation between clinical care and clinical research. Leveraging the infrastructure, data, and personnel within the clinical care environment is essential for realizing a "learning health model" that benefits both patient treatment and scientific discovery. • **Patient Centricity vs. Engagement:** While patient centricity is a universally accepted goal, execution is often flawed. The focus should shift to "patient involvement" or "patient engagement," treating patients as active partners in the process, ensuring scientific rigor is maintained alongside relevance to patient outcomes. • **Quantifying Diversity Disparities:** Empirical research has confirmed that the race and ethnicity of investigative site personnel are correlated with and predictive of the race and ethnicity of enrolled patients, providing quantitative evidence that supports the need for greater diversity and inclusion efforts within research staff. • **Eliminating Redundancy and Lack of Trust:** Two major inefficiencies that should be eliminated include labor-intensive practices like 100% Source Data Verification (SDV) and the redundant oversight stemming from an inherent lack of trust between sponsors, CROs, and contracted providers. • **Temporary Public Trust:** The increased public awareness and trust in clinical research generated during the COVID-19 pandemic were temporary. Sustainable public support requires integrating clinical research into the mainstream societal mindset and providing continuous education on its value, rather than viewing it merely as an alternative for the desperately ill. • **Impact of Technology on Data Management:** The introduction of certain technological advances, specifically EDC, inadvertently broke the focus on the patient by centralizing data management and fragmenting the process. The industry is now circling back to personalized medicine, requiring data systems that support patient-level management and distributed access. Tools/Resources Mentioned: * **Veeva Systems Inc:** (Channel host/context) A leading platform in the pharmaceutical industry, particularly for CRM and clinical trial solutions. * **Tufts Center for the Study of Drug Development (CSDD):** Research organization providing data and insights on drug development efficiency and trends. * **Center for Information and Study on Clinical Research Participation (CISCRP):** A non-profit organization dedicated to educating the public and patients about the clinical research process. * **EDC (Electronic Data Capture):** Mentioned as a technology that centralized data but inadvertently fragmented the patient focus. Key Concepts: * **Risk Aversion/Conservatism:** The deeply entrenched culture in the pharmaceutical industry that prioritizes safety and compliance over innovation, often leading to slow adoption of new technologies and methodologies. * **Protocol Amendments:** Changes made to a clinical trial protocol after the study has begun, often cited as a major source of inefficiency and cost. * **Patient Engagement/Involvement:** Moving beyond simply recruiting patients to actively partnering with them in trial design and execution, ensuring outcomes are meaningful to patients. * **Learning Health Model:** A conceptual framework aiming to integrate clinical care and clinical research, allowing data generated during routine care to inform research and vice versa. * **Site Centricity:** The concept that clinical trials should be designed and executed with the needs and capabilities of the investigative sites at the forefront, recognizing that sites are where research is localized.