At a recent conference, industry leaders gathered to explore the transformative potential of artificial intelligence (AI) in clinical trials, focusing on moving from theoretical concepts to practical applications. Moderated by Badhri Srinivasan from Novartis, the panel featured Christoph Koenen from Bayer, Christopher D. Corsico from GSK, and Darren Weston from Johnson & Johnson. The discussion delved into AI’s readiness for integration, its potential impact on clinical trials, and the challenges faced in implementing AI within the highly regulated pharmaceutical industry.
The Current AI Landscape in Clinical Trials
Badhri Srinivasan highlighted the pervasive influence of AI, noting its potential to revolutionize industries, including biopharmaceutical R&D. He emphasized the urgency for the pharmaceutical sector to explore AI’s practical applications, especially in clinical trials where precision and safety are critical. Christopher D. Corsico from GSK elaborated on the foundational role of data in leveraging AI’s capabilities. He explained that effective AI integration begins with robust data infrastructure, ensuring seamless data flow and accessibility. GSK actively explores large language models and generative AI to automate document creation, streamline operations, and enhance site selection and patient identification. By optimizing trial design and reducing patient exposure, GSK aims to deliver more effective treatments.
Christoph Koenen from Bayer provided insights into AI’s multifaceted applications in clinical trials. He emphasized the importance of contemporary data access, particularly in rapidly evolving therapeutic areas like cardiovascular disease. Understanding patient populations in real time allows for more accurate trial design and sample size determination. Koenen highlighted AI’s potential to revolutionize data quality assurance, which currently consumes significant trial costs. By automating data verification and monitoring, AI can enhance data integrity while reducing manual oversight. Darren Weston from Johnson & Johnson discussed the vast opportunities AI presents, likening the current state to “children in a candy store” due to numerous possibilities. He differentiated between AI and generative AI, noting that while AI has been used for tasks like protocol optimization, generative AI offers new capabilities, such as interpreting content and generating queries. Weston emphasized prioritizing AI initiatives that align with organizational goals and deliver the most significant impact.
Challenges and Considerations for AI Integration
The panelists acknowledged AI’s significant potential in clinical trials, emphasizing the need for careful integration to avoid disrupting ongoing projects. Christopher D. Corsico highlighted the importance of pilot programs to test AI applications without affecting the broader portfolio. These pilots should focus on areas where AI can deliver tangible benefits, such as reducing trial size or improving patient recruitment strategies. Corsico stressed the necessity of demonstrating the reliability and replicability of AI-generated data to regulators, ensuring AI-driven insights are accurate and actionable. This approach is crucial in maintaining the integrity of clinical trials and gaining regulatory approval.
Christoph Koenen and Darren Weston stressed the importance of prioritization and governance in AI initiatives. Koenen noted that the focus should be on areas aligning with organizational strengths and strategic goals. Weston highlighted the need for connected efforts across R&D to avoid siloed projects and ensure infrastructure investments address multiple challenges. They emphasized that AI integration should be guided by clearly understanding the organization’s current capabilities and aspirations. This strategic approach ensures that AI initiatives are innovative, sustainable, and aligned with the organization’s long-term objectives.
The Path Forward
The panel concluded with a discussion on AI’s future in clinical trials. Badhri Srinivasan summarized the key themes, emphasizing data quality’s critical role and the distinction between AI and generative AI. He noted that AI can automate repetitive tasks but cannot replace clinicians’ expertise. The conference underscored AI’s transformative potential in clinical trials, highlighting integration challenges in a highly regulated industry. As AI technology evolves, its successful application in biopharmaceutical R&D will depend on strategic prioritization, robust data infrastructure, and careful change management. The industry’s ability to navigate these challenges will determine AI’s impact on clinical trials and patient outcomes.
Moe Alsumidaie is Chief Editor of The Clinical Trial Vanguard. Moe holds decades of experience in the clinical trials industry. Moe also serves as Head of Research at CliniBiz and Chief Data Scientist at Annex Clinical Corporation.
