Novartis is at the forefront of modernizing clinical trial processes by integrating AI to enhance trial feasibility and site selection. This strategic initiative, highlighted by Novartis leaders at the DPHARM 2024 conference, aims to revolutionize the traditionally labor-intensive and time-consuming process of identifying suitable trial sites and principal investigators (PIs). By leveraging AI, Novartis seeks to streamline these processes, making them more efficient and reliable, ultimately leading to faster and more successful clinical trials.
AI Revolutionizing Site Selection
The integration of AI into site selection is a transformative development for Novartis. Traditionally, selecting the right sites for clinical trials was a time-consuming process that could take weeks or even months, involving the analysis of vast amounts of data to identify sites with the necessary infrastructure, patient population, and expertise. Novartis has developed AI algorithms capable of analyzing large datasets in minutes, identifying the most suitable sites for a trial based on a range of criteria. This accelerates the site selection process and enhances the quality of decisions. For example, AI can analyze data from previous trials to identify sites that have consistently performed well in patient recruitment and retention. It can also assess the availability of the target patient population at each site, ensuring trials are conducted in locations with a high likelihood of recruiting the necessary number of participants.
Extensive Data Resources
One of the key strengths of Novartis’s AI-powered platform is its access to an extensive array of data resources. The platform draws on data from 460,000 clinical trials, over 700,000 clinical sites, and information on the capabilities of 600,000 industry-wide PIs and millions of affiliated healthcare professionals. Additionally, the platform includes patient diversity data and de-identified patient lives, covering 1,100 diseases and indications, ensuring trials are conducted inclusively and representatively. This vast database gives Novartis a comprehensive view of the clinical trial landscape, enabling the company to make informed decisions about trial feasibility and site selection. The comprehensive nature of the data resources also allows Novartis to identify trends and patterns that may not be immediately apparent, providing valuable insights that can inform trial planning and execution.
Building Internal Capabilities
Over the past three years, Novartis has embraced a data-driven transformation by transitioning from disparate data sources to unified platforms and products. Central to this effort is the “Unified Ontology,” a digital twin of the organization that integrates semantic elements, such as objects and relationships, with kinetic aspects like actions and security protocols. This comprehensive system ensures that all relevant data is incorporated into the site selection process, enabling more informed and effective decisions. However, Novartis understands that technology alone cannot drive success; skilled personnel are essential to maximize the value of these tools.
To this end, Novartis is investing heavily in building internal capabilities and empowering its workforce. Through targeted training and capability enhancement programs, the company equips employees with the skills needed to utilize data-driven tools effectively. Additionally, Novartis adopts a human-centric approach to product design by involving end-users in the development process. By collaborating with business teams to understand their needs and challenges, Novartis creates intuitive and impactful solutions that align with strategic goals. This combination of people, processes, and technology allows Novartis to scale AI implementation seamlessly, improve decision-making, and enhance clinical trial outcomes, demonstrating its unwavering commitment to innovation and efficiency.
Successful Pilot in the US
The effectiveness of Novartis’s AI-driven approach was demonstrated in a successful pilot conducted on a large trial in the United States. The trial involved approximately 1,700 patients, and the results highlighted the benefits of using AI in site selection and patient recruitment. In this pilot, PIs with a high representative “HAT” in the CLIP S-MIX recruited 2.7 times more targeted Black or African American patients than their peers, demonstrating AI’s potential to enhance diversity and inclusivity in clinical trials. This ensures trials are representative of the populations they aim to serve. Additionally, PIs with a combination of fast-starter and high-performance HATs recruited 3.4 times higher than the median recruitment rate, highlighting AI’s ability to identify and leverage the strengths of individual investigators, leading to more efficient and successful patient recruitment. Overall, the pilot demonstrated AI’s potential to transform clinical trial processes, leading to faster, more efficient, and more inclusive trials.
Summary
In conclusion, Novartis’s transition to a data-driven, AI-powered approach in clinical trial feasibility and site selection marks a significant advancement in the field. By harnessing the power of AI, Novartis is poised to make more informed, efficient, and inclusive decisions in clinical trial planning and execution. This strategic initiative not only streamlines operations but also ensures that trials are conducted in a manner that is both efficient and effective, maximizing the potential for successful outcomes. As Novartis continues to innovate and refine its approach, the company is well-positioned to lead the way in transforming clinical trial processes and improving 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.
