AI is revolutionizing clinical documentation in clinical trials. In this interview, Anita Modi, CEO and Founder of Peer AI, shares insights on how AI enhances efficiency and quality in drug development through strategic partnerships and cutting-edge technology.
Moe: Anita, you mentioned 60% to 90% time savings and a 94% efficiency gain. Can you share a client example where these metrics were realized post-implementation?
Anita Modi: Absolutely, Moe. At Peer AI, we’ve partnered with a top 20 pharma company aiming to automate a full IND application. This initiative is part of a broader strategy to reduce cycle times and improve documentation quality, crucial given that 73% of new drug applications (NDAs) are rejected due to incomplete or inaccurate data. We’ve moved from pilot to implementation, showing compounding value over time. For instance, with clinical study reports (CSRs), we measured efficiency, looking at the time it takes to go from setup to the first draft, as well as quality, using a framework we developed that takes into account criteria such as accuracy, completeness, consistency, and readability. Between the first and third CSR, we cut time by an additional 50% while improving quality, demonstrating AI’s potential to enhance both efficiency and quality in documentation. This not only accelerates patient access to new therapies but also mitigates revenue loss due to regulatory delays.
Moe: Peer AI promotes traceability and compliance with ICH and FDA guidelines. Have any submissions using your platform received regulatory feedback?
Anita Modi: The regulatory embrace of AI is exciting, and it’s a testament to the industry’s readiness for innovation. The FDA’s move from pilot to implementation of AI for review purposes aligns with our design philosophy at Peer AI, where the platform is purpose-built for both human and AI reviewers. Our platform incorporates ICH guidelines and regulatory feedback as context for a continuous feedback loop that consistently improves the end result. This approach ensures that our documentation meets compliance standards, providing a robust framework for regulatory submissions that can withstand scrutiny and smooth approval processes.
Moe: Winning the whale tank at DIA is impressive. What tangible business impacts followed this recognition?
Anita Modi: Winning the Whale Tank at DIA was a significant milestone for us, validating our unique approach at Peer AI. This recognition has led to numerous discussions and partnerships, as the industry seeks partners to navigate this evolving frontier. What stood out from those conversations was our architectural approach and commitment to building Peer AI hand in hand with medical writers. Our agentic AI platform has document-specific agents and incorporates sponsor specifications to drive speed and accuracy across documents. To get AI automation right, we make sure the technology works hand in hand with the expert, augmenting their capabilities and ensuring their verification along the way. AI is here to stay and the industry is looking for a partner to build these capabilities together to work toward the same goal expediting the path to approvals.
Moe: Have you faced client pushback due to onboarding costs or data validation issues, especially from Big Pharma?
Anita Modi: Throughout my career in life sciences developing and implementing technology, I’ve seen how effective change management is crucial in technology adoption. At Peer AI, we’ve focused on minimizing friction by integrating seamlessly into existing workflows. We handle unstructured data as it is, reducing the burden on customers to change their data pipelines. Our approach ensures that customers can adopt our technology without the typical hurdles associated with data cleanup or validation, making it an attractive option for companies looking to streamline their processes without incurring additional costs. This strategy has been key to our customers’ success.
Moe: You’ve published extensively on AI governance and ICHM 11. Who else contributes to Peer’s thought leadership?
Anita Modi: In founding Peer AI, it was important to have advisors from diverse backgrounds, including heads of medical writing and leaders in AI technology and innovation. This diversity of thought is crucial for building a solution that delivers real value across the industry.. We have published whitepapers with a number of others in progress and are collaborating with customers to present results at upcoming conferences. These collaborations help us continuously refine our approach based on the latest industry insights and regulatory developments, and adapt with the industry and our customers’ needs to innovate further.
Moe: PeerScribe is a new feature. How mature is this capability, and how does it differ from existing tools like Teams?
Anita Modi: In speaking with customers, we saw how much of the context needed for key documents comes from the discussions happening during cross-functional meetings. Yet, most of the time those insights are not being captured. PeerScribe was designed to capture context from those meetings, crucial for writing clinical trial protocols and CSRs. It integrates seamlessly into existing workflows, minimizes the burden on teams and improves and improves documentation speed, accuracy and quality, setting it apart from generic meeting tools. This targeted approach makes PeerScribe invaluable for clinical documentation.
Moe: Is there anything else you’d like to add about Peer AI?
Anita Modi: As AI continues to get smarter, it’s important to have a deep understanding of how it integrates with existing workflows and when to bring human oversight. Even more importantly is ensuring it’s being used in the right context to drive real value at scale. At Peer AI, we believe in the synergy of AI and human expertise. As in our name, the platform is designed to be a peer to experts, medical writing experts, enhancing workflows and augmenting their capabilities to work faster and more efficiently. This thoughtful integration is key to scaling and making a significant impact in the industry. We are committed to continuously evolving our platform to meet the dynamic needs of the life sciences industry, ensuring that we remain a trusted partner in the journey towards faster and more efficient drug development. Our vision is to revolutionize the way clinical documentation is approached, setting new standards for quality and efficiency.
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.
