Generative Chemogenomics & the Future of Drug Discovery: Inside AI‑Driven R&D with Tom Neyarapally

Episode Description What if you could screen billions of potential therapies—virtually—in the time it takes to brew your morning coffee? In this episode of scientifica sessions, host Tabari Baker sits down with Tom Neyarapally, CEO and co-founder of Archetype Therapeutics, to explore how AI-native biotech is redefining what's possible in early-stage drug discovery. With a background that spans law, business, and executive leadership at companies like Sema4, Tom offers a rare vantage point on how data, machine learning, and strategic insight converge to accelerate breakthroughs in oncology and beyond. Tom breaks down the science behind generative chemogenomics, a novel platform that Archetype uses to computationally model and prioritize billions of molecules against real-world patient data. He shares how this approach is opening new doors for underserved populations—starting with patients facing non-small cell lung cancer—and gives an insider's look at the challenges of validating AI-driven assets in a tightly regulated environment. From AI-driven virtual screens to pragmatic lessons on leading AI-first biotech startups, this episode is a masterclass for executives navigating the future of translational science. If you're in biotech, pharma, or diagnostics—and responsible for building what's next—this conversation will leave you rethinking how you approach discovery, evidence, and leadership.   What We Covered Understanding Generative Chemogenomics Explaining generative chemogenomics in accessible terms and how it differs from traditional drug discovery methods The role of clinicogenomic data integration in enhancing virtual screening predictive power How regulatory and payer stakeholders are responding to generative AI outputs as evidence in early development Sharper Early-Stage Discovery in Practice Deep dive into Archetype's recent lung cancer program and how virtual screening translates to actionable candidate molecules Validation strategies for AI-generated molecules before advancing to in vitro or animal models Advantages and risks of AI-driven discovery models versus classic high-throughput screening approaches AI Leadership & Strategic Integration Essential capabilities biotech executives need to enable AI integration in drug pipelines Aligning AI outputs with Medical Affairs, Real-World Evidence, and clinical leadership strategies Medical Affairs' evolving role in educating stakeholders about AI-generated therapeutics legitimacy The future landscape of AI-driven R&D and commercialization across pharma Leadership Insights & Founding Journey Leadership lessons from scaling teams at Sema4 and Archetype in high-growth bio-AI environments Practical cultural and organizational advice for senior leaders building AI-first biotech startups Future Roadmap & Vision Next-generation developments in generative chemogenomics Strategic outlook for AI-native drug discovery becoming industry standard   Guest Bio Tom Neyarapally is the CEO and Co-Founder of Archetype Therapeutics, an AI-native company pioneering the use of generative chemogenomics in patient data-driven drug R&D in cancer and other diseases. Previously, Tom was CCO and founding team member at Sema4, a patient-centered health intelligence and genetic testing company that went public in 2021. He was also a member of the founding team and EVP, Corporate Development at the causal AI drug discovery company Aitia. After graduate school, Tom served as a corporate and IP lawyer at Chadbourne Parke LLP and Frommer Lawrence & Haug LLP. He started his career after college as an analyst focused on pharmaceuticals at the management consulting firm Arthur D. Little. Tom earned a B.S. in chemical engineering (Honors Scholar/cum laude) from the University of Connecticut and a J.D. and M.B.A. from Cornell University. His unique combination of technical, legal, and business expertise provides him with a distinctive perspective on navigat