Vikram  Agarwal

For the first time, AI is enabling us to imagine medicines that “think” - turning on only inside diseased cells or under specific physiological conditions. Neural networks trained on RNA, protein, and cellular data are unlocking a new generation of programmable therapies with unprecedented precision, from cancer drugs that remain inert until encountering tumor signals to RNA medicines capable of adapting to dynamic biological environments. But designing intelligent molecules is only part of the challenge. As AI expands the space of possible therapeutics, the field must also confront a critical question: how do we reliably build, test, and manufacture increasingly complex biological designs? This session explores the emerging continuum from AI-designed molecules to manufacturable programmable therapeutics, examining how advances in sequence design, synthesis, delivery, and validation are translating computational insight into real-world medicines. The future of medicine isn’t static molecules - it’s intelligent, adaptive therapeutics engineered across the full stack, from algorithm to clinic.