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In this episode, Alex Zhavoronkov, Founder, CEO and CBO of Insilico Medicine, explores how generative AI is reshaping drug discovery and opening new possibilities in longevity research. He explains how AI can move pharmaceutical R&D from searching for promising molecules toward generating molecules with desired properties, while orchestrating specialized models and agents across the drug development lifecycle. Insilico combines AI models across biology, chemistry, and clinical development to move from target identification to drug candidates faster, with multiple programs now in clinical trials.

Alex argues that AI can dramatically expand the number of experiments researchers can conduct, but the complexity of biology means failure remains inevitable and real-world validation is essential. He discusses the industry's shift from predictive AI to generative and agentic systems capable of orchestrating thousands of drug discovery tasks, while emphasizing the importance of rigorous validation.

Alex believes the strongest competitive advantages will come from proprietary drugs, scientific infrastructure, capital, and the ability to turn ideas into validated products. He cautions against AI hype and emphasizes benchmarking, peer-reviewed evidence, and clinical results. His ultimate ambition is to use AI-driven drug discovery to extend human lifespan and give people more years of life. Take a listen.

This guest appearance was facilitated through conversations initiated at Ai4 2026. 

Alex Zhavoronkov, PhD, is the Founder, CEO and CBO of Insilico Medicine (insilico.com, HKEX:3696), a leading clinical-stage biotechnology company developing next-generation generative artificial intelligence and automation platforms for drug discovery. Since 2014, he has invented critical technologies in the field of generative artificial intelligence and reinforcement learning (RL) for the generation of novel molecular structures with the desired properties and the generation of synthetic biological and patient data. He also pioneered the applications of GANs, transformers, and other deep learning technologies for the prediction of human biological age using multiple data types, transfer learning from aging into disease, target identification, and signaling pathway modeling. Under his leadership, Insilico raised over $530 million in multiple rounds from expert biotechnology, healthcare, and financial investors, opened R&D centers in 8 countries and regions, and partnered with multiple pharmaceutical, biotechnology, and academic institutions. In 2025, the company completed the largest biotech IPO in Hong Kong raising over $300 million. Since 2021, the company nominated more than 31 preclinical candidates, 13 reached clinical stage, and 1 program with a novel target and novel molecule completed Phase IIa in IPF with favorable safety, tolerability and encouraging dose-dependent efficacy. By 2023, 11 out of the top 20 pharmaceutical companies used a part of the Pharma.AI software suite.

Prior to founding Insilico, he worked in senior roles at ATI Technologies (GPU company acquired by AMD). Since 2012, he has published over 310 peer-reviewed research papers with over 30 papers in the field of generative adversarial networks, generative reinforcement learning, and multi-modal transformers, and 3 books, including "The Ageless Generation: How Biomedical Advances Will Transform the Global Economy" (Macmillan, 2013). He serves on the advisory or editorial boards of Trends in Molecular Medicine, Aging Research Reviews, Aging, and Frontiers in Genetics, and founded and co-chairs the Annual Aging Research and Drug Discovery meeting (12th Annual in 2025), the world's largest event on aging research in the biotechnology industry. He is the adjunct professor of artificial intelligence at the Buck Institute for Research on Aging.