Alex Zhavoronkov: Beating Aging, Designing Drugs and Betting on China | Frameshifts Episode #12

About this episode

Plenty of people will tell you AI is about to design our drugs. Alex Zhavoronkov already has. His company’s lead candidate, rentosertib, is the first drug with both its biological target and its molecule discovered by generative AI to post real Phase 2 results in humans. That gap, between the pitch deck and a drug in an actual person, is the whole reason this conversation is worth your time.

Alex started out in GPUs and high-performance computing, then left to bet that AI could design drugs better than people can. He retrained in biomedical science, and nearly two decades on, his company Insilico Medicine has gone public in a US$292 million Hong Kong IPO and signed a collaboration with Eli Lilly worth US$2.75 billion. That track record is what makes his bluntness about the rest of the field worth hearing.

We get into the only benchmark he thinks matters: the time it takes to go from target identification to a real developmental candidate, and why he treats funding rounds, papers and patents as mostly noise. We talk about how Insilico initially stalled while chasing aging “in the most hardcore way possible”, why he’s convinced that experimental validation rather than model size is still the real bottleneck in biology, and the claim that tends to make founders in Boston and San Francisco uncomfortable: that if you’re not competing and collaborating in China, you’re already behind.

In this episode, we also get into:

* What “pharmaceutical superintelligence” actually means, and what it doesn’t

* Why medicinal chemists aren’t getting replaced any time soon

* Why humanoid robots are the wrong bet for the lab right now

* Where embodied AI actually fits into biology

* Why owning the best software doesn’t make a drug company defensible

* How small, validated models end up training the bigger ones

* Can you still compete in biotech without building in China?

* When AI can design the drug, who actually captures the value?

In Alex’s ideal version of all this, you wouldn’t even open a drug discovery platform. You’d just tell a language model what you want cured, for whom, and with what tradeoffs, and let it go to work behind the scenes. It sounds like science fiction, right up until it starts working.

GUEST INFORMATION:

* Alex Zhavoronkov, CEO Insilico Medicine

* X (Twitter)

* LinkedIn

* Deep learning enables rapid identification of potent DDR1 kinase inhibitors (Nature Biotechnology, 2019)

* Rentosertib Phase IIa results in idiopathic pulmonary fibrosis (Nature Medicine, 2025)

CONNECT WITH US:

* Website

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* YouTube

* X (Twitter)

* LinkedIn

* TikTok

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