Vijay Pande made a major career shift. He left a16z's roughly $4 billion biotech practice last year to start VZVC, a much smaller fund built around artificial intelligence. His new approach is clear: fewer bets, more focus.
"We're not doing 30 bets a year," Pande says. That is a direct contrast to the high-volume style common in venture capital. Instead, he is betting small — but with a sharper thesis about where biology is headed.
Why Biology Is Becoming an Engineering Science
Pande's central argument is that biology is finally moving from a "discovery" science to an "engineering" one. In the past, researchers mostly found things by accident or through slow experimentation. Now, with AI, they can design solutions on purpose — like engineers building a bridge or a chip.
This shift matters because it changes how investors should think. If biology is engineering, then progress becomes more predictable. That makes it easier to place targeted bets rather than spreading money across dozens of startups hoping one works.
Clinical Trials Are Still Brutally Expensive
Even with AI speeding up discovery, Pande is honest about the bottleneck: clinical trials. He calls them "brutally expensive." No amount of AI can skip the step where a drug must be tested in humans safely.
This is a reality check for anyone expecting AI to instantly fix medicine. The technology can help design better drugs faster, but the final stages of testing remain costly and slow. Investors need to plan for that.
Open Datasets Over Walled-Off Ones
Pande also takes a clear position on data. He believes open, shared datasets — not walled-off ones — are what will actually let AI transform medicine. If every company hoards its data, no single player has enough to train powerful models. Sharing levels the playing field and speeds up the whole field.
This view puts him at odds with the common instinct to protect proprietary information. But Pande argues that the real value is in the models and the insights, not in sitting on raw data.
Our Take: Small Bets, Big Thesis
In our view, Pande's shift from $4 billion to a smaller fund is not a step down — it is a strategic move. Running a massive portfolio forces you to make many bets, some of which are bound to be weak. A smaller fund lets him concentrate on the few ideas he believes in most.
The "engineering" framing is also worth taking seriously. If biology truly behaves like an engineering discipline, then the risk profile of biotech investing changes. It becomes less about gambling on discoveries and more about executing well on known principles.
The warning about clinical trials is the most important part for readers. AI is a powerful tool, but it does not remove the hard, expensive work of proving a drug works in humans. Anyone investing in this space should keep that in mind.
Finally, his push for open datasets is a bet on the collective. It may seem counterintuitive in a competitive market, but if it works, it could be the thing that actually unlocks AI's potential in medicine.
