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Vijay Pande — who left a16z's roughly $4 billion biotech practice last year to start the much smaller, AI-native VZVC — talks about why biology is finally shifting from a "discovery" science to an "engineering" one, why clinical trials are still brutally expensive, and why he thinks open, shared datasets (not walled-off ones) are what will actually let AI transform medicine.
What this covers
This is a Mr. Informer briefing on “We’re not doing 30 bets a year”: Vijay Pande on betting small after running $4 billion at a16z — a detailed, automation-assisted summary of reporting from TechCrunch. Below you'll find the original reporting summarized in our own words, followed by editorial context on why this matters, technical background, and key takeaways. For full quotes, sourcing, and original detail, read the complete report at the source linked at the bottom of this article.
Why this matters
The transition of venture capital toward smaller, highly focused funds operating in specialized sectors like AI-native biotech reflects a broader evolution in how capital is deployed in emerging technology fields. Industry shifts of this nature highlight a growing preference for concentrated, thesis-driven investments over broad portfolio spraying. For readers tracking the intersection of artificial intelligence and healthcare, this signals a changing operational philosophy among elite investors targeting systemic transformations in medicine.
Technical context
The underlying shift involves applying artificial intelligence to biological sciences, which are moving from traditional trial-and-error discovery methods to predictable engineering disciplines. This technological evolution relies heavily on open, shared datasets rather than proprietary, walled-off information silos to properly train and scale medical AI models. Despite these computational advancements, the practical application of these models still intersects with clinical trials that remain brutally expensive.
Key takeaways
- Vijay Pande left a16z's roughly $4 billion biotech practice last year to launch a smaller, AI-native firm named VZVC.
- The new fund focuses on a smaller number of targeted investments rather than making 30 bets a year.
- Biology is experiencing a fundamental shift from a discovery science into an engineering discipline.
- Open and shared datasets are identified as the necessary catalyst for AI to successfully transform medicine, contrasting with walled-off data.
- Clinical trials continue to present a major financial hurdle by remaining brutally expensive.
Read the full original report at TechCrunch →