“We’re not doing 30 bets a year”: Vijay Pande on betting small after running $4 billion at a16z

Vijay Pande used to be the Stanford chemistry professor behind Folding@home, the distributed computing project that turned millions of home PCs into a disease-research machine. Then Marc Andreessen and Ben Horowitz handed him healthcare and life sciences at a16z, a category their firm had spent its first five years avoiding. Over the next decade-plus, he grew that into a practice managing close to $4 billion.

Now he’s gone the other way. In June of last year, Pande left to co-found VZVC with longtime investor Zach Werner, and the setup is deliberately spare: no associates, a heavy reliance on AI for day-to-day work, and only a handful of concentrated bets each year. He says the goal is not to spray money across the market. It’s to make maybe five investments a year and treat each one like a serious commitment.

That choice fits his view of where biotech is headed. Pande thinks biology is shifting from a science of discovery to something that can be engineered, with AI and machine learning helping identify drug targets, design drugs, and even improve clinical trials. The appeal is obvious enough. Clinical trials can still run into the hundreds of millions of dollars, and only about 20% of drugs make it from the first trial to the end of the third. Animal models, he says, are a weak proxy for human biology.

But he’s also clear-eyed about the limits. Biology is not text, and it can’t be scraped from the internet. That means companies tend to build their own locked-up datasets, which makes the field look very different from the AI world built on shared web-scale data. Pande argues that this is exactly why the next wave may come from biological foundation models and, eventually, more open-source ones that can have broad impact.

For VZVC, that translates into a very hands-on style. The firm is focused on AI for healthcare delivery and AI for clinical trials, and Pande says he wants founders with high integrity who are thinking years, not quarters, ahead. He also says the hardest part is still the unglamorous part: go-to-market. The technology may be seductive, but that, in his view, is not what usually decides whether a company survives.