Nov 18, 2015 ยท 9 minutes

Within five seconds it’s clear that Andreessen Horowitz’s new partner, Vijay Pande, will fit in with the firm in at least three ways:

- He believes software is the solution, answer, noun that follows every verb to almost every single one of society’s and the business world’s ills. He’s yet another preacher in the A16Z church of software. Hallelujah!

- He thinks big. Creating whole new categories of investment kind of big.

- He talks uncomfortably fast. I hope the following Q&A is mostly accurate. I had to ice my fingers once we were done. He joked that he wondered if they clocked him during the interview as some sort of test.

[Disclosure: A16Z general partners Mark Andresseen and Jeff Jordan are investors in Pando].

Pande is the six-year-old firm’s ninth general partner hire— a feat in and of itself. 20-year-old Benchmark, for instance, only has five partners. Partners at top venture firms typically describe hiring a partner in terms of marriage. It can take years of conversations. “Well, when we first met Roger, we knew that someday we’d want to work together…after ten years of dinners, we made an offer.”

A16Z, under that metaphor, is a raging, impulsive polygamist.

In general, A16Z has always had outsized ambitions in terms of what services VCs should provide, how many people they should employ, and –compared to some firms– the scope of their investing mandate. So it shouldn’t come as a surprise that part two of the news coming out of the partnership today is the intention to raise a separate, companion “bio+computer science” fund.

I chatted with Pande yesterday about the move and what it means. The following are excerpts from the conversation. At times it’s both thrilling and frighteningly sci-fi sounding.

Let’s start with your background. How did you meet the firm and how did this come about?

I came to the Valley in 1999, and I’ve been involved with several startups as an advisor and co-founder and a professor at Stanford in chemistry, structural biology, and computer science. I ran a 25 person research lab in this area and one of the things that got a lot of attention was the Folding@Home project. The level of compute power we have now really will transform biology. We built the world’s most powerful super computer thorugh this project.

So as to why now and why this is an interesting time, thanks to Moore’s Law and all the advances in mobile and sensors and cost and compute – the cost of all of this is essentially going down to zero. Those realities can kind of sneak up on us.

The human genome project spent $3 billion doing something you can now do for $300. What this means is when we have all the costs of the computing come down to zero… what’s left to do? What’s left to do is the software to connect everything to propel software forward.

I’ve been involved in this ecosystem for quite a bit. A year ago in 2014, I became a professor in residence at Andreessen Horowitz, because they wanted to have stronger connections with academia. If you think about it, some of the places where they get stronger entrepreneurs like Stanford and MIT are all places I’ve had experience. Once I got here, I was really excited about the way the firm runs. We started talking about what we could do together.

So you just got done explaining how you liked how the firm runs, but now you are going to run a side fund and the firm has never had a side fund. How is that going to work?

It doesn’t change it at all in terms of how we do things when a deal comes through. It’s the exact same process. Each GP sees it, it goes through the associates and then we see it as a firm. It’s a process that works, and it works because these are really software companies. It’s a huge asset for me to have the other GPs in the room. If there’s a bio deal that is very much a marketplace, I have Jeff Jordan’s eBay and OpenTable experience. I can handle the bio side. To do this as a team, that’s what sets our firm apart.

Why do it as a separate fund if it’s so integral to the broader software mission of the firm?

We are very excited about seeing this become something big. We expect it to grow larger in time and this anticipates that and sets it up as a possibility.  

Bio -- and other ambitious save-the-world sectors like cleantech-- have historically been avoided by the firm because of the fear of regulation that comes with many of those markets. Will you avoid that or is this a change in thinking?

The reason why those are good areas to stay away from is it’s hard to de-risk them if there’s a regulatory existential threat. It’s dangerous. That’s not something that’s changed. What is new here is the possibility of doing bio and healthcare and not bringing on those challenges.

This is definitely not going to be traditional biotech, where you put in $100 million and cross your fingers that you’ll make it to phase two.

There are three buckets of potential deals: Digital therapeutics, cloud biology, and computational medicine.

Explain each of them. Let’s start with digital therapeutics.

There are some places in medicine where the dream of Western medicine has really been realized. Things that could have killed you without antibiotics, and you take a pill and you are fine. That’s fantastic. But there are a lot of things when twenty years in the future we’ll look back today, and treatments will seem barbaric that our solution was a pill for everything. Things like insomnia, diabetes, depression, PTSD, a pill is not really the ideal solution.

What’s appropriate is behavioral therapy. These programs exist and work but they don’t scale. They only treat tens of patients. Stanford’s approach for pediatrics, obesity, and insomnia demonstrated efficacy, but they serve twenty patients a year and cost thousands of dollars per year.

OMANATK health is one of our portfolio companies pioneering in this area for type two diabetes. They’ve taken this diabetes prevention program and allowed it to scale. It’s a new type of therapy. It’s not a pill, but it’s judged on the same merits. We want to see clinical efficacy.

Let’s talk about cloud biology. What do you mean by that?

Cloud biology is analogous to cloud computing. At one time, if you wanted to build a startup you had to build a huge server farm and only after that demonstrate the product works at scale. Now you can give $2 million to $3 million to a couple of grad students and they can build a real product at scale.

In bio you can have experiments now done by people done by robots in a very cloud-like way. Right now you have rows and rows of people doing manual labor. It’s very expensive. Robots solve all those problems. They turn it into a software solution.

Just as a few grad students can go really far in cloud computing, we are seeing the same thing on the biology side. They can skip the lab and skip the huge series A.

Are you interested in the underlying technology you describe or companies that leverage this?

Really, both. There might only be a few companies who are the providers. But this is really going to be important for the ecosystem.

Let’s talk about the third bucket.

Computational medicine. Machine learning is being transformative in so many ways, especially in medicine. When you get into vision and image recognition, it can best human beings. How is this possible? It’s kind of amazing.

Moore’s Law for compute and its sister law for storage has driven the cost down to zero. The Achilles heel for machine learning isn’t the compute power, it’s do you have enough data? If you have enough you can do amazing things.

The great thing about medicine is there is tons of data in medicine, whether it’s radiology, dermatology, or ophthalmology. Image recognition is so critical to many areas of medicine. A lot of doctors’ training is image recognition.

But it’s not just that. Human genome sequencing is so cheap you can sequence cancer tumors. When people first get cancer, the initial drug will work for a while and then stop, as the tumor experiences mutations. The ability to sequence those mutations is truly transformative.

That’s a beautiful problem for machine learning, because we can track how this set of mutations responded to these drugs. This is an issue of life and death.

You are clearly describing a very different way of investing in bio than most VCs. Are you worried at all about finding follow-on funding from other firms?

We are expecting that these areas are something that will become really big because of the software approach. The beauty is the way we fund things and de-risk them is the same way we do on the software side. We may put in a few million and then expect they have a product and customers. After the A round, we expect them to ramp up sales, and then the sales look like an enterprise or SAAS business. By the time you hit B, C, or D rounds, you are building a huge organization that looks like how you build a software company.

That’s something familiar and comfortable and different than biotech, so we don’t expect any trouble seeing follow-ons. We’ll de-risk it at the early stages.

So is the ideal funding things at the seed level?

We are still stage agnostic. This isn’t a space that’s been around for ten years, so there aren’t the same number of growth deals out there as in the traditional software space. We are primarily looking at seeds and Series A’s, but we wouldn’t rule out later stages.

We are excited. This is a unique time in history. The description of what we do as a firm is all about software eating the world and now software has the opportunity to heal the world.