Protocol Manual: Health Care

The pandemic has caused a huge mindset shift in health care. An investor sees opportunities.

"The next big challenge is just solving the health care system in general," says Andreessen Horowitz partner Vijay Pande.

The pandemic has caused a huge mindset shift in health care. An investor sees opportunities.

Vijay Pande, a partner at Andreessen Horowitz's biotech fund, has been investing at the intersection of health care, biology and computer science for the last five years.

Photo: L.A. Cicero/Stanford University

In the future, we won't be discovering new drugs or cures to cancer — they will be designed by computers. And that process of bioengineering has only become more urgent as a result of the coronavirus pandemic and the need to find a solution fast.

Vijay Pande, a partner at Andreessen Horowitz's biotech fund, has been investing at the intersection of health care, biology and computer science for the last five years. Coronavirus has amplified the need for this kind of technology, but the pandemic also played a more important role: shifting the mindset of patients and doctors alike. People have become more attuned to what they need to do to stay healthy, while doctors are more open trying to new technologies and techniques, Pande told Protocol. The shift has also meant health care investing, particularly in AI and machine learning, has become more mainstream.

Protocol spoke with Pande to discuss what he's seen change as a result of the pandemic, how far out our AI health care future really is, and where he would like to see founders building companies.

The conversation has been edited for length and clarity.

Looking back at how this pandemic has evolved, when did you realize that COVID-19 would change health care?

I think one of the pros of being in venture capital is that you get to live in the future and invest in the startups today that will hopefully become big impactful companies in the future. We spend a lot of time thinking about future trends, and one of the biggest changes in COVID was its ability to change mindsets — that there were new technologies, new approaches.

Health care is an area that often is slow to change and slow to adopt new technologies. A lot of places still use dot-matrix printers and fax machines, technology that's 40 years old, and I think due to necessity and just to save lives, doctors are now changing mindsets very rapidly. And that's exciting because, due to having an open mind to do what you have to do in COVID, I think there could be huge changes for years to come and huge impacts on improving health care.

You said health care is often slow to change. How much of that is the mindset of doctors and researchers versus government regulations?

You could argue that we're all to blame for it in different ways. One of my friends, who's a physician, jokes that you can tell the doctors are slow to make changes considering that the language they still use often is Latin. There's some changes that take a long time to happen, but for good reasons — one has to be conservative when lives are in the balance. Then there's also people who pay for these things. You don't want to pay for shiny new things that maybe don't help as much. Then there's regulators who want to make sure that [they] keep people safe, and then I think the biggest culprit here that doesn't get [its] share of the blame [is] essentially us, the patients themselves.

Perhaps one of the biggest shifts that we're seeing is the shift of just everyday people thinking about their health care in ways that they didn't before, and especially healthy people thinking, "Oh I need to do this, this and that" to keep from getting sick. And that mindset, I think, is going to create a huge difference.

Hopefully people are going to do other things in the future to keep themselves healthy, instead of basically just eating whatever you want or doing whatever you want or pushing yourself in crazy ways, then getting sick and hoping that the medical system can take care of you.

What is the opportunity you're seeing emerge out of this?

I don't know if you've ever had to renovate a house, but you often need a general contractor to manage all the different people doing things. I think people are realizing that they have to be their own general contractor for their own bodies. They have to be in charge of all the doctors doing things. And part of that is, let's get more data.

We're seeing a revolution in people measuring things about themselves that they couldn't do before. One of our startups I'll note here is [A16Z portfolio company] Q Bio, which measures different things to help predict and anticipate health care problems before they come up.

We're also seeing companies that, once you know that you have an issue, they're working with you to handle it before it becomes more serious, whether we're talking about fighting diabetes or handling physical therapy issues. Basically, fighting diabetes and prediabetes is way better than having dialysis and being a diabetic. Handling things in PT is way better than having to get knee or hip surgery where you may never fundamentally be the same again. I think people are realizing that there are options for the whole health care paradigm, and hopefully we're using stereotypical health care as more of a last resort than the first one.

If we're amassing all this data now, that seems like a clear opportunity for AI and ML to play a big role in health care, but I feel like we've been talking about them playing a big role in health care for years now. Is anything really going to change?

The way I think about this is that we're in the middle of a 20-year arc for how ML and AI is going to change things. Maybe to make an analogy that we've all lived through: Think about the way the internet was around 2000. It was clear it could do some powerful things but were you buying dog food and shoes on the internet then? Probably not. You may have thought that you'd never buy shoes on the internet. And it took 20 years for me to buy dog food and shoes on the internet.

So I think we're on that 20-year arc, and we're seeing the first early wins — cases where drugs have been discovered through machine learning where the process is faster and cheaper, cases where diagnostics are designed through machine learning and have very high accuracies in early stages, in ways that you couldn't if you had just discovered it. These things are starting to come into the market, but the age when "everybody does everything on the internet" equivalent to ML or AI, that's probably 20 years away, where most drugs are designed using machine learning or most diagnostics are done through machine learning.

But in terms of you asking that it doesn't seem like things are changing, these things will be gradual. I think the internet and mobile basically just became part of our lives, quietly and slowly without us realizing it, but if you look at it on the 20-year timescale, obviously, the changes are fundamental. I think we'll see the same thing here.

So has the pandemic accelerated that timeline?

I think what it's done is that it's highlighted the significance of what machine learning and computation can do. It's gotten a lot of attention, and it's made it, at least on the investment side, much more mainstream.

Maybe a different analogy is what happened in Wall Street where again, 20 years ago, if you said you were going to use a computer to [become] an expert trader, [people] would think it's ridiculous, like, "This calculator can't outsmart me. I'm a 30-year veteran in the field. I know how to do investments. There's no way a computer can know how to do investments." But in time, quants and algorithms have really dominated Wall Street. It's gone from sort of this bespoke artisanal process to something that's very industrialized, something that's very data-driven. And that's something I think we would expect to see here as well.

Are you now facing more competition when it comes to investing in these health care companies?

In terms of investing there's been a lot of interest in these companies and we've invested in several. One way to think about this is that machine learning and AI are terms that evoke fanciful things like "2001: A Space Odyssey." But really what they are at their heart is just the most statistically sound way to handle information.

And when you think of it that way, who are you going to trust to design your drug or run your stock trade? When it's early days, humans will always do better than computers, but eventually things transition over. I think that's sort of what we're seeing — we're seeing pharma invest heavily in this space, either through partnerships or through building up internal programs. We've seen tech VCs and biotech VCs get very excited about this space, and this is something that's been a central thesis for A16Z Bio since its inception and something we've been looking at for five years. And I think we're at the point where now this can become mainstream.

What do you think is overhyped?

There's many things that have been around for a while, have turned a corner and get a lot of attention. A great example is telemedicine. Telemedicine is something that's been around for a while, and I think it rightfully so gets attention because of one of the key changes there, which is that the policy changed. Now, you can do telemedicine nationally in a way that you couldn't do before, and that's uniquely associated with COVID-19.

But in many ways this has been around for a long time, the technology's been here, it's been spring loaded waiting for this moment, and it was really not so much about the technology, but really about the policy change. It gets a lot of attention because it's very straightforward to see how it can help. I think under the surface, though, there are a lot of other sort of more fundamental shifts that will have a bigger long-term play.

Beyond AI/ML, what's another one of these fundamental shifts that you're seeing that's been particularly affected by this pandemic?

If we look at how AI/ML is connected to other things, I think one of the central threads is an engineering approach applied to biology.

ML/AI is really a means to engineer things. For instance, when [A16Z portfolio company] Freenome is going out to come up with a cancer test, they could in principle use their algorithm and their platform to come up with a cancer test for basically any cancer. They chose colorectal cancer because it was a great need, easily reimbursed, very actionable that allows them to actually start with the go-to-market first and work back. And it's a beautiful thing that when you have a technology that allows you to do almost anything. Now the question is, what should we do, what can you do?

But AI is not the only way to engineer. Another great example is something like gene-editing, like CRISPR. There's some beautiful work out of Stanford that is proposing to use CRISPR as a prophylactic antiviral [for COVID]. So, not a vaccine per se but a therapeutic you would take if you think you were exposed to COVID-19. Now it's about finding the right software part, like what is the sequence of COVID-19 that we want to chop up. In that sense, that identification of the signatures you want to get rid of is philosophically probably much more similar to antivirus software than to any sort of typical vaccine creation or discovery of antiviral therapeutics.

Where this is important is not just for COVID-19 but the idea is that, just as antivirus software can deal with lots of viruses as they come along, there will be other viruses after COVID-19. COVID-19 is one in a series of pandemics related to SARS, and so on. And the ability for us to rapidly engineer new therapeutics to handle whatever comes is a pretty major shift.

One of your partners famously wrote the "It's time to build" essay. I'm curious what you think entrepreneurs should be building now in health care and if there's any areas that you're particularly interested in seeing new ideas and new pitches?

I think there's no greater area, at least from my very parochial perspective, than to build in biology and in health care. Before COVID-19, I think people sort of forget that one of the most political hot-button topics was health care and will remain health care. The cost of health care continues to skyrocket, and it's something that will just destroy our economy if we can't control it, and controlling it in old-school ways means outcomes that people don't like.

So the question is, how can we cut costs and save lives? This is a place to build. This is the opportunity that tech really has, to save your life at considerably lower costs. It's a win-win for everybody involved. The ability to get drugs into the market way faster and cheaper, or even companies like Devoted Health [A16Z portfolio company] that are tech companies through and through that use tech in terms of logistics. I would argue health care is the most challenging logistical challenge problem we have in the world, especially in this country, and tech is fantastic at decreasing costs and improving outcomes and these sort of logistical nightmares.

Devoted is doing that in the context of Medicare, of being a provider and improving outcomes and lowering costs. I think these places are real opportunities to build where it has this beautiful "everybody wins" thing where you can build a huge company, make a big impact in the world, save millions of lives, improve millions of lives — probably billions. So, I would argue this is the place to build.

Are you actually seeing that translate into more people coming to you wanting to build companies?

Not COVID-inspired per se, I think there is a greater trend over the last five years where people normally go into a pure tech company, and instead they want to go into the companies that we invest in, which are tech companies in biopharma and health care. And I think that it's being built like a tech company, has a scale of output exits like a tech company, potentially, but then with the added benefit of being able to help.

Five years from now looking back at this time, what will you say is the biggest thing that changed?

I feel very strongly that the first and foremost the most important thing to change in this pandemic is our mindset to adopt technology to realize that there is so much potential here that has been untapped. And that's where it starts. It's the patients adopting this technology. It's pharma adopting the technology, and startups creating this technology and partnering with all the incumbents to roll it out to patients. I think every one of us is responsible for making these changes, and I think every one of us is seeing the impact of not doing it.

So I think we will be ready for the next big challenge like this, and the next big challenge isn't going to be a pandemic. It's not going to be as in our face. The next big challenge is just solving the health care system in general. And I think this crisis will give us the lessons we need to solve that.

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