The a16z Show - a16z Podcast: Players and Paths for Healthcare Startups

Episode Date: April 16, 2018

The creation of each new biotechnology enables a tool, a therapy, or a diagnostic: a molecule, a protein, an app, a platform. And the process underneath isn't just complex in the science and engineering of it, but in the go to market. So who are the stakeholders in this process? In this podcast (which was originally recorded as a video), a16z bio fund general partners Jorge Conde and Vijay Pande give a quick hallway-conversation style overview on the stakeholders -- as well as what the process is from inception to approval to market; how do go-to-market models differ; and what should founders know at the beginning of each path. Stay Updated:Find a16z on YouTube: YouTubeFind a16z on XFind a16z on LinkedInListen to the a16z Show on SpotifyListen to the a16z Show on Apple PodcastsFollow our host: https://twitter.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see a16z.com/disclosures. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Welcome to the A16Z podcast. Today, we're having another of our hallway-style conversations. These episodes are based on videos that are also available on our YouTube channel. YouTube.com slash C-slash A16Z videos. What's the path to success in the world of healthcare startups? Bio Team General Partners Jorge Condé and Vijay Pondi discuss how founders need to adjust their plans for bringing a new drug, process, etc., to market.

And how go-to-market models and players involved may differ depending on the product, be it a molecule process or platform. Hey, we got Vigipani and Jorge Conday here at General Partners at Andresen Horrods on the Bio Fund. So we got lightning round today. So, you know, we're seeing all these forces of biology coming to computer science and computer science coming into biology. You know, what's the lay a land of that? Well, I think, I mean, this is a, as we all know, health care is a very complicated landscape. So let's just take it at a very high level and then we can sort of dive in and go through sort of the various players here.

So if you're developing anything in the health care space, and let's just focus on human health care. for a second to put a scope on this. Generally speaking, if you're going to develop a technology or a tool, you're going to develop something that's going to enable a drug or a therapy, or you're going to enable something that's going to enable the diagnostic to help detect disease. I mean, at a very high level, it's tools, therapies, and diagnostic. So let's assume that you're playing in that space. And you're thinking quite generally, the therapy could be many different types of therapies.

I guess we'll see. That's right. No, it could be, you know, a chemical. It could be a protein. It could be a cell. It could be a gene. It could be an app. Right?

So it could be many, many different things. But generally, for the most part, if you're going to do anything that's going into humans or going to affect how diseases is treated and managed, you're going to have to go through a fairly straightforward process in terms of chronology, but it's very complex underneath. So you've got to, A, discover something that's relevant for human health. And that's sort of the R&D piece. If you're developing a therapy or a diagnostic, then you've got to convince the people, that matter, in this case, the regulatory agencies to allow you to put this or use this

with humans. Then you've got to figure out how to get it paid for. Then you got to figure out how to educate the health care system that this is valuable for patients. And then you got to figure out how to get patients to actually use it. So, you know, it's not easy. And, you know, the joke we have, this is not B2B, this is not B2C, it's much more complicated than that.

And so, you know, when you sort of dig into that, who are the various players there? So some of them are pretty straightforward. You have the regulatory agencies. So if you want to develop something on the therapeutic side, you're going to have to do human clinical trials. If you want to develop a diagnostic, it's a slightly different path, right? If you want it to make a diagnostic that is quite literally, you know, a little box to test something, you got to go to the FDA. Or Cleo, presumably. Yeah, so now that's different.

So if you wanted to develop something that could be tested in the lab, fortunately the FDA has made it such that you could do something called a laboratory-derived test in a Cleo lab. And Clea just means that you've passed sort of the basic processes that ensure that your lab runs a good process and that data is reproducible, et cetera, et cetera. So if you're going to do that, that's a less risky proposal. You develop, you set up your own lab and you can run test. And as long as your processes are robust, the regulatory agency will be doing that. And we've seen diagnostic startups take this LDD clear approach and that seems to be very natural to begin. I think that's a natural sort of initial approach. It's lower risk and lets you get to the market much more quickly.

On the therapeutic side, I think it's much harder, right? Because you do have to go through the traditional phase one, two, three clinical trials. And before that, you have to prove that it works in tests and both, you know, in cells and then in animals. It's a very long process. But then the other path is that you can develop a tool or technology that you sell into the R&D industry itself, which is a really interesting go-to-market path if you have a very powerful technology. Because it allows you to do a lot of things. Number one is you can figure out how to slice and dice this technology to sell to multiple players in a non-execlusive way.

Right. Number two, the R&D industry in the U.S. alone is like a $75 billion a year annual industry. So, I mean, there is a lot of spend that goes into the space. And so that's another path you can take. So if I'm an entrepreneur in bio, one of the first things I would say is, do I want to make my own drugs or diagnostics or do I want to empower the industry to make better drugs and diagnostics? These are two very different go-to-markets. Yeah, although I would think, and I think we've seen, it's hard to break into that, right? I mean, because you've got to have a tool that really changes the game so much that they will give you some,

fraction of that 75 bill. I think that's exactly right. And this is where this concept of engineering is important because it allows you to essentially convince player A to give you value and without you essentially locking out the ability to engage player B and C and D because if something is widely applicable and transformative, usually you can essentially sell it again and again. Is there any example of like a tools company that became like a huge thing? Sure. I mean, there are many examples. I think one of the classic examples is a company called Atomab that essentially came up with a better way to design monoclonal antibodies. And so what they were able to show is by partnering with virtually every company that is trying

to develop monoclonal antibodies as a drug, as a therapy, they could take a small piece up front. Once it proves that it works, they get a big piece of the economics on the back end. And they've shown this again and again and again. They're still a private company. And last I heard, it valued well north of a billion dollars. So they are a private biotech unicorn that has become that doing just that. Yeah, and I guess, you know, to some degree,

alumna is an example as well to the extent that it's driving research spend in addition to other areas in genomics. I think aluminum is a wonderful example, right? Because they basically took what was an impossible concept of being able to sequence, you know, full genomes at scale, cheaply and reliably quickly, and made it not only possible, but made themselves sort of necessary to do this. You can't do genomics essentially without alumina. So, you know, just I think we're running out of time.

I mean, so, you know, how would you sort of, of think of this whole space together. How do you conceptualize it? So the way I conceptualize it is it all comes down to, you know, your go-to-market should be dependent on your technology, right? So if you have a technology that's very broadly applicable and, for example, diagnosing disease, the LDT path makes a lot of sense because you can start to turn out tests as you sort of develop them.

If you've got a platform that allows you to develop drugs in a way that was not possible, maybe going and becoming your own drug development company might be the way to go. If you have a platform that's so broadly applicable at sort of elucidating disease biology, then doing that the partnership route might be the way to go because you'll never develop sort of the deep domain expertise in every single disease in parallel.

Yeah, I can imagine it, especially for our tech heavy founder style, sort of product style founders, that just understanding the go-to-market issues from the very beginning, I think would be very important in how they define the, and shape the company and shape the product.

I think that's exactly right. So the way I would think about this as an entrepreneur is, do I understand what I need to prove, how I'm going to get it approved, and who's going to pay for it? And that will help define your go-to-market. Perfect. Well, I think we're out of time. Thank you.