Harry welcomes back Andrew A. Radin, CEO of the drug discovery startup twoXAR, where scientists model pathogenesis computationally to identify potential drug molecules and, ideally shaving years off the drug development process.
Harry welcomes back Andrew A. Radin, CEO of the drug discovery startup twoXAR, where scientists model pathogenesis computationally to identify potential drug molecules, ideally shaving years off the drug development process.
Harry first spoke with Radin two years ago at the AI Applications Summit—Biopharma. (Listen back to MoneyBall Medicine Episode 9 from November 2018 for more details about the company's innovations.) Since then, the company has begun to use what Radin calls twoXAR's "discovery engine" to test hypotheses about new drug leads in 18 different treatment areas, counting a dozen internal programs.
"We go after complex disease where we think there is not only an unmet medical need, but where we believe discovery of new biology can unlock some opportunity for new therapy," Radin tells Harry. He says the company's approach compresses the time-consuming early steps of basic science, literature search, hypothesis formulation, and high-throughput screening into a single computational step. "We're going to take all the existing knowledge about the disease and set it aside and see if we can't make some new discoveries about the biology as the starting point."
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That's it! Thanks so much.
Transcript
Harry: Andrew welcome back to the show.
Andrew: It's great to be here. I think it's, it's been about two years since we, yeah, I was,
Harry: I went back. I was looking at, I was like, when, when did we record the last show? I'm like, Oh my, two years. And two years in the world of data is like,
Andrew: I don't know from the technology perspective, we've actually, let's see, in those two years, we've probably made about a hundred new releases, new iterations of our software over that time.
And so imagine, imagine like, you know, getting a hundred new versions of your car and of course technology just moves that fast.
Harry: Yeah, no, I, it's funny because I have this conversation with people regularly of like, you know, Well, you know, is this software done? I'm like, listen, it's software. It's never done. Right?
Andrew: Yeah. And so while it, it, it certainly depends. I think on how the software is deployed. I mean, there's, um, you know, as a guys built a lot of software systems, I've worked on, for example, early in my career in large scale, uh, telephony systems, the software systems that power, the nation's telephone calls.
And that's an example where you do a bunch of work, you do a bunch of testing, you deploy it and you don't touch it. Uh, in some cases for years, Uh, aircraft are very similar, right? Like cause changes. Um, you know, you would, for example, the software that powers your x-ray machine, you probably, you probably don't want that to change that often.
Um, but there are places where, of course you can dynamically change software know even multiple times a day. Right. Um, and uh, historically that's been more in web based applications, right? If you, if you go back to a website and you reopen your web browser, that software can change. And it's a very little, little risk.
And because of that, Um, you can actually increase the velocity of, of trying new things and trying new products and seeing what works and, uh, that sort of philosophy that, that rapid iteration is something we've brought to the drug discovery landscape, where our, our software stack, which is what we use in the discovery process.
Internally,we are changing that thing daily. Um, and then we ultimately get it to a, to a release that we, um, we use with our, with our discovery team. Um, but we are rapidly iterating that product. It's, it's been over hundreds of iterations, hundreds of software releases. And every time it's a small experiment, right.
We're going to make this change to our algorithms or data sources or that sort of thing, and see whether or not like, do the predictions improve, right. Are we actually making a new discovery or are we coming up with something that is more likely, uh, to be efficacious and safe? And we have some digital test to discover those things.
And that allows us to just move so fast, right? From the, from the computational perspective, as opposed to iterating, you know, in the physical world, right. We have an idea and you run a wet lab experiments and that can take months. And you just, you learn that one negative information of the course of a very long time, as opposed to the course of an afternoon.
Harry: Yeah. Yeah. Well, I'm, I, it's interesting. Cause I'm sure that anybody from Pharma now is like a zillion questions are going through their head of like, how do you check this? How do you know that? How do you. You know, uh, but, but let's step back for a second. So two years ago, if my memory serves me correctly, you were sort of doing more services oriented, work, right.
Testing, what, you know, you had built out and now you've made this what looks like a much stronger pivot that we talked about two years ago to your own products. And how has that, how has that pivot and why. Why did you need to make that pivot in a sense?
Andrew: Yeah, no, it's, it's interesting that that's, um, how people is seeing an externally, because internally, like from my point of view, our, our vision, our plans really actually, nothing has, has changed.
Um, but what has changed over the years is as we have more success, uh, we have the permission, if you will, to just gather more resources. And so in the, in the early days of the company, You know, we used our discovery engine, uh, to come up with, uh, new ideas. And what I mean by new ideas is, is our output from the technology, uh, is a new hypothesis, new understanding of biology.
We typically go after complex disease where pathogenesis is not very well understood. Um, and so as a result, we're, we're coming up with, with first in class solutions, right? These are these, this is biology. That's not been, um, not been tested in that disease before. And of course it comes coupled with a, with a molecule, with some chemistry to, to test out those ideas.
And so our, our initial, uh, programs were taking the output of the software, uh, with very little, uh, in some cases, no wet lab experimentation whatsoever. Um, and then licensing that knowledge, not, not necessarily a service deal, but you know, upfronts, milestones, royalties, the typical pharma deal, uh, to a pharmaceutical company who has the development team to then screen those molecules down, uh, identify lead, do the medicinal chemistry, all the, all the traditional work that comes post discovery, uh, to turn something from, you know, early chemistry and into a product.
And so we've been doing those deals, uh, for many years. Um, but part of. Uh, what we're very interested in, right? Which is actually meeting unmet medical need. Excuse me. And getting products to patients is, is all about the time. Right? And so it's very, time-consuming, uh, the sign up pharmas to, you know, go through a diligence process and in some cases, The time it took to negotiate the deal.
We could have actually gotten something to I and D at somebody's time. And so we sort of recognized, you know, how, like what, what are our Pharma partners doing that we, uh, that we can't do. Right. And that's about it. Um, preclinical execution, which to be clear, I think when, when we were speaking two years ago, I know we, we, uh, we were running back clinical studies on our own.
We had, we had that, but some of the other pieces around development, um, we didn't have as a team. So these days, couple of years later, we have, uh, new people in the company. So now our, our head of R & D is Mark Eller, uh, who wasn't with us back then. And so Mark, for those who don't recognize his name, Uh, he formally was, uh, the head of R &D at Jazz Pharmaceuticals.
Um, he was there, uh, for about a dozen years and saw it from its early days through multiple FDA approvals. Uh, and he's got a number of products, probably Allegra's the one he's, he's personally most famous for, uh, that he's brought, you know, to the approval process that, that make billions per year. And so now, now that expertise, um, is, is driving our R & D process.
Right. And so we're going beyond. Just the discovery and into the development. Um, and we've also brought on people like Anjuli Pandey, who formerly was, uh, the head of chemistry at Portola, uh, therapeutics. Uh, most recently was CSO at bridge bio. This, this guy has had a, had a very nice IPO recently. And so she's got, geez, Louise, I think over 60 patents to her name in the chemistry space, multiple products she's brought to approval as well.
And so she's leading the effort, you know, to take these, these, um, uh, early molecules, perform the med chemistry on them and get them into, you know, sort of the, the pharmaceutical product you would expect to go into the clinic. So we've been pulling those resources into the company. And now, you know, relying a little less on our pharmaceutical partners to do the development for us.
And we certainly, we continue to do those deals. We have, we have the ability to go after more diseases and we have the resources to pursue ourselves. So we, we continue to do deals like that, where we hand off the discoveries to others. Um, but nonetheless, we've got about a dozen programs now, internally that we're developing on our own, um, using our resources and using, using CRS.
Harry: Now, how quickly do you, you know, because of the engine and the capabilities, right? How, how. When you're trying to explain timeframe to someone, how do you frame it? Of how much faster the system can get you to something that looks like you should go after and then actually helping, you know, design a molecule and so on?
Andrew: Yeah, well, we, um, these days we say it saves years. We, we used to be a little more, more granular on that. Um, but the reason is it really depends on the disease area. Yeah. And sort of what the starting point is. Um, and so for us, as I was mentioning earlier, we go after complexity where we think there is not only an unmet medical need, but we believe where discovery of new biology can really unlock, you know, some, opportunity for new therapy.
And so if you look at the traditional approach of, you know, coming up, essentially with a new target, and I want to be clear, like we don't go to the literature and find a target and then, you know, start developing rather we collect a bunch of data and we, we discover those targets ourselves. I mean, if you look back like the heyday of big pharma, right?
In like the seventies, eighties, this is what they did. Right? Like they discovered new biology. They came up with new targets. They. Uh, you know, uh, came up with some BioEssays and that sort of thing to try out, you know, a bunch of chemistry hypothesis screen, right. And eventually little that down to some hits that they'd moved forward.
Like all that work. From the traditional sense. And by the way, like not many people do that anymore. Certainly not under one roof. Like we like we do. And the reason is as you just identified is it's just so time consuming. So time consuming to go through each of those processes, because the traditional approach is to do a lot of basic science and literature search and, you know, forming hypotheses and, and it's, it's a, it's a long road, right?
To get to the point where you've completed that first high throughput screen and have some hits. And so we do all of that in computation. Right. And so that saves you years. Um, and I would say some of the people that go well, does it really save yours? You know, there's, there's certainly companies that will in license, a molecule or they'll take something that other people have started in there they're, you know, being it's, it's being handed off to them, or they're pulling something in, from an academic lab or whatever. They've read about a target in a, in a, in a paper recently. So they've got a head start, right?
So that's maybe where there's a debate on the year saving, but I'm, I'm talking about like the old school approach. Uh, we're gonna, we're gonna just. You know, take all the existing knowledge about the disease and sort of set aside and see if we can't make some new discoveries about the biology and that's the starting point.
Right. And if you think of it from that, that perspective where I think the real opportunity is, um, in terms of making a big difference in, in going after something new, um, that is something for sure. We're saving years in the processing. Yeah.
Harry: I mean, I've had discussions with Joel Dudley about like, okay, you know, let's put all the data in and let's look at what the data is showing us in the direction.
And, and hypotheses that we can then go chase down that we in our, you know, even the human brain is an amazing instrument, but it's, there's way too many data points to look at simultaneously.
Andrew: Yeah. Like I meet for me to keep three things in my head is, is a good day. I mean, I look at billions of points of information and not only that, but to figure out like, what's, what's a false positive, right?
Like what's, what's a coincidence versus what's signal. Um, you're right. That's, that's not something that human brain does very well, certainly at that, at that scale. And so, you know, we're looking for, uh, uh, the patterns that represent signal versus the patterns that represent coincidence, if you will. Um, and that's not something that humans can easily view where they can look at, you know, massive.
You know, troves of information and, and try to try to draw those parallels, especially when a lot of the information we're actually processing doesn't really lend itself to like giving you an answer. A part of, part of it is going through it and figuring out what's relevant and not. And, and most of that of course is, is not relevant.
Right. It's it's um, uh, as Mark often says, you know, it's like looking for a needle in a haystack, right. And so that's. That's something that human brains can't do very well. Um, and I would say that one of the interesting things that comes out of this, we might even talk about this a couple of years ago.
But, uh, when we, when we go through this, this process and we come up with these ideas, all of our disease programs, every disease we work on, um, we have, we have okay well, we, we often connect, you know, with a luminary in that disease area. Um, and we, we bring them into the, into the projects and. You know, we show them the output of, of what we have or like, look let's, these are, you know, we say our ideas reality is the machine, the machine came up, the ideas, what do you think?
Right. And so part of it is we're going after novel stuff. Right? So they tend to say like one or two things, like one thing is like, Huh? I like this. This is an interesting idea. I hadn't thought of this before. You know, it kind of reminds me of something like, you know, okay. Like, you know, like, like seems crucible, let's try it out.
Um, but the other thing they say is I'll look at stuff and they'll be like, no way, like, yeah, like this is just stupid. Like you are wasting your time. Right. And, and those are my favorites. Um, we don't do this anymore, but we use, we used to ask people to write down, okay, we've got these 10, you know, these 10, the theories, if you will, at least 10 different targets, we're going in these 10 different molecules.
We're going to go screen. You know, you, disease expert, you tell us which ones are going to work and which are not. And, uh, and we found out that the disease experts were no better than random and in picking the winners, um, which I think is very, uh, sort of telling about. Uh, how little we know as, as humans, you know, inspecting literature and sort of the capacity of the human brain to sort of understand against, you know, again, these, these, these massive sources of information what's relevant and what's not.
Um, and so, you know, we've, we've had a number of, uh, very exciting and very pleasant surprises, you know, where we see through the screening process, we see signal and ultimately, you know, we get down into in vivo studies, you know, these, these gold standard models. Where we compare against standard of care.
Right. And then we see, uh, in many cases, you know, our molecules are showing stronger signals of either efficacy or maybe similar efficacy signals, but stronger signals of safety. And that tells us we've got something that's really compelling and worth moving forward.
Harry: Yeah. I always find it. It's a fascinating discussion, you know, and when like, again, you know, going back to Joel and Alzheimer's and him pointing out to people at NIH that, you know, look herpes, simplex two might be.
Right. And everybody was like that. You crazy, right? Yeah. Hey, listen, here's all my data. You'll run it. And you see what you find. Right. And, and so I, I think NIH now is sort of thinking about how to come at this a different way, but I always find that fascinating is like, you've got this incredibly complicated system and you're looking at this narrow little window that you are an expert at.
And how could it not be that anything outside that window influences what's happening in that it's, it's sort of mind-boggling. And now that we have computational capabilities to sort of, I don't want to say brute force, but I feel like 10 years from now, we're going to look back and go, damn, that was brute force.
We have much something much more elegant now, but a way of looking at these and looking at the complexity and seeing that a pathway that we never even thought of. Has an influence on this disease, um, is fascinating to me. I, how the whole industry isn't moving in this direction much faster is sort of always mind boggling to me, but I understand that.
You know, your expertise is not wasn't necessarily drug discovery from day one.
Andrew: Yeah. Look it's it's um, I think computer scientists, as we've gotten, I think more involved in this industry, um, we represent disruption. It's a very different way of thinking. And, and disruption takes time and industries, you know, resist disruption, you know, quite frankly, um, you know, I, one of my startups I did, uh, Nolan Bushnell was, was the chairman of the, of the company.
If that name doesn't ring a bell, not only did Nolan start Chuck E cheese, which he's very famous, but, but before, before Chuckie cheese, he founded a little company called Atari. And before Atari video games, the video game industry didn't exist. Okay. And so when I, when I first met Nolan, we went out to dinner and like any person who's just, you know, in awe of such an amazing technologist in a, in a pioneer, you know, for that industry, uh, we went out to dinner.
I'm like, so Nolan, you know? Right. Yeah. I'm just like, like this eager, eager young man. Tell me the stories of the, the days of Atari and, and at the time, uh, at our, at our, uh, startup, we were, um, uh, working on some fundraising. And so he, he told me this story. So you have to understand, like, let me set the scene, right?
This is like maybe late sixties, early seventies. And, uh, and I'm sure maybe Nolans going to listen to this podcast. I'll send it to him and he can get the story, right. Because this is a long time we had this conversation. So I'm, I'm sure I'm going to get the details wrong, but the, but the core of the core of the messages is there anyway.
So it's, you know, it's around that time period. Um, and video games don't exist. Humans have never seen them. They don't know what they are. Okay. And so he's, he's working on this he's she's building pong or whatever he's building over, over here in Sunnyvale and next town over. And, uh, and he's chatting with people in, you know, the, the game industry, but with that in air quotes, the game industry, I don't recall who it is specifically, but let's just say it's Parker brothers, right?
So he's, he's sitting down with the fine folks at Parker brothers. He's like, man, I've got this new, exciting innovation. It's going to change, uh, the gaming industry as a whole and just being a personal entertainment and I've combined computers and games and have made this thing that's called the video game.
That's going to be the next. Huge thing. Okay. And so he's telling me, you know, the guys from Parker, brothers, whoever it is, they're like Nolan, Nolan, right? Sit him down, hand on the shoulder. Uh, so first of all, games are made out of paper and card. Okay. But, but more importantly games, you sit around the kitchen table with your family and friends, and it's a social experience where you interact in the point of the game, you know, is this, is this social gathering.
And you're telling me, you're going to make a thing where people are going to stare at a television. And that's going to replace, you know, this, this whole sort of social ritual that is games like Nolan, you're an idiot get out of here. Right. Uh, and of course, you know, we know what he did. He, he built pong, he put it in a bar over in Sunnyvale and people lined out the door, pumping quarters into it, and the rest is history.
Um, but that, that story, I think really resonates for me because does your point, like looking forward to the future? Like the video game industry is today. It's like an obvious thing. If I'm not mistaken, it pulls in more revenue than, than Hollywood does, you know, from movies. Like it is just part of our culture.
It's just part of our experience. It's, it's part of, you know, growing up kids playing, you know, video games, uh, and, and before, you know, Nolan came around, like, people couldn't understand this, this what's now obvious, this thing that was coming. And I think in a very similar way, you know, as a computer scientist, who's worked on a variety of industries and Marc Andreessen.
Right, right. One of our investors, Andreessen Horowitz, like talks about this talks about all the things you used to buy at radio shack that are now just in software, right? Like all this, this stuff has been replaced. Um, and I think in a very similar way in this industry, it's, it's tough to imagine what it is until you already have it.
Right. And so for someone who, you know, started this company many years ago, and I've been very consistent in like my belief systems and what we do, and like our output and I've, I've gone from, in the very early days, everyone said like, this will never work. You know, you're a fool. Right. Very similar to the Nolan thing.
There were these days, maybe like half the people say that maybe a little more than half. Right. But like all the tapping, just the passage of time. And what's happened in that passage of time is people are starting to get a hint of what's possible, you know? And I also have an a conversation actually the night before last, or as I was chatting with an investor who was talking about, um, sort of his belief system and what's happening.
And so you, you look at, you know, recent IPO's like, like relay and Schrodinger. Uh, of course the guys at Roy van are doing extremely well. Um, and, and he was sort of saying, you know, because of the acceleration of technology. Uh, people are coming out of nowhere and they're challenging, you know, these large established pharmaceutical companies.
Now they have the advantage of products on patent for many, many years, and it's going to take a while to disrupt. Um, but this investor who, who I think was very thoughtful, it was sort of saying like this, this disruption. Is coming with, with so much momentum behind it. Um, and we believe, you know, some of these, these what look today, like small sort of innocuous players, um, are really going to disrupt the, the field and, and make huge changes in the pharmaceutical industry as a whole.
So that was an interesting perspective. Just kind of tying all those pieces together, where. You know, innovation and disruption, it comes from the outside, right? I am, I'm definitely an outsider, right? Like I, I built mapping systems and systems and advertising networks. And here I am making drugs. It's, it's kind of a weird transition from that standpoint, but it's, it's highly connected to this idea of, um, bringing disruptive ideas into a rather entrenched industry.
Harry: No. And I, I mean, look, I I'm, I try to read everything. I could get my hands on from the tech side. I'm scanning constantly. Um, I was listening to the, the, the guy who has the title futurist for paramount pictures. Nope. How about what they're working on, right? Yeah. I was thinking about that too. Maybe I can transition my next life into the future is that's a really cool title.
Andrew: Yeah.
Harry: But, but hearing about, you know, all these different sort of plays moving forward, you know, using. You know, uh, augmented reality and things of, of nature, of how you collaborate and so on and so forth. And you superimpose that.
I take all of these things and they try to superimpose that on our world and you can see the ball moving forward in ways that to someone who's only looking in the field cannot see. It's like looking through one hollow lens and you can't see the rest of the picture. That's developing around you. And, you know, I find fascinating that the status quo can't see that there, the world is changing at a rapid pace.
Now I do believe that COVID, we're going to look back at COVID and yeah, I know it's a, it's a negative for, for all intensive purposes, but I think from a moving things forward from a technological perspective, I think it's been a huge shot in the arm for remote monitoring of patients, for telemedicine, for all these other areas.
I think it's moved it forward five to 10 years, and I have to believe things that you're working on are now, or even should be even of more interest to a therapeutic company. Because if you can't get everybody in the same room to do the experiment, how do you do the experiment to move it forward faster?
Andrew: Yeah, no, look, I think those are, um, excellent observations. I think, um, uh, COVID is definitely an interesting time. Just sort of see how technology helps influence, um, society and you're right. Like, so here we are. I mean, the last time we did a podcast, we did it together. Right. We were standing together, where were we were, we were at the Harvard medical center.
We were, you know, in a hallway together and, and, you know, around the table recording and, and, uh, you know, we're thousands of miles away together. I've got to. You know, a fancy fiber optic cable, you know, coming into my house. I know what you have on your end, but like, I, I see you clear as day and here we are recording a podcast.
Right. And so, first of all, how cool is that? Now I recognize like that's something we've probably had for five or 10 years, but none the less like that, the point is, um, we're, we're still able to put this material together without physically being together. And I think, you know, even in our own company, As, um, as a, so Santa Clara County, which is, which is where we live and where our offices are, you know, we were one of the first places in the nation to have, uh, detected cases.
Uh, and so, uh, the health commissioner here, um, was one of them was one of the first places to put shelter in place and we knew it was coming cause we were, we were connected to some people. And so at our company, we, we trained everyone on how to use Zoom and Slack. And, uh, we had, uh, we had a goodbye party on a Friday, you know, we'll see, I'm sure we'll see each other again soon.
We're not. And we prepped everyone off and off we go. And the next Monday we started operating our business, um, completely through, you know, technology completely used for video. And, um, we have not gathered, uh, as a group in our office since this was months and months ago. And throughout this time, uh, in the early days you had some little adjusting you know, figuring out how to do this, but like, you know, by and large, like we're, we're operating, uh, just as efficiently and moving forward just as we were before.
We're in that physical space together. Now I will, I will certainly say there is, um, value to being together with people and sort of the, you know, there's, there's more than what just happens during the meeting time and, and building personal relationships. But, um, you know, it's a big question. Like, are we going to be able to function as a company without seeing one another?
And the answer is yes. Right. And, and I think one of the things that COVID has done for that type of question is like, okay, just this whole, you know, remote work stuff. No function. I think it was Melissa Meyer many, many years ago, like said very famous decree. Everyone at Yahoo shall come into the office, a Yahoo.
It will be no more remote work. And here we are now with all these big tech companies and small ones like ours, everyone's working remotely and it's. Kind of working out. Right.
Harry: So it's interesting. Right. I mean, Google just announced right. Then nobody's coming back to the office until July.
Andrew: So next summer. No problem. Yeah, yeah. Next year, next year. Yeah. So like, I, I think what that means is, so now, you know, people are, um, you know, in many industries, not, not all of them, um, you know, able to work from home. You know, we have people in our company, you know, my, my chief of staff. Uh, she was, uh, she was born in Mexico.
She's been living in San Francisco, you know, she just said to me the other week she was like, look, she's like, I'm in this, um, rather expensive apartment in San Francisco and you leave, uh, you know, they, they got the internet in Mexico and it was odd. She asked me, is that cool if I, if I, you know, go to Mexico and I'm like, why not?
Like, you know, like, I'll let you know when, when there's a chance we'll be getting back together in the office, but like go for it. And she's like, awesome. I'm going to go live like a queen. Right? Like it's. And so. That recognition that, you know, even, uh, physical places, you know, like, like why do you need to be in a high rent area, if you can just, you know, do your job effectively some, somewhere else.
So anyway, so all these, all these things are kind of unraveling. And I think to some of your points on medicine and healthcare, I think the other thing that's happened is, is people are very nervous to go in and see their clinician because they think there's other people around who might have covered. I don't want to get that.
And so, yeah, like the whole telemedicine. Piece of it is taken off, but, but the whole point is like, um, using technology, using the internet using, you know, like the technologies we're using right now to interact with folks, uh, on all sorts of levels, whether that's professional, whether that's, you know, that's patient care, um, all of that, the barrier has just dropped.
Right. And so I think it's, it will be interesting to see post COVID world what it does. Um, like are people are going to like get back into the office or not, right. Or are people going to think every time they're not feeling well, they need to go see their doctor or they're going go, Hey, you know, I think I'll do that mobile app thing that I did before, you know, last year, because it kind of worked and I realized I don't have to drive anywhere.
And yeah, I think those, those, um, events helped push innovation forward for, for sure.
Harry: So stepping back to where you are, do you think your, your. From a timeframe perspective, you're moving the ball forward faster by compared to say, you know, a traditional process, six months a year, two years. What's, what's a wild guess.
Andrew: I would say on average, if, if you're going to do a completely Denovo process from scratch, you know, we're saving about three to four years. Um, there's a point at which, you know, our processes don't speed things up and that's, as soon as we get the mouse involved, right? Like, I, I can't speed up the tumor growth than the mouse.
I can't say the activity of the, uh, of the potential medication to, you know, inhibit that tumor growth. I can't speed up the, you know, the histology and all the work that happens post that and all the activity that you need to do. And rightly so right. To, to carefully prepare for 90 filing. Cause, you know, when you get to the point where you're gonna test something in humans, you, you want to be absolutely sure.
Um, you're, you're being safe about it. Um, and you're, you're, you're doing something that's, that's worth the risk that you put onto your, um, your clinical trials efficient. So all of those processes, uh, they don't necessarily speed up. I, I think really where we're about speed in the discovery process. I think the real opportunity.
Post discovery is efficiency, not necessarily speed. Um, but you know, with patient trial selection, for example, um, finding the right population, finding the responders, you know, being able to do things where you maybe don't have to have as large a group, uh, you know, in your, in your clinical trials and example, those are things where now efficiency and cost efficiency. Uh, become, I think some of the values of what you can do with computational methodologies B can't really speed up, you know, a preclinical study or a clinical trial just to the nature of the biology and the time. And so that's how I see it. The first half is about speed and the second half is, is maybe it's more than half, but the rest of it is about just, just efficient use of, of capital, uh, to get the results that you're looking for.
Harry: Although I do see, you know, trying to look at the entire value chain. There are companies using computational methods to sort of find patients faster, make sure they, you know, they fit the trial better. Um, you know, remote patient, uh, remote clinical trials are becoming more of a thing. So I think we're seeing computations sort of failing gaps that can be filled in by that by technology advancement.
So I do see the process shortening over time from end to end, which I'm hoping also translate to. A lower cost at some point from end
Andrew: I think there's definitely the efficiencies to be gained throughout the whole thing. I think, um, again, if you're looking for, you know, we take some things that normally would take years, this is something we used to say early in the company, and we got critiqued.
So we stopped saying it, but it's still true. Right? Like we take, um, that very early portion of just understanding the biology, which, which can take many, many years. And like, you know, the computation does that in a couple of minutes. And so. That sort of stuff. That's a dramatic, you know, multi-fold, you know, increase in speed.
Um, and I'm not saying that some of the things you've talked about, uh, won't increase. I think the efficiency from that, from the speed perspective, but it's not going to take a process that takes, you know, four or five years and turn it in three minutes. That's for sure.
Harry: No, no, no, no, no, absolutely. And you know, it, it, it begs the question of, you know, like we need to rethink how we teach biology.
Right and understanding these things. Right. And it's, uh, I remember doing a lot of reading, a lot of textbooks, a lot of experiments. I feel like most of that now would be, I'd be sitting in front of a terminal and combining pieces of data and, and, and coming at the whole learning process differently than I than when I was learning.
Yeah.
Andrew: You know, that's, that's an interesting thing to poke at. Um, Well, let me, let me share some thoughts here. And I don't know if there'll be interesting if they, if they're concurrent with some of the things you're thinking. I think, um, so, so, uh, let me, let me gather my thoughts. Okay. So when I, when I'm, um, when I'm screening, when I'm, when I'm interviewing a software engineer, Um, to work on my team.
Uh, of course, now that people are gonna listen to this podcast, they're going to know what the answer is when I prefer one of the things I asked them, as I say, man, like, imagine it's, you know, whatever, the 17 hundreds, the 18 hundreds computers don't exist. Technology doesn't exist. You're still you, right?
You're you've been magically teleported back in time. What do you think you'd be doing? And it's very interesting. And I get these answers like, Oh, you know, I'd, I'd be a school teacher. I think that would be an awesome thing or whatever. I would be a musician, all this stuff. And, and then I, and then, you know, this is like the hook.
And then I go, well, why aren't you a school teacher now? And then the answer is, well, because software pays better. Right. Which, which is a reasonable, a reasonable thing. But what it says to me is that, um, there's a lot of people in the field. That don't do it because it's their passion or their interest, or it's, it's something that really excites them.
It's like, I can make some money at this. And I think the best computer scientists and the best engineers, I know. They are tinkerers there, there are people who, and they're also creatives, right? Cause because software has gotten this, um, uh, this artistry to it where it's it's the tool set is so wide and you can do so many things with it that, you know, like the people that are really into software, like, and you know, another great question is like, so what do you do in your free time to see if they actually write software for fun?
Which by the way, while I'm chatting with you over here on this window, I'm writing some software, um, to do something personal on unrelated to work, but like there's a, there's a, I think a, um, a connection between, um, really becoming an expert in your domain and also just like truly enjoying it, truly enjoying the, skill and the trade and that sort of thing.
And I, I think that. There's a personality that, that, um, science attracts, you know, people like me, computer nerds, right. Who really enjoy software. And there's, there's different personalities that, attract different things. And I think it's, it's really hard to find someone. Who really enjoys, you know, like the biology and the sciences and software together.
I mean, when I, when I was studying this in school, most of my classmates were medical doctors. They, they had a medical degree, probably like 75% of them. Um, and so they're, they're trying to, they're trying to learn software, right. And if you have them like really connect with it and they really enjoy it and it's their passion.
And I think those are also the people that just produce, like the coolest stuff. Like you, you did the podcast with Jake, I think maybe a few months ago. So Jake, I met him at Stanford. He was one of my classes, but like, he's one of those guys, right? It's like this biologists software tinker dude. And like, you know, we, we would get together and left philosophize on stuff and like, yeah.
Like, that's the kind of person you want to see, like just making big changes in the industry and like he's doing that. Um, but, but my point in that is there was a bunch of other people in those. Classes and there's, there's some other people like Tim Sweeney is another one who, um, uh, I think actually was a surgeon originally, and now he's doing inflammation, just doing super cool stuff. Combinations. There's a bunch of other people in his classes are kind of like medical doctors are like, you know, I should learn software because it would be good, you know, kind of thing. And I don't want to call anyone out, but I remember like one person who was, um, A project due or something like that and see what it was before class.
And she was complaining. She was like, Hmm, I can't do this. I spent my whole day yesterday working on the software and I couldn't get it to work. And it's like, it's using up all my time. She hated it. And I also spent that amount of time and I'm like, this is cool. Like, this is fun. Like this is putting this thing together.
And so I think. Taking people and saying, look, you know, as a biologist, now you have to learn software and we're going to pound you over the head over it. Like, I don't know if that actually will transform and look, and maybe it'll, it'll light something in someone who didn't know that that would be of interest to them.
But I think it's really gotta be connected with, um, the personality and sort of like the enjoyment of the person. And I, don't know if that happens. That late. I think it can start much earlier. Um, look, I first touched a computer when I was, um, jeez Louise and it's like when the Apple two came out, I mean, Apple had a headache, everyone, every, you know, school got a free Apple, two computer.
And, um, I was fortunate enough that my parents were able to purchase one, but I was a little kid, you know? And so that's sort of where the passion started for me. And I think that's. Uh, for whatever it is, whether it's biologists or whether you're working in engineering or whether you're working in financial services, it doesn't matter.
I think that, um, exposing really children to software and programming and that sort of stuff, like some are gonna. Connect with it and enjoy it. And I think those are the people that eventually, as they get into different sciences and different disciplines will use that enjoyment and that skill to do something interesting with computer science.
But it's just, it's just my belief. I don't, I don't think you can take someone at like the college level. Who's getting into biology and be like, Hey, let's
Harry: no, but I, I think, and what I meant by, you know, teaching it in different ways, you know, my fundamental belief is that, you know, everybody should be Ssteeped in software, not necessarily to do it, but to understand it as a process, as a language, as you, cause at some point you're going to interact with it. So you might as well understand it, even at the basic level. And then as you're going, you know, going forward, you know, if you want to take on different careers, you, there, there needs to be a combination of this.
You still are. You ended up like when we were in applied Biosystems, you're like, okay, Get the computer science guy and get the IT guy together and get the, uh, biologist together, put them in a room and, you know, having to make something and nobody could understand what anybody was saying right. For the first like third year.
Um, but, uh, but on the other side, you're absolutely right. I mean, my, my family is always saying like, you're working all the time. You're working all the time. I'm like, look, let's get something straight. Every once in a while there's a pain in the backside. I need to deal with it. I don't want to do, but for the most part.
I mean, I'm in a kid, in a candy store every day. There's something new every moment. And I'm like, this is the coolest thing ever. And I get to be involved. Well, that's, that's not work. That's just fun.
Andrew: No, and that's, that's an awesome place to be, you know? And, um, I think part of what drives innovation and change and industries are, are people who are really just connected with that passion.
Um, and they have the drive as well. Like there's, there's something behind them that, um, you know, really inspires them to go and do something and, and, and, um, try to do something new. I think innovation is. It's a hard game. I mean, I, as I often say, I've done these startups, you know, I wish I could say everyone would, this was an astounding success, you know, was bought by Apple, which, you know, I always liked to talk about, uh, I don't always talk about the one that, you know, we raised geez, 23, $24 million building exploded it.
I guess every, every startup is spectacular. This one was spectacular in the negative, in the negative sense. But, um, you know, I think you also, uh, for people that, um, want to change the world and change industries. It's, it's tough to describe, but like, uh, it's not necessarily the grit, but it's like, it's, it's the enjoyment of like the challenge.
And, you know, I think Michael Jordan has some great quotes about, you know, all the times I missed, you know, as opposed to all the times I was successful. And I think part of changing industries is like, You know, you just hear no, all the time. As I was saying earlier in the, in the podcast, you know, in the beginning of this company, you know, with a few exceptions, it was certainly nice to have VJ at Andreessen and be like, Oh yeah, this is it.
Or I'm giving you some money. Let's see what happens. Um, but like everyone else I've talked to is just like, no, no, no. And there's a, um, I think there's a, a type of person as well, who just sort of listens to that. And I don't hear, no, I hear. Not yet or not now I can just sort of, by my reality, right.
Distortion field kind of puts, puts words in people's mouths that they're not saying. And I think all those things kind of combined together, right. We've been talking about these different things. I think there's the, there's the passion for the technology and just sort of having like the, the, um, uh, personal interest in sort of those things.
There's the, um, You know, again, the feeling like it's not work, it's just, it's something that brings you, brings you joy and it's really engaging that sort of thing. And then I think that final piece is just, you know, people who enjoy, uh, a challenge and doing something, uh, very difficult and, you know, the no’s don't discourage them.
The no’s only encouraged them. And in some cases, I think it's kind of the combination of all those things that make industries change. And I think, you know, kind of the theme we've been talking about is just sort of changes in, um, In life sciences and healthcare in general, I think finding people like that and really tapping into them and giving them resources to go, uh, go try some things and to sometimes fail and to sometimes succeed.
I think that's what really is gonna make the biggest movements, uh, in our industry, right? Because those are the, those are the risk takers. Those are the pioneers. Those are the visionaries who want to do something new. And I think the more we do to help support and encourage. Uh, people have that mindset and that way of thinking and that, that sort of endless energy, uh, to go out and do something is, um, is something that's only gonna make the world better.
And, and, um, uh, and therefore we should, we should embrace it as much as we can.
Harry: No, I totally agree. And it, don't tough. The tough part is finding those people, right. And they're not falling off trees. Uh, I can tell you, at least with all them, you know, after all these years of all the people that I've interacted with there, most people are just too nervous to take that path, but, uh, I try to encourage them to do it.
Andrew: That's where, you know, startup incubators and places where people who don't know, or maybe a little timid can come. I mean, I'm, I'm deeply involved with, uh, with Stardex. I'm a judge there. Um, I, I sometimes lead the neighborhoods and, you know, it's, it's often, um, you know, students that are, that are coming out of Stanford who have got an idea for a company and they just don't know where to begin.
Um, and what Stardex does is it is it's a community, right? It's a support system. It's, it's a whole set of other people in similar circumstances. Uh, whether they've, you know, had some success through their very early themselves, um, to work together as a, as a group and as a community to help people get there.
Right. And so I think that, um, type of thing, uh, whether it's a startup incubator, that sort of thing, you know. I wish we did more on the governmental level, uh, to encourage innovation, um, and put, you know, pieces in place where, you know, young, bright people come out of school and, and they've got a choice, man.
This is, I think I've said this before in your podcast, but if I did, I'll repeat it again. But like one thing that's man, is it annoyed me is, you know, people will, will graduate with a degree in biomedical informatics. They literally learn how to use computers to solve medical problems and save people's lives.
Okay. And then the likes of Google or Twitter, or Facebook will show up with a wheelbarrow full of cash and say, Hey, you know, you know how to write software, you know, these, that, that skills in short supply, why don't you come with us? And, you know, we'll, we'll, you know, deliver movies to people. And not that there's anything unethical about delivering movies to people, but you've literally just learned how to save lives.
And as. You know, a student who's coming out of school and they're just sort of like, geez, what do I do next? And there's this big, impressive paycheck. And they've probably got some debt and we're thinking about, geez, I want to, whatever, buy a house, start a family, all those things that young people think about, it's really hard to go.
Yeah. You know, instead I think I'm going to just eat, you know, tuna fish sandwiches and sleep on my friend's couch. Cause I have this idea for a start up like practical. That's not an easy thing to do. And so I think if we did more to help encourage and by encourage, I mean, supply. Young entrepreneurs and people who want to experiment with the resources, not only the financial resources to operate a company, but so they can, they can have a reasonable existence while they're trying to these things out.
Um, I think the better off we are, we'll be as a society. If we put more, uh, sort of, sort of leverage behind again, governmental resources to help people like that. I think we can do a lot more innovation as, as a, as a country and as a nation. Um, to improve, you know, not only obviously talking about the medical space, but like all sorts of other things, you know, whether it's materials or aerospace or transportation.
I mean, there's, there's so many interesting problems to be solved, um, that helping entrepreneurs are creating environments where entrepreneurs can, can grow. Uh, I think would be a wonderful thing to do if we could, if we could get there, uh, as a country.
Harry: But, uh, I wrote a letter to tech and it got published.
I don't know where in AI med or something like that about, you know, begging tech people. Like you need to look at this space cause you can actually make money and make a difference as opposed to, if you go to, you know, Facebook or something like that, like you really, you know, it's not no offense to Facebook, but you're really not making a difference in any way it's life.
But, but in the last few minutes here, let's pivot back for a second. To the company, what you guys are doing, what do you guys see the next milestone and, you know, taking the technology forward and the impact that it's going to have, or is there a particular program that really you're excited about that it's really moving the needle.
Andrew: Yeah, that's a good one. So yeah, we've we, um, so we act a bit like a mid-size farmer, right? So if we've got a whole portfolio, we've got 18 diseases, uh, currently under active development. Uh, now a number of those are through, um, uh, these licensing deals with, with pharma. But like I said, there's, there's a dozen or so that we're moving forward internally.
Um, and of course, you know, what, what seems to be the most promising, uh, programs are always the one where the uncertainty is the lowest. So the ones that have been around the longest, which we know the most information about seeing the most promising, but there very well could be an earlier program.
That's actually way more promising, but we just don't know yet. Right. Because we haven't gotten that far. Um, but we've got, uh, these days, uh, five programs. Um, in, uh, medicinal chemistry, right? So this is we've screened things down. We've got a lead that lead has been tested in multiple preclinical studies.
We, uh, see us performance is better than standard of care. If it exists or maybe against, uh, annual positive and control, might've been a, like a phase three clinical, uh, candidate, if there is no FDA approved molecule in that disease area. So we've got about five programs like that. Uh, we're, we're moving forward from the Med Chem perspective.
We've got five more programs right behind those where we have screen things down and we see early signals of a potentially, you know, more appealing therapeutic than, than what's available or what's about to be available. Um, but we have some more work to do to either finalize the selection of the lead molecule or maybe run another.
Preclinical study to, to, you know, get a second confirmation that what we have is, is truly interesting. So out of those, those 10, um, I, you know, I think in the next few years, it's not clear. Which one of those is going to pan out and be the most, uh, appealing for the company. Um, to ultimately answer your question.
I think for us, you know, our next milestone, there's sort of like these credibility milestones as you reach them as a Pharma company, like people get more and more serious about you. Uh, and for us, the next big milestone is an I andD filing. Um, it's not clear when that will happen. I would say the soonest, it could happen.
Uh, it would be, uh, the beginning of, of next calendar year. Uh, we do have something that, um, has the potential to be there. Um, but again, as we move forward, we are constantly killing programs too. We have a lot of optionality. And so we're always trying to figure out which one is the most lucrative to move forward with.
Um, but I think certainly within the next year or two at the latest, um, we will get to that. I need milestones. And I think that's going to be a huge inflection point for the company where now we've gone from being a discovery stage company to being a clinical stage company. And then really all sorts of things change for.
Uh, how you're perceived and you know, what people think about for your future and a whole bunch of things. So that's, that's what we're focused on as a company is getting to the IMD milestone, uh, not only as quickly as possible, but also to do with something that the most compelling thing that we can, we can put forward.
And so we've got lots of choices to do that with. Um, and we're optimistic that we'll have at least one, if not two or those, um, uh, in the next few years.
Harry: Yeah, I was going to say, well, you know, at the beginning of the year is not that far away. Um, No, we've got an election and a few things to get done before then, but, uh, it's it's feels like it's it's right around the corner.
Andrew:, time does time does seem to fly, but yeah, it's still summer. It's still summer, but, uh, indeed. Right. It's uh, I think, well, and certainly in the, uh, in the warp speed, uh, that we're going out for the life science industry. Yeah. Like, you know, six to nine months is insanely fast where other industries that seems like a, you know, winter.
Geez, Louise. Why does it take that long? But, uh, but obviously very quick for, uh, for this industry.
Harry: Oh, yeah. I mean, I always, I keep telling people, I mean, the difference between evolution and revolution is just a measure of time. Now.
Andrew: I love it. I might have to steal that and use it later. No, no. Feel
Harry: free. I mean, it's actually, it's a quote in the book because it's, it's, it's true.
Right? If things take a long time, people call it evolution. If it happens overnight, it's a revolution, right? It's so, um, Look, it was great to catch up. I'm I'm um, I'm really excited for you guys. I mean, cause you know, having these periodic, uh, discussions to understand the, the arc of the change is, is, is always fascinating to me.
And I just don't understand how everybody can't wrap their head around the impact that this technology is happening. And whenever I hear somebody, you know, naysaying or poo-pooing, I'm like. What am I missing and why am I looking at it the wrong way? I, sometimes I have to go back and look at a few things to make sure, like, I'm, I'm not, you know, drinking my own Kool-Aid sort of thing,
Andrew: but let me, let me close with this.
So Mark, who I'd mentioned earlier, who's our head of R & D. Um, you know, he didn't just show up one day and say, I want to work here. Um, he actually was a, it was a KOL, uh, with a company. Uh, for many years, we'd brought him in to, to consult on some of the things that we're doing. And so you sort of got like the slow drip of the activity over time.
And, uh, you know, finally, you know, he came in one day and we were talking about, I think we were talking about results on the bus. I can't remember what, but you know, we're talking about that. And some other programs, you know, any, any recognizes, he sort of knows, like if people said they know this, but they, you know, they kind of come in the office and they see, they're like, man, there's like 18 programs here.
You know, it's like less than 20 people, you know, like it's, it's just this tiny little crew. And so, you know, he's kinda like looking around the office. He's like, this is it, isn't it. I mean, this is, this is the team, you know? And, and he knows, right. Cause he's been, he's been looking at the preclinical evidence and he says to me, man, he's like, you know, I had been waiting to do something special for quite some time.
It's like, this is it. I want you to offer me a job. I was, I was just like, it's like, like, uh, like a guru to me right now. He wants to now he wants to work for me. I'm thinking like, you know, what's going on here? Um, And so, and of course, like, are you kidding? Do you want to work here? Yes, we can. We can do that.
Um, the kind of, um, part of that discussion was him telling me sort of his evolution of his complete skepticism in computer science and artificial intelligence and, you know, the way he described it was, um, you know, he saw computers, winning games, like chess and go, but they have, they have defined rules and they have to find outcomes.
And he's like in drug discovery, there are no defined rules. Like every, every drug that's made to market is its own own little story. Um, but not only that, but that the moves that people made to get there are not known unlike a chess game where you can, you know, whether or not you're paying. Right. And, and, and his view was like, there's, there's just no way computers can solve this problem.
It's completely unbounded. It's not like playing a game. Therefore it will never work. Um, And so he's had a, uh, an evolution in his old, in his mind isn't as an old school, you know, drug developer, who's, who's had lots of success. Um, and he's gone from like highly skeptical, uh, to highly supportive. And in fact, um, we've been working on, um, a video that, that, uh, he's, he's, uh, sort of describing this transformation that we're going to get out, uh, hopefully in the next few months, um, To kind of share his story about that transformation.
And so I think Mark represents, you know, one of many, you know, sort of leading scientists in the field. Who in his case, he's obviously made the transformation from skeptic to full supporter to like, this is, this is now my next career move is I want to be involved with this. Um, and I think that story and hearing from Mark as, as we get the video out there about his own skepticism and what convinced him and how's things changed and how he came to understand what's possible.
Um, I think that transformation is happening all throughout the industry with a bunch of people. And, and I think that Mark's story will help. Um, kind of people understand how he's, you know, sort of perceive these changes and therefore, you know, we'll give them some, some fuel or some ideas to think about how the transformation will affect them.
So we, we look forward to getting that video out there and sharing with people and then, um, and people can sort of see it from, from Mark's eyes and Mark's point of view.
Harry: Yeah, please don't send it to me. I'd love to take a look at it, but you know, like I said, I, I read all this stuff in tech and I look at how.
People are trying to solve problems in completely different areas. And you look at the creativity as you said, right? Cause it is a creative job in a sense. And then I look at how that could pivot into our world. And I think it's just, you know, an opens up a whole opportunity, set that the current way that, that scientists look at the world in our world may not see the opportunity.
Andrew: Yeah, well, we'll get there. We'll we'll get there
Harry: so, well, it was great to talk to you. Um, I look forward to staying in touch and maybe one of these days we had talked about getting together for a beer, but I think we're going to have to wait until this whole thing is over
Andrew: next year. No problem.
It's all good, man. Take care.
Harry: Bye bye.
Harry: Andrew, welcome back to the show.
Andrew: It's great to be here. I think it's, it's been about two years since we, yeah, I was,
Harry: I went back. I was looking at-, I was like, when, when did we record the last show? I'm like, Oh my, two years. And two years in the world of data is like, I don't know
Andrew: It’s an eternity you know, from a technology perspective, we've actually, let's see, in those two years, we've probably made about a hundred new releases, new iterations of our software over that time.
And so imagine, imagine like, you know, getting a hundred new versions of your car and of course technology just moves that fast.
Harry: Yeah, no, I, it's funny because I have this conversation with people regularly of like, you know, Well, you know, is this software done? I'm like, listen, it's software. It's never done. Right?
Andrew: Yeah. And so while it, it, it certainly depends. I think on how the software is deployed. I mean, there's, um, you know, as the guys built a lot of software systems, I've worked on, for example, early in my career in large scale, uh, telephony systems, the software systems that power, the nation's telephone calls.
And that's an example where you do a bunch of work, you do a bunch of testing, you deploy it and you don't touch it. Uh, in some cases for years, Uh, aircraft are very similar, right?
Harry: Yeah
Andrew: Like cause changes. Um, you know, you would, for example, the software that powers your x-ray machine, you probably, you probably don't want that to change that often.
Um, but there are places where, of course, you can dynamically change software know even multiple times a day. Right. Um, and uh, historically that's been more in web-based applications, right? If you, if you go back to a website and you reopen your web browser, that software can change. And it's a very little, little risk.
And because of that, Um, you can actually increase the velocity of, of trying new things and trying new products and seeing what works and, uh, that sort of philosophy that, that rapid iteration is something we've brought to the drug discovery landscape, where our, our software stack, which is what we use in the discovery process.
Internally, we are changing that thing daily. Um, and then we ultimately get it to a, to a release that we, um, we use with our, with our discovery team. Um, but we are rapidly iterating that product. It's, it's been over hundreds of iterations, hundreds of software releases. And every time it's a small experiment, right.
We're going to make this change to our algorithms or data sources or that sort of thing, and see whether or not like, do the predictions improve, right. Are we actually making a new discovery or are we coming up with something that is more likely, uh, to be efficacious and safe? And we have some digital test to discover those things.
And that allows us to just move so fast, right? From the, from the computational perspective, as opposed to iterating, you know, in the physical world, right. We have an idea and you run a-
Harry: Yeah
Andrew: Wet lab experiments and that can take months. And you just, you learn that one negative information of the course of a very long time, as opposed to the course of an afternoon.
Harry: Yeah. Yeah. Well, I'm, I, it's interesting. Cause I'm sure that anybody from Pharma now is like a zillion questions are going through their head of like, how do you check this? How do you know that? How do you. You know, uh, but, but let's step back for a second. So two years ago, if my memory serves me correctly, you were sort of doing more services-oriented, work, right.
Testing, what, you know, you had built out and now you've made this what looks like a much stronger pivot that we talked about two years ago to your own products. And how has that, how has that pivot, and why. Why did you need to make that pivot in a sense?
Andrew: Yeah, no, it's, it's interesting that that's, um, how people is seeing an externally because internally, like from my point of view, our, our vision, our plans really actually, nothing has has changed.
Um, but what has changed over the years is as we have more success, uh, we have the permission, if you will to just gather more resources. And so in the, in the early days of the company, You know, we used our discovery engine, uh, to come up with, uh, new ideas. And what I mean by new ideas is, is our output from the technology, uh, is a new hypothesis, new understanding of biology.
We typically go after complex disease where pathogenesis is not very well understood. Um, and so as a result, we're, we're coming up with, with first in class solutions, right? These are these, this is biology. That's not been, um, not been tested in that disease before. And of course it comes coupled with a, with a molecule, with some chemistry to, to test out those ideas.
And so our, our initial, uh, programs were taking the output of the software, uh, with very little, uh, in some cases, no wet-lab experimentation whatsoever. Um, and then licensing that knowledge, not, not necessarily a service deal, but you know, upfronts, milestones, royalties, the typical pharma deal, uh, to a pharmaceutical company who has the development team to then screen those molecules down, uh, identify lead, do the medicinal chemistry, all the, all the traditional work that comes post-discovery, uh, to turn something from, you know, early chemistry and into a product.
And so we've been doing those deals, uh, for many years. Um, but part of. Uh, what we're very interested in, right? Which is actually meeting unmet medical need. Excuse me. And getting products to patients is, is all about the time. Right? And so it's very, time-consuming, uh, the sign up pharmas to, you know, go through a diligence process and in some cases the time it took to negotiate the deal.
We could have actually gotten something to I and D at somebody's time. And so we sort of recognized, you know, how, like what, what are our Pharma partners doing that we, uh, that we can't do. Right. And that's about it. Um, preclinical execution, which to be clear, I think when, when we were speaking two years ago, I know we, we, uh, we were running back clinical studies on our own.
We had, we had that, but some of the other pieces around development, um, we didn't have as a team. So these days, couple of years later, we have, uh, new people in the company. So now our, our head of R & D is Mark Eller, uh, who wasn't with us back then. And so Mark, for those who don't recognize his name, Uh, he formally was, uh, the head of R &D at Jazz Pharmaceuticals.
Um, he was there, uh, for about a dozen years and saw it from its early days through multiple FDA approvals. Uh, and he's got a number of products, probably Allegra's the one he's, he's personally most famous for, uh, that he's brought, you know, to the approval process that, that make billions per year. And so now, now that expertise, um, is, is driving our R & D process.
Right. And so we're going beyond. Just the discovery and into the development. Um, and we've also brought on people like Anjuli Pandey, who formerly was, uh, the head of chemistry at Portola, uh, therapeutics. Uh, most recently was CSO at Bridgebio. This, this guy has had a, had a very nice IPO recently. And so she's got, geez, Louise, I think over 60 patents to her name in the chemistry space, multiple products she's brought to approval as well.
And so she's leading the effort, you know, to take these, these, um, uh, early molecules, perform the med chemistry on them and get them into, you know, sort of the, the pharmaceutical product you would expect to go into the clinic. So we've been pulling those resources into the company. And now, you know, relying a little less on our pharmaceutical partners to do the development for us.
And we certainly, we continue to do those deals. We have, we have the ability to go after more diseases and we have the resources to pursue ourselves. So we, we continue to do deals like that, where we hand off the discoveries to others. Um, but nonetheless, we've got about a dozen programs now, internally that we're developing on our own, um, using our resources and using, using CRS.
Harry: Now, how quickly do you, you know, because of the engine and the capabilities, right? How, how. When you're trying to explain timeframe to someone, how do you frame it? Of how much faster the system can get you to something that looks like you should go after and then actually helping, you know, design a molecule and so on?
Andrew: Yeah, well, we, um, these days we say it saves years. We, we used to be a little more, more granular on that. Um, but the reason is it really depends on the disease area. Yeah. And sort of what the starting point is. Um, and so for us, as I was mentioning earlier, we go after complex disease where we think there is not only an unmet medical need, but we believe where discovery of new biology can really unlock, you know, some, opportunity for new therapy.
And so if you look at the traditional approach of, you know, coming up, essentially with a new target, and I want to be clear like we don't go to the literature and find a target and then, you know, start developing rather we collect a bunch of data and we, we discover those targets ourselves. I mean, if you look back like the heyday of big pharma, right?
In like the seventies, eighties, this is what they did. Right? Like they discovered new biology. They came up with new targets. They. Uh, you know, uh, came up with some BioEssays and that sort of thing to try out, you know, a bunch of chemistry [inaudible] screen, right. And eventually little that down to some hits that they'd moved forward.
Like all that work. From the traditional sense. And by the way, like not many people do that anymore. Certainly not under one roof. Like we like we do. And the reason is as you just identified is it's just so time-consuming. So time-consuming
Harry: Right
Andrew: to go through each of those processes, because the traditional approach is to do a lot of basic science and literature search and, you know, forming hypotheses and, and it's, it's a, it's a long road.
To get to the point where you've completed that first high throughput screen and have some hits. And so we do all of that in computation. Right. And so that saves you years. Um, and I would say some of the people that go well, does it really save years? You know, there's, there's certainly companies that will in license, a molecule or they'll take something that other people have started in there they're, you know, being it's, it's being handed off to them, or they're pulling something in, from an academic lab or whatever. They've read about a target in a, in a, in a paper recently. So they've got a head start, right?
So that's maybe where there's a debate on the year saving, but I'm, I'm talking about like the old school approach. Uh, we're gonna, we're gonna just. You know, take all the existing knowledge about the disease and sort of set aside and see if we can't make some new discoveries about the biology and that's the starting point.
Right. And if you think of it from that, that perspective where I think the real opportunity is, um, in terms of making a big difference in, in going after something new, um, that is something for sure. We're saving years in the processing.
Harry: Yeah. I mean, I've had discussions with Joel Dudley about like, okay, you know, let's put all the data in and let's look at what the data is showing us in the direction.
And, and hypotheses that we can then go chase down that we in our, you know, even the human brain is an amazing instrument, but it's, there's way too many data points to look at simultaneously.
Andrew: Yeah. Like I meet for me to keep three things in my head is, is a good day. I mean, I look at billions of points of information and not only that, but to figure out like, what's, what's a false positive, right?
Like what's, what's a coincidence versus what's signal. Um, you're right. That's, that's not something that human brain does very well, certainly at that, at that scale. And so, you know, we're looking for, uh, uh, the patterns that represent signal versus the patterns that represent coincidence, if you will. Um, and that's not something that humans can easily do where they can look at, you know, massive you know, troves of information and, and try to try to draw those parallels, especially when a lot of the information we're actually processing doesn't really lend itself to like giving you an answer. A part of, part of it is going through it and figuring out what's relevant and not. And, and most of that of course is, is not relevant.
Right. It's it's um, uh, as Mark often says, you know, it's like looking for a needle in a haystack, right. And so that's. That's something that human brains can't do very well. Um, and I would say that one of the interesting things that comes out of this, we might even talk about this a couple of years ago.
But, uh, when we, when we go through this, this process and we come up with these ideas, all of our disease programs, every disease we work on, um, we have, we have [inaudible], we, we often connect, you know, with a luminary in that disease area. Um, and we, we bring them into the, into the projects and you know, we show them the output of, of what we have or like, look let's, these are, you know, we say our ideas reality,
Harry Glorikian: Right
Andrew: Is the machine, the machine came up,
Harry Glorikian: Yeah
Andrew: -The ideas, what do you think?
Right. And so part of it is we're going after novel stuff. Right? So they tend to say like one or two things, like one thing is like, Huh? I like this. This is an interesting idea. I hadn't thought of this before. You know, it kind of reminds me of something like, you know, okay. Like, you know, like, like seems credible, let's try it out.
Um, but the other thing they say is I'll look at stuff and they'll be like, no way, like, yeah, like this is just stupid. Like you are wasting your time. Right. And, and those are my favorites. Um, we don't do this anymore, but we use, we used to ask people to write down, okay, we've got these 10, you know, these 10, the theories, if you will, at least 10 different targets, we're going in these 10 different molecules.
We're going to go screen. You know, you, disease expert, you tell us which ones are going to work and which are not. And, uh, and we found out that the disease experts were no better than random and in picking the winners, um, which I think is very, uh, sort of telling about. Uh, how little we know as, as humans, you know, inspecting literature and sort of the capacity of the human brain to sort of understand against, you know, again, these, these, these massive sources of information what's relevant and what's not.
Um, and so, you know, we've, we've had a number of, uh, very exciting and very pleasant surprises, you know, where we see through the screening process, we see signal and ultimately, you know, we get down into in vivo studies, you know, these, these gold standard models. Where we compare against standard of care.
Right. And then we see, uh, in many cases, you know, our molecules are showing stronger signals of either efficacy or maybe similar efficacy signals, but stronger signals of safety. And that tells us we've got something that's really compelling and worth moving forward.
Harry: Yeah. I always find it. It's a fascinating discussion, you know, and when like, again, you know, going back to Joel and Alzheimer's and him pointing out to people at NIH that, you know, herpes, simplex two might be -right And everybody was like that. You crazy, right? Yeah. Hey, listen, here's all my data. You run it. And you see what you find. Right. And, and so I, I think NIH now is sort of thinking about how to come at this a different way, but I always find that fascinating is like, you've got this incredibly complicated system and you're looking at this narrow little window that you are an expert at.
And how could it not be that anything outside that window influences what's happening in that it's, it's sort of mind-boggling? And now that we have computational capabilities to sort of, I don't want to say brute force, but I feel like 10 years from now, we're going to look back and go, damn, that was brute force.
We have much something much more elegant now, but a way of looking at these and looking at the complexity and seeing that a pathway that we never even thought of. Has an influence on this disease, is fascinating to me. I, how the whole industry isn't moving in this direction much faster is sort of always mind-boggling to me, but I understand that you know, your expertise is not- wasn't necessarily drug discovery from day one.
Andrew: Well, yeah. Look it's it's um, I think computer scientists, as we've gotten, I think more involved in this industry, um, we represent disruption. It's a very different way of thinking. And, and disruption takes time and industries, you know, resist disruption, you know, quite frankly, um, you know, I, one of my startups I did, uh, Nolan Bushnell was, was the chairman of the, of the company.
If that name doesn't ring a bell, not only did Nolan start Chuck E cheese, which he's very famous, but, but before, before Chuckie cheese, he founded a little company called Atari. And before Atari video games, the video game industry didn't exist. Okay. And so when I, when I first met Nolan, we went out to dinner and like any person who's just, you know, in awe of such an amazing technologist in a, in a pioneer, you know, for that industry, uh, we went out to dinner.
I'm like, so Nolan, you know? Right. Yeah. I'm just like, like this eager, eager young man. Tell me the stories of the, early days of Atari and, and at the time, uh, at our, at our, uh, startup, we were, um, uh, working on some fundraising. And so he, he told me this story. So you have to understand, like, let me set the scene, right?
This is like maybe late sixties, early seventies. And, uh, and I'm sure maybe Nolans going to listen to this podcast. I'll send it to him and he can get the story, right. Because this is a long time we had this conversation. So I'm, I'm sure I'm going to get the details wrong, but the, but the core of the core of the messages is there anyway.
So it's, you know, it's around that time period. Um, and video games don't exist. Humans have never seen them. They don't know what they are. Okay. And so he's, he's working on this he's building pong or whatever he's building over, over here in Sunnyvale and next town over. And, uh, and he's chatting with people in, you know, the, the game industry, but with that in air quotes, the game industry, I don't recall who it is specifically, but let's just say it's Parker brothers, right?
So he's, he's sitting down with the fine folks at Parker brothers. He's like, man, I've got this new, exciting innovation. It's going to change, uh, the gaming industry as a whole and just bring a personal entertainment and I've combined computers and games and have made this thing that's called the video game. That's going to be the next huge thing. Okay. And so he's telling me, you know, the guys from Parker, brothers, whoever it is, they're like Nolan, Nolan, right? Sit him down, hand on the shoulder. Uh, so first of all, games are made out of paper and card[inaudible] Okay. But, but more importantly games, you sit around the kitchen table with your family and friends, and it's a social experience where you interact the point of the game, you know, is this, is this social gathering.
And you're telling me, you're going to make a thing where people are going to stare at a television. And that's going to replace, you know, this, this whole sort of
Harry: Right. ‘
Andrew: Social ritual that is games like Nolan, you're an idiot get out of here.
Harry: Right. ‘
Andrew: Uh, and of course, you know, we know what he did. He, he built pong, he put it in a bar over in Sunnyvale and people lined out the door, pumping quarters into it, and the rest is history.
Um, but that, that story, I think really resonates for me because [inaudible] your point, like looking forward to the future? Like the video game industry is today. It's like an obvious thing. If I'm not mistaken, it pulls in more revenue than, than Hollywood does, you know, from movies. Like it is just part of our culture.
It's just part of our experience. It's, it's part of, you know, growing up kids playing, you know, video games, uh, and, and before, you know, Nolan came around, like, people couldn't understand this, this what's now obvious, this thing that was coming. And I think in a very similar way, you know, as a computer scientist, who's worked on a variety of industries and Marc Andreessen.
One of our investors, Andreessen Horowitz, like talks about this talks about all the things you used to buy at radio shack that are now just in software,
Harry: Right?
Like all this, this stuff has been replaced. Um, and I think in a very similar way in this industry, it's, it's tough to imagine what it is until you already have it.
Right. And so for someone who, you know, started this company many years ago, and I've been very consistent in like my belief systems and what we do, and like our output and I've, I've gone from, in the very early days, everyone said like, this will never work. You know, you're a fool.
Harry: Right.
Andrew: Very similar to the Nolan thing.
There were these days, maybe like half the people say that maybe a little more than half. Right. But like all the tapping, just the passage of time. And what's happened in that passage of time is people are starting to get a hint of what's possible, you know? And I also have an a conversation actually the night before last, or as I was chatting with an investor who was talking about, um, sort of his belief system and what's happening.
And so you, you look at, you know, recent IPO's like, like relay and Schrodinger.
Harry: Right.
Andrew: Uh, of course the guys at [inaudible] are doing extremely well. Um, and, and he was sort of saying, you know, because of the acceleration of technology. Uh, people are coming out of nowhere and they're challenging, you know, these large established pharmaceutical companies.
Now they have the advantage of products on patent for many, many years, and it's going to take a while to disrupt. Um, but this investor who, who I think was very thoughtful, it was sort of saying like this, this disruption. Is coming with, with so much momentum behind it. Um, and we believe, you know, some of these, these what look today, like small sort of innocuous players, um, are really going to disrupt the, the field and, and make huge changes in the pharmaceutical industry as a whole.
So that was an interesting perspective. Just kind of tying all those pieces together, where. You know, innovation and disruption, it comes from the outside, right? I am, I'm definitely an outsider, right? Like I, I built mapping systems and [inaudible] systems and advertising networks. And here I am making drugs. It's, it's kind of a weird transition from that standpoint, but it's, it's highly connected to this idea of, um, bringing disruptive ideas into a rather entrenched industry.
Harry: No. And I, I mean, look, I I'm, I try to read everything. I could get my hands on from the tech side. I'm scanning constantly. Um, I was listening to the, the, the guy who has the title futurist for paramount pictures.
Andrew: No.
Harry: How about what they're working on,
Harry: Yeah. I was thinking about that too. Maybe I can transition my next life into the future is that's a really cool title.
Harry: But, but hearing about, you know, all these different sort of plays moving forward, you know, using. You know, uh, augmented reality and things of, of nature, of how you collaborate and so on and so forth. And you superimpose that.
I take all of these things and they try to superimpose that on our world and you can see the ball moving forward in ways that to someone who's only looking in the field cannot see. It's like looking through one hollow lens and you can't see the rest of the picture. That's developing around you. And, you know, I find it fascinating that the status quo can't see that there, the world is changing at a rapid pace.
Now I do believe that COVID, we're going to look back at COVID and yeah, I know it's a, it's a negative for, for all intensive purposes, but I think from a moving things forward from a technological perspective, I think it's been a huge shot in the arm for remote monitoring of patients, for telemedicine, for all these other areas.
I think it's moved it forward five to 10 years, and I have to believe things that you're working on are now, or even should be even of more interest to a therapeutic company. Because if you can't get everybody in the same room to do the experiment, how do you do the experiment to move it forward faster?
Andrew: Yeah, no, look, I think those are, um, excellent observations. I think, um, uh, COVID is definitely an interesting time. Just sort of see how technology helps influence, um, society and you're right. Like, so here we are. I mean, the last time we did a podcast, we did it together. Right. We were standing together, where were we were?
Harry: We were at the Harvard medical center.
Andrew: We were, you know, in a hallway together and, and, you know, around the table recording and, and, uh, you know, we're thousands of miles away together. I've got to. You know, a fancy fiber optic cable, you know, coming into my house. I know what you have on your end, but like, I, I see you clear as day and here we are recording a podcast.
Harry: Right.
Andrew: And so, first of all, how cool is that? Now I recognize like that's something we've probably had for 5 or 10 years, but nonetheless like that, the point is, um, we're, we're still able to put this material together without physically being together. And I think, you know, even in our own company, As, um, as a, so Santa Clara County, which is, which is where we live and where our offices are, you know, we were one of the first places in the nation to have, uh, detected cases.
Uh, and so, uh, the health commissioner here, um, was one of them was one of the first places to put shelter in place and we knew it was coming cause we were, we were connected to some people. And so at our company, we, we trained everyone on how to use Zoom and Slack. And, uh, we had, uh, we had a goodbye party on a Friday, you know, we'll see, I'm sure we'll see each other again soon.
We’re [inaudible]. And we prepped everyone off and off we go. And the next Monday we started operating our business, um, completely through, you know, technology completely through video. And, um, we have not gathered, uh, as a group in our office since this was months and months ago. And throughout this time, uh, in the early days you had some little adjusting you know, figuring out how to do this, but like, you know, by and large, like we're, we're operating, uh, just as efficiently and moving forward just as we were before.
We're in that physical space together. Now I will, I will certainly say there is, um, value to being together with people
Harry: Yes
Andrew: And sort of the, you know, there's, there's more than what just happens during the meeting time and, and building personal relationships. But, um, you know, it's a big question. Like, are we going to be able to function as a company without seeing one another?
And the answer is yes. Right. And, and I think one of the things that COVID has done for that type of question is like, okay, just this whole, you know, remote work stuff you know function. I think it was Marissa Mayer many, many years ago, like said very famous decree. Everyone at Yahoo shall come into the office, at Yahoo. There will be no more remote work. And here we are now with all these big tech companies and small ones like ours, everyone's working remotely and it's kind of working out. Right.
Harry: So it's interesting. Right. I mean, Google just announced right that nobody's coming back to the office until July.
Andrew: So next summer. No problem. Yeah, yeah. Next year, next year. Yeah. So like, I, I think what that means is, so now, you know, people are, um, you know, in many industries, not, not all of them, um, you know, able to work from home. You know, we have people in our company, you know, my, my chief of staff. Uh, she was, uh, she was born in Mexico.
She's been living in San Francisco, you know, she just said to me the other week she was like, look, she's like, I'm in this, um, rather expensive apartment in San Francisco and you leave, uh, you know, they, they got the internet in Mexico and it was odd. She asked me, is that cool if I, if I, you know, go to Mexico and I'm like, why not?
Like, you know, like, I'll let you know when, when there's a chance we'll be getting back together in the office, but like go for it. And she's like, awesome. I'm going to go live like a queen. Right? Like it's. And so. That recognition that, you know, even, uh, physical places, you know, like, like why do you need to be in a high rent area, if you can just, you know, do your job effectively some, somewhere else.
So anyway, so all these, all these things are kind of unraveling. And I think to some of your points on medicine and healthcare, I think the other thing that's happened is, is people are very nervous to go in and see their clinician-
Harry: Right.
Andrew: Because they think there's other people around who might have COVID. I don't want to get that.
And so, yeah, like the whole telemedicine piece of it is taken off, but, but the whole point is like, um, using technology, using the internet using, you know, like the technologies we're using right now to interact with folks, uh, on all sorts of levels, whether that's professional, whether that's, you know, that's patient care, um, all of that, the barrier has just dropped.
Right. And so I think it's, it will be interesting to see post COVID world what it does. Um, like are people all gonna like get back into the office or not, right. Or are people gonna think every time they're not feeling well, they need to go see their doctor or they're gonna go, Hey, you know, I think I'll do that mobile app thing that I did before, you know, last year because it kind of worked and I realized I don't have to drive anywhere.
And yeah, I think those, those, um, events helped push innovation forward for, for sure.
Harry: So stepping back to where you are, do you think your, your. From a timeframe perspective, you're moving the ball forward faster by compared to say, you know, a traditional process, six months a year, two years. What's, what's a wild guess.
Andrew: I would say on average, if, if you're gonna do a completely De Novo process from scratch, you know, we're saving about three to four years. Um, there's a point at which, you know, our processes don't speed things up and that's, as soon as we get the mouse involved, right? Like, I can't speed up the tumor growth within the mouse.
I can't say the activity of the, uh, of the potential medication to, you know, inhibit that tumor growth. I can't speed up the, you know, the histology and all the work that happens post that and all the activity that you need to do. And rightly so right. To, to carefully prepare for 90 filing. Cause, you know, when you get to the point where you're gonna test something in humans, you, you want to be absolutely sure.
Um, you're, you're being safe about it. Um, and you're, you're, you're doing something that's, that's worth the risk that you put onto your, um, your clinical trial patient. So all of those processes, uh, they don't necessarily speed up. I, I think really where we're about speed in the discovery process. I think the real opportunity.
Post discovery is efficiency, not necessarily speed. Um, but you know, with patient trial selection, for example, um, finding the right population, finding the responders, you know, being able to do things where you maybe don't have to have as large a group, uh, you know, in your, in your clinical trials and example, those are things where now efficiency and cost efficiency. Uh, become, I think some of the values of what you can do with computational methodologies.
Harry: Right.
Andrew: We can't really speed up, you know, a preclinical study or a clinical trial just to the nature of the biology and the time. And so that's how I see it. The first half is about speed and the second half is, is maybe it's more than half, but the rest of it is about just, just efficient use of, of capital, uh, to get the results that you're looking for.
Harry: Well though I do see, you know, trying to look at the entire value chain. There are companies using computational methods to sort of find patients faster, make sure they, you know, they fit the trial better. Um, you know, remote patient, uh, remote clinical trials are becoming more of a thing. So I think we're seeing computations sort of filling gaps that can be filled in by that by technology advancement.
So I do see the process shortening over time from end to end, which I'm hoping also translate to lower cost at some point from end to end.
Andrew: Yeah, I think there's definitely the efficiencies to be gained throughout the whole thing. I think, um, again, if you're looking for, you know, we take some things that normally would take years, this is something we used to say early in the company, and we got critiqued.
So we stopped saying it, but it's still true. Right? Like we take, um, that very early portion of just understanding the biology, which, which can take many, many years. And like, you know, the computation does that in a couple of minutes. And so. That sort of stuff. That's a dramatic, you know, multi-fold, you know, increase in speed.
Um, and I'm not saying that some of the things you've talked about, uh, won't increase. I think the efficiency from that, from the speed perspective, but it's not going to take a process that takes, you know, four or five years and turn it in three minutes. That's for sure.
Harry: No, no, no, no, no, absolutely. And you know, it, it, it begs the question of, you know, like we need to rethink how we teach biology.
Right and understanding these things. Right. And it's, uh, I remember doing a lot of reading, a lot of textbooks, a lot of experiments. I feel like most of that now would be, I'd be sitting in front of a terminal and combining pieces of data and, and, and coming at the whole learning process differently than when I was learning.
Andrew: Yeah. You know, that's, that's an interesting thing to poke at. Um, Well, let me, let me share some thoughts here. And I don't know if there'll be interesting if they, if they're concurrent with some of the things you're thinking. I think, um, so, so, uh, let me, let me gather my thoughts. Okay. So when I, when I'm, um, when I'm screening, when I'm, when I'm interviewing a software engineer, Um, to work on my team.
Uh, of course, now that people are gonna listen to this podcast, they're going to know what the answer is when I refer- One of the things I asked them, as I say, man, like, imagine it's, you know, whatever, the 1700’s the 1800’s computers don't exist. Technology doesn't exist. You're still you, right?
You're you've been magically teleported back in time. What do you think you'd be doing? And it's very interesting. And I get these answers like, Oh, you know, I'd, I'd be a school teacher. I think that would be an awesome thing or whatever. I would be a musician, all this stuff. And, and then I, and then, you know, this is like the hook.
And then I go, well, why aren't you a school teacher now? And then the answer is, well, because software pays better. Right. Which, which is a reasonable, a reasonable thing.
Harry: Absolutely.
Andrew: But what it says to me is that um, there's a lot of people in the field. That don't do it because it's their passion or their interest, or it's, it's something that really excites them.
It's like, I can make some money of this.
Harry: Right.
Andrew: And I think the best computer scientists and the best engineers, I know. They are tinkerers their, their are people who, and they're also creatives, right? Cause software has got this, um, uh, this artistry to it where it's it's the toolset is so wide and you can do
Harry: Right
Andrew: So many things with it that, you know, like the people that are really into software, like, and you know, another great question is like, so what do you do in your free time to see if they actually write software for fun?
Which by the way, while I'm chatting with you over here on this window, I'm writing some software, um, to do something personal on unrelated to work, but like there's a, there's a, I think a, um, a connection between, um, really becoming an expert in your domain and also just like truly enjoying it, truly enjoying the, skill and the trade and that sort of thing.
And I, I think that. There's a personality that, that, um, science attracts, you know, people like me, computer nerds, right. Who really enjoy software. And there's, there's different personalities that, attract different things. And I think it's, it's really hard to find someone. Who really enjoys, you know, like the biology and the sciences and software together.
I mean, when I, when I was studying this in school, most of my classmates were medical doctors. They, they had a medical degree, probably like 75% of them. Um, and so they're, they're trying to, they're trying to learn software, right.
Harry: Right
Andrew: And if you have them like really connect with it and they really enjoy it and it's their passion.
And I think those are also the people that just produce, like the coolest stuff. Like you, you did the podcast with Jake, I think maybe a few months ago.
Harry: Yes, yes
Andrew: So Jake, I met him at Stanford. He was one of my classes, but like, he's one of those guys, right?
Harry: Ah yes
Andrew: It's like this biologists software tinker dude. And like, you know, we, we would get together and left philosophize on stuff and like.
Like, that's the kind of person you want to see, like just making big changes in the industry and like he's doing that. Um, but, but my point in that is there was a bunch of other people in those. Classes and there's, there's some other people like Tim Sweeney is another one who, um, uh, I think actually was a surgeon originally, and now he's doing inflammation, just doing super cool stuff. Combinations [inaudible]
Harry: Right
AndrewThere's a bunch of other people in his classes are kind of like medical doctors are like, you know, I should learn software because it would be good, you know, kind of thing. And I don't want to call anyone out, but I remember like one person who was, um, A project due or something like that and see what it was before class.
And she was complaining. She was like, Hmm, I can't do this. I spent my whole day yesterday working on the software and I couldn't get it to work. And it's like, it's using up all my time. And she like she hated it. And I also spent that amount of time and I'm like, this is cool. Like, this is fun. Like this is putting this thing together.
And so I think. Taking people and saying, look, you know, as a biologist, now you have to learn software and we're going to pound you over the head over it. Like, I don't know if that actually will transform and look, and maybe it'll, it'll light something in someone who didn't know that that would be of interest to them.
But I think it's really gotta be connected with, um, the personality and sort of like the enjoyment of the person. And I, don't know if that happens. That late. I think it can start much earlier. Um, look, I first touched a computer when I was, um, jeez Louise and it's like when the Apple two came out, I mean, Apple, everyone, every, you know, school got a free Apple, two computer.
And, um, I was fortunate enough that my parents were able to purchase one, but I was a little kid, you know? And so that's sort of where the passion started for me. And I think that's. Uh, for whatever it is, whether it's biologists or whether you're working in engineering or whether you're working in financial services, it doesn't matter.
I think that, um, exposing really children to software and programming and that sort of stuff, like some are gonna connect with it and enjoy it. And I think those are the people that eventually, as they get into different sciences and different disciplines will use that enjoyment and that skill to do something interesting with computer science.
But it's just, it's just my belief. I don't, I don't think you can take someone at like the college level. Who's getting into biology and be like, Hey, let's
Harry: No, no, but I, I think, and what I meant by, you know, teaching it in different ways, you know, my fundamental belief is that, you know, everybody should be Steeped in software, not necessarily to do it, but to understand it as a process, as a language, as you, cause at some point you're going to interact with it. So you might as well understand it, even at the basic level. And then as you're going, you know, going forward, you know, if you want to take on different careers, you, there, there needs to be a combination of this.
You still are. You ended up like when we were in applied Biosystems, you're like, okay, Get the computer science guy and get the IT guy together and get the, uh, biologist together, put them in a room and, you know, having to make something and nobody could understand what anybody was saying right. For the first like 3 to 4 years,.
Um, but, uh, but on the other side, you're absolutely right. I mean, my, my family is always saying like, you're working all the time. You're working all the time. I'm like, look, let's get something straight. Every once in a while there's a pain in the backside. I need to deal with it. I don't want to do, but for the most part.
I mean, I'm in a kid, in a candy store every day. There's something new every moment. And I'm like, this is the coolest thing ever. And I get to be involved. Well, that's, that's not work. That's just fun.
Andrew: No, and that's, that's an awesome place to be, you know? And, um, I think part of what drives innovation and change and industries are, are people who are really just connected with that passion.
Um, and they have the drive as well. Like there's, there's something behind them that, um, you know, really inspires them to go and do something and, and, and, um, try to do something new. I think innovation is. It's a hard game. I mean, I, as I often say, I've done these startups, you know, I wish I could say everyone would, this was an astounding success, you know, was bought by Apple, which, you know, I always liked to talk about, uh, I don't always talk about the one that, you know, we raised geez, 23, $24 million building exploded it.
I guess every, every startup is spectacular.
Harry: Yes
Andrew: This one was spectacular in the negative, in the negative sense. But, um, you know, I think you also, uh, for people that, um, want to change the world and change industries. It's, it's tough to describe, but like, uh, it's not necessarily the grit, but it's like, it's, it's the enjoyment of like the challenge.
Harry: Oh yeah
Andrew: And, you know, I think Michael Jordan has some great quotes about, you know, all the times I missed, you know, as opposed to all the times I was successful. And I think part of changing industries is like, You know, you just hear no, all the time. As I was saying earlier in the, in the podcast, you know, in the beginning of this company, you know, with a few exceptions, it was certainly nice to have VJ at Andreessen and be like, Oh yeah, this is it. Or I'm giving you some money. Let's see what happens. Um, but like everyone else I've talked to is just like, no, no, no. And theres a-
Harry: Right,
Andrew: And there's a, um, I think there's a, a type of person as well, who just sort of listens to that. And I don't hear, no, I hear. Not yet or not now I can just sort -
Harry: Right, right
Andrew: My reality, distortion field kind of puts, puts words in people's mouths that they're not saying. And I think all those things kind of combined together, right. We've been talking about these different things. I think there's the, there's the passion for the technology and just sort of having like the, the, um, uh, personal interest in sort of those things.
There's the, um, You know, again, the feeling like it's not work, it's just, it's something that brings you, brings you joy and it's really engaging that sort of thing. And then I think that final piece is just, you know, people who enjoy, uh, a challenge and doing something, uh, very difficult and, you know, the no’s don't discourage them.
The no’s only encouraged them. And in some cases, I think it's kind of the combination of all those things that make industries change. And I think, you know, kind of the theme we've been talking about is just sort of changes in, um, in life sciences and healthcare in general, I think finding people like that and really tapping into them and giving them resources to go, uh, go try some things and to sometimes fail and to sometimes succeed.
I think that's what really is gonna make the biggest movements, uh, in our industry, right? Because those are the, those are the risk-takers. Those are the pioneers. Those are the visionaries who want to do something new. And I think the more we do to help support and encourage. Uh, people have that mindset and that way of thinking and that, that sort of endless energy, uh, to go out and do something is, um, is something that's only gonna make the world better.
And, and, um, uh, and therefore we should, we should embrace it as much as we can.
Harry: No, I totally agree. And the tou- The tough part is finding those people, right. And they're not falling off trees. Uh, I can tell you, at least with all them, you know, after all these years of all the people that I've interacted with there, most people are just too nervous to take that path, but, uh, I try to encourage them to do it.
Andrew: Yeah, That's where, you know, startup incubators and places where people who don't know, or maybe a little timid can come. I mean, I'm, I'm deeply involved with, uh, with Stardex. I'm a judge there. Um, I, I sometimes lead the neighborhoods and, you know, it's, it's often, um, you know, students that are, that are coming out of Stanford who have got an idea for a company and they just don't know where to begin.
Um, and what Stardex does is it is it's a community, right? It's a support system. It's, it's a whole set of other people in similar circumstances. Uh, whether they've, you know, had some success through their very early themselves, um, to work together as a, as a group and as a community to help people get there.
Right. And so I think that, um, type of thing, uh, whether it's a startup incubator, that sort of thing, you know. I wish we did more on the governmental level, uh, to encourage innovation, um, and put, you know, pieces in place where, you know, young, bright people come out of school and, and they've got a choice, man.
This is, I think I've said this before in your podcast, but if I did, I'll repeat it again. But like one thing that's man, is it annoyed me is, you know, people will, will graduate with a degree in biomedical informatics. They literally learn how to use computers to solve medical problems and save people's lives.
Okay. And then the likes of Google or Twitter, or Facebook will show up with a wheelbarrow full of cash and say,
Harry: Right
Andrew: Hey, you know, you know how to write software, you know, these, that, that skills in short supply, why don't you come with us? And, you know, we'll, we'll, you know, deliver movies to people. And not that there's anything unethical about delivering movies to people, but you've literally just learned how to save lives.
And as. You know, a student who's coming out of school and they're just sort of like, geez, what do I do next? And there's this big, impressive paycheck. And they've probably got some debt and we're thinking about, geez, I want to, whatever, buy a house, start a family, all those things that young people think about, it's really hard to go.
Yeah. You know, instead, I think I'm going to just eat, you know, tuna fish sandwiches and sleep on my friend's couch. Cause I have this idea for a start-up, like
Harry: Right
Andrew: Practical. That's not an easy thing to do. And so I think if we did more to help encourage and by encourage, I mean, supply. Young entrepreneurs and people who want to experiment with the resources, not only the financial resources to operate a company, but so they can, they can have a reasonable existence while they're trying to these things out.
Um, I think the better off we are, we'll be as a society. If we put more, uh, sort of, sort of leverage behind again, governmental resources to help people like that. I think we can do a lot more innovation as, as a, as a country and as a nation. Um, to improve, you know, not only obviously talking about the medical space, but like all sorts of other things, you know, whether it's materials or aerospace or transportation.
Harry: Yep, yep
Andrew; I mean, there's, there's so many interesting problems to be solved, um, that helping entrepreneurs or creating environments where entrepreneurs can, can grow. Uh, I think would be a wonderful thing to do if we could, if we could get there, uh, as a country.
Harry: But, uh, I wrote a letter to tech and it got published.
I don't know where in AI med or something like that about, you know, begging tech people. Like you need to look at this space cause you can actually make money and make a difference as opposed to, if you go to, you know, Facebook or something like that, like you really, you know, it's not no offense to Facebook, but you're really not making a difference in anybody’s life.
But, but in the last few minutes here, let's pivot back for a second. To the company, what you guys are doing, what do you guys see the next milestone and, you know, taking the technology forward and the impact that it's going to have, or is there a particular program that really you're excited about that it's really moving the needle.
Andrew: Yeah, that's a good one. So yeah, we've we, um, so we act a bit like a mid-size pharma, right? So if we've got a whole portfolio, we've got 18 diseases, uh, currently under active development. Uh, now a number of those are through, um, uh, these licensing deals with, with pharma. But like I said, there's, there's a dozen or so that we're moving forward internally.
Um, and of course, you know, what, what seems to be the most promising, uh, programs are always the one where the uncertainty is the lowest. So the ones that have been around the longest, which we know the most information about seeing the most promising, but there very well could be an earlier program.
That's actually way more promising, but we just don't know yet.
Harry: Right.
Andrew: Because we haven't gotten that far. Um, but we've got, uh, these days, uh, five programs. Um, in, uh, medicinal chemistry, right? So this is we've screened things down. We've got a lead that lead has been tested in multiple preclinical studies.
We, uh, see us performance is better than standard of care. If it exists or maybe against, uh, annual positive and control, might've been a, like a phase three clinical, uh, candidate, if there is no FDA approved molecule in that disease area. So we've got about five programs like that. Uh, we're, we're moving forward from the Med Chem perspective.
We've got five more programs right behind those where we have screen things down and we see early signals of a potentially, you know, more appealing therapeutic than, than what's available or what's about to be available. Um, but we have some more work to do to either finalize the selection of the lead molecule or maybe run another preclinical study to, to, you know, get a second confirmation that what we have is, is truly interesting. So out of those, those 10, um, I, you know, I think in the next few years, it's not clear. Which one of those is going to pan out and be the most, uh, appealing for the company. Um, to ultimately answer your question.
I think for us, you know, our next milestone, there's sort of like these credibility milestones as you reach them as a Pharma company, like people get more and more serious about you. Uh, and for us, the next big milestone is an I andD filing. Um, it's not clear when that will happen. I would say the soonest, it could happen.
Uh, it would be, uh, the beginning of, of next calendar year. Uh, we do have something that, um, has the potential to be there. Um, but again, as we move forward, we are constantly killing programs too. We have a lot of optionality. And so we're always trying to figure out which one is the most lucrative to move forward with.
Um, but I think certainly within the next year or two at the latest, um, we will get to that. I need milestones. And I think that's going to be a huge inflection point for the company where now we've gone from being a discovery stage company to being a clinical stage company. And then really all sorts of things change for.
Uh, how you're perceived and you know, what people think about for your future and a whole bunch of things. So that's, that's what we're focused on as a company is getting to the IMD milestone, uh, not only as quickly as possible, but also to do with something that the most compelling thing that we can, we can put forward.
And so we've got lots of choices to do that with. Um, and we're optimistic that we'll have at least one, if not two or those, um, uh, in the next few years.
Harry: Yeah, I was going to say, well, you know, at the beginning of the year is not that far away. Um, No, we've got an election and a few things to get done before then, but, uh, it's it's feels like it's it's right around the corner.
Andrew:, time does time does seem to fly, but yeah, it's still summer. It's still summer, but, uh, indeed. Right. It's uh, I think, well, and certainly in the, uh, in the warp speed, uh, that we're going out for the life science industry. Yeah. Like, you know, six to nine months is insanely fast where other industries that seems like a, you know, winter.
Geez, Louise. Why does it take that long? But, uh, but obviously very quick for, uh, for this industry.
Harry: Oh, yeah. I mean, I always, I keep telling people, I mean, the difference between evolution and revolution is just a measure of time. Now.
Andrew: I love it. I might have to steal that and use it later. No, no. Feel
Harry: free. I mean, it's actually, it's a quote in the book because it's, it's, it's true.
Right? If things take a long time, people call it evolution. If it happens overnight, it's a revolution, right? It's so, um, Look, it was great to catch up. I'm I'm um, I'm really excited for you guys. I mean, cause you know, having these periodic, uh, discussions to understand the, the arc of the change is, is, is always fascinating to me.
And I just don't understand how everybody can't wrap their head around the impact that this technology is happening. And whenever I hear somebody, you know, naysaying or poo-pooing, I'm like. What am I missing and why am I looking at it the wrong way? I, sometimes I have to go back and look at a few things to make sure, like, I'm, I'm not, you know, drinking my own Kool-Aid sort of thing,
Andrew: but let me, let me close with this.
So Mark, who I'd mentioned earlier, who's our head of R & D. Um, you know, he didn't just show up one day and say, I want to work here. Um, he actually was a, it was a KOL, uh, with a company. Uh, for many years, we'd brought him in to, to consult on some of the things that we're doing. And so you sort of got like the slow drip of the activity over time.
And, uh, you know, finally, you know, he came in one day and we were talking about, I think we were talking about results on the bus. I can't remember what, but you know, we're talking about that. And some other programs, you know, any, any recognizes, he sort of knows, like if people said they know this, but they, you know, they kind of come in the office and they see, they're like, man, there's like 18 programs here.
You know, it's like less than 20 people, you know, like it's, it's just this tiny little crew. And so, you know, he's kinda like looking around the office. He's like, this is it, isn't it. I mean, this is, this is the team, you know? And, and he knows, right. Cause he's been, he's been looking at the preclinical evidence and he says to me, man, he's like, you know, I had been waiting to do something special for quite some time.
It's like, this is it. I want you to offer me a job. I was, I was just like, it's like, like, uh, like a guru to me right now. He wants to now he wants to work for me. I'm thinking like, you know, what's going on here? Um, And so, and of course, like, are you kidding? Do you want to work here? Yes, we can. We can do that.
Um, the kind of, um, part of that discussion was him telling me sort of his evolution of his complete skepticism in computer science and artificial intelligence and, you know, the way he described it was, um, you know, he saw computers, winning games, like chess and go, but they have, they have defined rules and they have to find outcomes.
And he's like in drug discovery, there are no defined rules. Like every, every drug that's made to market is its own own little story. Um, but not only that, but that the moves that people made to get there are not known unlike a chess game where you can, you know, whether or not you're paying. Right. And, and, and his view was like, there's, there's just no way computers can solve this problem.
It's completely unbounded. It's not like playing a game. Therefore it will never work. Um, And so he's had a, uh, an evolution in his old, in his mind isn't as an old school, you know, drug developer, who's, who's had lots of success. Um, and he's gone from like highly skeptical, uh, to highly supportive. And in fact, um, we've been working on, um, a video that, that, uh, he's, he's, uh, sort of describing this transformation that we're going to get out, uh, hopefully in the next few months, um, To kind of share his story about that transformation.
And so I think Mark represents, you know, one of many, you know, sort of leading scientists in the field. Who in his case, he's obviously made the transformation from skeptic to full supporter to like, this is, this is now my next career move is I want to be involved with this. Um, and I think that story and hearing from Mark as, as we get the video out there about his own skepticism and what convinced him and how's things changed and how he came to understand what's possible.
Um, I think that transformation is happening all throughout the industry with a bunch of people. And, and I think that Mark's story will help. Um, kind of people understand how he's, you know, sort of perceive these changes and therefore, you know, we'll give them some, some fuel or some ideas to think about how the transformation will affect them.
So we, we look forward to getting that video out there and sharing with people and then, um, and people can sort of see it from, from Mark's eyes and Mark's point of view.
Harry: Yeah, please don't send it to me. I'd love to take a look at it, but you know, like I said, I, I read all this stuff in tech and I look at how.
People are trying to solve problems in completely different areas. And you look at the creativity as you said, right? Cause it is a creative job in a sense. And then I look at how that could pivot into our world. And I think it's just, you know, an opens up a whole opportunity, set that the current way that, that scientists look at the world in our world may not see the opportunity.
Andrew: Yeah, well, we'll get there. We'll we'll get there
Harry: so, well, it was great to talk to you. Um, I look forward to staying in touch and maybe one of these days we had talked about getting together for a beer, but I think we're going to have to wait until this whole thing is over
Andrew: next year. No problem.
It's all good, man. Take care.
Harry: Bye bye.