Charles Fisher On Raising $70 Million To Help Develop Drugs More Ethically

Charles Fisher’s AI startup has attracted some significant capital as it works to speed up solutions for both pharma companies, and their patients. His venture, Unlearn, has attracted funding from top-tier investors like Mubadala Capital Ventures, Insight Partners, Radical Ventures, and DCVC Bio.

In this episode, you will learn:

• The fundraising process
• The future of medicine

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For a winning deck, take a look at the pitch deck template created by Silicon Valley legend, Peter Thiel (see it here) that I recently covered. Thiel was the first angel investor in Facebook with a $500K check that turned into more than $1 billion in cash.

Moreover, I also provided a commentary on a pitch deck from an Uber competitor that has raised over $400 million (see it here).

Remember to unlock for free the pitch deck template that is being used by founders around the world to raise millions below.

About Charles Fisher:

Charles is a scientist with interests in the intersection of physics, machine learning, and computational biology. Previously, Charles worked as a machine learning engineer at Leap Motion and a computational biologist at Pfizer. He was a Philippe Meyer Fellow in theoretical physics at École Normale Supérieure in Paris, France, and a postdoctoral scientist in biophysics at Boston University. Charles holds a Ph.D. in biophysics from Harvard University and a B.S. in biophysics from the University of Michigan.

Connect with Charles Fisher:

• Crunchbase
• LinkedIn
• Twitter

Read the Full Transcription of the Interview:

 

Alejandro: Alrighty hello everyone and welcome to the deal maker show. So today. We have a very exciting guest. You know we’re gonna be talking about going from almost academia to an entrepreneur and definitely you know a very inspiring story. Going to be talking about building scaling financing being almost you know close to to the end you know with just $9000 on the back account. But I think that you’re all going to enjoy very much this episode so without further ado. Let’s welcome our guests today Charles Fisher: welcome to the show. Great.

Charles Fisher: Yeah, thank you for having me.

Alejandro: So let’s do a little bit of a walkthrough memory lane here born originally in a Michigan so tell us you know how was life growing up. So.

Charles Fisher: um you know um I is normal. So I think that you know life was life was normal. You know Michigan Michigan’s kind of interesting I always joke that it’s kind of in an interesting US state because it’s kind of like.

Alejandro: Ah.

Charles Fisher: halfway ah halfway US and halfway Canada you know so I grew up like playing ice hockey when I was like three or four years old you know, ah living in in in in laancet. Yeah.

Alejandro: Now you, you never you know, really set out yourselves to yourself to become an entrepreneur I mean you had you know in your family. You know the the academia and and you kind of like wanted to be a professor I mean was that because your dad and and and how that inspired you and and then he. Took a different course or or why did you want to become a a professor.

Charles Fisher: Yeah, it’s ah it’s kind of a journey like when I went to college I went to the university of Michigan and I didn’t I didn’t enter college with like a declared major or some sort of idea of what it is that I wanted to do it was ah you know I’m at college now and I’ll figure it out. And I don’t know I was considering all kinds of things you know at that time trying to maybe maybe be in a lawyer maybe be in a medical doctor maybe being an an engineer I didn’t really know. Um, after you know my first year there I got a a research position. Radiology department at Michigan State over the summer and I think the idea was that maybe because I wanted to go to medical school I would be interested in doing this sort of research within the medical school at Michigan State but I got way more interested in the physics of how Mris work. Than in the actual medical part of using Mris for imaging so I kind of got really like just again engrossed in kind of understanding the physics of how and Mris work and that kind of then led me through the rest of my research trajectory I moved from. Magnetic ressonance imaging to them all the rest of my undergrad research was an and nmr spectroscopy and then I just kind of evolved from ah really that that interest in research in actually doing research to want to be a professor that’s definitely where I wanted to be at that.

Alejandro: Now in your case, very interesting. The fact that I mean obviously you were you were on your way I mean you were on the path I mean you did the the undergrad then the grad. You know you went to Harvard then you did a dog then you did ah ah a em bos on that you did a postdog.

Charles Fisher: That point.

Alejandro: In the sorry a postdoc in boon another postdoc in Paris and it sounds like a you were on track and and and you have like this interesting blend of interest between biology biophysics machine learning. So how do this three come together. And why do you develop that a specific interest towards this problem. 

Charles Fisher: Um, if I had to describe an overarching mission to my professional life. It would be to turn biology and medicine into a computation first science that is fundamentally what I want to do I think that you know when you look at. Those fields um, you know mathematics is really the language of computation and computers are getting faster and more powerful all the time and people are consistently underestimating particularly well in many fields but especially in biology life sciences consistently underestimating. How. What kinds of problems we’re going to be able to solve with computation in the future. So like they think like oh well we can’t solve that today. It’ll never be solved and then five years later computers are None times more powerful and they solve it right? and so that’s really kind of been my my. Like I said kind of my life’s mission. How did I get to that um know I like said when I kind of was doing that research at Mris I got interested in the physics under underneath it right and studying sort of sort of that piece I went back to school that fall at Michigan um, and started basically. I think I was originally trying to double major in biology ah biochemistry and math. Um and somebody approached me at some point and they said hey we’re creating a new major called biophysics so you can just have one major instead of None but study this study you could get the same. Ah stuff but not have to take twice as many classes and I was like that sounds great I’ll stay I’ll do that so I was yeah in that first graduating class from Michigan’s bioph physicssics program I think there were 4 of us. Um, and and yeah, that was the whole idea of it was this kind of really kind of a new idea. Of saying like how can we use computers and mathematics to understand you know biology. Unfortunately I feel like despite you know the growth in computational biology over the past you know, 20 years that concept is still pretty nascent. You know, um biology is not a mathematical driven science. Yet. But I do I do think that it will be.

Alejandro: Now in this case for you. You know everything took a turn took a turn into a different direction when you know you got a call to to go and join pfiser. So so why.

Charles Fisher: I think that when you’re in academia. It’s a there is this sort of like black hole that people refer to as industry in industry. It’s like the whole of all of this like it’s all the same like if you go to financer if you go to pharma if you go work in manufacturing that’s all industry and it’s all the same. And say yeah I had no idea what really happened in industry at the time I had spent. You know my whole career in in um, in academia my parents were in academia. so um yeah so I had a friend ah ah who a colleague from from grad school who had gone to work at Pfizer um, and you know he really was able to convince me. Um that ah that going and moving into industry would be an interesting step. Um. And I’m super glad that I did it I wasn’t at Pfizer for a very long time but I learned a huge amount ah and actually not just a huge amount about business because yeah, you learn things about how the business works about how pharmaceutical companies work. But what matters what does it matter about how clinical trials work all things that are really important for unlearned today. But I also learned a bunch of things like ah how to do better software engineering which is really you think about as being something that’s a ah. Sort of an academic discipline but a lot of actually like there’s much more emphasis on certain kinds of technical disciplines within industry than there even is within academia software engineering be None of them so I came out of out of my time at pfizor I think a much not only like knowledgeable about the field and about the industry. But with more better technical skills than I had when I went in.

Alejandro: You know it’s funny because they say that when you are uncomfortable is when there is growth and and I can see how you know taking those you know crazy turns you know in your career and journey. You know probably made you uncomfortable. But. It sounds like you were from being uncomfortable to even more uncomfortable because after Pfizer then you go pack your backs go to San Francisco and then enter you know venture world the venture world I mean that’s like so random charles. What I what a switch of events.

Charles Fisher: Yeah I mean I guess it was because like its but well the biggest thing was that my whole career had been doing research at that intersection of biology and math and computers I Just said that’s kind of my life’s mission is to is to make biology more mathematical but then I went and worked at a virtual reality company right.

Alejandro: Um, ah right.

Charles Fisher: Yeah, nothing to do with biology at all. Um, and it and and it was also a huge cultural shift because there was already. There was a culture shift moving from academia to Pfizer but actually not that big of None in some ways. Academia is like a distributed bureaucracy There’s a huge amount of bureaucracy that you have to go through and everything every paper is peer reviewed by these people. There’s editors who do it. There’s all these grant and grant making agencies and you have all so everything ends up being actually kind of committee and bureaucracy like it very very slow moving so working. It’s just distributed. So working within academia and then going to like a big giant bureaucracy like Pfizer doesn’t actually feel that different in some ways. There’s different emphasis but the pace of work and people’s attitudes aren’t particularly different but moving to a tech startup like a 50 person tech startup is. Super do hard different so there was also a big I’d a kind of culture shock for moving to pfier to then going to work at in in in technology. Um.

Alejandro: So but in this case though I mean you were also in San Francisco you were also exposed to innovation to you know other entrepreneurs to other startups and and I’m sure that that kind of like got you contagious too and and that to certain degree. It allowed you to understand hey. It’s possible I can do it myself so how did you come across the idea of unlearn and why did you think that it made sense to live up. You know your your career or your corporate you know type of of. Which was everything that you know what do until that point you know and really to say you know what? I’m just gonna you know, give it a shot.

Charles Fisher: Um, you know people start businesses for all kinds of reasons right? Um, and you know if you look at my background like I said I never really intended to be an entrepreneur. It’s but not what I was trying to do I started unlearn out of frustration. That’s entirely None frustration driven business in the sense of like that whole career trying to bring computation into biology in academia working to be. You know do this so we go to conferences the computational part. Like in a side room like maybe in another building don’t don’t bring that computation into the main building when you put develop new computational methods. You publish that in scientific journals. They put it in the supporting information. It’s not even in the main text and then. You know you go to Pfizer and I’m thinking like oh well there’s this computational sciences. Group Pfizer is clearly going to value computational sciences and the thing is like not really the people who are actually mostly in charge of these companies are biologists medical doctors or financial people actually a lot of the people your ceos have. Big pharma companies are from a finance background. Um, so no one really cared about computation and that was very frustrating for me because again my whole life’s work is to say like I want to develop these computational mathematical methods for biology and if no one cares about it. It’s frustrating. So what I would say that kind of became. The attitude of silicon valley that got to me this entrepreneurship attitude was that really you can go take that sort of frustration feeling. Um and rather than just sort of complaining about it. You could do something about it start a company build. Tools and demonstrate value and if you can do that you can build a really successful company that actually solves real problems that uses these methods. We now have a lever to actually be able to demonstrate that these computational methods are valuable for medicine and that’s really something that attitude of of. You know, sort of frustrate like really frustration driven company but building I think it’s actually really, ah, it’s really effective. Um I think there’s a lot of companies that do that? Well because everybody who builds a company. Everybody is going to run into some sort of obstacles. There are a lot. Of this everyday difficulties I mean as a startup founder I like I don’t take vacations really you know I work all the time I work every day I work Saturday I work Sunday I work. Monday Tuesday Wednesday Thursday Friday and I don’t take vacations and that’s kind of what you have to do and you don’t not doing that because of.

Charles Fisher: Ah, you know because you want to you’re doing it. You’re driven out of frustration to kind of solve this problem that you see in the world I think it’s a really powerful motivation that gets you through the difficult periods in building a company.

Alejandro: So then walk us through the journey really or the ideation. The ideation to lunch you know phase with a learn.

Charles Fisher: Yeah, so the early days of unlearn we I like to describe it as a reverse company actually a little bit so there’s this one hand of saying well we have all of these new machine learning tools is there some way we could use them in medicine to make it better. And you’re really basically saying that we really care about solving these problems in medicine we’re just gonna be an applied machine learning group. So the founders myself and John and Aaron all 3 of us theoretical physicists all of us doing machine learning research and in industry we kind of actually thought about it in the reverse which is that. We we were looking at you know, especially at the time you know on a dollar for dollar basis. Maybe ¢1 of every dollar that had gone into machine learning research went into machine learning research for medicine. All of the money was being spent at Google and Facebook and Amazon and Nvidia. And those companies don’t care about medicine right? They’re working on problems that are relevant for their business. So almost no research. Ah you know out of ah by a fraction had really been done on. How do you do machine learning for these kinds of data and so we thought. Well if we focus whenever in machine learning or statistical methods at all you encounter a new kind of data. You’re going to have to develop new methods like we’ve seen that consistently that a lot of actually breakthroughs in machine learning come from seeing a new kind of data. You get convolutional neural networks by looking at. Images you get transformers by looking at natural language processing right? So when you encounter a new kind of data. You get a new kind of architecture and so we were like that’s that’s how we thought about it. We thought that by working on these clinical data. We would discover interesting machine learning that was really the genesis of the ideas we were really a machine learning driven shop. Like ah at our core a deep learning based technology company not trying to apply but trying to invent we want to invent new methods that solve these problems in medicine and that’s really still fundamentally. None of the key components of how we think about it.

Alejandro: So then for the people that are listening to really get it. What ended up being the business model of unlearn. How do you guys make money.

Charles Fisher: Um, so we are aiming to pioneer technology that we call a digital twin of a patient. So The term digital twin is been around for a long long time comes from engineering. And people build these digital twins of devices. In fact I think if you type in digital Twin Dot Com it like redirects you to Ge’s website and some article about building digital twins of like airplane engines or something like that. So the whole idea of a digital twin is that you have a computer model of an individual thing that you can simulate. And you can then ask various questions about so our question kind of for unlears. Well, how could we build that thing for people Now. There’s a big difference because in engineering we designed the thing so we have a blueprint and we can build this model that has all of the pieces we describe how they work together and get this computer model. Um. But we don’t have that for people you know people have 37000000000000 cells in the human body so you can’t try to build this bottoms up model. So We take this other approach of really developing machine learning and ai based methods for that. So Then you have these series of questions with you know, setting aside how you actually create these digital twins of patients. You could say Well what? what could you do? if you had that in this this whole universe of potential possibilities of things that you can do and for really our go to Market Strategy is to focus on how we can leverage use these digital twins of patients to accelerate medical research in a particularly in clinical trials.

Alejandro: Got it.

Charles Fisher: Um, so every clinical trial is a comparison you’re comparing a new treatment experimental treatment to what exists So we create these digital twins of patients as they enroll in trials and we simulate what would happen if they got this existing treatment then you can leverage all that information to run clinical trials that are smaller and faster.

Alejandro: Now I know that for you guys. The early days were not easy. You know you were trying to raise money and the Vc community just didn’t get it How how how was that how was that how was that journey for you guys like.

Charles Fisher: But I mean the very the early early early early days of you know a None person company working out of the garage or whatever is challenging for everybody I do think right? and you know we had raised a small less than $1,000,000 ah pre precede round. Um, from data collective and there’s a handful of these firms like data collective that are doing that like those bets on these really really early stage early stage companies. But then you have like you know you have the small amount of money that you have to use. You know to build your business over a couple of years and trying to do that when you’re building a new technology. It’s not just like we’re taking a thing and we’re trying to sell it to you have to build the technology before you can sell it um and clinical trials as a area were not hot at the time like the people didn’t really know what they were. We had to take all these meetings where we’d say. You know, explain what a clinical trial is and and and so forth. So we had the technology piece. We had the clinical trial pieces like a lot of things that are complicated and scientific. Um, so we yeah I mean there was one point I remember those ah right? we were aiming we were going through our fundraising process to raise our our seed round. And I think we had None total people on on the payroll and we got down to $9000 in our bank account waiting for It’s actually it’s even it’s even worse than that because we we fought we saw that coming. We knew that this was gonna happen months before we were we we were like okay.

Alejandro: Man.

Charles Fisher: Because we were doing this project with the farmer company and they were going to pay us right and we knew that they they were going to pay us. We could just do a burn down chart we could be like well we’re goingnna run out money before they pay us so we cut all our salaries to make sure that we could get through that point and we hit that. That lowest point was $9000 um, we then got that pay that that to be ah the cast we cash the check ah from that pharma company raised our seed round and you know now we’ve raised over $70,000,000 um, are running clinical trials face 2 and three clinical trials with big pharma companies. So um, yeah, you’re gonna go through those really really really difficult and make difficult choices right? again we had to sit there and we had to say well we can’t pay ourselves as much anymore and we weren’t paying ourselves a lot to begin with. Um, yeah, so there’s this period where yeah this idea that somehow so a startup is somehow a glamorous thing to create is not true. The majority of the time. It’s really frustrating and challenging.

Alejandro: Ah, hundred percent a hundred percent now in your guys’ case has as you were alluding to I mean you now have raised seventy million bucks but I guess the question comes to mind is as you have put in more and more color to this making it a little bit more tangible. Has it gotten in a little bit easier with raising money or how has that progression and those expectations have shifted from one cycle twenty yeah.

Charles Fisher: Sure has yeah yeah yeah I mean sure has gotten a lot easier. Um I mean in the end what we do is actually relatively easy from a value proposition to understand right? and I think that that’s where you get to like. Forget the methods and all that stuff that’s complicated but the value proposition if you’re a pharma company. Let’s say you’re going to run a clinical trial with a thousand patients 500 of them will receive your experimental treatment 500 of them will receive a placebo if you work with us. You get to run a clinical trial. Let’s say None patients 500 received the experimental treatment. 250 receive a placebo and that means that you’re going to cut off somewhere around six months of off of your clinical trial timeline so you now say okay my clinical trial six months faster I can make hundreds of millions of dollars in additional revenue by selling this drug because I could get it to market faster. Um, so from the pharma company. There’s a clear value proposition. But for the patients participating in those trials the number None reason patients want to participate in a clinical trial is because they’re aiming to get access to this experimental therapy. So in trials that we work in patients have a much higher probability of being given that experimental therapy instead of. Placebo so it’s a win win for the pharmaceutical company and for the patient. Um and when you can find something like that. That’s a win-win. Um, once you sort of you can clearly articulate that value pop of proposition investors investors get it quickly right? It’s a win win for everybody. And so you know then you start to sign up customers and yeah, then it becomes way way easier ah to to do to to raise capital you know we get I’m a mean I don’t know I not Amelia I was gonna say 1000000 that’s but we get you know dozens of inbound emails from venture capital firms every week about trying trying to invest. Um. And yeah, the the big thing that I would say there in terms of also the way that I think about venture capital investing is I really don’t like the idea of treating it as transactional. So if you look at you know who we’ve taken capital from over the years every single one of the people who’ve led one of our rounds I’ve known for years before they led that round right? So even though we just closed. Ah, you know our series b in April of this year a couple months ago. Um I’m gonna go out and start talking to venture capitalists now in building that relationship over the next few years and letting people. Yeah, be familiar and follow the company I think that’s so important you’re not just looking for a cash these people somebody joins your board and you’re gonna work with them for years and it’s I think it’s really important to just kind of build that relationship. 

Alejandro: And in terms of building relationships with investors I think that this is fantastic. The way that you’re positioning. This is not like hey don’t wait until you need it. You know, build it and then you can activate it whenever you know that is actually needed and you already know that individual but in your case and in your experience. How does it go from being less active to being more active I Mean how how do you make that transition when it comes to building those relationships and raising the money right.

Charles Fisher: Less active versus more active. Um, so what actually doing a financing like when you’re going out to raise the financing is a lot of work. There is you know a period of. Usually about three months because you have to put together all these materials and stuff right as well. So you’re getting your materials ready. You’re getting your deep practicing. Um where you’re really totally externally focused. Um, and you know as the Ceo and the people who are really involved in doing that aren’t really internally focused on like what’s happening at the company right.

Alejandro: Yeah.

Charles Fisher: Um, and so I think that spending too much time in that mode is bad some but like it is important to like focus on building your business in the end like having a good product and having good customer service and having that stuff’s really really important and it’s probably more important. Um, so ah, you know I think that the key aspect again is is to um. Is throughout the year you know take I don’t know None or 3 meetings a week these will be you know 30 minutes maybe maybe an hour grab a coffee. Whatever it is with people and figure out the people who you want to you know through those meetings who you want to. You know, build that relate who do you think is go to be a good fit for your next round and catch up with that person. You know every two or three months into until it’s ready and because then there’s again, they’re just seeing that that um that that progression over time you want to be showing them that your business over that period is growing is. Hitting milestones is doing better and then they’re going to have that feeling that they that they that they know you that they know your business and that that it’s is something that they want to invest in so I think that it’s just that’s the best thing is you want to rather than trying to do this thing where you’re like running this massive process. You’re gonna set up this huge list of investors that you’re gonna talk to you all go to go pitch. Pitch the deck I think it’s better to basically have like None like over those periods like the year or whatever between your raises year and a half two years however long it’s going to be spend that time figuring out who the None people are that you want to that are your top picks for investing in that round getting to nova. Um, that that’s ah, just much better way again, you’re building that relationship so when they join your board. It’s gonna be a lot better but also um, you now don’t have to spend constantly all of that time just pitching you. You can still kind of focus on thinking about how to run your business.

Alejandro: I Love it now. Imagine you know you go to sleep tonight and you wake up in a world charles where the vision of unlearn is fully realized what does that world look like.

Charles Fisher: I Think it looks like Star Trek is ah you know like the vision is very interesting. It’s this like Star Trek Medicine Um, that’s the real vision when yeah I think about that long term vision The long term vision is that you know like basically there’s a virtual model of every human being.

Alejandro: Ah.

Charles Fisher: Um, and that you you rather than having to say like go run experiments on real people I’m running those experiments in a computer and I’m getting instantaneous information about what the right? What’s what that patient’s prognosis is what how their health state of current state of health is what’s the best treatment option I’m getting that instantly in silicone. Um, and then you know maybe you don’t even have to really go to the doctor like this’s just the doctor just pulls up the virtual you that’s a vision do I think that that’s a vision that will happen in my lifetime right? like like when you’re talking about that big of a leap in technology. You’re talking about generational leaps in technology. Not not today um, yeah, so in the shorter term this question about you know with with clinical trials. Our real vision. You know we we have ah an approach to using these digital plans of patients in clinical trials that really just makes those trials better in the sense. It makes them more efficient. Um, it makes them more patientcentric is aligns with what patients want um and we can actually prove mathematically prove. We have like peer reviewed mathematics papers that prove that they that these trials still generate rigorous evidence just like regular trials and so you get all of these things. Ah, tremendous benefit with very little downside so you know within the next you know None ears you know our goal is to say that this becomes a new standard approach to how you run clinical trials that every clinical trial is including this information from patients digital puts.

Alejandro: I got it now in this case, imagine I was to put you into a time machine and I bring you back in time you know perhaps to that time that you were still at leap and you know trying to figure out. You know what was gonna be next and you know maybe that you were gonna start something on your own. If. You had the opportunity of having a chat with that younger self that younger charles and being able to give that younger charles None piece of advice before launching a company. What would that be and why given what you know now.

Charles Fisher: Um, ah, that’s a um, that’s a really really good question. What I would say is um.

Charles Fisher: I think that you know, especially for people coming from my background coming from the scientific background. There is this um, sort of lack of confidence that people often have starting a company around the business side of. Of of the you know what do your finances look like how do you do sales? How do you? you know sell the customers how you raise venture capital how you do? Ah how you do all those things and ah, there’s not much discernment when like when I interview especially back then when I would like interview a person who is like doing business. And then I were like I couldn’t tell if they were good or bad. Good or bad business person. They were a business person. They were just very different from me is kind of the way that I viewed them as kind of like an other I really think that that attitude that a lot of scientists have is is really detrimental to being in a startup. You can’t view the business side as being something other that like you’re not going to be good at um so honestly, the piece of advice that I would have given is just to believe in myself in terms of being able to go out there and do that because the venture capital raising like yeah, that’s stuff for that I’ve now all done right? like I did all that. Going out and pitching to customers. Yeah I mean certainly for the first you know None ars basically of the business. It was me going out and pitching to customers. Um, you know now of course we have ah brought on additional people to help with those things but ah yeah, the early days are are kind of like that. None website it was like me and and our none employee Graham like we sat down and we built but way we built the website. Yeah, you do all that stuff yourself. Um, and ah ah yeah it said the piece of advice I would have for myself and for other people coming from the scientific background is just that you’re gonna have to do that stuff. And you just have to believe in yourself that you can you can learn how to do it.

Alejandro: I Love it and charge for the people that are listening. What is the best way for them to reach out and say hi.

Charles Fisher: Ah, well you can follow me on Twitter I’m Charles K Fisher or you could just email me charles at Unlearned Ai

Alejandro: Amazing! Well hey charles. Thank you so much for being on the deal maker show today with us. It has been an honor to have you.

Charles Fisher: Yeah, thanks for having me.

 

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