Founder Stories: Bob Nelsen, ARCH Venture Partners

0:00 earliest Whispers even when the data are too early for just about anyone else so UCSF people take note this is the guy you want to talk to if you're doing a startup how many of you are doing startups in here and I think right so often as early companies we just got instincts was another quote from Ford so I didn't write this stuff but someone else did I've got to read this Lee Hood when he appears random and Scattered and

0:29 marvelous at avoiding Focus but in the end he has been a genius at creating companies like Illumina that have really transformed whole Industries so I think it's a little more to Randomness that's probably correct so Bob grew up in Washington he went to the University of Puget Sound majoring in biology and economics which is an interesting combination he did an MBA at University of Chicago and from what I can tell that really that really made

1:01 this path happen so he is co-founder and managing and director of arch Ventures which is not a Silicon Valley firm in fact it's roots are out of the University of Chicago and and the thing that we should all remember the university is this was a University's fund so we don't have one yet at UCSF but maybe we'll get one the archventure fund in 2007 fund had a 47 return the sixth best performing

1:33 Venture fund of the decade 24 of his companies had IPOs 16 reached billion dollar evaluations so he's just had an amazing run in this 30-year career he co-founded icaria which he sold for 2.3 billion kythera was sold to him to Allergan for 2.1 billion he was the first seed investment for Illumina which has a 21 billion dollar market cap he founded kybella or invested which sold

2:06 to alleghen over 2.1 billion and the list goes on so what we're all fascinated about are sort of the newer Investments The Grail which is a blood test for all major cancer types he actually pulled off a one billion dollar series AMD and when I read that I read it before the B had been raised and then I had to go back and say well did he actually do that because you know and then there it was

2:30 he raised that Juno we all know as cancer immunotherapy raised 310 million and did a 265 million dollar IPO Denali Therapeutics that some of you probably saw Ryan Watts here not very long ago was a 217 million dollar a round at the time the biggest a round ever done in biotech and attracted Mark Tessier Levine as chairman who at the time was Rockefeller University and now is Stanford the syndicates who invest with Bob and Arch

3:02 Ventures read like The Who's Who of Biotech Venture Capital their Pension funds family foundations and even a sovereign fund so this man is quite extraordinary and we're very fortunate to have him here and so thank you for coming back so we're going to do this like an interview and see how this goes mainly unrehearsed because I had 10 minutes with Bob a couple days ago while I was driving is

3:34 like okay I can pull over and write notes for a while but it's hot in this car and I need to get going and so so what I learned is about your childhood strawberry picking why don't we start there you know first we have to have it cool on how long it's going to take me to just say that word well like you have any any thoughts I'm sorry I swear a lot I will try to

3:58 cut it down in this I actually yeah I I used to once have this theory that everybody that worked for me should have worked on a farm and it turned out that the narrow the applicant will significantly but but I kind of so I started working on porn when I was nine and so my social security statement when they send you that thing you know it starts when I was nine and then I started saving that money and

4:27 started investing in the stock market when I was 11. so I did have a certain you know risk seeking Gene nothing has really changed that much over that time but I do think that it engenders a strong work ethic and if you're going to do seed Venture Capital as opposed to later stage ventric capital or private Equity where you just kind of sit around take a couple meetings you actually have to work really hard to

4:58 try to make these companies go and it's not without you know you know if you're not in for kind of 80 or 100 hour weeks you shouldn't be in it so just go back to the stock picking thing the age 11 on earth made you decide you wanted to get my mom encouraged me to like because I had a thousand dollars that I had saved up and so she incurred her 900 or something it's pretty good for an 11 year old yeah

5:22 I know it's better than that it's better than some and so she encouraged me to explore the stock market as a place to put it sorry I bought first I bought white Westinghouse which was kind of a conservative you know it'll bet and then I actually where I made a lot of money was back in the first Mr company called phonar which actually invented Mr and then GE ripped it off or is there some sure there's a technical term for that

5:52 but improved on the technology by stealing it and then and then you know made more money than the original phonear guys I traded that stock for a lot okay so you grew up and you went to college and then you went to grad school and then how did you end up in venture capital I read an article one day I was at University of Chicago in my first year MBA and I read an article in the paper

6:21 actually it was the Wall Street Journal about a fund I'm not a a company that had been created by the trustees of the University to help commercialize the technology out of the University of Chicago and and they kind of described this you know person that they wanted to hire which was the first employee and I just remember seeing the salary which was forty thousand dollars it was like I don't know 86. was that a lot of money that would

6:52 be a lot of money though yeah although I set my original salary when I got the job at 1200 a month because I was a bad negotiator at that time so I remember turning down like 82 000 a year when I was so I went straight out so I would have been 20 three or two twenty three and turning down 80 plus thousand a year which was to be you know equivalent today of like you know it was it was higher than

7:22 McKinsey at that time or building attacks and and to work for twelve hundred dollars a month and literally every single person that I knew except for one guy told me to take the money and this one guy told me that I should do what I wanted which turned out to be all right it took a while but

7:55 so basically I I started by essentially volunteering and then I eventually asked for a salary so my first year of business school I was volunteering hanging out with professors to try to figure out what to do with their technology and and that's actually how we created this program that we call the Arts Associates so we had up to 100 business school students working for us as volunteers including like George catifa who then

8:26 went on to to run the Hewlett-Packard software Division and choreo and a bunch of other places you know our alumni have kind of gone and done some really interesting ly cool so you tried to get in touch with Brooke Byers someplace was it looking for your first yeah I wanted to be a venture capitalist but I didn't really know what that was I actually didn't know what an investment banker was either so on my application for Chicago I put

8:53 on there that I want to be an investment banker because I knew they got paid a ton of money and so and then once I figured out what they actually did I decided I didn't want to be an investment banker but but I didn't buy this thing called so there wasn't the internet obviously your cell phones or voicemail so there's a thing called Pratt's guide to venture capital which is the most expensive book ever made as far as

9:20 I could tell like it was yeah 250 bucks for 300 bucks back then and so I bought Pratt's guide to venture capital and I would just go through there and like look at the different firms and I decided that this firm called Kleiner Perkins was cool and they had done Genentech and and a bunch of other stuff Tandem and Etc and and so I called them up and and I called this guy first buyers who Brooke would have been I don't know

9:57 yesterday or something he's not he's older than me but and so I had to call him 35 times actually before he took the call but you know I wasn't you know I think I think when I when I got rejected from Stanford or I actually got on the wait list at Stanford my my adjective I make it to some Dopey thing right you have to choose an attitude to describe yourself so I I chose persistent and

10:29 and so I was persistent eventually he called me back and we had a good talk about how to get an adventure capital and of course there is no algorithm to get into veteran people and this was in the 80s yes it's like 85 April early yeah and and there was nobody in a new adventure Capital was back then outside of like a few places in the Bay Area like you would go on a plane and sit

10:52 next to somebody and then and you would say well you know I do Venture Capital even in the late 80s and then like you know a business person what's that yeah so you were persistent you tried in the morning and at night and in between and eventually you picked up the phone excellent I guess that stays with you this yeah here to Mark testing Levine long enough to start a neuro company that I'm actually decided to start

11:15 denology like you know actually Steve Gill has said that it but basically that's how he decided he had to work in ours to get me to stop calling him so tell us about Arch what's the philosophy you know you said it started out of the University yeah so we were kind of bread in the you know the bowels of the University of Chicago Ivory Tower which was basically science driven faculty-driven institution that it really is faculty driven so

11:45 it's it's all about kind of the science and the data and and so we were you know nobody there I mean admitted to wanting to make money you know here kind of now in these days like it's kind of out there right I mean people I was negotiating with the professor at you know a very famous Professor on the East Coast recently and you know I mean it's it's really out there right there no it's not all about the money it's

12:15 just it's you know some of us money I think it's first about the science almost every almost all the people we deal with it's first about the science the money you know is a marker it's it's be treated fairly I remember when I when people the reason ours was created at the University of Chicago was that Gene goldblosser is a scientist there purified a molecule called erythropodin file the dementia disclosure on it which

12:47 would have dominated Amgen and Gi and the university decided not to pass it so the npb of that decision is actually greater than the entire University of Chicago endowment today okay so it's big money an issue that they lost okay that's probably one of the biggest drugs ever right and you know take a royalty on that and so the trustees actually the reason the Arts got created is a trustees decided that you know they were just as smart as East

13:18 Stanford and Harvard people and how come we didn't have startups around and so we were given an incentive we got to keep 20 of the equity and 10 of the license royalty in a bonus pool so I think when I was 27 or 28 I made more than the president of the University of Chicago and so giving up that earlier deal with 80 000 was a good decision yeah it was it was okay I mean that that company

13:46 actually was a k-6 math curriculum company that allowed me to do okay that year but and it was out of the University of Chicago but but I think it just the money is a piece of it but the science is really what motivated me and and being kind of learning in that place was a really good place to learn about good science and and to just you know hear the history of of the place and kind of

14:15 I think once you're kind of forged in that that saves with you and in biotech I was just explaining this to a very famous Tech investor about couple hours ago to biotech the data and the Science Matters right if you make the second best dating app you know you're still you know probably get you know successful probably acquire an STD just like the person you know the first best dating outfit like in Tech it

14:47 very rarely matters who has the best technology sometimes it does and you can argue like semiconductors in some places where it really does but most of the time it doesn't in biotech you know nobody wants to second best cancer cure right I mean it's just one of those things where if you know the data really does matter and the Science Matters and there is science that's better than other science and you can't make that up so we grew up

15:15 starting with the science without management teams so it never was this kind of you know a management team B science I mean we we usually had a science and we're pretty good even to this day of picking a science sometimes you pick B management teams or C we try not to do that we try to consolidate our errors actually in one company so we have certain companies and we use this example for that where we actually

15:44 picked the wrong science and the wrong person and like everything do you want to tell us about one of those well yeah probably probably could learn from things that you think that's concerned Elixir bio attack button Elixir was a really good idea it was just too early and we also Seattle said the upward there technically the word is up the management

16:15 decision so we hired the wrong guy a couple times and you know it doesn't mean they're bad people it just means that they're not appropriate for the situation and in that case actually somebody else kind of ran with one of the other co-founders and and the same idea and sold their company for 700 million because they knew how to sell and and when you're doing an anti-aging company which was the first anti-aging company

16:47 you had to be able to sell the dream you couldn't really sell you know part of the dreamers have sell the big picture and even then the science was too early but and and the people that sold the company for 700 million their science was too early too and the Pharma figured out that you know it was only maybe 10 or 15 years too early but from an npv basis or however you do the math it's probably not a good investment

17:15 decision but that same science is coming around again so you deal in very early how do you know when it's too early you don't really you know I mean you just have to there's a certain amount of faith that that occurs I would say that you have to have a certain amount of scientific judgment and you can't get too mired in the science either you kind of have to have an algorithm of knowing that if you apply smart people to problems you

17:42 can solve them without you know without getting too mired so I think you know most Venture capitalists have like MD phds if they use them are not very good if if they don't use them and they you know have other instinctual because if you get it's like you know in your own lab or the lab next door right you probably don't even know what's going on in the lab next door right so it's it's very hard for people to think about

18:14 applying their technology to a dis a different problem or a different discipline when they've spent the last 30 years thinking about one aspect of their technology so I'm reasonably good at at kind of templates and thinking about you know where where things might go and I think there are to do early stage Adventure Capital where you're actually starting the company like we do about half the time

18:45 you know you have to be able to picture what the future is going to be like right you have to be able to say okay I think we can cure a bunch of infectious diseases how can we haven't and you know we should put a bunch of smart people and and I think the science isn't the right place that we can do it differently than all the other people have done it before all the other very

19:07 smart people I've done it before or the same thing with you know Alzheimer's or whatever so how do you figure that out and what are your sources of information that lead you to a hypothesis I usually start with the problem right and and figure out if the problem is very big and then well actually probably half the companies usually the bigger ones start with the problem and about half the company is our start with an invention

19:35 so like Gene editing right so we're doing company now in nucleotide and that's just a really hard thing to do if you could do it it would be really cool and so it's you know gotta somebody call us up said I can do this and we said that's cool let's start a company and then you know you pull in the best people and try to manage that into some you know funded entity the other way is to say

20:08 Gene I think Pharma and everybody else have kind of screwed up the search for Alzheimer's drugs and things are different now in the sense that science has progressed in our understanding of you know maybe how to deliver drugs to the brain or how you know how to measure things in Viva to be able to actually know you know to get feedback loop on what you're actually doing so let's let's take a broader approach kind of a systems approach

20:39 to that with really smart people and if you do that at scale aim with a lot of money maybe you could approach people who normally wouldn't join an effort like that and kind of get this kind of amazing and denali's a great example of that like if you meet the people at Denali you would not want to compete with those people like they will kick your ass absolutely I don't care who you are in the world whatever big Pharma thing you

21:09 have you know they will kick your ass that is unbelievable resonance between not just one or two a pluses like you go around the table at the board meeting everybody there is just like you know three standard deviations exceptional and when you get them all together then your five standard deviation is exceptional you know there isn't anything like it and and then you know it doesn't take long for people to recognize that either people with money

21:38 or even pharmacist and they're kind of like okay can we give you our stuff you know how can we collaborate with you and that then that is as it becomes a self-fulfilling prophecy you know when you think about value or you're thinking about kind of innovation right so you what you want to do is is you know try to take risks in a in a smart and calculated way but you also want to try to take risks and my

22:04 biggest criticism of venture you know in general is that venture capitalist you know sometimes don't take enough risk and really what a surprise for all of us so you know I mean I think it's just one of these things where that's why they call it Adventure capital supposed to lose money I remember I was meeting with some famous lvo dude in New York and he's a he's a really nice guy and but he kind of starts his

22:32 conversation with you by saying you know since 1981 he hadn't lost money in a deal and I went to University of Chicago so the first thing out of my mouth and this guy's known to be kind of you know strong will I said oh you must not be taking enough risk and he was used to people saying oh isn't that this is the greatest thing right and I told this vice president that I said that you said yeah because like it's true you

23:00 didn't use the f word though probably yeah so you sort of started on the Denali story why don't you just fill in some of the gaps how did this all come together so Denali was a the weird intersection of multiple people thinking the same thing so I had been pestering mark for a long time that it was you know we should do something in neuro we should start a neural company because the clinical problems were really big and he had kind

23:31 of said you know it's not time you know I think calm up and come let's do it you know either say no it's not the time you know and at one point I called him up and he said okay Now's the Time okay is that 35 phone calls like yeah a few and you know some of them were scientific discussions on why and then I have been having the same conversation with Doug Paul about let's do a neural company someday and and

23:58 then Fidelity has been thinking about and actually funding a little neural company and and I kind of convinced everybody that we should pull all of our efforts together and and fund it with kind of more money than any of them were comfortable with and I was really taking the lesson on how to do that from Juno which was to try to assemble you know we go through and basically try to create an align interest group of

24:27 investors and and there's nothing that hurts startups more than misalignment either in the board or the investment investor if there's too many multiplicative probabilities that are working against you in the startup you don't want to screw around with dissonance in the board you don't have to screw it up and screw around with investors that have different interests it kills companies and and you you know it's a manufactured risk versus an actual risk and so what we decide I I kind of was you know

24:59 interested in creating a long-term aligned group of investors that wasn't comprised of people who wanted to flip in and out so I don't see a lot of value as much as I like some of the later stage Venture Capital friends that I have probably less recently after making speeches like this you know I don't see a huge need for or value in later stage Venture Capital right it's just money and if you're smart in the early stage you can create

25:30 a board and expertise that you really don't need you know more investors telling you what to do so and the same thing with some of these guys that flip in and out of of companies and so the idea behind Geno is that we would pick people who wanted to hold it for 10 years and that was their that was their time frame it's actually when we closed the B round of Juno I think they'll average holding period for the investors we've

25:57 got was like 11.3 years or something it was crazy and and it turns out that that has no impact it actually increases the probability of an earlier Financial return So if you think long term it's just like trying to sell your company right if you're trying to sell your company you're going to be screwed if you're not trying to sell your company but you're just kicking ass and running your company that then gets bought right and the probability of

26:23 getting Buzz higher if you if you actually just do well and and but if the minute you so it's the same kind of thing it's if you think long term good things happen and your optionality increases and you know the way to think of startups is the linked option Theory right it's not MPV it's all about increasing your optionality the only thing you need to know I think about thinking about startups is you want to just maximize your options at all time

26:51 and you want to be able to to pick options right you have to be able to pick a plan but you're still maximizing optionality within any plan that you pick whether it's Financial optionality or any other way you define optionality you just don't want to get down the end of the maze and there's you're stuck because you know then you really are kind of screwed so so University of Chicago no I mean I once used to know option three because I

27:21 actually worked on the oex actually I forgot that chapter but tell them what that is the Chicago Board options exchange so I actually actually they don't want to be a runner because I wanted to kind of trade in my own account so when I was 17 I got this job because I was on a chairlift of some dude who owned a seat and I said can I come work for you that summer by the time I was off the chairlift I had a

27:43 summer job and so I went there and and start trading options in his account and my account I had no idea why he left me trade options in his account and so I guess maybe I was 19. but anyway you know I learned a little bit about the theory and I think that mpbs you know one of the reasons pharmas are so bad at decision making is because they use MPV analysis on on

28:15 you know what should be I better tell them what that is well and just you know that present value I mean they they don't a lot of scientists in the room they don't appreciate the uncertainty the uncertain the multiplicative probability uncertainties involved in like making it run and and so but eventually it gets some Financial guy who who has you know who comes up with a number and and

28:47 whenever you have a system or that's very complicated you know you tend to want to believe the analysis you know whether you're talking it doesn't matter which model you're talking about if it's complicated and you can see all these lines anyway and it comes out with a number you're like oh that number is better than this number even though it's just all and and so and you know you can pick drugs all day long that where the market analysis you

29:14 know whether it's gleeback or any other you know just pick drugs all day long marked analysis always wrong and and sometimes wildly run around the Blockbusters and so that's where you you kind of have to I kind of look at the clinical the size of the clinical problem so I'm doing a big infectious disease company right now it's the biggest one I've ever done we were like you're crazy to do infectious disease because you can't make money in infectious disease or like

29:41 you mean you know those fancy mansions in Hillsboro are not owned by Gilead Executives I don't know I mean they're there somebody's making money somewhere but but I think if you cure things if you either prevent things and can capture the value which is hard or you you know cure or disease modified things you'll make money so I don't I don't model that out I seem to know that it's a big clinical problem and that's enough

30:09 for me I don't I don't think I think you could get lost in the weeds that doesn't mean there's not a lot of nuance in how you might do it so like one of the things that we think about is like hey you know can you make money giving people prophylactic antibodies that you know treat disease or maybe prevent disease and that's complicated right that could be you know maybe it's a cocktail of them five years ago you

30:35 wouldn't think you could do that profitably but now antibiotic costs are gone this maybe you could make a cocktail of you know antibiotics that you could you know there's there's you know you have to think about the business but you don't want to let that overwhelm the the kind of sign what we always used to say at University of Chicago which was kind of what makes fun of the Harvard people actually was the harder people would

31:01 have this really complicated model that would show like that if you increase taxes unemployment went down and the Chicago people are like huh that doesn't make any sense it's like everybody we know like if you increase the taxes a lot of them they don't go out and hire more people and that you know it turns out if you throw like growth into the equation or something like that or reverses the sun if I had all kinds of arguments with

31:28 people so sometimes it's just better to like pick really big problems and and then focus on what's the probability of the technology actually being able to solve the problem and that is actually tricky so you sort of alluded to beer you want to tell us a little bit about it George scango's famous CEO from Biogen just joined his CEO here so beer kind of arose from he's really kind of simple but I just

31:59 decided that that if you look at the world of of kind of infectionist disease there are lots and lots of unsolved problems and I kind of looked around at like who is the competition and I thought huh you know I wonder if all this way of Immunology Etc that is being applied to cancer can be you know applied to infectious it turns out a lot

32:30 of the cancer stuff was actually invented for infectious disease it just has been applied to infectious disease and so so it's kind of a simple idea that maybe you know Immunology meets infectious disease from host perspective would be a cool company to start and then one model it could be Genentech and the other model it could be you know Celgene or orgilia or maybe it's a combination of all some aspects of all three of those business models

32:59 some r d focused science driven and so I just decided to start it and I decided to call it dear because that was like virus and then luckily I had already recruited a female chairman before somebody told me you know Veer means mail and I was like oh I don't know but anyway so we have a chairman named Vicky Sato who is a female which gives me some cover calling my company mail but but it also fits on a license

33:31 plate which is the most important thing you should remember about naming any startup it has to fit on a license plate unless you know how to drive so anyway so beer I just decided to start it the one of the luxuries of having a few successes is that I can kind of do stuff now to some degree

34:03 even if people think it's crazy so most of the stuff I do for like one or two years people think is pretty nutty like an Alzheimer's company people thought that was actually quite nutty for a while it's catching on now and then so in that one people definitely thought I was and still do you kind of think it's a little nutty although they're trust the concept they're churning the concept was just Immunology means infectious disease science is at the

34:30 right that there's a wave of science hitting and understanding the host and that hasn't been applied very well in all the nasty infectious diseases that you can think of whether it's resistant TB or you know HIV or herpes or Hepatitis B or you know just go down the list there's just a lot of stuff and then not not even saying anything about the emerging viruses and stuff and then there's this computational component that you know we are in the Dark Ages

34:58 right you go into a hospital and they're like oh let's try this let's try this let's try this let's try this oh you have you know we have no idea what we're treating in terms of anti-effectives or or even viruses they didn't know whether it's a virus or you know they can you know oh you have something right let's guess what it is and then we'll try this and then so you know the idea is to

35:20 to have a more quantitative approach to profiling what it is and that informs drug Discovery we also have a computational Immunology component which is actually direct so we're actually using computational data to think about new Therapeutics in a entirely different way than it has been done and then we're still collecting technology so one of the things I have thought about which I didn't really know which is you know it's a little bit of

35:52 if you build it we will come if we build this big thing with lots of money with really good people that we'll be able to go get cool stuff that's out there because there probably is some cool stuff out there I say the stuff out there is cooler than we thought most of it's in the bowels of Biotech companies and some pharmacies and even there it's underfunded and so it is accessible which is the surprise and it's also rare that when you go

36:23 into the Pharma the first time and say you know I'm willing to give you 50 million dollars will you give me your stuff they're like you're gonna pay us and you know and more more interestingly I'm willing to take your r d budget off here you know your piano and then they're kind of that gets there that gets their interest and so we're able to do stuff at a bit of a different scale than has ever

36:47 been done really in in the space so because of the resources that we have who's who's investing with you or do you have a normal Syndicate you like to pull in tends to be you know Sovereign wealth funds and big public funds and then hyena or a very very high net worth people so with with Vera the we haven't really talked about who the other investors are yet but we have talked about Gates so they actually invested in the company

37:15 and then our our funding some of the some of the programs so it's quite unusual that you've got the Alaska fund and involved with Denali anyway and Juno I believe so how does that happen so first tell them about the bun which used to invest in bonds or something 30 years ago yeah I mean there's a bunch of it is a symptom of something that's going on in the world which are there's a disintermediation of intermediaries

37:47 so fund of funds and and other folks are being disintermediated by big pools of money going Direct and they don't go direct you know willy-nilly they go to wreck with very few relationships so they have somebody kind of guide them in in their efforts whether it's cic in China or you know or the big Middle East Sovereign wealth funds or the U.S Sovereign wealth funds like Alaska Permanent phones I think the only or one of the biggest

38:17 Sovereign wealth funds here and then you have tomasik and Singapore GIC and then the same thing is happening with big public investors so some of the investors that used to be very hard to get in and I was very active in kind of pulling some of these folks in early four or five years ago into kythera as an example These funds that manage a trillion

38:48 dollars or three you know kind of anywhere from a couple hundred billion to a couple trillion are you know they want to own 15 of you in five years or 10 years and just hold that's a really good investor so I want somebody that buys in the a the B IPO the secondary and then in the market and that's the definition of a long-term investor and that's what you really want and it turns out those two things are

39:19 coinciding the bigger money wants interesting things to do they're not interested in putting five million dollars in something cic I think their entry points 200 million maybe they're a little smaller to 100 million but it's you know big money most these folks don't want to write a check less than 25 million so what you can't do is Rerun the era that Venture capitalists made in in the 90s and and first decade of the 2000s which was

39:50 if just add up all the money and then put it into one big round and don't change any other you know systematic you know if you don't shift the curve of probability set of the company I eat better management better opportunity set better technology you've got nothing right you end up with a 1X and a lot of VCS you know got that I mean I haven't deals where we successfully prosecuted the company to an IPO and had a 1X

40:20 yeah generally not good it's better than a less than one accident so so you know if you if you're gonna do the kind of the big money thing you have to do it in a way that fundamentally shifts the opportunity set and therefore the value kind of sets of the option if you want to get quantitative about you could probably run them all of a series of linked options and say you know we've we've changed the probabilities of this and

40:53 you could say you're changing it because you have a better and different human capital in some sense you know one of the things I'm proudest of of Denali is they have a really good kill algorithm right they know how to kill projects so the the very first platform that the company brought in they killed six months later it wasn't it was an entire platform I mean it's killed kind of down I don't know if it's you know somewhere you know

41:19 in the negligible burn right but you know watching the science stuff it's science is cool but and very few companies have the ability to do that so if you recruit management teams like Georgetown or Iran then you can deal with the portfolio of assets where normally kind of historically biotech companies haven't been very good and Pharma companies are definitely not very good at killing stuff right and the whole culture of a pharmacist like to preserve

41:51 the project because that's your job you don't see people getting promoted for like killing their clinical trial in phase two you should I mean audios has a party every time they kill a DC and give out bonuses so I'll get tried they all kind of celebrate the effort and that's very rare but very cool because that's what should happen right I mean you should be kind of rewarding people for being disciplined and and admitting that the

42:19 data sets and you know but but Pharma 100 does not do that and and a lot of Biotech like if it's your lead product and you got one product you know how many people want for you to let me go into the CEO and say you know your baby's ugly and and so so you know we've tried to do some of these companies like there's multiple you know there are multiple assets so so you aren't dependent on a single

42:49 event and and one of the things that these big pools of wealth fear and don't never liked about biotech even in public companies they buy a public company some happens and it goes down 80 percent the next day you know that's not good if you're like a sovereign just bought 10 of the company and so you know they want some kind of way of balancing risk but not in a way that's just putting a whole bunch of

43:17 shitty assets together in one place which is what people have done historically so you have to do it differently and you have to do it in a way that either has some scientific Insight or some different way of looking at the problem or some better way of killing them so I'm going to open this up for questions in just a couple minutes but I really want to know about Unity biotech you're anti-aging approach and you're personal and a one

43:43 yeah and you want to talk about start with that self-experimentation so you know I think if you're going to be in the pharmaceutical business you should be willing to take so including prophylactically as long as you run your renal and liver function off so I do run my renal and liver function oven but but I do think that they're you know I tend to be a little bit ahead of the I'm willing to extrapolate from Mouse data to to humans fairly

44:16 rapidly because I you know I actually fear death it's like the Pirates of the Caribbean you know I actually feared up and so I'm going to live longer and I would prefer to live longer in a healthier State and so we started one company that was a you know wild unsuccessful land and we lost 15 or 20 million 15 years ago which is a lot of money in that context and then

44:48 decided to do it again with better data with the unity company founded by David which is based on deleting senescent cells and you know the Gladstone and the genie Camp pv's work and mail so some really interesting data hypothesis driven which is a little scary but then now the data is getting better and better and better in terms of the you know the real biology underlying so it's when we started kind of

45:19 you know truly a hypothesis driven you know it's not usually what we invest in but it's just it was such an interesting result and we said okay we'll give you a little bit of my so we I think we invested 7 million Millions over five years and just getting a better day and getting better today and getting better data until it appeared that we had you know the ability to drug you know to have a small molecule that

45:45 would delete semester cells and then we'd put in real one which is we just raised I don't know well north of 100 million to make drugs that first start locally so they're going to start in you know areas like the knee or the I or the lung or something and then eventually you know and it's not just limited to Sonesta something we've broaden the mission so we're looking at other signs other than sin Essence but you know the idea is to

46:14 have drugs which increase health span right which can prolonged and it's always fascinating to me when if you just look at kind of the data about risk for disease right so pretty much anybody in this room anything you do whether it's your genetics are your behaviors that are still less related to disease than your age this is pretty wild if you think about it you can have all these genetic risk factors you can have you know

46:46 you can smoke you can drink do all this stuff but you know the probability of you getting one of these big nasty diseases is correlated more with your age than any of those other things unless you're you know kind of a 55 year old you know I believe four or four unlucky person all right I guess you're unlucky if you're an April 844 so so I think that's the kind of thing that that motivates me I do take

47:16 you know metformin prophylactically and Lipitor prophylactically and yeah nicotine might riboside because and and and then if you're gonna do that kind of stuff you should definitely get your renal function of liver inflation but I don't think it's any dopier than a vegetarian diet right I think that's much more dangerous than taking

47:47 to them taking you know metformin you know yeah to train my high fat high protein diet you couldn't get me to trade it for a vegetarian or vegan diet I hope you eat also you're not just taking pills no no okay good I eat I try to eat I'm not ketogen Jack because I have no not enough discipline to be ketogenic I like wine and but but I do try to I have a very high fat diet

48:16 okay I'm sure there are lots of questions here so who wants to start off go for it great talk I was really interested by a comment you make early on that's the concept of trying to try and swing for offensive by hiring a really big big name team put in a lot of money and then good things are going to happen you also noted that typically farmer is really bad at killing projects and it has all

48:45 these kind of bad behaviors that have otherwise not necessarily always led to good out so you talk a little bit about how you square those two things how do you find but I don't think so I think big name team is the wrong way to think about it I mean I think like with beer we happened to hire a big name guy because he's really good but it wouldn't matter to me that whether he was coming from Biogen or

49:12 some other place right so it's not about them it's it's about the the way I would say it is you know we hired DNA right so I I don't I'm I want great DNA and I don't even care if they're a cancer person going after infectious disease or infectious you know you don't do box checking you know it's kind of like you know getting married right it's like if you try to do the whole box checking exercise it's

49:38 going to be you know I was you know absolutely convinced in my life that I was going to marry you know MD MD PhD Nobel Prize Wing winning Economist and I married my hairdresser you never know so so I think you gotta you know you gotta go with the gut of the on the hiring part I think Pharma is a fundamentally broken incentive structure

50:09 it is broken it because it can possibly be so you're the CEO of a Pharma you're lauded in the press and get to go on CNBC for some decision that the guy that got fired before you made 10 years ago right and no correlation at all with with compensation and and you know Merit whether you're in the r d organization or whether you're in you know business management the only people

50:40 in Pharma that are truly like you know have incentives that are aligned are the sales people right which is they're supposed to sell more stuff and now that you know is is you know controversial because you can't really you know that creates incentives that are you know possibly bad which is to sell something off label so you know like in nicaria we had a we had a non-sales force I mean a non-sales-based compensation structure for our sales people

51:08 but but so I I just think the the incentive structure is broken it's not a meritocracy and there's a lot of really great people in Pharma that we like to hire sometimes when they get pissed off but but it's a super frustrating thing because most of them you know you know know that there's a lot of this stuff that just is perpetuated and it's just impossible to to kill and nobody you know why if you're if you're

51:38 the head of that program leader would you want to kill essentially your job you know in Microsoft if you kill your job you can get promoted especially old Microsoft like the first 20 years of Microsoft that was Swift so cool about it you know you could be you know somebody with a pierced nose and a tattoo on the middle of your forehead and like lose 600 million dollars and they're like yeah we you know we thought that

52:03 was you know the right decision and then get promoted and Google and some of the places in the valley one of the cool things about those places is they they recognize Talent really well and they continue to give those people a shot not indefinitely but eventually okay down on the floor so something that still puzzles me you seem to take a decidedly non-scientific approach to deciding on the

52:33 potential for Science Now based on that model it seems like a lot of your Investments would be theranists type Investments yeah we turned out there and us pretty early so so we have a pretty good network of scientists run stuff by so did we not act in a vacuum like I'm acting in a vacuum when I'm deciding to do there but when I'm making you know the science nest of

53:06 their you know spigisado who's you know was CSO applies and idac president of Burdock vertex Jeff Bluestem you know from here Tom Daniel president of Celgene Mark Davis from Stanford Emilio amini from The Gates Foundation he used to run infectious Merck Larry Corey who is head of yavi and and and head of the hutch and you know

53:38 good merger merger of infectious disease so kind of and then Phil sharp to you know I called Phil and George called film it's like you know why do you want me to do an infectious disease company and it's kind of like you're really smart you know part of the problem with infectious disease we need you know some orthogonal views to come in to challenge the existing dog list which I believe is always important in these things so you can't just

54:08 you need to mix it up a little bit to get creative so I mean I probably have 20 Nobel Prize winners cell phones you know I don't pay any of them ever Consulting fees so so I you know sometimes I pay them in wine if they me long enough so but basically you know and the reason I we do that intentionally we don't have a paid scientific Advisory Board you know we do that intentionally so the bar is

54:38 really high right if you call a Nobel prizer and say you know I want you to do this for free and they're used to getting five thousand dollars an hour or something right they have to think that it's cool science and then so it's an opt-in kind of thing and it's a way of testing out you know how crazy is the idea but sometimes it's just you just need to have orthogonal other science code mix up the science

55:07 because people are kind of hanging out with each other too much what about the valuation then you're you're sinking a certain amount of money you must have some scientific calculation to decide what the value yeah well I can attest to this it's and we just make it up as we go and and it's it's valuations are are actually not the issue it's it's option Theory again that's the issue how much do I own how big is it going to be

55:39 that's all you need to know and and what's the probability of that and and so so what you don't want to do is Miss the ones that are big so I'm actually willing to pay up in later in deals that I think are going to be really big that I missed because there are only going to be let's call it I don't know let's say there's five deals that matter in the world per year it's probably about right matter I mean

56:09 that are going to be big and transforming and maybe it's one I don't know but it's it's not very meaning and you need to kind of be in some of those or else you don't make excess returns and and so you can you know that's from the financial side from the transforming side you know it's just following the the clinical problems and and so about half of our stuff is invention based right and then we need to check like is

56:36 it going to work so somebody came and pitched me a deal and was started by another venture capitalist it was really good they came in and said hey I've got this Gene editing thing they could do in Vivo High Fidelity Gene editing not Christopher cast today I was like okay almost you know if it works all of us five minute investment decision I said that five minutes into the conversation and you know and then we you know and

57:04 it had been validated in two Labs outside of that lab now you know do you have Partners you have to take things in front of yeah then I called Steve Gillis and said can you make sure this works and like you know and like he's way smarter than me and then he went in and like like made sure that it worked right but but there's a certain amount of of you know it has to be good science right

57:33 so I would say interestingly the thing that we fail the least at relative to even to other firms is picking the good signs we're probably 19 out of 20 18 out of 20. in terms of picking science that works even Ireland is that because you surround yourself with the kinds of people that you just described It's a combination of picking the right platforms so and yeah and picking the right people so a lot of times you're betting on a

58:01 scientist because the individual data that you might not that you may be betting on a certain set of data that they have but in reality it's a flow over four or five years that's gonna and it may be year three that they come up with the really cool thing that's the way and so the company I'm creating right now is one of those where it's kind of really cool really cool we backed them in a deal that

58:26 failed then we backed them in a deal that succeeded and then he came up with this new thing and you know it was a little bit of you know enough data to go wow that's really really cool and if you could do these two other things you know then it would be super cool and can you do that and you know it's about I don't it could be wrong so we're willing to take that risk I

58:54 think a lot of other people were not willing to take it and and we'll see if we're right or not but so there's real scientific risk in some of these ones that we bet on it's a bet how important are the relationships with the individuals versus just the raw signs would you take raw science from people you don't know at all and figure out you can make that work I think it's a trust but verify thing so the the one the other Gene I

59:21 didn't think was the person that wasn't really well known and so the other BC that was involved had it replicated in two Labs before they wrote the check so there's a certain amount of you know if you're you know a young graduate student it kind of depends on pedigree depends on who's and you know we'll definitely look at you know all the way down into lab notebooks and and making sure that it's it's real we have back

59:51 it's a couple things where you know it wasn't real like it was not real and and that was interesting we were super nice about it we didn't like insist on you know flailing them in public but you know they were just you know retractions happened and not through it okay over there I see a lot more sort of traditional Tech VC getting involved in biotech there's a single develop an appetite for it do you think that's

60:23 fundamentally misguide on their part and also maybe from the entrepreneur's standpoint to take their money and if they're doing something right or wrong what do you feel they're doing whatever across well I think it's always a question of Alternatives right I mean I mean somebody's going to give you money and nobody else will give you money then I would take that much so but you know I think it it depends what the deal is I think

60:49 basically what happens that you know there's two things that are driving that one is there are a lot of advances in data and you know if you say the word you know kind of machine learning big data and Healthcare you can get funded today say them in the right order you know to the right door you need to whisper it into the little box and then so I don't and the other thing is the Aging of Rich tech people right so and

61:21 the Aging is a relative thing could be 28 year olds turning 32 and realizing that one of their relatives got sick or that they just want to live a long time or it could be you know 50 year old you know deciding that they are going to live forever so I think it's all those things converging I think it's a good thing generally and you know we've we've reached out to and have co-invested with some of

61:48 those folks I think they have something to add to some deals some some things are just Observers okay they're just learning about like you know gee what's the FDA how come you can't do this you know and and all that kind of stuff but I I kind of like the the thing I like about outside of pure Therapeutics where they definitely have less to add you know in

62:19 some of the health care things you know they ask really hard questions like you know what a up system we have today why do we have that system go try to talk to your doctor about preventive health they just look at you like what the hell are you talking about just lose weight your blood pressure should be lower see you in you know when you're set and and so I like the tech VCS kind of asking

62:47 the very difficult questions about the system why things aren't do you touch that digital Health Arena yeah so like with Grail and other things so we're we're quite interested we have a company called holiday that's kind of ACO but we're not not as much like Ben Roth or somebody who would you know kind of go really long and sort of the same although lately we've been thinking about screwed up the system as and whether

63:18 there's you know ways of making it better better this lady I'm going to repeat that because I'm not sure the back heard it what what does he think about exit strategies timing IPO conditions so I think it's it's back to the optionality thing so what I want to do is be able to control that completely inside so and you know that's hard to do and

63:50 very few companies can do that so I want to you know walk into the investment bankers and tell them we're going public here's our here's our range and here's our book and do you guys want to do it and we have done that works it's difficult you know so you have done pretty strong internal Syndicate to be able to come up with that kind of money in advance but all of the big companies that we have I

64:21 want the ability to do that inside I think IPOs are fine as long as you have your long-term shareholder base right so if you have a shareholder base we have in our private companies and they maintain the public shareholder base it's going to be really stable and long-term thinking doesn't mean you're not going to be subject to you know shorts coming in and you know if you if you have a clinical failure your Stock's going to go 50 but it doesn't matter the

64:48 long term kind of is is is baked in there so I don't mind we don't mind selling companies as long as for a lot of money right so we're not you know we're not in the business to sell companies for three or four hundred million dollars and and really declare Victory I mean that you know we do do that it's not necessarily a bad thing but it's not our goal our goal is to hit it out

65:16 of the park on every single deal we don't try to balance the portfolio we don't try to kind of do some things that are less risky just invest in cool stuff and just keep investing in cool stuff that's really the house in terms of to go out I don't think anybody knows that so anybody tells you they know that it's including investment bankers or anybody else right they don't know I mean there's I have this one deal on the

65:45 road once and so we're kind of almost ready to go like on the road show in a week or two and they're like okay you know Windows gonna be open for another couple months it's getting a little bit choppy out there and then we have these calls every few days right getting ready and and so we have another call later and they're like oh you know it's really getting choppy out there the window May close and you know just a

66:12 week or 10 days we better get on the road two or three days later Market goes down another six seven percent and they're like oh you know the windows actually closed and it closed two weeks ago so who knew right so the best bangers are very good at reading the data after it's happened and so and so I think you know you need to have your your they don't raise money for you you raise the money that's the thing

66:42 there's this idea that somehow investment bankers go out and raise the money for you they're facilitators of you getting to the right people to make your pitch but you make the pitch and you raise the money and and that doesn't mean that there are no differences investment bankers there are in terms of their Network and access and positioning and how they think about it and how long term they're thinking what the hell that is it's not an

67:11 earthquake or a protesters outside but any case I think you have to be careful because when the you know the musical chairs game right when the party stops like you better have a plan because everybody else is going to be running for the chairs and so there's like you know today you know if there's a war in North Korea or something or pick your event

67:43 and the money dried up there's you know more companies chasing the money there is money and somebody loses so you don't want to do that you know you always need to be contingency planning for that at the same time you have to play offense so you can't just play defense and there are some of these companies are just like you know so defensive that they actually never do the experiments to generate the data to create the value right they're just kind

68:12 of almost hoarding their cash and and so and they end up living with the probability one product and you know the good thing about one product that works is you you get receptos in yourself for 7.8 billion and the bad thing about one product is you know sometimes it doesn't work we have plenty of examples for it you know it goes to zero and if you don't have a portfolio or something a bunch of wow okay I'm gonna give

68:43 everybody numbers so one two three four okay you remember your number let's go one all right so when you mentioned MTV a few times the Vintage of your funds and the amount of time that you'd be put in your Port Coast is that simple different or similar in relation to your investing in style and on top of that taking a

69:13 crossover I don't think we we don't really think in our are we thinking cash on cash okay good and we don't actually care about irr at all some of our limited partners don't like it when we say that because our bonuses are based on our so but we were just cash on cash flingers so when I think of like a good fun I want to make a 3X or better cash in cash and and so and I think to

69:42 do that you know this is all the modeling I need right I just think okay you know some of the companies need to make a 10x to 20th and if I have a few of those you know then and I have a reasonable amount of money in those that I'm probably going to do and I can take you know 20 losses and so you know people are like oh what's the percentage I don't know probably five out of 10 succeed

70:15 reasonably well to crater and you know one or you know of the five maybe one or two hit it out and but some funds I mean we had one fund where we would turn 35 cents on the dollar it sucks that's it matter of fact I had this one meeting when I was fundraising because I started with that and I said you know here's I start fundraising by going through our errors and so I kind of said you know here's

70:47 what we up here are the three things we've screwed up over like 20 30 years and and they said yeah I said that's one of the worst like here period in like 96 to 2003 is one of the worst records we've seen in Vendor capital I was like yep it sure is and and you know if it was was a non-systematic error that would really suck we know what we did and we cracked it and so that's what you we

71:21 did a bunch of Internet investing turns out so it turns out like if you want an algorithm to lose money in the internet you take our algorithm which was it's Technology based so it has to be a fundamental platform technology and it's a milestone base so you don't want to put two in your eye drop ring the money in and you don't know anything about markets which you know

71:51 so so if you put all those things together we actually lost money in something like in in 99 you know 99 to 2001. something like 17 out of 19 deals in an era where you had to be an idiot not to make money on the internet I mean you know you you could just randomly back some 25 year old and there are Partners at Sand Hill Road firms who kind of you know randomly back some 25

72:20 year old made their career and that was the only deal you know I mean they got one deal you can make your own assumptions about what that means but but but you know we we systematically chose an algorithm which I think if you applied that album of the day with it also not work and so so you know with maybe a few exceptions and then we're really good at semiconductor deals it turns out you just can't make money in

72:48 semiconductor deals so we took us about 20 years to figure out hey you know we're pretty good at this but like the outcome just sucks so so let's not do that anymore and so that's how we ended up most of the time all right number two as a VC do you believe the valley of death is real or really promising discover has happened in the University lab and they don't Advance because people like you consider too risky and

73:15 the final company is considered too risky or it's just a matter of scientists thinking their research is better than it really is I mean it's a combination of all of those things right so I do think that there's very interesting research at universities that does not get kind of that 50 to 250k and I actually think that's more of a universally institutional problem than than it is a venture capital problem I mean you can take that money

73:45 from Angels or other you know you can get it from philanthropy I think Venture philanthropy is a good way to get that kind of money to to be able to and a lot of times the the academics don't know what question to answer so we go through universities all the time just telling them like here's the question you really need to answer here's the value inflection point that's incredibly valuable because they don't know what it is

74:11 usually and and then once you know what it is you can decide okay then I have to just change what I'm doing or this data is a lot more important than some other piece of data to get outside Venture money but the universities need to have these pools of kind of I think discretionary kind of slush fund money maybe it's controlled by a few people not big committees not peer-reviewed I think one of the biggest problems with

74:39 these and I think at the NIH level that also needs to change so I think you know there needs to be a section of the NIH that is less peer-reviewed so you don't already have to cook Data before you go in I cook the data but I mean experimented so so basically you know it's more like DARPA where there's you know maybe it's up to a million dollars can be just done at the

75:10 discretion of somebody who isn't going to be an NIH for life and so that you get some of these young investigators or even old investigators with a crazy idea I mean I've had something like just a across the spectrum of kind of age and experience people come with some orthogonal idea that very much is worthy of being funded that that in the case of icaria got funded by

75:42 the director so I carry it actually I asked Lee Hartwell a question which I knew he would hate and think was stupid which is who's the smartest person and like that's an important you know impossible stupid question to answer but I I was trying to get a list right so he said well that's a stupid question you know you should go talk to Mark Roth and I was like okay great good talk to Mark and Mark was doing

76:14 suspended animation of zebrafish by using wrote known to kill mitochondria basically you can suspend a zebrafish indefinitely basically just stop them and that's pretty cool so we we you know so Lee gave him some money I think is not very much 100K or something because I said you know what you really need to do is do that the mouse like zebrafish you can do all kinds of weird that zebrafish you know freeze them in your

76:45 freezer and undom and they live and you know stuff but but you know Mouse like that's harder and so so a couple years later I mean we kept in touch a couple years later he's like okay you guys see this so he you know figured out using hydrogen sulfide that you could suspend the mouse like you could make an animal a poison you give them the stuff and you just watch them they slow down the temperature drops to 15 degrees C they

77:15 have you know one respiration a minute heartbeat goes to ten and they sit there indefinitely and then you turn them back on they run around and as Mark says do what mice do and so that's pretty cool so we decided to fund I carry it based on that having no idea what the therapeutic would be like what the hell we would do although we did know that if you take a a Montana

77:46 ground squirrel and you hibernate it and then you know somebody did this experiment which is not a very good one so let's just say that you yeah wow the ground squirrel is hibernating you put a needle in it spring and then take it out and you know when they're they're functional so there's a lot less damage to a Montana ground squirrel where they're hibernating so the question is hey you know would that you know if you could induce

78:17 this state you know would it be good for surgery or other things and it turns out that the benefit of inducing the state can be done without hibernation and that was cool like when we figured that out I was like okay we have a drug company because we could induce benefit you know without actually putting you to sleep and and so and there's all kinds of cool things you know I mean if you do a hypothalamic shock model

78:47 you can get you know survival and models where you have 100 death rate in the control group and you know 80 of these mice where you know you you basically it's kind of a nasty experiment I won't describe it but let's say you know normally it's it's called it's a battlefield wound simulation and and and so you know you can have all kinds of interesting therapeutic effects and so then we put more money in the company

79:13 and you're at the exception no no one would do this deal no one everybody thought it was crazy and then you know I I pitched to Brian Roberts after we had seeded it and I think Brian you know did it because he thought it was you know cool and and you know so but I think most people would would not have touched that with a yeah

79:43 okay number three where's number three so since most startups here do not start with our adventures with multiple Nobel laureates and 10 million dollars but rather a couple graduate students and a professor and 750 000 could you talk about the transition of the skill sets that are needed in that first phase and then as you move on I think the figuring out what the value inflection Milestone is is super important what question are you trying to answer

80:16 and is it a question that anybody gives a about that's what Stephanie's classes do so startup and things like that you you but it's important and often those are those are both scientific questions but they're also kind of related to what other people have seen right or what they're skeptical about so you know if you're playing in the you know if you think you have an in Vivo Gene editing technology you better have some you know you know something

80:46 that that shows that it really actually works in Vivo or figure out the experiment in vitro that's going to convince you that you know that data could be real and it's a big enough thing so I think figuring out and that would be good to get other people's advice who are not you right so so whether it's somebody in kind of that's done it before or a business development person in Pharma or somebody who has some perspective on

81:18 G you know we've seen 20 of those you know I don't believe it but if you could do this you know then you know I had a guy once we started a company in the with a woman named Angie Belcher Who can make all kinds of cool things out of phage and and they it turns out it's good for catalysts Carl knows this company and and so we did comedy Trail

81:51 callus Discovery with it we said oh what's the biggest problem in cotels is that and and so it's awesome coupling of methane making C1 to C2 and if you may see two then you can make C4 and they're like well and so so and we're like oh okay you know we don't know anything about to tell us but that sounds cool so I call my friend who helped me to be running Lindy at the time it's the largest gas company he said oh

82:16 that's interesting you know we've had you know 50 German Engineers working on that problem for 20 years and there's no way you're gonna solve that and you're out of your mind so don't do that so we did it anyway and two years later Lindy invested in the company because at least we had like the he's like and here's the data you I said you just humor me like what would you need to see you know and and so I think

82:41 that's the kind of thing where you need to figure out exactly the minimum amount of dollars that you can put to a problem to create the data that is is not necessarily going to be publication day but it's not going to be FDA data this drive science is crazy or clinical people crazy I just want to know if it works in humans like for instance if you're it's a clinical question I just want to know if it works

83:06 as an investor it doesn't have to be a bomb proof phase two trial I don't even have to I don't care if you repeat the phase two trial I'll take it to Australia put in 10 patients and see like doesn't work it doesn't even have to work to a p-value of you know whatever but I just want to know kind of directionally if or or another question is does it not work like are we wasting our time

83:30 so in a smaller lab sense I think you just have to figure out like in in the in the scale of the problem that you're trying to solve you know where are you relative to the rest of the world so will you fund that first 100K to find out if it works like 50k and stuff you know but it just has to it has to be an interesting problem of course so you know it was the Mark Roth

83:55 problem that still intrigues me so we ended up selling that company for two billion dollars because we bought some other gas technology that turned out to be valuable the management team didn't know what to do with the existing technology they kicked it back to us we started a new company called Faraday doing the same thing and then discovered some other cooler stuff that we ended up working on that company is like close to the clinic now

84:20 but so I think if it's an interesting scientific and high impact I think the main thing is in high impact now all companies don't have to go cure every seat right some companies are just going to do some cool thing along the way and those things can get funded we may or may not find those but but there's a lot of people out there who who are interested in funding things that they can sell for 300 million

84:44 dollars that only take you know 10 or 20 million or you know 30 you know they'll do them and doesn't mean we wouldn't it just means that our bar is high number four so I guess there's a follow-up on one of the things I mentioned before like where do these deals come from for you because you've actually funded and then I guess secondly can you talk about the importance of the relationship that you do have with these teams and these

85:12 companies as they progress as accomplished so the question is repeating where the deals come from and what about the relationship with the teams and the companies so the the people I would say Christina Burrough who's my partner here in San Francisco and I were laughing the other day because we were in this presentation and we're saying wow when's the last time we actually were in a presentation together where a company was pitching with PowerPoint we couldn't

85:44 remember it and that I mean could have been 10 years so like it's not like Sandhill Road where there's a bunch of people coming through so we're much more likely to have phone calls with scientists and maybe they're walking through a deck of science but it's it's not usually companies every once while it's companies like we just we took a meeting you know so I found out about a deal

86:14 a week ago or 10 days ago I took a meeting sent two guys out there two days later I committed 25 million total turn around six days but that's rare so but but I do think the relationships like I talk to Geno guys four times a week three or four times a week public company so there's a lot of relationship there

86:47 and a lot of involvement from from our side it's not a passive I'm surprised actually on the tech side is totally different and then in the tech world it's like you back a person and you let them run with it and in spite of their flaws or whatever they might be you know perfect you kind of made your bet Tech it's a lot more money like I was meeting with one of the bigger Tech VCS and there's like man

87:19 these tears money in these deals like India and they're not just us I mean all but it's a lot of money so it's a different level you came back you're usually not back in kind of a 22 year old graduate student although sometimes you will and then you make a part of something bigger or you know help build it so we're not averse to that but a lot of times it may be it's two or three

87:41 things come together to be one thing and and the relationships matter because you're just having to people have to trust that you're going to figure out a way to look out for their interests as well as your own interests and I think that we're pretty good at that you know I think venture capital in general is not particularly known for that right so we kind of figured out a long time ago that other people didn't make money

88:05 then they're less likely to tell their friends to bring cool ideas to us so at universities as well so we don't we're not trying to constantly trying to screw the university because like then you know they tend not to bring us other things so and conversely universities tend to bring us really cool stuff when they know about it because they know that we're not going to screw up there's a lot of under Venture capitalists really do spend a lot of time trying to

88:28 like minimize everybody else's plan I'm kind of the viewer where like I just look at my own pie I want to make a lot of money so I don't care if other people make a lot you know I want other people to make a lot of money and so but you know that's an education process that scientists scientists as you know selling in the return like it's a foreign thing right they just don't want to be taken

88:53 advantage of and they want to be rewarded if it works and more importantly and the thing I learned at University Chicago very early on which is you do not want their competitor to make money that really drives me nuts so so like the hated you know the only way I got people at University of Chicago to literally the chairman of Immunology said that he thought patenting was unethical and and that that if his faculty spend money on patents I mean

89:24 spent time on patents to the detriment of their scientific work that should impact their tenure decision until he invented something about like it was very shortly after that like six months later and he's like I don't want to pound it I'm like really and I kind of forgot who it was somebody at at Harvard you know I'm like huh my guys worked in the same area a bunch of heat pounds it and then it was immediately like changed

89:50 his entire world view he's like well he can't do that I'm like screaming it's gonna copy your stuff and then he's going to take credit for it and then he's going to make money off your stuff and it's going to drive you crazy and then he changes his mind totally as well you know so what are the next hot areas that you're thinking about no you know we're very active kind of in gene editing ish of every flavor

90:16 because it's really cool oh nobody's yeah figure it out I mean money out of it we have a really cool company called egassist which is working in xenotransplantation so they have you know they're editing picks to be able to do human you know to be able to transplant organs into humans so they've already created the most Gene edited mammal on the planet they also have the same team as doing

90:47 the woolly mammoth as well as well and hopefully they'll do the full emails in spare time and then so that's kind of cool and we're very I guess infectious because I've seen kind of interested in in an alternative approaches to healthcare delivery and thinking about the whole system and

91:18 how screwed it up and how screwed up it is so you know figuring out ways of using data to change to make things more preventive and or to discover things in a more rapid manner let's see what else and they are always just cool orthogonal things that come our way so usually what we get is just somebody that knows somebody

91:49 sounds of something you know and and then it correlates through the we need to send it out amongst the group we usually want non-confidential information unless it's you know somebody we know who says you know I have a secret you know I can't hear it and and and then sometimes we'll sign an MBA but it has to we have to kind of know what it is for signing and often with the universities we do if it's something novel and orthogonal

92:22 and sometimes it's just something you know it's there oh I've got a new car T Cell idea of like right you know you should talk to Chino we you know introduce them and and they you know have a sometimes even if it's competing we have a you know there are ways to have those conversations in a way that you know we're we're buying a company this week where you know the person was absolutely sure they wanted

92:49 to do new code they'd already taken 20 million dollars it was the best thing to do blah blah blah blah you know no it's like you should you know you should do it a different way and we can create a synthetic structure that gets you all the things you need plus you have scientific control and and if you you know every company everything you do does not have to be a newcomer so you both want to test the hypothesis

93:19 of doing a new call and believe in what your idea you also can think about you know align with other people and not having to reinvent the wheel and still they're they're kind of some novel structures now to be able to kind of simulate you know if you're sucked into the board you don't necessarily have to be you know part of the board so we've done things like we've done a couple of these actually in Via where we're putting

93:49 we make a subsidiary so like you get your own playground and and some money and off you but you're still part of a bigger and so you create both the downside protection which is you have stock in a more certain thing and then some upside incentive that basically says hey if your stuff works you know you get an extra kicker in cash or stop whatever you want so that kind of is there are ways to

94:21 deal with that but you know every Professor every graduate student every like wannabe graduate student has to start a company and in the internet you know I was I was riding on the plane with somebody who's a like a senior BP at salesforcement that was just like my daughter starting her second company I was like oh really how old she is like 12. I was like you've got everything like actually like if she's got a term

94:45 sheet for her actual Venture Capital term sheet at 12 for her second company wow and I was like that's not going to happen in biotech you know it's just unlikely so the the capital requirements are high and if you're in if you're in Diagnostics or you have tools or you have some widget or analysis that can be a much lower barrier to entry but if you're making a therapeutic you know it's going to take money and

95:15 you'll look at Diagnostics and tools and yeah we look at all kinds of weird stuff we look at you know computational machine learning crazy things you know at some point like 20 years from now most or maybe it's 50 but at some point drugs are going to be discovered in computers that doesn't mean that there won't cellular assays and all kinds of other stuff but like a lot of it's going to

95:48 happen there and and that you know and it's more likely going to be hey and Healthcare is going to look like I think I get in trouble and this is where I get over my skis in science but I think I'm right so I was having this argument with Jose that who's the physician in Chief of Sloan Kettering and he's a smart dude I'm like okay here's what's going to happen Jose and he's like we'd had some wine

96:12 so I think we're gonna add a preventive disease within five five to ten years so you're going to come in we're going to look at your circulating you know factors whatever methylation or whatever pick your pleasure of what it might be and I'm going to tell you you have seven of the eight real drivers for pancreatic cancer

96:46 and you know if it's me of like hey you know I don't really want the haze you know I can wait around and then I'll have stage zero or stage one pancreatic cancer which is still quite curable generally would suck so what if we took the sixth factor and edit it out edit it back right so you go from a 98 risk to a one percent and if you could isolate that to the pancreas why not right I think that will

97:15 happen so I think we'll be treating pre-disease you know so if you think about that if you're a pharmaceutical company and everything gets diagnosed early I was having this so I had this conversation with two different CEOs of top five farmers and one got it and one didn't get it and one is like I don't understand this Grail thing like it seems like you know pan cancer screening like I don't understand why that's gonna matter I'm like okay you're an oncology

97:43 company I need to ask Matt or you're totally if everything is diagnosed that stays zero right like you sell drugs for stage four okay like you can't figure that out and I swear to God they're like oh it's way out there you know I don't know it's like if I was in that business I would put like 10 people figuring out like if there's any probability of this happening it's gonna fundamentally you know that's Polaroid over here and the other people are like

98:09 okay I want to write you a check for 225 million dollars so I'm like first of all you're my friend and and second of all you must have Vision right but but you know that's super interesting because this company absolutely understands that that it fundamentally changes everything if you can go to early diagnosis and then you start thinking like okay is it going to be conventional therapies that treat Things Early that exist today which may

98:39 be maybe just need surgery and radiation or something if you're in oncology but or maybe it's something entirely different like maybe if you're in Psych if you can identify you know a driver mutation like in some of my relatives we know what it is unpublished it's in you know because we have it's just an interesting databases you know it can snip it out you know would you do and and so that's where it gets it's going

99:09 to get really interesting you know treatment of pre-disease treatment of risk factors as a big debate actually at this conference I was at recently which had mostly tech people Bank was is do humans have to edit themselves to be smarter to keep up with AI to just kind of dominance and kill us and so there's a certain amount of probably weed being smoked at this meeting but but if you you know it is is

99:43 really interesting because everybody says oh you know it's terrible to we're in Ted and they last week and they threw this thing up so this is okay to Gene edit Amber nose to make things smart and or you know to select attributes and like you know most of the tab people who are technicals like no it's not okay and I said you mean you selected your wife based on

100:13 no attributes of physical beauty or intelligence or anything else they're like well that's not the same I think really no because it kind of is and it turns out Chinese are already doing that if you look it is out of the bags happening today like you know there there's very sophisticated analysis of embryos happening my own view is it doesn't matter because it's going to be a bell-shaped curve again you can think you're picking the smartest person but the randomness

100:43 is you know it's going to be this and everybody's going to pick different stuff but I think we're going to be in the realm of these Technologies rapidly going into Data driven treatment of pre-disease you know and treatment of things way outside of cancer that we didn't think so the pharmaceutical business is going to look entirely different 20 50 years from now than it will today and and I know that you asked me earlier I don't go to conferences I don't listen

101:14 to Pharma because I'm not supposed to think about things that they're already thinking about right that's the idea of you know this doesn't mean I'm not going to think about the signs but I don't I want to think about the graduate student in the back of the room who has this crazy orthogonal idea or I want to think about the famous person who is super smart who really is four or five standard deviations

101:45 who has you know figured out how to do nucleotide editing or whatever and then and it turns out like there is very much a 99 one it may be 99.991 but there's a disproportionate impact of some really smart people on on this area right so and and it is not you cannot just go down the list of degrees and stuff so it really is

102:16 hard to figure out where they are if you go into the head of the departments at UCSF and say who are the smartest people here they know who they are right and they they don't they may not be even people with the most grants or somebody might have just gotten a couple graphs you know rejected but there's they have some orthogonal way of looking at something or they're the Mark Roth of the group where they have they made a

102:43 career in one area but now they're thinking about a new area in a different way and that's where the really cool stuff comes and and you have to be kind of open-minded to that at least I think we sort of need to stop here but just to pull a couple of themes out that are orthogonal ways of looking at problems get it out of the sort of herd mentality and go try something completely new don't send in your business plan on a

103:12 website it's knowing someone who knows someone who gets connected to you so it's all about relationships and that you truly are one of the few VCS will take risks around here so that Sandhill crab doesn't like to do what you do no they might you know there's like some of the you know I think angels are are worth talking to just to realize what I always tell people about Angel Investing is this create flexibility in your fine

103:44 so take it as a bridge make sure that you don't bake in some wacky High evaluation that is going to prevent me from you know I just won't do it right so so you'll have to figure out like but it's really easy to get you know stars and drives so you have to figure out a way to approach these things in a way that's flexible enough but you know if you need some money to like reduce stuff practice

104:08 or just get up and going and take the money but do it with a cap or a convertible or some sensible structure where you have it kind of priced yourself out of the market okay well on that thought we're going to thank Bob for coming and speaking with us today