Ep146: Jeff Huber on Life in Tech and Biotech

Welcome to the long run. This is a podcast for biotech adventurers. I'm your host, Luke Timmerman. Today's guest is Jeff Huber. He's the co founder and general partner at Triatomic Capital. It's a relatively new venture fund that seeks to back century defining businesses in engineered biology, new materials, next gen compute, new energy and automated economy. Jeff and his partners are looking at startups that collect and analyze data to address big challenges of the 21st century where deep learning artificial intelligence could be useful. Jeff was the founding CEO of Grail, the company that sequences DNA from blood samples to detect early signs of for 50 different types of cancer. Before that, he had a long and storied career in Silicon Valley, including 15 years at Google. Jeff has his fingerprints all over some of the most common apps that Google developed in those rapid growth years and which are now used by people around the world every day. Jeff has certainly come a long way. He grew up on a family farm in northwest Illinois, about 20 miles away from where I grew up. I had no idea we had this much in common until we were hiking together on the trails of the Himalayas in 2022 on a fundraising expedition for the Fred Hutchinson Cancer Center. In this conversation, Jeff expanded on some of those early life experiences and how they affected his life and career trajectory. Part of Jeff's story involves personal tragedy. His first wife, Laura died of cancer in 2015. This experience was part of what motivated him to work on Grail to help more people detect cancer earlier. Although we didn't discuss it during this conversation, I should note that Jeff is now happily remarried and has a blended family. I asked some about his oldest daughter, Grace because I got to know her on that same expedition in Nepal. This conversation ran a bit longer than usual, but I think it will be absorbing for people thinking about the intersection of tech and biotech, where so much potential for innovation resides. Now please join me and Jeff Huber on the long run. Jeff Huber, welcome to the long run.

Thank you very much Luke. I'm very excited. I'm a first time podcastee, so looking forward to this.

All right, well, not a first time listener, I know that much. Well, you know Jeff, as you know, I like to start these podcasts with a bit about the person and where they come from and I happen to know your story. We have a lot in common here. So tell our listeners about northwestern Illinois.

Indeed, Sue. I grew up in the very corner of Illinois, the northwest corner. My family home was about three miles from Iowa and about 50ft from Wisconsin. In fact, the road that I grew up on, it was a gravel road, was the state line between Illinois and Wisconsin. And it is a neighborhood that I know you know well, because I think we grew up about 10 or 15 miles away from each other.

Yeah. Yeah. I discovered this of all in. Of all places, the Himalayas, which we could get to later. But. So what was it like growing up on a farm in northwestern Illinois? What. What did your family do? Sure.

So I grew up on a small farm. It was about 150 acres, which is very modest in the scheme of things. And it was a very democratic farm. We did a little bit of everything, but primarily dairy, but also beef, cattle and crops and hogs and chickens. It was a great place to grow up. But I relatively, early on in life, figured out that it was not the future that I wanted to have. So it was very motivating to go out and explore the world and see if there were other things possible.

Now, Jeff, why do you say it was a great place to grow up? What kinds of things did you learn or were instilled in that way of life?

So I think growing up on a farm, you quickly learn responsibility because you're, as a farmer, you're completely accountable for results. There's nobody else that you can look to that's going to do the job or nobody else that you can blame, other than perhaps the weather. So you get from an early age a very strong sense of accountability. And I think that was amplified being on a dairy farm, because with a dairy farm and with cows, you were milking the cows twice a day every day, whether you want to or not, the cows don't take vacation. And in fact, my father, from a very young age, he became kind of the head of a household. When his father passed away when he was young, and from when he was 14 years old until he retired in his late 60s, he was never away from the farm for more than a day because of that responsibility.

Yeah. Yeah, that very much resonates with me. Although we did not have dairy. We had beef and hogs. But the same thing applies. They need to be fed and cleaned up after. And it doesn't matter if it's 20 below zero in the winter or 95 degrees and humid in the summer, you have a job to do.

Yeah. Although dairy farmers would say that was. You were doing hobby farming.

Yeah, I know. Oh, I know. Well, so when did things turn for you? Like, you kind of realized that there's. There's this wider world out there that you wanted to explore and and learn something different.

Sure. So I had the, the good fortune of having kind of role models and mentors as I was growing up. I have a, a brother that is 14 years older than me. I'm the youngest of five. So I have two brothers, two sisters. And my older brother in particular was kind of the vanguard of exploring life beyond the farm and beyond the immediate area. And then I also had an uncle who was lived in Chicago which was three hours away and very exotic as a kid of the big city. And they were both instrumental on kind of helping me understand possibilities beyond. And, and I also got just kind of flat out lucky in timing and opportunity where I was in part inspired by my brother and uncle, was interested in computers and then had a godfather that, that unfortunately passed away, but left as part of that a little bit of money for me actually through my parents. And at basically 13 years old, I lobbied that a good use of that money would be buying a computer. Specifically an Apple II computer.

Okay, now what years are we talking here?

You know, I'm bad at time. That was like 1982, 83, Apple II.

Okay, so this was the first one that was kind of becoming popular in schools.

Yeah. So around those years, an Apple II plus very specifically 48k of RAM, entirely uppercase only typing experience. And you usually hooked it up to a TV monitor that gave you, you know, 40 columns of text for doing things. So after successfully lobbying to get that computer, I then kind of self taught of how to do things with it and a little bit of demonstration that of my latent engineering interests. One of the first things I did was take a soldering iron to it because there was a modification where you could make it tight both lowercase and uppercase. So I ended up soldering in the, the, the lowercase mod to soup up my, my Apple II plus computer, which frightened my parents that a 13 year old with a soldering gun was getting in the guts of the, the then quite expensive computer. They were about probably $3,000 for the whole setup by the time we were done.

They were worried you'd fry this or ruin the TV or something like that.

Right.

Okay, so but what was it about the computer that intrigued you?

So you could see already then that was the 1980s and I mentioned kind of brother and uncle and they were working in the financial industry. Not a terribly sexy corner of it. They were both accountants. But they would describe how their business and their industry had been changed already by computers in the early 1980s compared to how things had been done just a short Time before, and I became just really excited about the future of computing. And my dream quickly became that I wanted to design the next generation of computers that would just keep increasing those capabilities. And then the other side of it, pragmatically, is growing up on the farm. There are some people who are born to be farmers and some who aren't, and it's a very noble profession. But I pretty quickly decided that it wasn't for me because if I, if I continue doing it, essentially my future was filled with cow poop. And that was dramatically demonstrated to me. There was one time I was, it was springtime, and I think I was 13. And if you've grown up at a farm, you know the phenomena of cow yards, which is where all of the animals collect to, to feed. They produce prodigious amounts of byproduct from that. And particularly in the springtime, when you get the spring rains, sort of the cow yard turns into a, a thick soup. And there was one time where I had to cross the cow yard to go let the cows out on the other side. And I was wearing my, my rubber boots. And I got about halfway across the cow yard when I got literally kind of stuck. And my boots were, were stuck in the muck and, and wouldn't pull out. And I remember very vividly thinking in that moment that, you know, I see my future and it's filled with cow poop and, and there's got to be a better way. And the cows were there looking at me not very sympathetically. It was like, yeah, there's, there is another future.

Hopefully I'm getting this visual now because you could slide your feet out of the rubber boots. But then, of course, you've got to step in everything around there, which you don't want to do. So how did you get out?

I, I, I, I finally sort of wiggled enough to get them maneuvered out and got to a slightly safer place. But no, it was a, a moment of clarity.

Yeah.

Did.

Now, what kind of school did you attend and what kind of student were you at school?

Oh, okay. So I think in the scheme of things, I was a, a pretty good student, a fairly precocious student. I had a little bit, the benefit of being youngest of five and having older siblings mentioned my older brother, but also two older sisters and a mother who was a schoolteacher. So I was kind of on the, when my other older siblings were bored, they would teach me stuff. So I had a little bit of a head start and then kind of a nice foundation with my mother being A schoolteacher. So did well throughout school, high school. I ended up going to the nearest town of any sizable note. You probably have been to Dubuque, Iowa. So I went to high school at a college prep school there, which was a big, A big shift because my grade school graduate graduating class was 12 kids. And then I went to the prep school there, which was over 400 kids in the class.

Was that Waller High School?

It was. It wasn't neat.

Yeah.

There were more than a few Timmermans there.

Yeah, well, that's actually where my dad went to high school and I used to write for the Dubuque Telegraph Herald. Little known fact during my high school and college years. Yeah. So you were obviously pretty good student and you had this hobby here with the computer. You decide to go back to the University of Illinois. Were you thinking that you would study computers there from the beginning?

From the very beginning? Yeah. No, in fact, the program and it was kind of serendipity of I was very interested in computers and had kind of laid out a personal vision of I wanted to design the next generation of computers and, and ultimately supercomputers without having any knowledge whatsoever of what that meant. But, but it turned that.

What was that place like that computer science department at Illinois that you encountered there?

Yeah, no, I got, I got incredibly lucky or was fortunate that kind of in not exactly in my backyard, it was five hours away, but in the state there was a world class university that. Yeah, just I was lucky enough ended up being the, the intersection of an amazing place, but that also I could afford to go.

Yeah. In state tuition.

In state tuition. I. I think it was my, my freshman year tuition was I think $1,300, which was fantastic.

And you get to go to a department that had. Was Larry Smarr on the faculty there?

Yeah, yeah. So Larry Smarr was leading the national center for Supercomputing Applications and very strong program. I actually ended up doing computer engineering, which given some of my interest in computer design, kind of brings together all of the underlying core engineering disciplines of, you know, physics and chemistry and all of the core engineering prereqs within. When I did my electives, they were all computer science programming electives.

So this was, this was late 80s, early 90s.

You were there late 80s. So I was there 85 to 89. And I sort of appreciated but didn't fully recognize that when I was there I was living in the future because University of Illinois was a very early on and very progressive around adoption and actually had been involved in the Creation of the Internet. So when I was doing my classes there, many of them were online, had online instruction. All of the programming classes were, you know, working on, you know, relatively advanced for the time, mini computers it, you know, and I was interacting with people across the, you know, campus, but across the country and across the world on the Internet in, you know, Internet discussion groups. And in fact, my senior thesis foreshadowed a little bit other interesting things to come from Illinois later in terms of Internet browser, et cetera. But I did find when I graduated, it was kind of a shock that all of those capabilities didn't exist in the real world. So later one of my goals was to recreate the magic of having, you know, continuous high quality Internet connection like I experienced at Illinois.

Did you have a, an email address at that time?

I did, yeah.

Huh. And even in the 80s.

Yeah, yeah, yeah. My, my university email address and was, you know, using things like there were the Usenet discussion groups for, you know, my, my senior thesis ended up being kind of a self designed program where I ended up creating things that foreshadowed the Internet browser where it was using the underlying protocol of Usenet discussion groups in ntp. But then I created a markup language that has some similar properties to HTML. And then it was multimode, where it worked across Macintosh and Sun computers in native mode. So the goal was that you had a, you know, magical front end that gave you access and insight of the riches of the Internet. But it worked, you know, in, in native mode on whatever device you were using. So if you use it on a Mac, it felt like a Mac. If you use it on a Sun workstation, it felt like a Sun, which are some similar properties that later emerged with the Internet browser and Mosaic and Mozilla that ultimately came out of Illinois.

So you're in a whole environment there where people were, I mean, using computers with the old, you know, DOS style, you know, text heavy interface, you know, black screens, and it wasn't that user friendly, but you were in this place where people were thinking about how to make computers a lot more user friendly for the masses.

Exactly. So it was multimedia, it was hyperlinked and interactive. Yeah. So I, I thought it was cool at the time, but yeah, it wasn't until I graduated that I suddenly realized how much I had been living in.

The future there and the Mosaic browser and everything else that became very well known that came a little bit later.

Yeah. And for, and for what it's worth the other releases, there's been a lot of excitement in the last while around AI, but it was in, you know, AI classes and building neural networks and expert systems and things that in the late late 1980s, although then it was a somewhat of a, even to me then felt like an academic curiosity. They were super cool, but you didn't have the combination of data and compute that you really needed. You know, that then now has become a big part of the environment and huge driver of innovation across life sciences and many industries.

Well, you know, from reading my publication, I'm something of a cheerleader for big government investments in infrastructure and kind of catalytic basic research. And you know, I just, I, I smile thinking about that decade's worth of investment in a great state university like that you have there in Illinois and what that enabled people to do, including young people like yourself who grew up on a farm somewhere in Illinois, could come there and learn. I mean this, these are the kind of resources that exist in the United States and they aren't everywhere.

Yeah, no, it's, it's, it's, it's a pretty, it was and is a pretty amazing institution and just the scale and impact it has. And then more recently I've actually gotten involved here now on the west coast with, with UC Berkeley that in a lot of respects is kind of a sister or a cousin school of University of Illinois in terms of the scale and impact that ultimately has for sure.

So you got this amazing education in computer science at this fortuitous time and place. And then what did you do?

So actually one other brief digression in that that kind of fits the story together is so I was the youngest of five and my parents, after supporting the older kids, somewhere in the middle of that, had come up with a really interesting policy which was they were very supportive of the kids going to college, but came up with a policy that said, okay, if you want to go, we'll pay for the first year. And then after that you're on your own. You need to figure it out. And thankfully rel. I heard about this when I was 13, so I started a process to figure out how to do that. So I actually started a business when I was 14 years old in high school that was kind of an E commerce business. Before the E existed, it was actually a mail order computer products company. So I was one of the first pioneer companies that was advertising in the back of computer magazines and selling computer equipment and then software, you know, from the bedroom of my farm in, in, in Illinois.

That's so cool. That's like the, you know, you're creating a Catalog for basically the stuff that you wanted to buy and figured, well, maybe some other people want these things.

Oh, exactly. That was the first motivation. I remember going to the, the store, computer store in Dubuque, Iowa and trying to buy a box of floppy disks. And it was $50 for a box of, of floppy disks that you needed continually then. And yeah, so it started with I, this is the problem I need to solve of I want to be able to afford the things that I want to support my computer habit. But then parlayed that into providing it for others.

Okay, so you got the whole entrepreneurial DNA expressed now along with gaining your technical training in computer science. So some, some braids are coming together here, I can see.

Yeah, exactly. And then that was a business that I ra. Ran through college while I was pursuing my degree. So I was, I was pretty busy as a kid because I was running, running the business and ultimately had kind of 10 or 11 employees working for me while I was going through the, the engineering program. But then tying that back to kind of where, where'd I go from there. As I was wrapping up senior year, I had a kind of faced a choice of do I want to continue doing this, running this business or do I want to? Because at that point it was doing pretty well. I was up to kind of few hundred thousand dollars a year in revenues and you know, had more than, more than paid for school. In fact, my, my college graduation present to myself was I, I bought myself a Porsche.

At 22.

That's a pretty big deal. A red Porsche 944. And I thought that was, yeah, that was, that was, that was cool then. But then I had a decision of am I, am I going to continue this or do something else? And kind of, as I looked at it, I could imagine, you know, what it, what it would mean to go from, okay, I've got 10 employees today. You know, I could imagine 50 or even 100. But I looked at big companies and was really mystified of, you know, how do you get, you know, big corporations, how do you get thousands of people, tens of thousands of people to kind of organize and all pull the same direction? So ultimately I ended up selling, selling that business, which was really just kind of selling the customer list and kind of the running operations to then just focus on learning and learning more. So I ended up going into consulting because I thought that would be an interesting way to just get exposed to a bunch of different businesses and segments and try to understand how, how business works.

Uh huh huh. And how long did you stay in consulting?

Yeah, not that that long. So I ended up going to a startup consulting firm that then was actually, it was a technology consulting company that was then acquired by McKinsey and Company, the big management consulting firm, Management and strategy. And I think that was McKinsey's first and only acquisition ever because it, I think highlighted at the top levels the, you know, how complicated politics can be of bringing partnerships together. But actually the younger people, the class that I was in, ended up being an amazing experience for us and actually ended up being a group that went on to great leadership positions at McKinsey and other places.

Was there any particular project that stood out for you or did you just get a variety of exposures to different management teams, different kinds of problems that existed in business?

It ended up being really interesting. So ended up building, writing code, building systems in support of McKinsey strategy projects. And I mean there were a couple like we did a job for a project for a very large kind of brand name insurance company near Chicago where they had multiple product lines, but they didn't have any way of understanding kind of which of their customers had bought which. And they wanted to be able to cross sell and they wanted to be able to understand risk across them. So three other. Actually it turns out University of Illinois students and I built a system that kind of sucked the data out of three different mainframe systems and a mini computer system, integrated it in a front end that then kind of visually let them understand and see who their most valuable customers were. What the best cross sell opportunities were kind of automated, the process of providing suggested cross sells to the agents. So it was a really interesting system that was, you know, for the very early 1990s, was pretty ahead of its time.

Using computers to really enhance business processes, speed things up, make them more efficient. That sounds pretty cool.

Yeah. Yeah, that was a fun one. Also worked, actually ended up working in Mexico City for six months. And I spoke nothing more than high school English or high school Spanish, sorry. And was working with an entirely Spanish language speaking team. So quickly kind of got my head around. I can either learn Spanish really quickly or have a dozen people learn to speak English. So it's way easier for me to get good at Spanish. So I ended up kind of learning Spanish, doing the project entirely in Spanish and then actually similar themes, building a system that integrated across five or six different computer systems, that they had an integrated view of the customer so that they could do a much better job of risk management and kind of cross selling products.

Okay, now how did you end up going to the West Coast.

Ah, so back to kind of that moment of clarity in the, in the cow yard. And I mentioned that the dream was to, to ultimately build and architect computers. The kind of coming directly out of University of Illinois. There now is a well worn path from there to Silicon Valley, but there wasn't at the time I was coming out. But I had figured out that my, my dream company, Apple was there and there were other companies that were coming along that were really cool like Sun Microsystems and Silicon Graphics and that's ultimately where I wanted to be. So I ended up using the work in consulting to, after doing a couple of these initial projects, steering to, okay, I really want to work on things in Silicon Valley. So I ended up then getting on projects that got me to San Francisco and working in Silicon Valley and building a network here that ultimately then, you know, helped cement my position here.

So what was your first job out on the West Coast?

Ah, the first project was working with a, a company that made very leading edge technology at the time, which was corporate voicemail systems. And it was working with them around kind of designing the next generation. And I don't know if you remember this in the, in the early 1990s but before email was widely prevalent, like voicemail systems had gotten wildly overused where at least on a lot of companies it was the, the precursor of email and the kind of things you would do now with email or things like Slack people did with voicemail. So there were actually really sophisticated systems for being able to, you know, you know, both record and route and process voicemail based interactions.

People probably left longer than necessary messages even then too.

Oh my God. Yes. I remember working in consulting of getting like the five minute voicemail from a partner about what, you know, he or she thought was the next things that we were supposed to do and then furiously taking notes to try to capture all of the wisdom that was shared.

Well, at least it was in a digital format. I do remember the old school answering machines with mini cassettes or micro cassettes. Okay, so let's fast forward a little bit. You spent like a major part of your career at Google starting in the early days. How did you get started there at Google and what did you work on?

Sure. So the, the quick Silicon Valley path was after landing in, in Silicon Valley, I worked at a company called At Home Network that was building out broadband Internet. So that kind of ties back into when I was at University of Illinois and living in the future At Home Network provided an opportunity to, to build out the Internet and make that accessible for all of my friends and families so that, you know, they could live in the future like I had been, you know, seven or eight years prior. And then from there I went to ebay for a while. And ebay was an amazing company at the time. I was really inspired by their mission of democratizing commerce and enabling little guys to, you know, play on the same playing field as big merchants. But ultimately what I found there was it was more of a marketing company than really a. A company that believed in technology driven innovation. And then that was the springboard of moving to Google. And from the first discussions I had with people at Google, things that would take weeks or months at ebay of convincing people the right thing to do were literally kind of a 2 minute or a 5 minute hallway discussion of, of course you would do that because it's the right or most interesting or most innovative technical approach. And then what?

Go figure it out by the end of the day or end of the week?

Pretty much, yeah. Yeah. And at the time I started there, Google had a radically flat structure and some really interesting cultural properties. So I had had gotten to the point of an at home network and then at ebay I had fancy titles and big teams, but ultimately going to ebay or sorry, going to Google, I came in as a, as an individual contributor because with the culture of Google, Google, it was far better for somebody to come in and kind of get their hands dirty and prove themselves technically. And then there needed to be some management structure. But kind of you agreed to, or consented to be a management leader after you had proven yourself technically.

So you're not just management sitting in meetings and trying to work through other people. You had to get your hands dirty and do things.

Exactly.

Show your value.

Yep. And it was interesting. And I remember discussions with my, my boss at the time, who is the CTO of, of Google, of, of having that explicit discussion of, you know, I'm coming from a fancy title and, and having teams do things. And he's like, no, no, no, just, just trust me, just, just dive in. You'll, you know, people will do great and there's want and people will force you into, into a leadership role as opposed to, you know, if I declare it now from the beginning, then people will be suspicious or, you know, might resist, but go in and prove yourself and then it'll happen naturally.

Now what year was this that you joined Google?

2003.

So 2003. And how many people were at the company at that point?

So it was beyond garage Stage, but it was roughly a thousand or so people at the time.

But not yet a public company, correct?

Yeah. Google went public the next year 2004. Okay, okay, so it was a really crazy hyper growth period. And my boss's, the CTO's prediction very quickly became true of kind of within three months people had nominated me as okay, you should be the manager of the team group and director and vice president. So things did develop very quickly as he, as he forecast.

The fancy titles came later, but Google at that time, it was the prevailing search engine. It was a verb. People knew the name and were using it widely, but it wasn't making money yet at this point was.

Was so it was private, so no one really knew. But at that point, yes, it was search engine only and it was perceived as, you know, company people who are really smart. But it was externally perceived as kind of chaotic and not very organized. And if you're going in as a manager, director, vp, it's kind of like herding cats and kind of when I landed there, I ended up focusing first on, on how Google makes money. So I ended up being pretty quickly responsible for Google's advertising system, which ultimately was the economic engine that powered Google. And I did that not because, you know, I loved advertising, but because I had so bought in and identified with the, the, the mission of, of Google to organize the world's information, make it universally accessible and useful. And I thought that was important and would have a big positive impact on the world. But also saw the ambition of the founders and the team and recognized and appreciated that there needed to be an economic foundation that that was built upon to enable all of the other things that Google wanted to do. So I dived in kind of with the team, ended up building the advertising system and in some respects it was kind of a backwater within Google because Google was a search engine. You know, the, the, the, the top engineers wanted to work on search and, and had, it was almost perceived as a little bit unseemly to make money. But having come from, from ebay previously, I was like, you know, making money is a, is a pretty good thing, but you can do it the right way. So part of what I tried to lay out and share with the, the engineering teams there was, you know, it's not an advertising system. It's actually, you know, this one system represents the world's largest real time auction system. Actually even then their, their auction volume was higher than, than ebay and kind of knocking on the door of the kind of volumes that the NASDAQ did in terms of transactions per second, transactions per minute. It's also the world's largest micropayment transaction system because Google and advertising kind of 25 cents at a time and this part was ended up being really key. It's the world's most interesting and valuable machine learning application where my teams built the first machine learning systems at Google to support ads quality and kind of content targeting and other features in the ad system. So it ended up being kind of getting people excited about those really fascinating technical challenges to then build the foundation of what became the way that Google made money.

Yeah, well. And as they say, the rest is history. It's gone on to make a lot.

Of it worked out all right. It's knocking on the door of trillion dollar company.

You moved on to other projects over time. I'm not going to talk about all of them. I know Google Maps was one that's one I happen to use quite a bit getting around town. It's quite nice.

Then you got products that it's hard to think about what life would be like without it.

Well, I remember and it wasn't really better with those Thomas guides that were kind of flipped open and you'd have to flip it over from one side to the next or flip pages while you're stopped at a stoplight.

Yeah.

Okay, so you, you, how did you make the move into life sciences? What piqued your curiosity there? And, and this was at Google too, right?

Yes. So yeah, fast forward in clock. After building the ad system, I then ended up kind of being involved, being involved in bootstrapping what we then called Google Apps. Now it's Google Workspace but kind of Gmail Calendar Docs, that set of products online collaborative products now used by kind of latest stats are frightening. Over 2 billion people. And then you mentioned Google Maps was involved at the early days of that and then ran Google Maps as a large, you know, 5 billion dollar P L 5000 person organization. But right at that point I had hit my an interesting milestone. I had been at Google for 10 years. I'd been there for a decade. And that seemed like a good opportunity to pause a little bit and reflect and look back at kind of what had I done or what had I accomplished. And if I were contemplating, you know, starting a second decade at Google, I wanted to go into it with combination of I wanted to make sure I was doing things that are important and valuable and would have an impact on Google. But also I wanted to go into it with. With energy and it felt like just kind of turning the crank on the next big system at Google wasn't enough. I had self diagnosed that I'm very energized by learning and I wanted something that was going to be important for Google but also would kind of throw me in the deep end of continuing to learn and grow and be challenged. And after a little bit of reflection I decided that life sciences was that. And so I ended up making a move to Google X which was the collection of crazy new projects, things like self driving cars and then being a co founder of Google's life sciences efforts. And you know the Google pitch on it was there's now a, a tidal wave of data being created from technologies like genome sequencing that, that's a, a Google scale opportunity and challenge and then applying the kind of big data and machine learning deep learning techniques where I'd spent the prior decade building those systems across Google applied to life sciences should be something that could drive new insights, new innovations, accelerate the rate of learning and scientific discovery in life sciences.

And what did you know about biotech or life sciences at this time?

I was enthusiastically interested but had no official background. So I joked to friends at the time that I was starting my night and weekend PhD in biology and it was, it was kind of like that. But I mean we live in, in amazing times now where you can learn, you can self, self teach. So it was really kind of diving into to journals and online resources and you know, books available and kind of building up from you know, literally the, the big red book of molecular biology that everyone goes through probably as a sophomore in college to building up from.

There but quickly ran into a lot of the challenges about, around data sharing and you know, between biology institutions and healthcare institutions and you know, different types of data that don't really communicate well with each other and proprietary formats. I mean this is a, something of a swamp you had just waded into.

It's a, it's a swamp. But it's funny, there are things that, that people kind of overstate the challenge of and if you kind of approach them from first principles and build the systems right the first place, things like, you know, data privacy, security, hipaa, they're, you know, they're, some of them are just clearly necessary and things like HIPAA are, are well intended and now kind of legally necessary. But if you build from the beginning with those properties or requirements in mind, it actually isn't that much of a, of a constraint or limitation. I've seen kind of far too often people hide behind them as excuses when they are solvable but that said kind of the business side of things. Like I remember there was a discussion about collaboration as we were ramping up the efforts at Google X and Life Sciences, a collaboration, data analysis collaboration with a very large hospital system that Shogun Nameless that I think I kicked it off in 20, late 2013 and I heard later after I had left Google, they finally got the deal done in kind of 2017, 2018 and were able to start making progress four or five.

Years just to begin a collaboration.

Exactly. So the pace of things, I was used to a bit more urgency of pace in tech.

Okay. Now you, you stayed there at Google till 2016. This is when you made a big shift. But there might have been some interim steps. You, you got involved with this work at Google, branched out to Illumina, you started to get to know some people there and that led to Grail. What's the story there?

Sure, sure. So shortly after I had made the decision to head towards Life Sciences and make the move to Google X and help kick off and co found the efforts there. Sometimes the universe conspires in good ways. And I got a call kind of out of the blue from Illumina who was looking for a board member to help them kind of sort out their, their big data strategy because similar observation, they saw this tidal wave of data coming and they saw it is ultimately limiting for their customers and, and correspondingly for them if people couldn't make sense of the data. So they wanted, you know, somebody with a big data background to, to come and join the board. And then I ultimately did that and, and joined the board and, and helped them set strategy and direction there.

So this, this was with what, what year was this?

2014.

Uh huh.

2014 was part of it. I think by the time I joined it was 2014. Actually it was the very beginning of 2014 because there's another dimension of the Grail story. So that's the professional story. The personal story is right when I was joining the board of Illumina, my wife Laura was diagnosed with very late stage cancer which ended up being a material part of the genesis of Grail.

Yeah, yeah. So we'll get there in a second. But for now you're just joining the board of Illumina and your wife has got this scary diagnosis. What happened next?

Yep. So on the diagnosis, so it really kind of came out of the blue and was, and was a shock obviously to her and me. She was 45 years old, super healthy, super fit, did everything right, ate right, exercised way healthier than Me and had no family history really at all of cancer and started having some vague symptoms kind of over the winter, which she then coincidentally was going into her doctor for annual checkup. And the doctors are looking for horses, not zebras or unicorns. So the initial diagnosis was, oh, you're a woman in your mid-40s and it's kind of wintertime, so you've got a little bit of seasonal depressive issues and get some sunshine, everything will be fine. And, oh, you're in your mid-40s, so welcome to early stages of menopause.

Oh, wow. So there wasn't any, you know, molecular diagnostic that she could take at that time to look broadly for cancer.

Yeah. And then that nobody thought of it. Yeah, exactly. And that was really the beginning of what became a multi month odyssey as her symptoms accelerated from kind of just feeling tired at first to then having some hip pain, which then again, doctors looking for horses, not zebras, said, oh, your family history, your mother had hip replacement, so you're probably hitting the early stages of that. You'll need hip replacement someday. And then there was another month of, oh, she started having some GI symptoms which were very unusual for her. So then they decided to do a kind of exploratory colonoscopy, endoscopy to see, you know, the hypothesis was this might be mild irritable bowel syndrome or Crohn's disease. Mild Crohn's disease. And then, you know, it was a month long scheduling process to get that set up. And then when she finally did have that procedure, that was kind of the beginning of the official diagnosis of, you know, they found a very small tumor 2 cm in the colonoscopy. And the original hope was that, you know, this could be the success case of a coincidentally discovered cancer early detection, because the prognosis for early discovery, colon cancer, is quite good. But then as she and we went through the next steps of workup on that, unfortunately that wasn't the case. When they did a CT scan, the CT lit up and demonstrated that there had been extensive metastases to liver and through her lymph system, and then ultimately in treatment to lung and to bone as well.

So this is now all over the place. It's really spread. And then what in terms of treatment, just. Just standard chemo radiation, or were you able to then get some kind of molecular characterization of what the two. What the driving mutations might be?

Yes. So we had the combination of kind of where we are in Silicon Valley and having Stanford and UCSF in our backyards. And I'm on the board of Illumina. That's at the leading edge of molecular testing capabilities. So you know, we started a full court press on, you know, yes, while the diagnosis is bad, this could or should be a solvable problem with the amazing state of technology and medicine that we have today. So we pushed the limits of the system. She actually did the first foundation test that was ordered at least out of the GI department at Stanford. Ultimately ended up using other products foundation medicine test to assist in just kind of quantifying or helping identify what are the drivers of the cancer. And are there targeted therapies that would.

Make sense now which at that time it could look for maybe 200 or so common mutations, not all of which had drugs. Well, still don't.

But if I remember correctly, it was a little more narrowly scoped. It was on the order of 50 or so then, okay. Grown over time. But the net is that the combination of, you know, there were starting to be good tests but you know, we had to really push the system including at leading institutions like, like Stanford of you know, we, we. This is a test that should be ordered and this is how it could and should be used in the treatment. Because it wasn't being used that way yet. It was considered kind of speculative or research, you know, even by a very leading edge institution.

And did you, did these tests find anything actionable?

They did. But what the entire process demonstrated to me, so there is a standard of care and the very strong preference for the oncologists and they are noble and well intended is you kind of go with a standard of care and then when you run out of options in toolkit then you look for other things like would be indicated with a molecular test. So she jumped into a very aggressive kind of three chemo drug cocktail of treatment, saw some initial gains and successes in that. But ultimately what that process demonstrated is kind of the futility of the current cancer treatment model when cancer is discovered at late stage. Because though you would sometimes kind of based on the biomarkers available, which are not perfect, but you would see some kind of progress, but ultimately you would see kind of regression and kind of the cancer taking off again. Because cancer at late stage, cancer is a disease of mutation and it's evolving under the evolutionary pressure of the immune system and any treatments or drugs that you're throwing at it and it basically gets more complex, more aggressive and meaner as you go along. So you were kind of always behind and always chasing in that treatment process.

If you like listening to the Long run, you'll love a subscription to Timmerman Report. This is where you can read my in depth reports on the most interesting startups in biotech, my regular Friday Frontpoints column that concisely covers the issues with the week, plus insightful coverage of current topics in biotech from a rotating cast of expert contributing writers. Individual subscriptions are available on a monthly, quarterly or annual basis. Group subscriptions provide a license to companies who have more than one reader. Go to timmermanreport.com and click on subscribe for more. This is your rational brain talking. You know this, you've been going to school on PubMed. You're, you're inhaling everything you can learn about the state of the art technology and science. But this is, this is your wife and ultimately there's nothing much you or anyone else can do.

That was ultimately ultimately the case.

And you, you had, well, have kids.

Yep.

How old were they at the time?

They were 12 and 10 at the time.

And when did she die?

She passed away in late 2015. In November of 2015, which in in parallel I was on the back to Illumina. I was on the board of Illumina and Illumina was super in the and the board members and management was super helpful in, you know, identifying options and connections and potential, you know, diagnostics that would add insight and connections to therapeutics that could add insight. But you know, in parallel with this, Illumina had kicked off a project shortly after I joined the board of a project that was motivated initially by an accidental discovery that ultimately became the kind of seed crystal of what became Grail.

Okay, Jeff, so this really terrible thing happens to your family now at this time you were on the board of Illumina. You connected to the best cancer doctors out there, a lot of leading edge researchers. This is the market leading DNA sequencing company and you really had a front row seat for seeing the promise of personalized genomic medicine for cancer, but also its limitations. So now around this time you learned about these, I guess incidental findings from some of the work at illuminating around cancer. Can you tell the story of like what did you hear at first and what was so interesting?

Sure. So as, as is seemingly often the case in, in science, many times the, the biggest breakthrough discoveries are are ones that are accidental. And in this case, and this was happening right in the window where I joined the board of Illumina, as mentioned, they had recently acquired a company in a different segment, specifically Veronata, that was focused on non invasive prenatal testing which is an Amazing test that has really changed that segment of clinical practice in the industry. Non invasive prenatal testing is a test that with a blood draw from the mother, can find circulating fetal DNA in the mother's blood and can provide indication of fetal abnormalities and issues, things like down syndrome, et cetera.

Yeah, these were, I remember this company, they were looking for those, they call them trisomies, chromosomal abnormalities. So these are kind of like bigger obvious red flags that you can detect in that circulating that DNA that circulates in the mother's blood, Correct?

Yes. And what Illumina found with the working with the Veronata team was they had gotten to the point of having on the order of 100,000 tests that they had performed, and there was a handful of results that they couldn't explain where the signature looked very different than kind of the expected case for those fetal abnormalities. And the team was working on the makeup of those. And a combination of kind of inspiration from multiple angles. The person who was leading Veronata's lab, and coincidentally Illumina had just recently hired the head of the National Cancer Institute as their chief medical officer. But combination of great minds coming together then identified that, wow. The only thing that really possibly made sense was that these were instances of late stage cancer as yet undiagnosed in pregnant mothers.

So they were looking for whether basically the fetus might have down syndrome or something like that. And they incidentally found the mother actually had cancer. And no. And no one knew this.

Correct. So these were cases of undiagnosed cancer that this test that was developed for a completely different purpose was identifying. And it was finding those, you know, very large scale chromosomal rearrangements as signal in the blood that were coming from the mother instead of the fetus. And then that lit the light bulb at Illumina of okay, here's this test that was developed for a different purpose, but clearly there is signal there. What would it take to do it right? And instead of being able to detect, you know, only this small subset and very late stage cancers, what if we could slide way down the sensitivity curve and instead detect cancer at its earliest stages when it could really make a difference in outcomes? And then that led to kicking off the research project R and D project and collaboration with Memorial Sloan Kettering at Illumina that ultimately became kind of the research and technology seed crystal that became grail.

And the idea here is that tumors for all kinds of people might be walking around just shedding tiny trace bits of DNA might be sloughing off into the bloodstream. And if you had this very sensitive tool, a DNA sequencing instrument that's tuned in to do deep sequencing, you might be able to detect cancer at its earliest stages, when it is most treatable.

Exactly, exactly. And it really is a needle in a haystack problem. Because if you think about cancer at its earliest stages, cancer starts from literally a single cell and then grows from there. And it's the perfect combination, perfect bad combination of being mutated, not sufficiently mutated that it's inviable and just dies of its own accord, but viable, and reproduces or multiplies, and then has the ability to evade or in some cases even co opt the immune system to be able to grow unregulated. But it starts from a single cell, and at its earliest stages, stage one, when it's localized, it is a scant signal that you're looking for.

So you learn all this while you're on the board at Illumina. And I'm guessing you had to be thinking, gosh, what if this had been around early enough for Laura?

Yeah, absolutely. It was seeing in parallel the current state of the art of late stage cancer treatment, which again, there's incredibly smart and incredibly noble people that have been trying to develop drugs and aspirational cures for cancer for a long time, but it's just such a formidable foe because of its complexity and how it evolves. And then in parallel, we're seeing this technology that, yes, if it had existed a few years prior, you know, two, three, four years prior, could have changed Laura's outcome, potentially by detecting early where the prognosis can be dramatically in your favor. But more broadly, this is a technology that could ultimately impact and change the outcomes and save many millions of lives.

Now, how did you end up diving into this with both feet and forming a company and being the first CEO?

Yep. So Illumina, we saw the potential in the discussion that we had with the management team and board from the very beginning, recognize the potential importance and impact of Grail. And the discussions at the board were, you know, beyond the level of this is a, an interesting technology or, you know, potentially a good business to really, this is a, a moral imperative to make happen. And the discussion at the board and with management team was how do you, how can you maximize the success of Grail and provide the highest chance and probability of it having the impact that it should? And ultimately the board and the management team made the bold choice to, instead of staying an inside project, to spin Grail out, because then we could attract the capital and talent and focus that we needed to make Grail a, you know, hopefully a very substantial success.

So you're having these conversations with Jay Flatley, then the CEO, and Mustafa Ranagi, Chief Technology Officer. You're all kind of huddling and thinking about what's the best way to develop this technology and get it most broadly in use.

Exactly, exactly. And then timing wise, I mentioned Laura passed away in November of 2015. It was actually literally the same week, the Monday of that week, we made the decision as the board to spin Grail out and to attract the funding that we needed and make that happen. Actually, Laura passed away on Thursday of that week.

Oh, wow.

Very poignant. Just alignment of timing.

So you didn't have a lot of time to grieve before going back to work?

No. And, you know, the Illumina board and management team knew that I was deeply passionate about Grail and the topic, but were appropriately sensitive on the timing is terrible. But a few weeks after Laura passed away, they approached me about leading the cause and building the foundation of Grail. But we're very thoughtful on the timing is terrible. So do it at some point in the future, six months from now, a year from now, when you're ready, and we can have an interim CEO or things like that. But as I thought about it, I decided to kind of dive in right then. And ultimately Grail was announced in the first week of January at the J.P. morgan Conference that year of 2016.

I remember this. I. I covered it then. And Illumina had a penchant, or used to, for making big announcements around JP Morgan.

So that was the. That was the big announcement of 2016. And I just felt like that was the critical period where the foundation was getting built, the culture was being set, the key hires were being made. You know, we knew that we were going to be shot out of a cannon, and there was a huge amount of work to be done. So I decided to kind of jump right in then.

And you got involved right away in making a lot of these key decisions, hiring people, putting together together the key experiments. You'd need to demonstrate that this was going to be worthwhile. But, of course, what were you up against? There were, I mean, lots of skeptics. I think, really from the beginning that with cancer screening, the tests that had been around for a long time either weren't that reliable, they'd missed things, or they were invasive or expensive. There's something with that. Cause people to have their doubts. How did you think about setting up a development program that would win over the research world, the healthcare world, and ultimately patients.

Yep. So anytime you're doing something new, it's hard because if it were easy, somebody would have done it already. And we had the foundation then of the data was incredibly promising from the work that had been done to that point, the collaboration with Memorial Sloan Kettering. So we felt like we had a very strong foundation to build from. But then we recognized that we needed to do that at a kind of. With rigor and at scale that, you know, everyone else could. Where it would be very clear and everyone else could align around it. And as part of that, we built a culture from the beginning of earning trust through our integrity and rigor and just how we define the clinical study work, the scale of it, so that we were appropriately powered, that the data would be very clear. The approach that we took to it, the transparency, a mindset of sharing and publishing data as we went along and sharing it with the community, engaging the FDA from the very beginning. So we felt it was too important to not do it un. Unquestionably right.

Huh huh. And what was the first big break where you thought, okay, we might have a product here that there's a line of sight to taking this to the market?

Yep. That. I mean, there was confidence in the decision originally to, you know, again, based on the data that we had seen as an R and D project at Illumina. So there was very strong confidence. It really felt like the challenge was execution and scale. And one of the things that we quickly had to confront, though, was there was some aspirational thinking at the time of spin out of. Of what it would take to do that, what the timeline was and what it would cost. And I forget the exact numbers, but it was on the order of, okay, it will cost, you know, 100 or $200 million, and it'll be a, you know, might be as BIG as a 10,000 subject clinical study, which felt very large at the time. But then when we went through it with the, again, that mindset of unassailable integrity and rigor and really thinking deeply about the product and the impact it. It can and should have and the specification needed for that, the clinical study program ended up being an order of magnitude larger.

Yeah. And it took over a billion dollars.

Yeah. Ultimately has been a, well, a billion dollar clinical study plan and has had, you know, now over 300,000 subjects in the. In the overall clinical study program.

And what kind of results has the Grail test been able to deliver?

So the results. And just being clear, Grail is Now a commercially launched product. We launched commercially about two years ago. So now there's Grail has been public and Illumina has been public well over 100,000 commercial tests that have been done. The combination of sensitivity and specificity that Grail was able to achieve, and then additionally, very importantly, an additional dimension of the test that took some really breakthrough work to make happen, which is also having a very high accuracy. Tissue of origin prediction has really kind of been the combination that is demonstrating impact. And specifically around tissue of origin, we ended up using an additional dimension of, of sequencing of looking at methylation and methylation signatures, which was both a sensitivity enhancer for the test itself, but then enabled us to do a highly accurate kind of 90 to 95% accurate tissue of origin prediction. So if the Grail test says that you unfortunately have cancer, it then says, and oh, by the way, it's pancreatic cancer or colon cancer, or breast cancer, or lung cancer or, or whatever the prediction of the organ system involved so that it can be directly actionable.

So this was an important technology iteration that occurred along the way and ended up yielding a test that is now commercially available and can detect something like I think 50 different types of cancer in a blood sample with 90% and above sensitivity.

So the sensitivity. So the specs of the test are it's a multi cancer early detection test, which is a first and a new category of test being created. So it's helping create and define a new industry. The sensitivity is on the order and it varies across the 50 cancer types, kind of varies in ranges, but the average is on the order of between 70 to 80%.

So that means it catches those cancers, but misses a fairly significant portion.

So here's where you get into a little bit of kind of an ontological discussion. So the majority of cancers, over 70% of cancers, don't have any screening paradigm today. So for example, pancreatic cancer, ovarian cancer, stomach cancer, many of the GI cancers, lung cancer, with the exception of people who are, you know, multi pack a day smokers and who are eligible for low dose ct. So the vast majority of cancers don't have any common screening paradigm today.

Right. So if you're catching 70% of them in the blood versus catching none of them with whatever test you've got today, that's, that's actually quite a step forward.

It is a massive step forward. So the sensitivity of a test not taken is zero. So it's a huge step in advantage of that.

And really the specificity part though, when it calls Cancer that it can do with a higher degree of confidence.

Correct. So given that this is a screening test being used in a. The primary use is in an asymptomatic or healthy population, the specificity is a really key part of it and could be the thing that really, you know, would make a test not viable for screening. And that's where Grail put a lot of emphasis. The specificity of the test is 99.5%. And specificity, the complement of that is the false positive rate. So it's a kind of 0.5% or 1 in 200.

And that's really important because this has been the knock on a number of other cancer screening tests where they have a fairly high rate of false positives, which causes people a lot of anxiety. It runs them through the medical system with lots of additional tests and potentially treatment that is unnecessary. So, like, there's just some taint around false positives. We want to avoid that. And that's what you did, correct?

Correct. So it has a very high specificity, which we felt was critical for helping create this new category. And, yeah, if you look across other screening tests that are done and ones that are used very broadly, I mean, they'll have on the order of, you know, 85, 90, 95%, whereas grail is an order of magnitude better than them in terms of the specificity or the absence of false positives.

And what's the price?

The price is $950.

That's the same as when it launched, is that right?

That's the same as when it launched. And at this point, I have no affiliation with official affiliation because Grail was acquired by Illumina. I was a board member and vice chairman of the board at the time of the acquisition. So at this point, I have no official connection to Illumina or Grail. So I can express personal views. And a personal view is that that is a. At the 950 price point. That is. It's great that it's available to people, but ultimately, Grail should be a reimbursed test, and it should ultimately be much lower cost, and it should be available to everyone that's eligible, as opposed to it just being, you know, available today to people who can afford that price.

Because coming back to the original vision, if what we have here is a screening test that can be done off of a simple blood sample in otherwise healthy people like, say, in their 40s, 50s, maybe 60s, if you want to reach the masses, the true mass market, it's going to have to be at A lower price?

Absolutely, absolutely. It should be substantially lower cost and it should be a reimbursed product.

And insurance companies have been balking thus far. Do any reimburse for it.

Not the insurance companies of their own volition. So what grail has been doing is while that process of getting reimbursement settled, Grail has been going out and engaging employers, self insured employers and concierge doctors and actually interestingly, life insurance companies who are offering it as part of their services. So for example, you know, progressive companies offer it as a benefit for their employees as opposed to it being offered through the, the large payers directly themselves of their own choice and volition.

That's interesting. Trying to find some creative ways to get it more widely adopted and which may take some time for this to really find its full footing.

But a fascinating demonstration of the lack of alignment of incentives in our medical system, the US medical system, at least today is I mentioned life insurance companies. So life insurance companies aren't using it as a condition of offering coverage. But once you have life insurance with them, life insurance companies want you to live forever because they want you to keep, keep paying your premiums and then they want to delay the payout as long as possible. That's good business for them. So the fact that life insurance companies are offering Grail as a benefit for their covered customers says something about the, the math that they were able to.

Do that is fascinating. If they've got a 50 year old customer, catch a little bit of cancer, catch it early, whack it with some chemo, live forever, keep, keep paying your premiums.

The incentives are aligned whereas our, our healthcare system, the incentives are not nearly as well aligned.

Yeah, yeah. They look at this and say gosh, this is going to cost us money. And then if we catch something, well then they're going to run through more tests that we're going to have to pay for, which we'd rather not pay for.

Yeah, the, the health insurance model is caught in a prisoner's dilemma which is they the, the kind of short term thinking is drive driven by in the US are most people get their insurance through their employer with the exception of Medicaid and, and a few other programs. But most people get their insurance through their employer. The turnover rate as our economy has shifted to be more and more of a service based economy is getting, you know, lower and lower. It's on the order of two years now. So the insurance companies, the payers look at things as unless they can get less than a two year payback on a product unless it's, you know, legally required or mandated. Unless they can see less than a two year payback, they don't want to pay for it. They would rather kick the can down the road and have you get a late stage diagnosis at your next employer rather than paying the preventive cost upfront.

Let's try to move that off onto some one of our competitors, some other health insurance company can pay for that down the road and if they could.

Actually coordinate and recognize the systemic costs, it is strongly in their interest to do so. Like life insurance companies have figured out or like. Grail is also now working with the UK national health system, a single payer system where they take a longer term view and you know, both the, the impact outcome of saving lives aligns with ultimately saving money for the system.

I wonder if this tips at some point when enough people get access to it or aware of it, maybe from Grail, but others too. I mean Exact Sciences company, you know, has offering here Thrive earlier detection. That's coming down the road. You get more voices in the marketplace. Maybe that will change this paradigm.

Yeah, no, we, we at Grail and have been working with Exact and others to try to build awareness of the segment which is now broadly called multicancer early detection. So Grail is an instance of that test of that category. But there will ultimately be multiple products in that category and we really need to demonstrate the impact that this has on most importantly in my view, saving lives but more broadly the healthcare economic system impact which ultimately will be quite positive.

Okay. Now Jeff, you're no longer on the board of Illumina, so I think you're at liberty to talk a little bit about this. But you know, Illumina decided a couple years ago to reacquire Grail. You know, it had spun up, been an independent company and then Illumina bought it back for I think $8 billion or so it was. Since then regulators in Europe and the US have kind of looked askance and tried to or I think the FTC ordered a divestment from Illumina to get rid of Grail, that this was anti competitive. This has been caused a lot of shareholder consternation and activist battle. The CEO has since left. What do you think is going to, what is going on here with Grail? And, and do you think this is going to resolve itself in any sort of positive way?

So I think at the time of the acquisition we, Grail and Illumina were naive unfortunately with how politicized the regulatory system has become or at that point it was really tipping towards becoming. And again, I'm not a representative of Illumina nor of Braille. I'm sharing my personal views. But it has become evident that the, the FTC and the EU authorities are at this point not aligned with kind of any reasonable interpretation of, of laws or of historical precedents. They really are trying to set new precedent because they want to expand the, the remit and the scope of, of, you know, what they can do in their power and their findings. And the, if you look back on the, on the history of it, you know, the, the FTC objected when Illumina and Grail went to them with the deal and the FTC objected, which was kind of a surprise. But then there's a process for resolving that and you go to court and there were then a multi month lead up to what was going to be a court hearing that where Illumina and Grail could make its case and the FTC could make its case and then there would be an impartial judicial finding. And a couple of weeks before that was actually going to happen, the FTC kind of looked at the facts and reality of it and seemed to recognize that they were going to lose that court hearing. And instead they withdrew their objection without prejudice, which is legalese for we reserve the right to screw with you in the future and then communicated with, slash, colluded with the European Union authorities to have them raise an objection. And at that point Grail had no customers, no product launched in the eu. Pretty clearly by most interpretations shouldn't be part of EU jurisdiction. But that was then a, you know, go fetch water there and when you resolve things there, come back and we'll restart the clock on you here. So it felt like they had created a model where regardless of the legal legality of a deal or historic precedence of a deal, they could disrupt or blow up any deal they wanted with this new technique.

Well, it's a pretty serious allegation you're alleging there. I the only thing that I would say without having a representative from the regulatory agencies here to rebut, I think that listeners should know Illumina does have the dominant position in DNA sequencing. Something like, I don't know, 80 to 90% market share of the DNA sequencing instruments themselves. And I think there is now, while they don't have that dominant market share in the clinical diagnostic applications that come from that platform, I think that is the theoretical concern at least that they could use that, that dominant position to lever in and achieve dominance in this adjacent field. Now I mean, just a few minutes ago I mentioned Exact Sciences is a pretty significant competitor in this, this area and it's nascent, so by definition there is no dominant player. Yeah, so I think that that would be, that be. Would. That would be the argument the Illumina lawyers would be making.

So yes, this is a segment that doesn't exist yet that does have multiple participants in helping define the segment. And I mean the FTC and other regulators have tools when there is an issue to intervene. But in this case, I don't know if you're a science fiction fan. Have you ever seen the movie or read the book Minority Report?

Yeah.

So if you remember the Minority Report, pre crime police can, can identify crimes before they happen and prosecute them. In this case, it feels a bit like the authorities are, are the Minority Report pre crime police.

And that is a bit concerning.

That's quite concerning, yes. And, and the other side of this is, you know, they're, I, I am confident that they are, have positive intentions in what they're trying to achieve. And this is really kind of Grail Illumina as one instance, across a much broader set of mergers and acquisitions being blocked or slowed across multiple industries, across biotech and tech. And I'm sure that they have positive intentions around what they're trying to do, but there isn't recognition of the cost of what they're doing, which in the case of Grail, the, the net effect has been. So Illumina ultimately decided to, to go ahead and close the deal while the FTC had withdrawn their objection in the US So it was within their purview to do that. And Illumina then did it in the face of objection of the eu, but it seemed pretty clear that the EU shouldn't have jurisdiction. And as part of that, Illumina had a, did a hold separate where they agreed not to integrate or accelerate the activities of Grail. The net effect of that has been that Grail, you know, is now part of Illumina. Illumina owns the asset. It is a commercially launched product and is available but not nearly at the accessibility or scale that it could and should be. And the effect of that is that Grail isn't as accessible, available, low cost as it could be. And ultimately people don't have it available. And the cost of that is lives lost where every day people are not getting a test that they could, that could have detected early and their cancer is being detected late when the odds are against them and the outcomes are much worse. So you know, while on one hand, you can say that, you know, it's politics or it's the regulators doing their job. The real cost of it today is lives lost.

Well, it's a really interesting case study because, and I don't, I don't want to move on here pretty quick, but the antitrust enforcement, historically or last, I don't know, 30, 40, 50 years, has been about policing these things so that in cases where consumers get harmed with products that are set at higher prices by monopolists, which they are apt to do. But there has been increasing literature that this isn't always the only kind of harm that can happen with mergers, that mergers can be used to squelch competition and hold onto dominant market positions even when the product itself is not really being price gouged onto the consumer. That we want to create a lively, dynamic, competitive business environment where startups can compete with big companies like Illumina. And so I think that's partly the guiding intent, at least that's what I've read. But as you say, there, there may be some, some consequences to going down this road.

There is a very real cost of it that isn't being recognized and there are tools in place to, if and when that ever becomes an issue, to appropriately deal with them. And a dynamic environment where, you know, the sequencing market itself is dynamic and there are multiple competitors and, you know, great products and tools coming out all the time.

Okay, we're out of time here, Jeff, but I want to ask you just a little bit about your new thing in venture capital. You started this firm with a couple of colleagues called Triatomic Capital. What is this first off? What are you trying to do?

Sure. So once the deal was closed with Illumina and it was clear the grail was not going to continue to be an independent entity or continue on an IPO path, that then freed me up to decide a next chapter and after a little bit of contemplation, decided to join forces with a couple of friends and colleagues who were builders of two of the kind of very prominent venture capital firms out there. One from CO2 Management had been there for a decade. The other had been at Deerfield Management, Health Tech, Medtech oriented firm had also been there for a decade. And we joined forces to create Triatomic Capital. And our mission together is that we want to work with great entrepreneurs to build century defining businesses and technologies.

Century defining.

Century defining so underscores the ambition behind what we're doing. Our focus is on what we call applied AI, which is our very opinionated view of Where AI is going next and where value is going to be created. It's ultimately kind of a data first, data centric approach. So our thesis is that value will disproportionately go to teams and companies that are generating important strategic proprietary data at quantity and quality that then they're able to unlock and accelerate with AI tools. So we're big believers in the power and impact of AI, but take a data first view to it and then we concentrate that into a set of what we call our industry, or sorry, our century defining themes, which are really our bets on kind of the five megatrends that will define the next several decades and ultimately the balance of the century. So that's where the greatest impact will come and therefore the greatest opportunities for returns.

This sounds like first principles thinking like first, what types of data do you want to collect? What for how high quality of a means can you use to collect this data and then push it into the AI systems to analyze it? Is that right?

Yes, yeah. So it really starts with data. And then the other observation is, you know, some of our perspective on this is I think I mentioned earlier when we, we covered some of the background and history, you know, I with my teams built some of the first AI systems, the first machine learning systems at Google and then another wave of them of deep learning systems. So have, you know, we have kind of 20 years of perspective of seeing the trend lines of AI and where things are going and in that evolution from machine learning systems to deep learning systems to now the generative AI systems, I mean in some respects the systems are becoming bigger and more complex, but they're actually getting conceptually simpler. And if you look at now the excitement around generative AI and large language model systems, it really is a conceptually very simple model where you're just applying massive amounts of data and compute to it. So increasingly in AI, the input data defines the output of the system. So in a lot of respects in AI systems the strong trajectory is towards the data is the code. And for us that underlines, underscores the importance of data and kind of our data first approach.

And you can apply this toward applications in biology, chemistry, energy.

Exactly, exactly. So we, I mean we believe strongly kind of a cornerstone of our approaches around what we call engineered biology, which is kind of encapsulates all of those things. It's very data centric. There's still a huge amount that we're, we're learning and discovering around biology. But ultimately we're on a trajectory where, you know, we think that if there's one thing that stands out that could be the thing that defines the 21st century. It's really our. In our ability to now engineer biology at a cellular level. And you can see that already with, you know, breakthroughs and cell therapies and gene therapies, where now we're able to. You know, we're at the early days of it, but already we can cure previously incurable diseases. You know, the therapeutic progress in the therapeutic war against cancer is going to come probably disproportionately from our ability to engineer the immune system to do the right things against cancer. And then even beyond that, beyond human biology, of synthetic biology, of being able to, you know, engineer cells that. Or engineer at a cellular level to create, you know, turn cells into the manufacturing factories of the next generation of capabilities we need.

Hearing you talk about engineering cells and bioengineering, it makes me smile, because I know that your daughter is studying this very, very field as an undergraduate. And I had the privilege to get to know both you and her on the Everest basecamp trek that I organized in 2022 for the Fred Hutch. Do you want to share just a little bit about why that appealed to you, why you chose to do that at that moment in your life?

The move towards kind of early stage investing?

No, no. Joining the Everest base camp trek. Giving back to cancer research.

Oh, absolutely.

Spending time on the trail with your daughter.

Well, it was also an opportunity to spend quality time on the trail with you, Luke.

We had some trail conversations.

Yes, we had some trail conversations. No, it was so. So thank you again for the opportunity to include her in. You know, I saw it as. Here's a. An opportunity for an amazing, inspiring adventure with a group, a community of people that you're building through kind of all of your philanthropic efforts. Efforts, but, you know, in a really unique space and place, and then the additional dimension of it being for the benefit of cancer research. And if you, you know, think back to the. The group that we had, and. And actually, the group stays very active. We still have an ongoing discussion group, chat group that's quite active still almost on a. On at least a weekly, if not sometimes daily basis.

I know. I love that.

So a great group that came together, but really one that was unified and inspired by cancer. And we had, you know, people whose lives who had lost loved ones to cancer, so it was extra meaningful. People who were cancer survivors, so it was extra meaningful. So the combination of those factors, it ended up up, you know, great group of people for a great cause, and Ended up being a, you know, in part because of the, the place as well, being very spiritual, a, you know, a spiritual experience. In addition, and I'm so grateful that you agreed to have my daughter come along who is interested in, in this field and, and wants to have an impact and the opportunity for her to meet other people on the track who were a few years further down the line of their professional careers and development and the kind of sense of purpose that they had around what they were doing and the impact that they have had. But also to see that people were sharing their stories and very personal stories of how it's not always a straight line of kind of what are the twists and turns and bumps that people experience in their professional and personal lives of getting to where they are now, which, you know, each of the people there was very impressive, but kind of hearing the stories behind it I think was extra interesting and impactful for my daughter who's now, you know, looking up that big hill of how do I get there from here?

Yeah. So she's about, I don't know, 20 years old, sophomore now.

Yeah. Studying biomedical engineering and bioinformatics.

I mean, what a time in the history of biology and Biotech to be 20 years old and studying these things and to think about what you might do with your career. It's pretty, pretty amazing.

We live in incredible, amazing times. Yeah. Just seeing the rate of discovery and evolution and impact and I'm an optimist and part of our back to the investing side of things, the focus on century defining themes. Ultimately those are the areas that we think will have the biggest impact and ultimately the biggest positive impact on humanity.

Does this remind you a little bit about when you were entering computer science in the 80s?

You know, I, I, I was right before, so computer science was really interesting then. But I think the thing that really took it to the next level of, of where my mind expanded was with the growth of the Internet and seeing the impact that that had and how just kind of universally impactful that could be. And I think it's been, you know, there are some, some, some sharp edges to it, but I think that the net has been pretty amazingly positive.

Last thing I want to ask you, Jeff, you're. You made this move over into venture capital. You've got your thesis around century defining companies. I'm sure you think there are, there are opportunities out there. Why do you think now is a good time to build a biotech company or invest in one?

Yep. So I think the foundation is the discussion that we just had of, you know, the rate of scientific insight and discovery and learning is incredible. And it's accelerating and I think it's being accelerated dramatically by kind of the big data generation capabilities and then now AI tools to help understand and, and, and accelerate it. You know, more specifically on why. Right. Right now, you know, we're the, the. The market has gone through a bumpy period. Things were kind of frothy a couple of years ago in an. On an. Unsustainably. On an unsustainable trajectory. It has been a pretty significant readjustment and you're seeing a lot of impact of that of, you know, companies scaling back or layoffs or, or things like that. But the reality is that we had gotten too far ahead and this is a necessary readjustment. And you know, we see now amazing companies and opportunities and you know, really inspiring teams that want to go after things, but now with a more reasonable place in terms of valuation and I think ultimately better companies being built because they're getting the right culture bits set from the beginning of having a mindset of frugality and a mindset of focusing on kind of customers and partners and generating revenues as a measure of value that's being delivered and then using those margins to drive the future capital requirements of the business. You know, the, the previous model of. We went through a, A very unique period and it was fun while it lasted of, of essentially money was free. That's never existed before in the modern economy. So we think that this period now is more realistic and kind of the, the, the. The new old reality where, you know, great companies will be built and you know, now you can kind of build from the right foundation.

Maybe you could call it back to the fundamentals. Exactly. And I totally agree. I look at all these things that you mentioned and also just the accumulated scientific knowledge, the speed of accumulating new knowledge, the pool of experienced people and all these technologies that, that have been emerging kind of in parallel for understanding targets and new modalities and the computation to analyze all the data. I mean, all these things are emerging and making it a really great time to be doing this kind of thing.

It's an incredible time to be alive. It's an incredible time to be in this industry that is making such progress and having such impact. It's incredibly exciting.

Jeff Huber, thank you so much for joining me on the long run.

Thank you very much, Luke. And I just want to say thank you for all that you do in this industry. Between your philanthropy that we talked about earlier, you've raised millions of dollars for great causes, for cancer, research, for poverty, the great work you do with the Timmerman Report and here in the long run, I mean, I'm so honored to be counted among the, the, an amazing group of, of accomplished people that have joined you on this. I'm, I'm honored and humbled. But what you're really doing is bringing together people and building community and telling positive stories about people who are very, and companies who are very purpose driven and trying to have an impact. And I think, you know, for doing that, you were an absolute treasure. So thank you for the opportunity to join you here.

Wow, that's very kind of you, Jeff. And if folks made it all the way to the end of this podcast and you want to listen for two hours, let me know and maybe we can extend these long runs to two hours. Thanks, Jeff. Bye. Thanks for listening to the long run. A production of Timmerman Report. Pedro Rosado of Head Stepper Media was the sound editor. Music is from Da Wallach. See you next episode.