From Operator to Fund Manager

All right, everyone. Well, we are nearing the end and we saved the best for last here with a conversation. So you can tell throughout the day on the panel side, we've had a number of different expertise in the investor that you heard about, right? We had angel investors who, you know, do angel investors on themselves or as a couple. We had Ashok who manages an angel group, right? And now we have— I'm going to be interviewing Mr. Will Alanik who manages a venture fund. So I want to give you a taste and a lens through a few different I guess, 3 different lenses of how people are investing, right? Some are on their own money, some are on helping a group invest, and some are managing an entire fund on behalf of LPs that could be individuals, institutions, family offices, and more. So without further ado, let me introduce you to Will from Phase 2 Ventures to the stage. Thanks for being here.

Thanks. Yeah, thanks for having me.

Uh, you want to quickly give your background and then we'll dive in?

Sure.

Um, I trained as a scientist, I guess, is my origin story. And I worked for 14 years in 4 different Howard Hughes Medical Institute labs with 4 different National Academy of Science mentors. At the Salk Institute was where I ended up doing most of that work. And then in about 2009, I got kind of pulled into a project looking to develop something called a flow cytometer, cell sorter. And that became a company called NanoSelect that's still going. In 2015, I started another company called Arima Genomics doing genetic testing. I call it 46andMe because you get all 46 chromosomes sequenced with Illumina, not just the 23 merge that they typically do. And that matters. And they recently launched a cancer diagnostic that helps— that can detect chromosomal fusions that cause these driver genes that drive cancer. And then a company called Defined Bioscience that is vegan cell culture media. I call that because there's no animal products. And then in 2023, we started Phase 2 Ventures. All that was Phase 1. This is Phase 2. And the idea was we've worked with a lot of venture groups. We've seen really great people. We've seen some counterexamples. We've learned, you know, kind of MBA on the streets, how to operate companies. And we thought we could help scale our knowledge by investing in some tools companies. And that was the principal tools. We've also invested in therapeutics and some diagnostics. So yeah, that's the nutshell.

Okay. Well, the main takeaway that we'll be focused on eventually is after the check, what is it like What is the— what is— where does the relationship start after the check is written? Okay. But as you can tell, Will is a serial builder. At some point, I think you're— you've done some of your own direct angel, right? Invested into companies directly or at least started companies and invested through equity, sweat equity, and then this fund.

And then raising a lot of government grants.

Okay.

Which was so I That was my contribution, was getting that money.

Okay. So, what I want to talk a little about is kind of the founder-investor, founder-funder relationship through kind of these main phases. Way before fundraise, how much time are you spending both on both sides, founder and funder, assessing, getting to know versus in fundraise now, how much work was done on you in your founding days by investors?

So you mean for the fund?

How much time did it take? No, let's talk more your perspective.

How I vet the opportunities to invest in?

No, let's talk about you, the founder. How much work was done on you by your potential investors versus the ones who actually cut the check?

It's not 100% hit rate, that's for sure. I think when I was first starting this, I didn't know how to select the right venture investor in me. So we were just, like I said, kind of learning it on the streets as we went. We had trained in science, not finance. But eventually, you kind of bump into people who are good advisors and kind of help you along and make introductions. And eventually, we got in touch with people who understood our stage, where we were, they made investments at this stage in this kind of technology. And it's really just a matchmaking game at that point. It's— they have to understand where you are. You don't necessarily need to understand where they are, but it's helpful. And so I would say we talked to maybe 10 or more groups before we started getting our first checks. Yeah.

OK. And from a science perspective, and take this through the lens of Angel Academy, where, or, uh, St. Angel Conference, right, where we're going to have a, we're gonna have a wide range of companies in here. We're gonna have consumer, tech, life sciences. The life sciences, and everything's gonna be super early, the life sciences, think through the lens of pre-seed or seed of the kinds of companies we're going to see. Now put your belt back, back on those shoes. Like, what did you have in terms of you versus product and data and lab work that was tangible at the pre-seed and seed stage versus them really betting on you and the team and the, the science aspect of your backgrounds?

Yeah, I would say in a way both of those are table stakes, right? You have to be credible and you have to be reasonable counterpart to work with and you have to know your stuff and be driven to go get things done. And then you also need to have the table stakes of this gadget needs to work. We worked with an engineer at UCSD who had published some work in this space. He had prototypes, he'd shown some data, but it was really, you know, an inside-out pinball machine of a gadget, right? The full Rube Goldberg device kind of thing. But if you kind of blurred your eyes, you could see, OK, this could be— this could work. And at that time, there were no kind of personal flow cytometers. These things were the size of a refrigerator. And we were arguing, you know, you can go to Kinko's and use a huge printer, but don't you want just a desktop printer? It's not as many functions, but it's good enough oftentimes. So we kind of kept pitching that idea and just organizing the data, doing preliminary experiments. We— before we got our first investment, we actually had built a prototype that literally had duct tape in it, and we had leased it to Agilent. So that was some credibility, right? And they had a very accommodating early adopter mentality, and they're very super great to work with, very high integrity, not aggressive or sharp-elbowed.

Did any of your investors ask to speak to Agilent? Yeah. Cool.

Yeah, and they didn't speak to the CTO, but they spoke to the people running the machine.

The users.

Yeah. Agilent was like, we get it. It's a prototype. It's going to break. That's fine. We want to get early access. So it was perfect beta tester, or maybe alpha tester would be a better fit, better description.

Okay. Um, okay. Thanks. Um, okay. So let's go through. Well, no, let's talk about after the check. As you as a founder, what were you expecting your investors to be like and spend time with and what actually ended up happening? Time-wise, in every way, every sense of the way.

They were— so the group that invested in us, a company called FusionX here in town, and they had kind of evolved a strategy in partnership with D&K Engineering up in, uh, Rancho Bernardo, right? And so, um, at first they were like, you know, you're seeing a lot of gadgets coming through here for engineering, and people must be somewhat organized and have their story straight by the time they want to hire you guys, so maybe I'll see if I want to invest. And then they really collaborated, and D&K invested, became an LP in that, and they really work closely together. So that was perfect for us because we were looking to build a box. We had a prototype, we needed design for manufacture. Even though we thought our baby was pretty, it could use some help. Um, and so it was— they were a really good partner for that because they had a whole ecosystem that was ready to just take us in and help us along. And we worked with them for our first two generations of machines and a, and a little sidecar we built at one point too.

And did they take a board seat? Were they pretty actively involved?

Yeah, they were.

Ken Hood?

Yeah, someone was on the board. Um, and, uh, the guys at DNK were really helpful, and we got one of their longtime kind of, uh, contractors, a guy who had worked with them previously, became our kind of, um, operations guy. So we, you know, he knew who the cool people were at DNK, so we were kind of immediately insiders. So, that was good for finding the cool people to work with.

So, you got governance, besides the capital, you got governance from them, people who'd run a bunch of companies. You got talent, it sounds like.

Yeah.

And you got operational capability and manufacturing capability built into all from your investor.

That's right. Yeah. So, that was a good match. And that teed us up. We got that machine built and Then we went for our Series B.

And were they involved to help?

Yeah, they kept— they stayed involved. And yeah, they would coach us.

And, you know, did they make intros to funds?

I think so. I don't remember chapter and verse the whole story, to be honest with you. It's been a while now. Sure. But we— in the second round, we got ANZU Venture Partners here in town and Illumina Ventures to invest and some other folks that like the Triton Fund and the Highlander Fund through UCSD and UCR. Yeah, and a group, a woman named Jenny Rook who now has Genoa Ventures. So yeah, some good, some solid people came on board. Paul Conley, who is still— we were in touch with him earlier this week. Still stay in touch with these folks.

That's great. And I forgot, did you take angel capital originally before FusionX?

No. Fusion was the first check. And they were an only check for that round. We called it a Series A. It was only just over $1 million back when that was a Series A. Now it's— yeah. It's different.

Okay. So, at what point in the journey did you say, "I want to be on the other side of the table?" When did you say investing is where I want to spend time and make it a full-time?

It was always interesting to think as a student of life, you see people operating and you're like, "What do they know that I don't know? How do they get over there? What's going on? What do they do to get in that position?" So, just paying attention and seeing what they're doing. I don't know if there was a moment exactly. I think it was kind of a gradual progression.

Okay. And now that you are sourcing cap— sourcing founders and coaching them and then investing, what are you— and mostly in the science space.

Yeah.

What are you coaching them on to get ready to raise?

It depends on where they are, right? Some of them are coaching me probably. Some of them kind of don't— aren't familiar with the stages of development. Or they're not— like, for instance, there's a group that I was working with, and their device was pretty big. And I'm like, if you're going to go do a demo of that, you want to put it in your overhead compartment. Otherwise, you've got to put it on a pallet, or you don't want to check it in the luggage because it'll get destroyed. We went down that road with NanoSelect, which was interesting. But so just little things like that, or, you know, who's your persona? And think about this is just your alpha prototype. You have a beta, you're going to go through multiple iterations of that, then you go to pilot. And just introducing them, just the steps, a lot of the steps you go through. And that's true for demos, manufacturers, sales, IP, Hiring people, just any number of processes that you go through. In fact, I wrote this book to make sure that I knew what I was talking about and then also that I could give to our— as support to our portfolio companies so they understand the language of venture and some of the rudiments of business. And, you know, it's kind of a starting point. And if you have the same language, you're not going to clash as much because you're you can speak the same language, you're communicating.

Yeah, Venture Capital for Life Scientists.

Yeah.

And you can find— it's like a true textbook, by the way. I have one at home. Uh, yeah, there you go. Where can you find the book?

It's on Amazon.

There you go, perfect. Is it— I mean, it's a hefty book, and it is written like a textbook, right? Like a science textbook.

Yeah, I got, uh, that's, uh, I should probably put a picture of my Breville coffee maker on the front of it, you know. Thank you. As an acknowledgment. Yeah, I just kind of started chipping away on it. It kind of got away from me.

I think you and your co— you had one co-founder of NanoCellulite, José?

We had 3, 4, 5 co-founders at the outset.

Oh, wow. Everyone in science?

2 engineers, 3 biologists.

Okay.

And so we were, you know, the dream team, so we thought. And The professor at the university was— I still work with him, great guy, Yuval Low. And he was very supportive. He taught us how to write SBIRs. He had raised money before. And he was super technical. So it was like a great guy to work with. And we seed funded it with about $3.5 million of the SBIRs before— maybe it was closer to $6 million before we took our first check. And we ended up doing another $6.5 million as like skunkworks to develop our third-generation system, which is just coming out now.

Oh, wow. Okay.

It's an imaging sorter, so it takes pictures of the cells as well as sorting them.

So now when you are managing your fund, I want you to tell us about your fund a bit. Like, what are you looking for and what kinds of— where stages you're investing in? Give us a little bit of a—

Sure. Early, early as possible investing. So we've even co-founded one thing. So far. And one of our companies was kind of a warehouse deal that José and I co-founded. My co-founder is José Morachis. We're both managing partners, and we've been working together for 17 years. And we had started the company prior to this called Defined Bioscience that I mentioned earlier, and that one we invested in as a convertible note. We're not going to price it. It's going to be all square. And then the other companies, we look for a number of qualities, right? It's got to be the people and the technology. And they have a certain way of doing things that you can get along with, right? It's kind of the softer factors matter as well, for me at least. Especially with our first fund, and we don't have a ton of money, we have to make sure we're picking people that are pulling the same direction we are.

And is it specific area within life sciences or broad?

We started off with the principle that we'll do life science tools based on our history, right? I've done— we did a diabetes diagnostic company, we helped out on a spinal cord stimulator company related to my background and my postdoc. And then the 3 companies I talked about already with NanoSelect, Arima, and define bioscience. So that was kind of our experience. We thought, let's— we probably shouldn't jump straight into pharmaceuticals. That's a different animal. So we've been— tried to stay on principle, but, you know, strong principles loosely held is a good approach. And there were a couple of companies that had— they were a therapeutic company, but they had a core that was a platform that was kind of a gadget or a tool that we could wrap our heads around. So, we figured worst case, we can advise at that level and be helpful.

Talk about teams that you've invested in. Do they look a lot like your NanoCellit team? 5 founders, mostly science and engineering, all the above?

Some are very similar. So, there's a group out of Georgia called Anson. Biotech, and they're making a microfluidic— which, and our sorter was microfluidic— gadget that sits upstream of a mass spectrometer. And you put your sample in it, and it passes through this chip in seconds, and it gets rid of the impurities so you can analyze antibodies for therapeutic use. So you can QC them as you're going. And it just made a lot of sense to us. Like, here's a little box. I understand the demo process for something like this. It's similar enough. And there was a guy who was just out of grad school and he paired up with his, uh, his doctoral mentor. And he also had a— looked like he was going to get backing from a team that did Axion, which is this box that does electrical analysis of cells and tissues. So we thought, okay, he's got some mentors that are there in his town that have kind of been over the mountain before and he seems super coachable and energetic and smart, and his thesis advisor's there to help, and just kind of looked like a good team. Or at least maybe it's just pattern recognition that, you know, at least I understand that, what that looks like.

Yeah, I mean, you can speak the language, uh, specifically because you've been their operator, academic, and now funder as well too, and kind of co-founder again of, of companies while also thinking through the funding mechanism, right? When you're starting companies now, you're also thinking this could be a company that we could fund their next round as well too, or you're— or you are seed funding it when you're co-founding a company, right?

What's the question again?

You've co-founded a company now while also having this fund?

Yeah, so that was, um, that's a little— that was one of those companies we invested in that's a therapeutic, and they had a technology inside it that we thought we We could— so when we invested, one of the reasons I almost didn't invest is this guy is like a mad scientist genius, really super cool guy. But I'm like, you're doing like 3 different things. I can't keep track of what you're talking about, which isn't great. And I said, you need to get like— I would have said to Jose, it's like he needs an adult in the room. And he needs— and so he found a co-founder who had been like the VP of business development for a antibody therapeutics company, and his company wants to make therapeutic antibodies. I'm like, perfect, okay, that guy's cool. You figured out your IP issues. Maybe what we'll do is we'll invest, and then this core thing, maybe we'll spin that out since you're not— you're going to want to use it, but that's not going to be your business. And we all kind of agreed, yeah, that sounds cool, so let's do it.

Okay, uh, most life science companies need multiple rounds of capital. What are you coaching and preparing your portfolio companies for to be ready for more rounds of capital?

Be lean. I think that's always a good idea, of course, but it seems to be an extra good idea these days. And then, what are the milestones that you need to reach in order to attract the next round of investment? And start those relationships now. Because those people are going to want to see you, talk to you 3 different times, and track your progress. I heard a good saying last night that fundraising is not a picture, it's a video. So you're going to have a whole movie, multiple episodes and cliffhangers. And so you might as well get started on that as soon as possible and build a relationship where people— can see that you're a reliable person, you're achieving goals, you're doing what you said you're doing or to your best ability.

I have my own, I call it capital connectedness during my diligence of do you have the next round already in mind kind of thing, right? I look at people's CRM saying if we're going to invest now, do you already know the VCs you want for next round or even thinking about that? And are they tracking you already? Is that something you look at during due diligence?

I don't know if we explicitly look at that, but we do make sure that they have enough money to get somewhere and that they have the wherewithal to start that process. And we encourage them to start that process as soon as possible. So they may not need it. They may not have it today. Some of them are just raising their first money ever, so they're new to venture. They don't necessarily have a Rolodex anyway. Or they have a Rolodex for writing grants and papers, but not raising money. And that's where we can try to help, right? So one of the things we're doing is kind of building a Rolodex of connections from all of our portfolio companies and our prior experience and trying to think, OK, who are the cool people? And if they don't know somebody, can they make an introduction? Networking. Nothing— it's not super fancy. We haven't turned it into AI. It's just, you know, an Excel spreadsheet.

And but you're sitting across a bunch of companies who each one has different investors in them.

Yeah.

You have the ability to actually connect and say, well, we're all invested across of you. Let's make sure you're all introducing each other to each other's investors.

Yes. And that's when we had our general meeting last year. That was one of the principles, is try to get everybody in the same room. And we're all kind of, we're all scrambling trying to get ahead. So these are your peers. These are people you can probably rely on to make more introductions.

Give us a little macro sense of the state of life science investing. Obviously last year had a little bit of like blood in the water in terms of SBIR and NIH funding felt like it was slashed. And then also then in turn, I don't know if it was cause and effect, but also VCs were writing less in the biotech life science world. Give us a sense of where, if that is true, and if you think what the state of capital is now for life sciences, especially for if we're thinking, uh, for downstream capital, if we were to invest in companies now.

Yeah, so the, the short answer is there was a huge boom for COVID, right? If you, you can just look at Moderna stock is a great trace of like a little bit slow, boom, and then a little bit slow again, right? And A lot of other companies followed that same trajectory. 10x Genomics was the wunderkind of new startups, and they suffered similar, well, not as dramatic course. And so I think there's the underlying positive note is that there's still— this is a bad way of putting it, but there's 100% death rate in the United States. So everybody needs help. Everybody gets sick. Medical care is still needed. We haven't figured it all out. There's some great advances, but there's a ton of work to still do. And every one of these new types of technologies— you have CRISPR, then you have a little CRISPR bubble. You have CAR-T, you have a little CAR-T bubble. There's different antibody variations that create their little bubbles. But underneath that all, I think it's still up and to the right, and it will have to be for the foreseeable future. Entropy is still 100% on. From that point of view, I think there's still security in we all will need healthcare and better drugs, better devices, better diagnostics. As far as the NIH and SBIRs, That, yeah, there was a lot of uncertainty. When Elon's saying, tell me the 5 things you did this week, that's not that helpful. And then there was talk of reducing the NIH budget by 30%. It actually went up slightly. That's pretty typical course. That's kind of a solid core jewel of American innovation, and we don't want to mess with that too much. The SBIR program, I think, might be signed back into law today if our dear leader's not distracted by something else today. And then hopefully that will get kicked off maybe in May. I think we're going to miss the April deadline for SBIRs from NIH. So that's— on the other hand, if you have an SBIR that's in right now, I think they're to go back and look at the B+ grants. They're still reasonably good, they're just very competitive. And I've been seeing program officers say, "Write me a 2-page response to the reviewer's criticism." That usually means that they want to take it and bring it to council and fund it. And since they missed, they kind of need to go ahead and get that money out the door because they missed a cycle.

Okay. Give us a little bit— one more on SBIR. Let's say you don't know the life science world, but you're assessing it, startups that already have SBIR funding, how do you look at that during diligence? How much is a good sign versus—

I think it's a good sign. I think there's the classic criticism of any non-dilutive money is, is it distracting you? Is it aligned with your objectives? Is this going to get you customers or are you building something not relevant to your core business.

There are these SBIR mills where all you do is just build for the SBIR but never actually solve a customer's problem.

Yeah, I think I felt like I was getting close to that at times. But what we would do is write an SBIR and the distracting part would go to Yu Wa at UCSD and he's doing the basic research stuff and he's he needs to publish something that's a little not commercial necessarily. And then the rest of it would be, we're going to build, you know, so our skunkworks budget for doing X, Y, and Z to build the guts of this machine, the core technology of it. So that was one way to break into two vectors.

And do you track companies getting SBIR Phase I, then to II, then to III as they sign, like this is progress towards something? That shows that they're—

It can be. I mean, it depends on what they're doing in that, you know, hopefully they've done stuff that's well aligned to a product and commercialization and not just an exercise in basic research, which is cool, but it's not very commercializable oftentimes. And that's usually the case that they usually have some sensibility about they shouldn't go off on a wild goose chase. But yeah, any sort of traction, progress, money, that's all a good sign. Yeah.

What's, what's your daily life like with your portfolio founders now? How much time do you spend? Take board seats, check in with them when you haven't heard from them? Take us through a little bit of life with them as a portfolio.

It depends on some of the— one of the principles that I like to stick to is having had venture people come to me and go, can you run 3 more models of that? I don't want to be that guy, right? I think I want to definitely find cool people and let them run and not distract them with too many helpful suggestions, right? So I really check myself on that. And then occasionally I'll really dig in and try to be helpful, especially if I think I can be, or if they come to me looking for advice, then it's go time. And then Try to just check in with them. Some of them are really good. There's a variety. Some of them are really good and send out a monthly newsletter update with everything you'd ever want to know. It's just done. Some of them are— they won't reach out to you, so you have to kind of reach out and grab a lunch, grab coffee. Others, like with this company Ribodyne that's doing the therapeutic antibodies, I see those guys weekly. I'm on there. I'm in their lab weekly talking about stuff. So, and other groups I'm on, you know, 2 or 3 sales, you know, commercial meetings and stuff like that. So it really varies. And sometimes I like, I was writing a, one of these response to reviewers thing earlier this week. So I do write SBIRs or chip in on it when, if and when those are a thing again.

Do you get hit up by other investors assessing your portfolio to get feedback from you? And just like referral slash just due diligence, background check kind of? Is that pretty typical?

I'll have— yeah, just check in and what do you guys think about this? And just general questions about the team, the technology, the market, the usual questions.

Okay, sounds good. We're near an end here. I want to open up for questions, so get ready for that part. But you mentioned these little micro bubbles. What's, what's a bubble that's right now that you're seeing within your area, your space, besides AI?

Yeah, I was going to say AI is not a micro bubble. It's a whole kettle of fish. I would say Maybe I think CAR-T is going through many different— and I should say CAR-X, chimeric antigen receptor. T cells are one thing, but it can be macrophages. It's being used in all sorts of cells. There's a move to go from making those outside the body to inside the body. So can you inject the virus or the nanoparticles that will transform those cells into be the cells you want? And I think that's probably the manifest destiny of that technology. It just makes way more sense. Your body already makes cells.

Well, you need all these machinery to send blood out to do stuff to then send it back to the body.

Yeah, there's that as well. So the current state of the art is you do plasmapheresis and get somebody's white blood cells, freeze them, which is not good for them. FedEx them, as it were, to a central facility, do the magic, freeze them again, send them back, and infuse them. And in the meantime, that person is really cutting the cord from their parachute and hoping to intercept your therapy. There's— a halfway step is building a device that is in the hospital, for instance, right? So you don't have to send it out. You don't have to freeze it. Go down in the basement, there'd be a nice clean area for it, a dedicated laboratory. Um, one of our investments is doing something along those lines.

Dan Knudsen involved in that one?

Yeah.

Okay, got the pitch today.

Yeah. And then, um, there's, uh, the other way is just use the human body to generate these cells since it's already making cells. But it's— the immune system is unbelievably complicated and fiddly and varied and it's not going to be simple.

It's not going to be simple. All right, let's take your questions for all the above around this. Right here.

I have a question on the AI and the life sciences. Yeah. With the AI available across the board, many industries, what do you see AI will disturb or add into to life sciences. Like, I'm more curious, the area we didn't break, like cancer or other, where you see there will be more development to cure a disease using AI?

Yeah, that's— yeah, thanks. So the— I would say the first inroads will be in helping out the whole life sciences process in the English language. So if you can do documentation that can be CMC documentation or clinical trials or keeping track of verbiage. That's something that LLMs do already, right? They're language-based. Then there's companies that are already doing in silico analysis of small molecules docking to proteins, like AlphaFold is doing tons of protein work. There's a company here in town called Iambic that has better models and they're boiling the ocean and doing And then I would say there's a jumping off point from what you could do in silico. You have to ground that to the counterintuitive or the unknown biology stuff that's happening. So I think lab in the loop will probably be a next iteration of making AI better. But I don't think we've really figured out how to have you know, a trillion-parameter wet lab experiment, right? Do we— 384-well plates or 1536 plates are feasible, but what's your assay? Is it the case that we can have a boatload of those that are kind of messy by human standards, but it works for AI? I think that's— I see that as kind of the next frontier before before we are curing things. I, and I, I'm also a little wary of, um, there could be AI that is not understandable. The answers are not understandable by people. We don't speak RNA or DNA, or I don't, you know. Uh, and so there's going to be— right, how hard can it be? There's— it's going to be— there's, you know, if you've looked at one of those wall charts of metabolism You know, that's the simplified version and it's static, right? And that's kind of an idealized cell. So we got a bunch of different cells all at different times, depending what you ate. Did somebody just step on your toe? You know, there's a million different things that are gonna make that vary. And we are not gonna be able to read the answers and understand it 'cause it's overwhelming. So yeah, it's gonna be, fits and starts. And I think bringing a wet lab into it is going to be very helpful.

I have a friend who left venture a year or two back, and he said for him it felt like more he was just hearing pitches all the time and had to say no all the time. And then you occasionally get to say yes. And so it felt like just a lot of no. Do you find you have the same experience?

No. Yeah, that's a pretty common situation to be in because we have finite money and a finite amount of processing power to look at companies. So we'll look at lots of things and try to triage them as soon as possible for— to be humane to people coming to us and tell them, you know, this isn't a fit right now. But it's good. I try to keep I'll keep the pitches in a folder, and I try to keep that in mind. And I tell them, if there's a way to connect the dots down the road, maybe it's kind of an Ocean's Eleven situation where you've got the explosives and demolition expertise, and we got a safe cracker over here. So it may be no now, but who knows in the future.

And I just stole this from Chris. So a follow-up question. What percent of your job is listening to pitches you have to say no to, and what part of it helping companies develop into the next unicorn?

I would say we're winding down Fund 1, so we're only going to make like 2 more investments. So I think that phase is tapering. And so I spend most of my time trying to constructively interact with the portfolio companies without being that guy that has a million great ideas, right? And then we're also beginning to warm up our approach to our next fund, which we're going to be raising this year. So, most of the time is not listening. I still hear a lot of pitches because you never know. You got to still also keep in touch with people and track them and keep in touch with them for next, you know, the next round and next fund.

Hi, thanks. Thanks for taking the time. This is a group of kind of returning investors and relatively new investors, and by nature being in San Diego, we do get a lot of life sciences companies. For a lot of the first-time investors in the room who might see a life sciences deal for the first time, what's your framework for evaluating them in kind of a first principles way?

The simple answer is it's the team, the technology, and the timing is how I think about it, right? So the team is pretty straightforward. Are these people experts in their field? Are they motivated? Are they entrepreneurial? Are they Do they have kind of an it factor of some sort that you can kind of hang your hat on? Is the technology real? Is this cold fusion? You know, stay away from that. Or are they, are they so, are they unreasonably ambitious, right? Are they saying we're going to cure cancer? It's like, well, take it easy. So do they have something accomplishable? And do they have a path to get to advance the technology, right? Because you could have a super cool technology, and that kind of comes back to the timing part of it. Is the world ready for this? Are you too early? Are you too late? Are you gonna have to evangelize this product, or are people gonna be knocking down your door to get it? So those are the simple top, you know, the big chunks. It's kind of like Porter's Five Forces kind of breakdown, right? You know, and then And then we like to do what we call nerd out, right? And just talk to them, what do you, you know, really get into the nuts and bolts of does this work? Is this reasonable?

I ended up getting the mic while you were answering that, but my question was similar. So I guess I could drill down a little bit more into that same question and answer. You have a very deep tech background and you, in answering his question, you mentioned team first, then technology. Than timing. Did you put it in that order because you prioritize team above the other two? Because there's also a saying, "Bet on the jockey, not the horse." So I'm just curious for the thoughts by you on that. And then do you have a certain kind of strict methodology or set of principles that you kind of check off when you're doing your analysis? I've seen other investors that actually have spreadsheets and assign numbers to certain things. So curious about that.

Yeah, I've, I've, I've played with those rubrics. You know, I remember when we were setting up the fund, I'm like, okay, there's TRL levels and there's these blah blah blah and there's a bunch of different matrices and you can do all this stuff. And I think there's also— you have to also trust your intuition and having operated companies and founded companies, I think I have a different intuition maybe than the average bear, but I rely a lot on that. I think, you know, there's, there's a place for quantitation, of course, but I think a lot of decision-making is not conscious. And so you're going to—

it's—

you're just going to make a decision. You know, it occurs to you that this is a yes, this is a no. You got to check that, of course. But that's— I think, I think it's also very valuable to listen to that. So the team, I think as I said earlier, it's table stakes. If you're not a good team, it's not going to work, right? Or the— yeah, I've heard the bet on the horse, or bet on the jockey, not on the horse, or it's better to have the right people on the wrong bus story, you know? Because the right team will figure it out, right? They're going to adapt. And it's rare that you have the technology figured out Even if you do, you're still going to hit a million snags because that's life. And also, it's alphabetical— team, technology, timing. So—

Do you do syndicated deals? And if you do, do you trust the due diligence of your partners? Or do you still go through the full due diligence process? Just because my experience, sometimes you think someone does a due diligence. and when you start peeling about, they have different methods.

I think one of the common threads is it's not one size fits all. So when we're assessing the team, technology, and timing, or if we're doing the diligence, it's really a case-by-case story. So some companies are— you can just tell they've got their story straight, their data room's clean, they've got everything in place. It's very professional, you know, perhaps they had— we have a CEO who was a consultant previously and he worked at a large company previously. He kind of gets it. And there's others that are like, what's a data room? You know, so you've got to help them help themselves. And sometimes they have— we do syndicate and we're happy to co-invest with people. We try to have— not have sharp elbows and be collaborative. And so, again, case by case, sometimes they do good work and sometimes it's not that helpful. So.

Do you have a geographic preference for your investments?

This first fund, we don't want to go outside of the United States just because of the complexities of it. We want to keep it simple from that perspective. But this next fund will probably open it up. We're by nature, most of our connections are here in San Diego. But like I said, we've made one investment in Georgia. So that's not the beaten path. We have a little bit of a chip on our shoulder just for gamesmanship saying we don't want to invest in the Bay Area and Boston. We've got to invest in San Diego. Go on, baby. But you know, you want to have strong principles that are loosely held.

One last question. Yeah.

You mentioned a couple of times before about how in life sciences there is the almost research aspect to it, and then your team's kind of spun off this skunkworks to commercialization. Having been a previous SDAC member before, you sometimes see people are in various processes of government approvals, whether it be FDA, et cetera. What are the green lights you see on the path to commercialization and what are the big red flags that you see on that process and journey for a company?

Oh man, there's a— I'd say a green light is they've kind of got a prototype of some sort, whatever, in whatever domain they are. It's like something looks like it can work, right? Even if it's held together with duct tape, that's okay. That can be fixed. As I say, you have the adults work on it, right? You send it to Design for Manufacture and they make sure it doesn't have 17 different types of screws, right? Then as far as red flags, it's, I guess, the reciprocal of that. Then people who are maybe a little obstinate about or insistent And what occurs to me as unreasonable, it might be that they— a lot of founders need to be unreasonable to make things happen. So you have to be patient. But there's a dose dependency of unreasonableness that you want to look out for, I think. And then is the project too ambitious or too technically complicated? Can this thing be built? Shipped, sold, supported, serviced. You know, what's— it's not— you're not done after you sell it. You got to make sure it keeps working or you're going to have just a ton of headaches servicing it.

Let's give a hand to Will.

Thank you.