0:00:00 - (Yaniv Sneor): We only invest in fewer than 1 1/2% of the companies that apply to us.

0:00:04 - (Alex Pederson): There were very few exits. So you had about 7% of this set that had achieved an exit in one form or another.

0:00:12 - (Yaniv Sneor): We tell them, you know, we think you're probably more of a VC opportunity than an angel investment opportunity, and you might want to start that route now as opposed to, you know, wasting your time with us.

0:00:23 - (Andrew Kazlow): Welcome to the Diligent observer, where we help angel investors see what most miss. I'm your host, Andrew, and every week we explore what works, what doesn't, and why through conversations with experienced startup investors and operators. My guests today are Yaniv Sneyor, co founder of Mid Atlantic BioAngels and a biotech CEO, and Alex Peterson, an oncology commercialization pro who turned a capstone project into one of the most thoughtful self assessments that I've ever seen from an angel group. Now, the two of them recently analyzed data from over a Decade and nearly 1100 life science startup applications to ask whether the group's screening criteria was truly effective.

0:01:00 - (Andrew Kazlow): The short answer, yes. And in this episode, we discuss what it was like for them to go back through all the notes on these deals that they had missed.

0:01:09 - (Alex Pederson): Why?

0:01:09 - (Andrew Kazlow): One of the group's very first screening questions is, how much money do you need to reach an exit? And why? In life science investing being acquired early is far more important than, than growing big. I hope you enjoy learning from Yaniv and Alex as much as I did. Yaniv, Alex, thank you so much for being with me today.

0:01:35 - (Yaniv Sneor): Thanks for having us.

0:01:36 - (Andrew Kazlow): Well, I am looking forward very much to unpacking the analysis that brought us together. So you two recently published a really thought, thoughtful breakdown of a question that most investor groups have but don't take the time to fully examine and in particular examine with the level of depth that you all did. And so I'd love to start with a question for you, Yaniv. As the founder of BioAngels, tell me more about what this analysis was and then maybe how it came about, why you decided to do this.

0:02:16 - (Yaniv Sneor): So we've been around for about almost 14 years or so as a life science angel investor group, basically a group that invests exclusively in the life sciences. And by that we mean therapeutics or drugs, devices, medical devices, diagnosis, and digital health. And we do keep the records of everything that we've done. And we always wondering, you know, we have a very specific set of criteria that we base most of our decisions on, and we always are wondering how well we could do. And then Alex came up and said, hey, I, I'm, I'm doing a school project.

0:02:55 - (Yaniv Sneor): I'll let Alex describe exactly. I think it's more than just school projects and MBA and basically saying, could we work and we use your data, could use Mid Atlantic BioAngels data to take a look and to see how outcomes and everything else followed through. Alex, I'll let you sort of jump in to say what was the first question that you asked and how we sort of evolved into the analysis that you ended up doing.

0:03:25 - (Yaniv Sneor): Yeah.

0:03:25 - (Alex Pederson): Thank you, Yaniv. So like you mentioned, I was working on a master's in biotechnology and the capstone project. I wanted something that I was really interested about and it would expand my existing base of knowledge. Spent most of my career in mid to large size biotech companies with oncology, therapeutics and digging in deeply and looking comprehensively, really fit that bill. So I mean, like Yaniv mentioned, you have a high degree of visibility into the companies in which you invest.

0:03:57 - (Alex Pederson): People are tracking them very closely. You have a small set and you're, you just know everything about those companies. However, we had in the ballpark of 1100 companies that had applied. And periodically when I was a new member and talking to other people in the group, folks are like, yeah, should we loosen our criteria and bring more investments to the table? So this analysis dug in and took a look at the remainder of those companies, those that applied, but you decided to pass on for one reason or another, what happened and are we being unduly cautious about the investments that we're making?

0:04:36 - (Alex Pederson): So, I mean, it's an exciting analysis and it's one that I found very interesting to look at as an investor.

0:04:44 - (Yaniv Sneor): It's a good point because there is always complaint internally within the group that we don't invest enough. And should we be more, should we be more big risk takers or promiscuous in terms, whichever way you want to call it, we only invest in fewer than 1 1/2% of the companies that apply to us. And so it's a natural question to say, hey, you know, should we do something different? And that led, you know, fed really well into Alex's analysis.

0:05:14 - (Andrew Kazlow): Well, and this is, I think, such a common experience for the angel group operator. Right. Because you're bringing together 50 or 100 investors that you may have a general preference for the kind of things that you're looking at, but within that broad alignment, you've got all these different ideas, hey, can we see more of this kind of deal or that kind of deal or this other thing? And I Feel like there's this constant pressure test around how committed is the core operations team to the foundational thesis, or whatever the thesis is at the time?

0:05:47 - (Andrew Kazlow): Had you been pushing against or fending off that pressure for a while? And this was like, okay, we're going to do this analysis to finally give some data, or was it more of just a, hey, this would be really interesting, I think, would serve the members well.

0:06:00 - (Yaniv Sneor): The thesis had evolved, so it really has been the group that has evolved a certain thesis. And I think that it's based on preferences and valid arguments, you know, but it hasn't been pressure tested against a large set of data. So we have very specific investment criteria. Those criteria have stayed similar, but have evolved over the years. And people who've come into the group have bought into that thesis, but we've never pressured to sit it against a large set of data to see whether, you know, whether it causes us to miss something, whether, you know, because of that.

0:06:44 - (Yaniv Sneor): We obviously know about the things that we were about, the ones that provided us the return, but we had no idea about the ones that we said no to and whether we were being too strict, et cetera. And, you know, within a group and different personalities, certain people are more comfortable with higher degree of risk and they wanted to take more chances, and other people are less comfortable with it.

0:07:07 - (Yaniv Sneor): And so you're trying to balance that. Even though people internally do have the ability to write individual checks, if you really love something and the group doesn't necessarily want to go into it, you can always do it yourself. So we don't restrict anyone from doing that. We do have mechanisms to. We have an internal fund that we call a pool, where it's a mechanism to engage people, to get a very active discussion going and to have people create a portfolio and for everybody to sort of invest together.

0:07:36 - (Yaniv Sneor): But beyond that, and on top of that, people can always add more or add directly into a company if they want to. So it's the central thesis is there people are still welcome to do what they want, but in general, we end up using the expertise, the total think of the group to benefit ourselves.

0:07:59 - (Andrew Kazlow): Well, and I really want to get into some of the takeaways, specific outcomes, findings from the analysis. But before we do, Yaniv, could you just define maybe at a high level, what the thesis is, what the focus is for our listeners who may not be as familiar. What would you say are the core distinctives for the kinds of deals that are a fit for bioangels?

0:08:20 - (Yaniv Sneor): So first and foremost, we like to invest in regulated Products. So we want things that the FDA is going to get involved with. Right. And the group was formed to invest specifically in the life science space because we felt that in order to properly invest in this space, you really need to bring together a lot of expertise to properly diligence that area. And the idea for the group is to focus on a specific area where you can attract that kind of expertise into the room. So the majority of our members have day jobs in the life science industry that work for pharma, they work for device company, they're consulting in the area, they're doing regulatory work, etc. So that's the main focus. We like the deep science, the deep data kind of stuff. And that's where, that's where we want to concentrate. So we naturally invest in therapeutics, drugs, medical devices primarily. So between those two, that covers around 90% of our investment.

0:09:25 - (Yaniv Sneor): Plus and a little bit of digital health and diagnostics, which are sometimes especially the digital health isn't often as data heavy or science heavy, but we like the data and the science heavy ones and we can explain why. So within that, and by the way, geographically, we'll invest all over the world wherever there is an FDA type of entity that regulates the market. So within that we're looking for first and foremost, strong management team. And by that we mean a team that is led by a commercially minded individual when they already can understand and can elucidate to us how they will make money from the opportunity until they don't know how to monetize an opportunity. It's a bit too early for us to get involved.

0:10:17 - (Yaniv Sneor): We're looking for products that will change the standard of care, which will make basically doctors, systems health systems, et cetera, operate differently as opposed to things that will be just a little bit incrementally better. We're looking for products that will address large enough markets where there is a reason for somebody big, a big acquirer to come in and buy you for a lot of money. And when the market demand is strong.

0:10:42 - (Yaniv Sneor): And lastly, which is a little bit different than perhaps other angel groups or other investors, we are concerned with the potential heavy dilution that will come from future large VC rounds. We, as in private investors who write relatively small checks, we can't compete with $100 million checks coming in later on will just get diluted too heavily. So we try to concentrate on companies that may not need more than 25 or $30 million in total, which we hope that they will raise in multiple syndicated rounds. A syndicated round is where multiple angel Groups get together, some small VCs, et cetera, all put in maybe between 5 to 10 million dollars in that round.

0:11:29 - (Yaniv Sneor): The company takes the money, they go back to their lab, they, they hit some milestones and they come back a couple of years later to rate another one of those rounds. That kind of raise process is usually fairly friendly to all of the prior rounds, which means hopefully there's a step up in valuation. There isn't some large entity coming back in the future and cramming everybody down. And most importantly, it's an opportunity for us to eventually make money.

0:12:04 - (Yaniv Sneor): So we believe that we can actually be successful with that kind of scenario. So those are our basic criteria that we look for in our investment opportunities. And we apply that and have been applying it fairly consistently over the years.

0:12:19 - (Alex Pederson): And Andrew, one point on that is Yaniv's done a great job of articulating those preferences and the characteristics that applicants should be steering towards. So if any of the audience members go to the website, they can see these bullet pointed out, fantastic.

0:12:36 - (Andrew Kazlow): And that is, I mean, just so critical. I mean, so often there's drift and it's like, what are we doing here? So, well, well done that. That is very clearly articulated throughout. So, Alex, I want to shift to you into this analysis specifically. So given the focus, you said about 1100 deals over the last decade or so that were a part of this analysis. You're specifically asking, how are we doing in deals that we passed? Was our screening effective, so to speak? So tell me one, what the analysis process was like for you kind of running this project. And then two, what the core findings were from your work.

0:13:17 - (Alex Pederson): I mean, it was covering 11 years. And so over 11 years you had about 1,100 companies apply. Some of them, like the upper bound was they'd have up to five applications. It was pretty common to see two applications, three applications for the same company. And so you see a few more of the actual applications than the companies. For these companies, Yaniv had been collecting information that came in as part of their application, however, to conduct the analysis. How have they been doing? Where are they at now? Did they reach an exit?

0:13:51 - (Alex Pederson): I also dug in a little bit on did they have signs of life? Were they making clinical or commercial progress? Or had they stalled out? And so it required taking the starting point of a strong data set of what we knew when the company applied and then supplementing with where are they at now? And then taking a look at those other characteristics. Has an exit occurred? Have we seen signs of the clinical or the commercial progress and supplementing all of that so that the analysis could move forward in a comprehensive fashion.

0:14:27 - (Alex Pederson): To me, it was really, really instructive, if you think about it, in the form of different hypotheses. So one hypothesis that you can test is there are a lot of companies that would have produced meaningful exits that we passed on. So testing that hypothesis, did we see it? What would a meaningful amount be? A. There were very few exits. So you had about 7% of this set that had achieved an exit in one form or another.

0:14:56 - (Alex Pederson): And then looking beneath the hood there at the quality of the exit, the quality of the exits were rarely the type that had bioangels invested at the time of application that this would attract through. And so that was a big part of the analysis. Digging in there, what happened, how many exits were there, what was the quality of the exit? And then what were the other learnings that could track back to?

0:15:22 - (Alex Pederson): I mean, ultimately this is about whether your screening criteria are working. And with this, it looked like high level, the screening criteria were working pretty well in terms of invest in the companies, see a difference in the performance of those portfolio companies versus the applicants where the group passed, and then also not be woken up in the middle of the night with the nightmares of those. Those deals with the massive exits that you passed on.

0:15:53 - (Andrew Kazlow): So this is fascinating to me because I've done similar analysis with angel groups, you know, trying to look back at data over a few years. I haven't attempted a full decade, so that's quite the achievement. But like, tell me how you actually did this, because oftentimes, you know, when you passed on a deal, you're not an investor, you don't really have much information on these companies. A lot of the time it's not publicly disclosed. How did they do?

0:16:21 - (Andrew Kazlow): And 1100 companies is a ton of companies. So I imagine this took a long time. What was the process like for you actually running this analysis? If I'm listening to this and saying, man, I want to know how's my group doing? And I wanted to do something similar, how would I do that?

0:16:37 - (Alex Pederson): If you take a look at this industry, there's actually a lot of information about these companies. So if you want to see, for a therapeutics company, for example, where are they at what stage? You can pull up their website and then they'll tell you where their portfolio is at. Do they have a commercial product? Where are they at in terms of the. The clinical trials? So that was one way to see it combine where their portfolio is at with the news updates. And that'll usually give you an inference on are they still alive?

0:17:07 - (Alex Pederson): Have they stalled out? Because you can have shadow companies where there's a posting on LinkedIn and they have a company landing page, but they haven't made any progress in two years. Probably not a viable entity at this point for the exits. I was leveraging PitchBook. So PitchBook, you know, they do a pretty good job. If an IPO has occurred, it's probably in PitchBook. If an acquisition has occurred, it's usually in PitchBook.

0:17:36 - (Alex Pederson): It's the deal quality where sometimes there was a bit of a divergence. IPOs, you can see what, what happened with the IPO and you know, you can back into whether this would have been a fruitful deal or not. With the mergers, you had two different main sets. Were the deal terms disclosed or were the deal terms not disclosed? My general assumption was going to be take a look at the ones that were not disclosed.

0:18:03 - (Alex Pederson): However, if they didn't disclose it, A, it's probably not a material enough deal and B, the ones that were not disclosed might working hypothesis was that in general it probably wasn't going to be the sort of mega deal that you, you'd lose a lot of sleep over. But I'd take a look at it. Where were they at? How much clinical progress did they have? Did they have any commercial project progress, who acquired the company?

0:18:28 - (Alex Pederson): And those were some of the inferences. And so there were a couple of undisclosed that moved up to the, to the possibly good deal category. But with mergers with deal terms disclosed with IPOs, you have a lot of information about that publicly when you take a look at how much was your front end payment, how much is coming in, the milestone payments. So a lot of this stuff is out there. It's the process of knowing where to look, aggregating and structuring it.

0:18:57 - (Alex Pederson): I mean, it turned out to be a monster of a database and it was pulling all this information through in a comprehensive form and then supplementing it for each of the companies to be able to perform the analysis and answer those questions. Were there good deals that we passed on and were there any other trends or, or signals that we were seeing that should impact our screening criteria?

0:19:23 - (Andrew Kazlow): A quick note before we continue the conversation. Alongside the Diligent observer podcast and newsletter, I also run an outsourced operations service specifically built to serve angel networks. My team handles things like initial screening, social media, newsletter prep, platform management, and a whole lot more. The kinds of things that either aren't getting done or shouldn't be done by busy community leaders.

0:19:45 - (Andrew Kazlow): If that sounds interesting to you, send me a note. Now back to it. Love it. So, Yaniv, coming back to you, one of the things I loved about the analysis was that you actually broke down sort of categorically how these outcomes mapped. So you had 1x ers. And I forget the exact breakdown. It's in the report, which everybody should go look at. One of the things that was interesting is you had four winners in the past category. So, Yaniv, I'm curious for you. As you're reviewing this analysis and working with Alex on it, you see these winners and inevitably you've got to be thinking back to when they came through and you're like, what did we miss?

0:20:26 - (Andrew Kazlow): I'd love to hear what that was like for you to actually do this analysis. Because that's, I mean, tough for anybody. You talk to VCs all the time, and the stories they tell are, hey, this is when I passed on Google. This is where I passed on Uber. And they just regret those moments for their whole career. Obviously, the core outcome from this analysis was that in general, the screening is pretty good.

0:20:49 - (Andrew Kazlow): But I'm curious what it was like for you to have to face this list of man, what if we had moved? What was that like for you and Yaniv?

0:20:57 - (Alex Pederson): Were you nervous at all going into that?

0:21:00 - (Andrew Kazlow): Yeah. Yeah. It's bold.

0:21:01 - (Yaniv Sneor): Actually. I was not. I really. I was not. I mean, it's interesting because Alex says, this is a monster database. And I always was waiting off to do an analysis because I felt that our n. You know, our size was too small in terms of the database, the. The number of companies, because we invest in so few companies. I always felt like we don't have enough data, you know, to actually run a significant analysis. So when Alex came over and says, I'm thinking of doing this, it was great. And obviously we had enough data when we saw. When we began to see some companies and, you know, we worked on some of the criteria together, etc. But the ones where proved that perhaps we potentially missed.

0:21:47 - (Yaniv Sneor): I went through my notes for every one of those to see what was the discussion like? Basically to understand what was happening at the time. Because, you know, the ultimate goal here is to learn from what we do so that we can do things better. We're trying to constantly improve ourselves, improve our processes, and learn from it. And I don't know about all of them, but in many of the situations at the time.

0:22:14 - (Yaniv Sneor): And one more thing to understand, an application is a frozen moment in time, right? So you could receive an application from a company right now that on January 1st is in disarray or doesn't have a product or the CEO is in flux, et cetera. But six months or a year later, suddenly they've gotten their act together, they've had it discussion with the fda, there's a new CEO on board or whatever it is.

0:22:44 - (Yaniv Sneor): We may not see that company at that time. We may have not received an application at that plus 6 months or plus 12 months period. We can only evaluate the application that we received at the time that we received it. And so going back to those companies and when they applied to us, it was often the case that in a couple of situations the company was in disarray. There was one company, I remember very clearly that there was a very strong internal discussion that there were multiple investors and the cap table was not clean, as we call it. There were a lot of different investors.

0:23:22 - (Yaniv Sneor): There were issues with the valuation. The company wasn't moving forward. People were figuring out what to do. The valuation wasn't appropriate and people were not happy. The existing investors were very unhappy and it was difficult to bring in new investors. So we sort of sat out and said, let's get it cleaned up or let somebody clean it up. Somebody did, but we weren't offered the opportunity to invest after they were, you know, that's, you know, can we take a look at those situations in the future and maybe be more proactive or maybe somehow see if we can check in on those companies when somebody, if somebody comes and cleans them up. It's hard to tell, but at the time when those decisions not to invest were made, they were made for the right decisions for the right reasons.

0:24:16 - (Andrew Kazlow): Were there any adjustments or changes that came to bear as a result of you doing this? Look back, did anything change in your process now as a result of this or did you just sort of validate? No, it's working really well. Let's continue sticking to our guns.

0:24:33 - (Yaniv Sneor): Well, we are incorporating this now into. So we've created our own internal data analytics committee. We've, we've. Anybody in the group, if you want to join, by all means join it. Because we're all. This is a data intensive industry and so we have a lot of geeks in the group who love data and people are excited about this and we've opened up.

0:24:55 - (Andrew Kazlow): Yeah, this, seeing this analysis from a group in focus in the life science space did not surprise me at all. I was like, this is very on brand. We got to have data for every decision. I love it.

0:25:04 - (Yaniv Sneor): So people love it and we are opening it up to our members. And we're saying, okay, what else do you want to ask from the data? What else can we do about it? Right. We've. The first thing that Alex did is share our data internally. We ran a few internal webinars for our members where Alex talked about the data, the work that he did, and the outcomes that came out of that data. And then once we've talked to all the group about it, we've posted the data internally, created our own committee from it.

0:25:39 - (Yaniv Sneor): And the idea is for that committee to continue to work and ask questions of the data. And as we meet, we have a summit every year where we, you know, because the group has gone virtual, right? So we meet virtual and in person, but most people, you know, they like to stay home. But in our summit, we tell people, come on in once a year, if you have to fly from wherever you are, please do so. And we, what we're going to do this year is we're going to have the data analytics committee actually report on its findings at the summit and use that as a basis to continue discussion as to what can we do better, what should we, should we or can we do in terms of our screening process as well as our decision making process and, you know, all of our other SOPs and standard operating procedures in terms of our diligence, et cetera. So nothing really earth shattering has changed. And Alex, please let me know if I'm wrong.

0:26:38 - (Yaniv Sneor): But, you know, I think it's incrementally small changes that we're looking at things where it's nice to validate that what we have been doing is sort of, has been good. And then we just, as we refine the analysis, I think we'll get more and more, you know, more data out of it and, you know, improve the process even more.

0:26:58 - (Alex Pederson): And I agree with you, Yaniv, again, going to what's laid out on the website, going to the way that the group has approached screening and what the group has been looking for for an investment, I feel like it was more, you said, validating. It was more a confirmation that it's not wildly out of whack and it's not so conservative that you're missing out on a ton of home runs. But some of the little nuances in there, it's things like whatever your paradigm is, if you have five main criteria or seven main criteria and what you want to see, how willing are you to loosen up if one or two of them is not up to par?

0:27:40 - (Alex Pederson): Do you require everything? How stringent are you with that criteria. I think this is one of those things where the vibe I got from those discussions was a lot of members found it illustrative, and it was reaffirming on the way that the group had been approaching screening as opposed to, you need to completely restructure. For me, one of the things is taking a look at your type of technology, the speed to commercialization, the amount of capital required if you break it down into your therapeutic, your med device and the diagnostic.

0:28:15 - (Alex Pederson): Yeah, they just have different paths, different time requirements. And so we may want to put a little more nuance on there for the company type. And then like Yaniv mentioned to me, once I get the time, I'd love to take a look at a couple of years of how many large exits were out there that were not part of this applicant set and that would be that type of extension. And so, I mean, Yaniv said it, we're an analytical group.

0:28:44 - (Alex Pederson): We're not going to stop at one publication. It's something where we keep on looking to see, is there an angle that we're missing. And it's also a competitive group. We want to make sure that when we're cutting a check, this is going to be the right place, that we have confidence that it from a procedural perspective for things that are foreseeable at the time of application, that we're working with a process that's going to be as effective as possible to identify those companies with the highest likelihood of reaching an exit with the right amount of capital and the right amount of time.

0:29:20 - (Andrew Kazlow): It's funny, as you both are talking, I'm thinking about how often the pattern emerges where great analysis is done, and then the customer that's receiving that analysis says, this is wonderful. Give us more. And you just get another homework assignment. And it continues on because more questions emerge and people like being able to make these decisions driven from data. So I'm very excited to see the continued evolution of the group and the publications that you all put out.

0:29:49 - (Andrew Kazlow): One topic I wanted to pivot to, to make sure I understand because this really stood out to me from this initial analysis and the following analyses I know you're working on. You all have a very thoughtful focus on a specific dilution framework, a specific time to exit, a specific size. Help me understand that, because general principles, perhaps I'm not worried about dilution because if the pie is getting bigger than the size of my stake is also getting bigger. And so even if it's a smaller piece of the pie, no big deal.

0:30:26 - (Andrew Kazlow): But you are in a very Specific market. So help me understand the emphasis on getting deals closed before they go big. You have a specific quote in the very first analysis that I really loved and it said I'm going to quote exactly. Angel scale life science exits are about being acquired early, not growing big. So tell me more about why that is and what you found in the data that supports that.

0:30:52 - (Alex Pederson): For me, it was really helpful to take a look at what could happen. And so if you look at what could happen, that helps to illustrate the importance of the criteria that are in place. If you take a, like I've worked in oncology, you take an oncology therapeutic company, okay, from the point where they would apply, it's going to be a preclinical asset. They need to wrap up their pre clin, they need to get into humans, they need to go through generally three phases of clinical trial development.

0:31:20 - (Alex Pederson): You could be talking 15, 20 years. And then if it is going to be ultimately successful and launch commercially, you're probably going to be bringing in, I mean, at least $500 million, if not more, to be able to fund all of this clinical development to account for any sort of hiccups or mistakes in your clin plan if you want to actually scale up the company. So I think of it as the more time and the more individual nodes that could fail, that increases your risk.

0:31:52 - (Alex Pederson): The time obviously impacts your rate of return that you'd rather get your payoff in one year than 10 years. But then also the likelihood that you'll hit a situation where, whether it be the company or whether it be the macro environment, you're going to need to raise in a form where it's going to disadvantage your early investors. The more time, the more money, the more risk that you're going to hit one of those rounds where the new investors are going to squeeze the old investors.

0:32:22 - (Alex Pederson): And so, I mean, even in the set, the companies that exited, we saw a lot of the exits in that ballpark of seven years, and that includes mergers. So they didn't actually hit the commercialization stage potentially and they were acquired by another company. It's still a long time frame. And so I think of it as the companies that don't have their eye on the ball in terms of what is your exit going to be.

0:32:48 - (Alex Pederson): What specifically are we strategically putting in place to be able to achieve that exit? Whether it be running the right trials, producing the right evidence for a lot of the med device or the diagnostics companies, they probably need to have some commercial traction before that acquisition. And, and so what would that look like it's having a hypothesis on that path. And then as the investors, we're able to pressure test that other alternatives are companies that have like three to five different programs that they want to run.

0:33:19 - (Alex Pederson): They're trying to raise $5 million, but they want to run five different trials. Like sometimes there's an inconsistency in what they're asking for and what they're going to need. Some of the companies that angel groups would decline in a reasonable basis. They might be great venture investments, but they're going to need $750 million before they hit their exit. It's just foreign angel group, what we're investing on the front end, the time consideration and then the likelihood of dilution in one of the later rounds.

0:33:53 - (Alex Pederson): These are some of the considerations in terms of why those are our working hypothesis.

0:34:00 - (Andrew Kazlow): So it sounds like some of the key questions you ask more in the founder diligence. This comes back, Yaniv, to what you mentioned about really focusing on the team and understanding can they take this to market? Maybe center around what is your exit strategy? That is a common question in angel investing, but particularly important here because if you hear them say something like, oh, we're going to IPO in four years, you go, okay, thanks for your time.

0:34:27 - (Andrew Kazlow): Is that. Am I tracking?

0:34:29 - (Yaniv Sneor): Yeah. So to add to Alex's point, even before I answer yours, there is a very specific purple unicorn that we're looking for. It is traditionally a money and data intensive industry and an area where people, where companies require a lot of that to exit. But there are specific situations where you can exit earlier and with less amount of money, which would allow people who write check sizes such as ours to actually be successful. So that's, it's. We're not saying this is not a great company or this is not, or this is a good company. What we're saying is, is this an opportunity for us to make money in.

0:35:16 - (Yaniv Sneor): Right. Given the amount of money we can put in, given how much money will be required in the future, potential dilution from the future, etc. Etc. So that's what we're trying to figure out. And as time, as things take longer and longer, uncertainty builds as well. I mean, you don't know. You can sort of see what's in the ClinicalTrials.gov pipeline right now. Basically, you can track every company that currently has a clinical trial open, but what's going to happen in 7 years or 10 years or 15 years? Very difficult to tell what other technologies are going to go after. So time adds a huge amount of uncertainty that we don't have the money to or to take, you know, to deal with in that sense.

0:35:58 - (Yaniv Sneor): And so we try to look at opportunities where a company can generate enough data in an area that is of interest enough to the farmers. And this is where the background and our day jobs of our members comes in is critical because our members see and have these discussions in their day jobs all the time, so they can bring that perspective and we can understand what, you know, hey, if this is really good and they have the right data, they'll exit with this size of trial in this amount of time because all they need to show is X and somebody who's going to come in and buy them.

0:36:36 - (Yaniv Sneor): So, apologies, but I wanted to discuss that.

0:36:40 - (Andrew Kazlow): Yeah, the question is just how does this shape your screening because you're specifically looking for these types of outcomes. So I imagine a lot of this comes down to the founder's vision and strategy and how are they currently. Right, because you're engaging in them at this present moment. How are they currently envisioning the future of the business? And so what's your exit strategy has perhaps extra nuance here than it might in some other industry.

0:37:05 - (Yaniv Sneor): We go to a lot of conferences and now since the pandemic, we can do, we can be all over the world through Zoom and meet many, many companies. And they, and we get tens and hundreds of, you know, we go to bio, we get 300, 400 invitations to meet with companies. And almost always one of our first questions to the, to the company that's trying to engage with us is how much money do you think you're going to need to reach an exit?

0:37:32 - (Yaniv Sneor): That's almost always the first question. And you, it tells, the response, tells you a lot about how much the founder has thought about that, that path. And, you know, because for us, it's a way to figure out is this appropriate for us or not. So we, we only meet with them if they, if we find out that it's a, you know, more than $30 million or so, we tell them, you know, we think you're probably more of a VC opportunity than an angel investment opportunity, and you might want to start that route now as opposed to, you know, wasting your time with us. Because we want to make sure that they don't, you know, they only spend their time applying to us if it makes sense for them. There's a chance for them to do that.

0:38:13 - (Yaniv Sneor): We ask those questions in our application. We, it's one of the first things that we screen for. It's with the top of our application. So the first thing that we screen for when we talk about a company, so it's a very quick discussion. If we see that somebody has gone over those numbers and in the preamble in our applications, we say these are the things that we prefer. These are the things we generally look for.

0:38:35 - (Yaniv Sneor): And the amount of money to reach an exit is there. It's right up there. So it's we, because we, we don't want to waste people's time filling out an application for us with very specific information if it's not the right fit. You know, again, we're not trying to figure out what companies are good or bad. We're just trying to figure out if there's a fit and whether we can make money in that opportunity.

0:38:54 - (Andrew Kazlow): Well, I know we're coming up on time. Yaniv Alex, final lessons or takeaways from your recent analyses that you'd like to share with our audience that we haven't covered?

0:39:05 - (Alex Pederson): Yeah, I mean, one of my big takeaways is that a lot of these companies, they have really exciting promise. And we're just looking for the companies that have thought through, excuse me, are able to bring together each of those different elements that are important to make it a successful company. As an investor, I mean, you need to nail it. It's just if you're going to be an angel investor, you need your return in a period of time in a relatively low dilution environment to be able to make that work. And so we're excited to help more companies to bring these technologies to be able to help some patients. So it's nice to be able to help the patients and to come up with good returns.

0:39:48 - (Yaniv Sneor): At the same time, for me, you know, it's all about working with great people like Alex, you know, surrounding yourself with, with people who are experts and who are thoughtful and bringing together many different people in and, and with different disciplines and backgrounds and generating an environment for thoughtful analysis and discussion so that, you know, together we can come out with the best kind of, you know, outcome based.

0:40:19 - (Yaniv Sneor): We start with a discussion as to what we want the criteria to be. We continue to evolve it, and then we try to make sure that everybody contributes to the discussion so that ultimately we can make the best possible decision. It's impossible to tell how good or how bad it's going to be in the end. But, you know, going back to your question as to do I have any regrets, you know, if you did the best possible analysis you could with the information you had at the time, I'm happy with it.

0:40:48 - (Andrew Kazlow): Love it. Well, special shout out to the Angel Capital association, specifically the Data Insights Monthly, which is where this analysis was initially featured. And I believe there's going to be multiple installments, so if you're not on that list, check it out. We have will include links in the show notes Yaniv Alex, thank you for your time today. I look forward very much to our next conversation. Thanks for listening to this episode of the Diligent Observer. I'm your host, Andrew, and if you're an angel investor looking for essential angel intel in five minutes every week, I think you'd enjoy my newsletter. I send my best stuff, interesting deals and more straight to your inbox so you never miss a thing. Subscribe today@thediligentobserver.com.