In this special bonus episode, we explore the world of venture capital for medical diagnostics with an industry titan. Ever wondered what it takes to get an early-stage health tech startup funded? We're sitting down with Michele Colucci, the founder and managing partner of DigitalDx Ventures, a venture capital fund focused on personalized medicine and diagnostics. Michele, a serial entrepreneur and attorney turned investor, unpacks the complex process of identifying and funding the companies that will shape the future of healthcare. This episode tackles the core problem for so many innovators: how to secure capital and navigate the treacherous path from a scientific breakthrough to a commercially viable product.
Michele Colucci shares the origin story of DigitalDx Ventures and their unique investment thesis: funding companies that enable earlier, less invasive, and more accurate diagnoses through technology. She reveals her firm's rigorous 72-point evaluation framework, a machine-learning algorithm used to vet the hundreds of companies they see each month and separate hype from true potential. A major focus of the conversation is the reality of AI in medical diagnostics. Michele explains that while technology is a critical enabler, true AI is often not necessary or even relevant for many innovations; the key is digitizing biological signals to gain new insights.
We dive deep into the most significant hurdles for founders, including the critical importance of scientific validation and why so many academic papers fail to be replicated at scale. Michele offers invaluable fundraising advice for health tech founders, emphasizing the need to clearly articulate the problem you're solving, prove your science, and build trust through transparency. The discussion also covers the immense challenges in diagnostic reimbursement, exploring how new payment models from employers and direct-to-consumer approaches are creating opportunities outside of traditional payers like Medicare. Finally, Michele breaks down the trends shaping the future, from the rise of non-invasive diagnostic technology and point-of-care solutions to the "box" problem, where companies oversaturate the market with proprietary hardware. This is a masterclass in what it takes to succeed in the high-stakes field of venture capital for medical diagnostics.
Learn More From Our Guest / Episode Resources:
Introduction
Dr. Trevor Royce: Welcome to Health Tech Remedy. We're doing something special today. You're tuning into an episode on our bonus series on investors. In this series, we sit down with investors, including venture capitalists, who focus on health technology, allocating capital, and providing guidance that shapes the future of care delivery. I'm Trevor Royce, joined as always by my co-hosts, Tim Showalter and Paul Gerrard.
Dr. Tim Showalter: And today we're thrilled to kick off the series with Michele Colucci. Michele is the founder and managing partner of DigitalDx Ventures. Michele is an attorney, investor, serial entrepreneur, and philanthropist. She serves on a number of boards for diagnostic companies.
Dr. Paul Gerrard: Michele, welcome to Health Tech Remedy. Thanks for joining us.
Michele Colucci: Thank you. Nice to be here.
Dr. Paul Gerrard: First, we'd love to learn some about your story, your background. You and I have met in the past, but you've done a lot. And so, for our listeners, we'd love to hear about it.
From Serial Entrepreneur to Health Tech Investor: The Story of DigitalDx Ventures
Michele Colucci: I'm a lawyer. I'm a serial entrepreneur, founder and managing partner of DigitalDx Ventures. We are an early stage venture capital fund in Silicon Valley focused on personalized medicine diagnostics and targeted therapeutics. Anytime you touch the healthcare system, you got to figure out, make some decision your doctor has to do or you do based on what's wrong with you. Is there anything wrong with you? Might there be something wrong with you? Might it be something that doesn't seem like it is?
It's that whole challenging piece of diagnosing what's wrong with you and then based on who you are, your personal genetics, epigenetics, microbiome, et cetera, what works for you as a treatment and what doesn't. That's the type of companies we invest in and the impact we're looking to make on the healthcare system, moving everything to early from late.
Dr. Paul Gerrard: And how did you get into this world of venture capital? A lot of lawyers out there, most of them don't go into venture capital.
Michele Colucci: Yes, life takes us in many strange ways. And I think people always think that they map out their life. But I think sometimes if you let life take you in the direction you're meant to go, then the opportunities present themselves that are exciting and game changing. I've been, as I mentioned, a serial entrepreneur, an attorney first, and then I knew what law was.
I really studied law as an empowering way to become an entrepreneur because I could do my own contracts. I understood what was being said. I never intended to practice long-term, but I did give my law degree some real life experience. I practiced a few years. And then over the years, I used law, of course, all the time. But I was very excited about building and creating value.
And solving problems has really been, I think, my M.O. I've been in multiple verticals, and all of those verticals are about solving a problem, gathering people together, finding solutions, thinking about problems in nonlinear ways. Not the traditional A to B to C, but sometimes it's A to P to Z to B.
I've been about seven years guest lecturing and mentoring at Stanford Engineering School in Global Marketing and Entrepreneurship, and that's one of the classes I always love to do, which is on the whole concept of the non-linear approach. Whether you're looking for investors or whether you're looking for customers or you're looking for KOLs or team members, thinking about how to do that in a non-traditional way and thinking about your solutions in non-traditional ways is something that I've always enjoyed and found consistent through every business that I've done.
Dr. Trevor Royce: That's fantastic and I guess to continue on that thread a little bit, will you bring it in for us and tell us how that applies to what you're doing today with DigitalDx or digital diagnosis and a little bit about what sets you guys apart and what your focus is.
Michele Colucci: I had a company in technology and one of my lead investors is a good friend of mine who was the most successful investor in this diagnostic area, Ted Driscoll. I sent him companies; he was very successful. One of his most successful companies was one I sent him and he just looked at me one day and he's like, "Why are you doing this? I love what you're doing. I've invested in your company, but I really think you should be investing in healthcare. And if you would consider it, then I'll back you and can start a fund. I'll be retiring at some point soon. But I think that this is a good area for you and you should seriously consider it."
I went to one of my close friends in private equity. And I said, "Here's what I'm thinking of doing." I laid it all out for him. And I said, "Does this sound crazy?" Ted was a fantastic mentor. He's amazing, brilliant. He was the first investor in GeneWeave. And so my friend said, "Not only do I not think you're crazy, but I'll give you your first check."
He seeded our first fund and we were off to the races. We brought on Eric Weiss, who was the head of emergency medicine at Stanford, first concierge medicine doctor here at Silicon Valley. We really wanted an MD. And Eric, I'd known for 20 years. He was a great choice and a good person, very innovative and wonderful to his patients. And so he joined me.
And then we met with David Kirk, who was at NVIDIA at the time. He was their chief scientist and architect, built all the technology on our line, gender of AI. And he's like, "I'm really interested in this. Can I meet you on April 28th to discuss it?" And I thought, okay, sure. That's specific, but all right. "I'll be in the Bay Area. Let's have lunch." I said, "Sure." So we did.
What he told me at that point was he couldn't tell me before, but that was his last day at NVIDIA and he wanted to join the fund in addition to investing. I was thrilled because there is no bigger authority on AI and technology. The reality is all these companies come to you—we see 100 companies a month—"Oh, we're doing AI." Well, 90 percent of the time they're not. And because you don't actually even need to in a lot of these cases for what we're doing in science, technology, biology, chemistry, et cetera, that technology overlay of all those verticals. You're really digitizing signals, digitizing the biology to be able to analyze it and predict things or identify things that are coming together or things that are setting or whatever your answer is, amplifying signals.
So David was a fantastic addition. And then we built out from there. I just said to myself, I didn't grow up with science, although I've been involved in multiple health journeys. Two of my closest friends died from later diagnostics, one of whom's daughter is my daughter. And now, so I felt very strongly that this should not be the case. We should not have to figure out and spend months or years trying to figure out what's wrong with you.
It's that overlay of technology that really gives us insight and more specificity, more sensitivity, specificity, more accuracy at earlier and faster. And oftentimes for less money because we're focused on non-invasive. What goes out of your body is telling you what's going on inside your body or digitizing the signals of what's going on inside your body, non-invasively. Those are all opportunities to be able to find solutions that are accessible to everyone.
And one of the other things we focus a lot on is because of this, of some of the people that are close to me, some who survived illness, some who died from illness, was that they come from all over the world. And one thing I noticed was there's not a lot of companies that were focused on different genders, different ethnicities, and really trying to understand, look, if you grow up in this one area, your body will react different because the immunity is different. Things that around you are different, what you grew up on and what your body developed in immunity is different than when you travel somewhere else.
Just trying to make sure that all patient populations were considered when we do these testings, when we get these tests out there so that people can really feel comfortable that this is an answer for them personally, not just a generic answer for 80 percent of population. It works for them and it directs them and it directs their doctor of how best to treat their patient. And we want to help doctors make better decisions, because they're inundated with data. Before they had no data. It's like a stick in your mouth and a light. And now they have too much data.
And there's as a lawyer in me, there's also liability associated with that. So being able to really empower these doctors to find these things earlier and not say, "Oh, this person's complaining. They're just complaining." No, actually, there is something underneath that. There's been so many studies about how people listen to women complaining about something versus men. And so I feel like there's this felt like there's a huge need to fill this gap. And Ted pulled me in to do that.
So I built out this global expert and entrepreneur network of experts because there were so many areas that I saw we needed to understand. We need to understand genetics, epigenetics. We needed to understand regulatory reimbursement. We needed to understand AI technology. We needed to understand the patient journey. We needed to understand the doctor's practice and their standard of care, the way they integrate products. We had to understand how hospitals operated, how the incentives work, all that stuff. And those are multiple 40-year careers. There's no way that a small team of two or three or four people, whatever it is, can get their head around all that.
And when you hire people to do that, they don't have the same skin in the game. So we built out this group of global experts and that's really been what's catalyzed our firm to the forefront of this area, other people come to us to validate. Other people come to us to lead the investments. If they lead, we'll follow. And that's been, I think, one of the most gratifying pieces of what we've been doing.
The Hype vs. Reality of AI in Medical Diagnostics
Dr. Trevor Royce: That's amazing. I want to just quickly go back to a comment you mentioned earlier about how AI is so hot from the investor side that companies in their pitches basically feel like they have to shoehorn it into whatever their product is and it may or may not actually be a good use of AI. And I'm sure we'll talk more about this as we go into diagnostics. But have you seen that where pretty much everyone feels like they have to have some AI piece of what they're doing?
Michele Colucci: I've seen it both ways. Let me be honest. Almost all the great opportunities are enhanced by technology. That doesn't mean AI. That could be microfluidics innovation. That could mean machines that process stuff in a more efficient, effective way. That could be multiplexing. That could be something with that can have a thousand wells instead of or, there's all sorts of ways that technology has improved or is improving diagnostics.
So I do think that people feel the need to have some kind of a component of AI, but oftentimes it's just not relevant. So technology is relevant. That's different. So we really focus on the technology overlay, not just the AI, although the AI, when you're talking about examining biofluids, that is a big piece because it does, when you digitize all those signals.
You can see things differently and more accurately and you can see things clearer. If you have a small amount of something that's shedding the blood and you put it through a machine and you digitize that signal, you can amplify that. So all of a sudden you can see a lot of it instead of just a little bit of it, which makes it much easier to identify what you're trying to see in the body.
So yes, people are all initially rushed in on AI, in the same way they all rushed in to have at least a female face on their deck, which I don't, it's not really what I want to see. I want to see diversity of thought, but I want to see meaningful diversity of thought.
So people who really contribute to the solutions and the thinking behind the decisions the company makes because it's just better decision making. But in terms of AI, people did rush in initially. We all have been challenged that how they were articulating it. 90% of the time they back down. Yeah, actually, it's just machine learning or it's just because AI is just not always relevant. That's the bottom line. So maybe it's pattern matching you need, or maybe it's, as I said, a new form of microfluidics. Maybe it's printing, 3D printing you need or something. But technology is pretty much enabling this vertical in a way that produces all the innovation.
An Investor's Diagnostic: The 72-Point Framework for Evaluating Startups
Dr. Tim Showalter: You mentioned you're sometimes looking at 100 companies in a month. And my impression is that the diagnostic side of this industry is among the most challenging. There's the technology and there's lots of different approaches. People have different clinical indications they're pointing towards and all of that shifting. And as you mentioned earlier, there are particular reimbursement considerations in this space. And I'm just thinking as you look at all these companies, what is your diagnostic approach or what's your overall decision framework for how you're trying to prognosticate, so to speak, for the various companies in front of you?
Michele Colucci: When I started this, one of the things I was insecure about was some of my knowledge of very specifics. So what I did is I spent a lot of time analyzing the most successful companies out there. And out of that couple of years of research and getting myself comfortable that I was understanding a lot of these areas with global experts' input, I created a 72-data point machine learning algorithm that identifies the major things we want to see, how we think about them, and benchmarks it against other companies.
So early on, I created that algorithm to help with a gut check and identify the areas that we do need to look into. And it's not all areas for all companies. Sometimes certain areas are more important than others. One thing that you do realize is on the first pass, there are some major things. And that also has to do with your strategy. For instance, we identified this sweet spot for us: earlier, less invasive, more accurate, enabled by technology.
Large markets, unsolved problems, global experts, et cetera. So there are certain initial parameters that are benchmarked to get some kind of an informational score on. Then from there, depending on what they have, there's more detailed information we analyze to be able to come up with a composite, three different machine learning scores that help us say, okay, this company, we say our team goes, this is amazing. And then the scores are really low. Well, what are we missing? Is this person just a really great salesperson, which happens a lot.
We have some of the best storytellers in the world in Silicon Valley, as we know. And then on the flip side of that, there might be somebody who comes in, maybe English is not their first language, maybe they've never pitched a company before, they don't know what's important, what's not important, how to share those things. And so we might say, hmm, and then the scores might be like, wow, off the charts. So it gives us a gut check to say, okay, take a second look and let's understand why.
I think we've used AI technology early on with these 72 data points and then narrowing down. So we have a dozen or so that we really look for to sift and filter and then get deeper in diligence. And then ultimately it's a funnel. So you go through this funnel of here's all the stuff, you narrow it down, you narrow it down. So you kind of get to the one where, okay, this one we're in the diligence. I'd say there's 72 points to be honest but not all apply to all companies. And depending on our first pass and our strategy, it influences that calculation.
The Critical Role of Scientific Validation in Health Tech Fundraising
Dr. Paul Gerrard: You just talked about all this diligence that you do. And I'm going to guess that part of the diligence is evaluating the science and the commercial potential. When we take a step back, my belief is everything has to have some legitimate science underneath it to have commercial potential. But at some point, in terms of what the company does, you can go overboard in the science and shift from being a science-first commercial company to being a think tank. So how do you figure out and vet out that sweet spot between making sure that the company really has the scientific integrity and the scientific promise while still prioritizing the commercial needs of whatever future product they're going to have?
Michele Colucci: Yeah, actually, that's something that I've spent a lot of time on. The validation piece is probably one of the single most important pieces next to the IP and the team. And so what we often do is people will come in or a company will come in with some validation data. Like we've done 30 subjects, we've done 3,000 subjects, we've done this. We get into the weeds on that.
So when people come and they're presenting to us, I always tell them, look, focus on the science and what your validation is. We want to see that first, then tell us about the IP and tell us about competitive analysis. Those are three critical pieces when you're investing that you have to really understand, because if you look at the number of Nature papers that were replicated at scale, it's extremely small. Replicated at all.
And I think that I've learned a lot more about academia because of that, which I was not so aware of, where there's so much pressure to publish that oftentimes it makes people rush to get something. They have a first little answer, they do it, and then they don't really do the proper steps to ensure that you can replicate it.
So that's something we spend a lot of time on. We look at where the samples came from. We look at what the mix of the samples were in terms of gender, ethnicity, et cetera. We look at the way they handled that in the lab. We look at what lab, what are the procedures in place? Who's looking over their shoulder?
And does the process or the reason why this works make sense underlying? And one of the big questions we answer when we consider a company is, can this be replicated on a larger scale? So I'm very fortunate to have people like Jerry Lanchbury.
Who was the former chief scientist at Myriad Genetics, helped me dig in on some of those. I'm helped by, on the regulatory side, Richard Frank, who wrote all the rules for reimbursement for CMS to understand, is this path right? Are they, because oftentimes people come, and this is one thing I will say to companies, know your codes. If you're going to present, we're going to get paid under this code. If you're not going to get paid, if that's not a code that's valid or that code is changed or that code doesn't apply, we're going to know.
And I think that most of the time companies pitch to funds that there's no way they would know. So they put whatever they can up. I had an entrepreneur tell us something once; I was just done. He had numbers. And so we test him on it. We said, well, this doesn't make any sense. How would you get this? He's like, "Well, yeah, this was someone from overseas. That's what the VCs want to see." I'm like, but if it's not accurate, then that seems to be a problem with the team, your veracity. Now, how are we going to invest in someone we can't trust? That was just, everyone on the call was just stunned because this was in front of my group of 20 global experts and we're all looking at, what did you just say?
So I think it's super important that you come prepared. If you're looking for money, we don't want to pay for you to make mistakes. We want to pay for you to execute a well-thought-through plan that has the best chance of success that you and us as a team can get you to. And we're stewards of capital. It's not all our own capital, though we are a big investor in our funds, more than I think most.
And so we have to be convinced of the chances of success. And we have to be able to not only feel like the risk is understood fully, but also that our team is capable of helping the company mitigate some of the risks that they're facing to increase their chances of success, hence why they come to us to lead or to get involved. We're on the boards. We jump on their boards, their advisors. We sometimes join the C-suites that my EIRs join. So it just depends on on how excited who is about which company.
Navigating the Gauntlet of Diagnostic Test Reimbursement
Dr. Trevor Royce: I just want to quickly follow up on something that you touched on earlier. I think is worth highlighting for our listeners is on the topic of reimbursement and how in new products and healthcare, obviously the user isn't always the one paying for that product because you have to go to payers or some other intermediary. And those challenges are particularly true in diagnostics where we need to have a clear path for payment with billing codes and everything that you've touched on. I'm curious how you guys approach that when you're evaluating companies, how early on did they have to show that they have a proven path forward for a payment structure for their new products. Love to hear you reflect on that a little bit.
Michele Colucci: Yeah. So when you're financial investors, you don't want to just know it's going to work. You want to know it's going to get adopted and people are going to pay because otherwise you have no exit. So I think that's something that entrepreneurs sometimes forget. When you get into it, you're like, this is so amazing. This can change. That's great. But if nobody adopts it, it's not going to help. We've seen that before, which is really frustrating, because sometimes the standard will change, and new things will get adopted. But a lot of times the medical field is slow to adopt change.
So you have to make sure that there is a path where they can get paid. Now, there's different payers that have come to market than traditional. It used to be the Medicare and then the private insurers. And that was pretty much it. Now you have companies that provide benefits as a result of trying to keep people working at their companies, trying to increase the stickiness of the position. So you have things in fertility, you have things in elder care, things that really impact their work life.
And so that's a new payer. You have consumers that are a lot more empowered to buy our own tests on their own dime in areas that reimbursement does not cover. So it could be hormonal things. It could be areas that people have been very frustrated with.
And so where there's a pain point and a price point is comfortable for the pain point, then you have a business. So I think you have to look at if it's a direct consumer product, can they afford it, how important it is for them to get it. We have a company that had the first FDA approval for a small cartridge of a syphilis test, 10 minutes, you do it at home. Well, there's a lot of stigma attached to syphilis. So, yes, it's important to be able to get it at CVS, at Walgreens, and be able to do it at home, sit it on the shelf 10 minutes, because there's medication you can also get remotely. There's things you can do. And so it does. It keeps the person from the embarrassment sometimes. Same thing on the pregnancy front. We have the same cartridge can take blood and identify pregnancy very early.
So that also is something that people say, "Well, there's other tests, seven days, even if it's earlier, it doesn't need it." But if you're a hospital and you're giving someone medication, you want to know if they're pregnant as early as possible. You don't want to get sued or you're trying to get pregnant. You're anxious every minute to know. So when there is a big need, people will pay for it, whether it's out of pocket or whether it's through the system.
I think that or my hope is this administration will focus on what we focus on, which is earlier identification of illness, because two thirds of the health care spending is in the late stage. It's ridiculous. People shouldn't have to get to that late stage before they identify something and then try and address that because the cost of a healthier system is horrible. The cost of lives is horrible. You can change your survival from 20 percent to 80 percent if you get something early in some diseases. So just that I'm hoping that we become more proactive.
And I think that has been one of the biggest problems about the diagnostic vertical is that the way Medicare or private payers pay is very much, "I'm not going to deal with it until it becomes a big problem." And that's just not been smart. You can spend a lot less money screening a larger population and avoid the big dollars later.
And some insurance companies say, "Well, average person stays with me two years. They'll be with some other insurance company at that time." And to that, I always answer, "Yeah, but somebody else was at that insurance company coming to you." So it's a circular argument. Everybody, private payers, Medicare will pay if you don't get it early. It doesn't matter when. So it's in everyone's interest to do this as early as possible. And I'm hoping that we focus more on that than what we have been focused on. So more outcomes space, more earlier diagnostic, more impactful, where you can have maybe a larger population that you can screen. But of those you catch that would have otherwise gone to late stage, you have really made an impact. You've changed lives, you've changed dollars, and we can save our health care system that way.
Emerging Diagnostic Technologies: From Point-of-Care to the "Box" Problem
Dr. Tim Showalter: That's very well said. I've actually never heard anyone make that point, which I think is a very good one, that if you look at the nature of insurance, it all should balance out so that at some point it's in the best interest of all the insurers to embrace some of these interventions. Just to follow up on what's going to move the field forward, I'm curious, you must see a whole host of emerging technologies and diagnostics all the time. And you hear things about multi-omics and, of course, artificial intelligence-based interpretation. Can you give us a sense of some of these themes that you think are definitely overhyped? And maybe if you've got ones in mind that are underhyped or really are actionable right now?
Michele Colucci: The movement to point of care has been impactful. So that is one area I think that is bringing a lot of good and will grow tremendously because there are new players in that game. There are the CVSs, the Walgreens, and the LabCorp that are now in hospitals running labs and the Quests and et cetera that are coming up with new models, new distribution channels, new ways globally to distribute things. We have population health stuff, the Gates Foundation. We've got a lot more ability to distribute stuff to areas and people who traditionally didn't have access. So I think that's been something that's fantastic.
Global access to health care and equal access for everyone is really the dream. It used to be you only have to have so much money to be able to get really quality health care. Well, if you can take testing and expand that globally, then you will move the needle so far up when it comes to outcomes for populations. So I think that's one of the exciting things I've seen, all the technologies that are able to be implemented at point of care or over-counter, et cetera.
Something that's overhyped, I would say some people look at, and this is an area that's critically important, but it's actually the lowest hanging fruit and that's at the imaging level. So the MRI radiology, all that kind of stuff, we're taking data, we're taking the data before it goes into an x-ray and pixel, taking the pixels and doing different things. That's interesting. That's some really great things you can do in that area. But there's a lot of people that can do that. And it's very hard to get IP around that.
So I think in some cases, the most valuable idea is the data sets. So we have a company that has a hyperspectral imaging of the fundus, and they have about several thousand patient data set correlated with PET scan data. So they have been able to identify six to 10 times the drusen in the eye with AMD. They're working on an Alzheimer's, because they're digitizing the signals for beta amyloid and tau debris. That, I think, is unique. And it's a big problem, and it's something that is perfect for machine learning.
I think just a generic, "We're going to take all these scans and we're going to tag them and we're going to identify which ones are more likely, less likely"—those are helpful products, but essentially they're just licensing and they're not going to be the larger companies. The ones that are also innovating a lot are in robotics. We see some amazing things in robotics that are improving that. So I think that we're going to be moving away from the larger machines. We still see some of them, and some of them are interesting, but we're going to get smaller and more compact in our technology and our delivery methods of these diagnostic solutions.
And I think we're going to be more efficient when it comes to, as I said, multiplexing and things like that. Will I say anything's really overhyped? I would say probably that those companies, because there are so many of them and there's so many people that can do that. We're in Silicon Valley. They're brilliant people in machine learning. So there's a million companies that can do that. But that's going to really be surpassed quickly. Whereas the real, I think the real barrier to entry is in the intersection and the interplay and the interwoven piece of the biology and AI. So the digitization of the signal, that's where I think we're going to find the most innovation, the most excitement, the CRISPR technologies, the sequencing, but on a newer level and more insightful level.
The machines that actually we saw when we were saying you could put a tissue in and then find out if you got all the margins. Those kinds of things are going to be impactful. And you could do that in a way that you couldn't before. You used to run things to labs. So we're going to see a consolidation of processes when it comes and getting answers faster right in the OR room when they're right there on the bed still. So you don't have to bring them back for another procedure, another time, another this, another that. We're going to identify a lot of mistakes earlier. And so we'll be able to fix them without them turning into a mistake that has a lot of bad outcomes. And so just a general consolidation of stuff.
The other thing I think is a little bit overhyped, I will say, is the box. And I refer to it as the box because everybody has a box and they all want you to buy their box. And then the razor-razorblade model is, "OK, you put it in your practice, you're going to be able that, run a million tests on this box." We see so many boxes. And I think some of the boxes are really interesting. But at the end of the day, you have to think about, talk about the realistic piece.
How much is your box? How long is it going to take you to break even? And how often are you going to use that box? And how much is it related to all these other boxes that you've had to buy? You have to buy this machine and this machine and this machine. And practices, we're cost cutting, we're in an area where Medicare rates are, costs are cutting and all sorts of things. So hospitals are getting squeezed, people are getting squeezed, people aren't getting access to this stuff.
So to the extent you can get tests to be done over the counter, or you can be mail in, they can mail, pee in a cup and mail it in and get an answer on your computer with a full report. Those are I think effective. The company we have in New York that got the first genomics based approval for their urine-based genomics assay for UTIs that is I think game changer. UTIs take so long to figure out; there's people who have constant problems with those. And so to be able to just pee in a cup, send it in and in 24, 48 hours, whatever, you have an answer.
And they can also identify 7,000 pathogens globally. They're tracking pandemics with a global pandemic dashboard at the same time. That, I think, is stuff that really is impactful. A third of the sepsis cases are from UTIs. The elder care facilities have problems with UTIs all the time. Finding solutions that are easy for the consumer to do. We have a kidney test for transplant rejection. If you're in a remote area and you don't have access to major hospitals or places like that to test constantly to see if you had a transplant, it's not rejecting. That's a barrier to entry and by the way you might not even get as high on the list for that transplant because they don't think that the chances are it might not last and they want to make sure these kidneys last and it's only so many of them. I love the work we're doing in creating organs and in it's just amazing organoid development or things like that.
So I think that the stuff that really simplifies and gives you the best answer for this specific thing.
From a Single Test to a Platform: A Founder's Guide to Scaling
We talk about a platform versus an individual test.
For a company to really scale, you need a platform, but you need a proof of concept in one test. So if you just have one test, that's great, and you might be used for a while, but eventually there'll be a platform they'll be able to do that one test too. So if you think about it from a monetization standpoint and a long-term value creation, if what they're doing, like we have a company that looks at the glycocalyx. It's one of the earliest markers for neurological. That's very different because they can, all sorts of neurologic guys, Parkinson's, MS, MD, but they have a proof of concept in a few. They're trying to narrow down to which one is their first really strong indication. So they can take that one to market first and then follow.
When you look at exits, you look at a company that has one product that is scaling very nice, has 10 million, let's say in revenue. You look at that. They have a second product that's in the market and just starting to follow that same path. And you've got a third and or fourth in R&D. That's a good profile for an acquisition.
So if you can think of it in that way, then you'll be more prepared, I think, for creating opportunity in the minds of investors that they can see. Because investors, a lot of investors are pattern matchers. They see something successful. "Oh, that was like this. That worked like this. That one was sold, therefore." Which is not always the case, but often can be the case. Or this is a fast follower. And so if you can match the pattern from the exit point of view to them, while you're creating your product on the, it's top down, information, but from a bottoms up approach, then I think you're much more likely to have success on the fundraising and of the company in general.
Fundraising Advice for Founders: How to Pitch and Build Investor Trust
Dr. Paul Gerrard: If you're going to give advice to early stage company leaders, founders, people who are looking to start up a company, and they're trying to, I feel like you've given them a mini course on how to do it here. But if they were going to have one big takeaway, one big piece of advice, is there one thing you'd say should be the primary thing that they keep in mind?
Michele Colucci: I would say one of the single most important things is they're starting a company and then they're getting investors. Those are two different things. So starting a company, your single biggest issue is what is the biggest problem you're solving and who else is trying to do it and how are you better? That's really, if you can't explain exactly what you do, that's a problem. I have a done a fellowship since 2018; we've put over 250 students, mostly MD, PhD, MBA, MPH students all over the world through our program. And one thing I ask them after, so they bring companies every week, they have to present, find new companies anywhere in the world, diagnostic. And so they'll pitch a company and then I'll stop and when they finish their pitch and I'll say, okay, you guys listen for a moment. Anyone else who's in the call here, what exactly are they doing?
What biofluid are they working in? What exosome or cell or telomere or whatever are they using as their biomarker? What exact, how does it work? Is it photonic? Is it phosphorescence? Is it what, what are they doing that makes it work? And 99% of the time at the beginning of the fellowship, it's silent. Because that's the one thing entrepreneurs don't crystallize. I am identifying breast cancer in exosomes through photonic or assay or whatever. And I am looking at the clusters of these three analytes that come together in my studies.
Indicate stage one breast cancer. Whatever it is, that's a really tough one. And by the end of the fellowship, they are great at it. And so that's part of the training we do is how you pitch, how do you pitch, how do you pitch? What are the questions? My dad used to do that to me. He's like, go, you do this. I come back and give him the answer. He's like, "Well, what about this?" "Well, I didn't ask." "Well, go back and ask." So it got me used to saying, what are all the possible questions that somebody could ask me? And let me make sure I have the answers in advance. So I don't have to go back and forth and back and forth and back and forth. But it's great learning. And so I try to do that with our fellowship and I say, tell me exactly what they're doing.
So I think as forming a company, you have to be able to articulate that extremely well and you have to be prepared to validate what you've articulated and why it makes sense. Because if somebody who understands the science biology that can get their head around the concept, then they're like, "OK, I buy that now I'm listening. Now I'm listening to how many samples you've done. I'm going to test you on those samples. I'm going to test you on how you did it. I'm going to ask you if you thought of this, that, this, that. Did you normalize for this? Did you eliminate those?" And through that process, I'm going to actually gain more confidence in what you do. I'm going to lose it. But if you out of the gate can't articulate exactly what you're doing, "Oh, it's secret." Look, don't come to us then. We're not signing NDAs. If you can't explain it, by the way, we don't want to do what you're doing. We're busy enough.
But that having been said, I also think that there are some entities in venture and investors that aren't great stewards of information. So I understand the concern and I've been concerned about that myself. But the way in which you say it and how you explain it and how you analogize it, analogies are great. They help people get their head around things. So if you can, we used to do that 20 years ago in tech. It's Uber for for the aging population or it's this or it's that, whatever, it gives people an analogy, something to get their head around, go, "Oh, I get how that works," if it's a tough concept.
So articulating what you're doing really well is critical. On the investment side, if you want investors, of course you need to articulate, you need to come prepared and having thought through how you're going to make money. That's really important. This is not a science experiment we're investing in. We want to invest in a company that makes money. And you're also going to say, how transparent are you? Because what is most important is you as a founder or CEO, that's who we're investing in. Are you transparent? Do you cut corners? And sometimes we can't tell. We can't tell until we get into it a few years. Then we're like, oh, great. Now we got to fix this. It's a pain in the neck. Investors don't want to get involved in your company. They would rather just invest and make a lot of money. But the reality is.
Half the time, there's stuff that goes on and somebody tries to say, "Oh, I know it, I know it," but they really don't know it. They don't take the advice. They don't take the input. They're not transparent. They don't share enough. And then you're really stuck because then you can no longer have confidence in that person, in their decisions. And then you're going to micromanage everything they do. And that's not fun for them. It's not fun for you. So a founder who is open to information who's not so scared that they're going to be replaced and is more excited because a founder who wants their company to go, if there's somebody who could do your job better, you probably want that. You want to do what you do best. You want to get people that they do best. But that's not always the case. Sometimes ego gets involved. And we have to really understand the ethos of the innovator here of the founder and CEO. And that's probably the single most important thing on the investment side.
Dr. Tim Showalter: Thank you so much, Michele. It's been fantastic hearing your insights about investment in this space. Really appreciate it. I've learned a ton. I would love to have another hour to talk to you because I feel like there's so much more there to go through.
Michele Colucci: Thanks so much for your great questions.
Dr. Tim Showalter: Thank you.
