Too often we define the Medtech sector by the number of dollars raised, IPOs helped or companies sold. But the focus neglects the very foundation of the sector: the people. Join the Medtech Talk Podcast each month to hear from entrepreneurs, investors and executives who spend their days developing the tools that make sick people well and health care more efficient.
The data gap in women’s health has always been a major issue and challenge. Ridhi Tariyal, CEO and co-founder of NextGen Jane, is on a mission to de-risk the women’s health field and fill in the blanks with critical information and research. Host Swaril Mathur speaks with Tariyal on how NextGen Jane is collecting data through menstrual blood to make diagnoses and treatments easier. Tariyal also shares advice on the pros and cons of going the cash-pay consumer route and pitching the right business proposal to gain investors’ attention, as well as NextGen’s plans and focus points.
GUEST BIO
Ridhi Tariyal, CEO & Co-Founder, NextGen Jane
Ridhi Tariyal is CEO and co-founder of NextGen Jane. At NextGen Jane, Ridhi has driven the development of a novel menstrual data platform characterizing uterine biology at a molecular level. In this effort, she has raised capital, established an IP position, and developed a team to create both novel hardware and software to change how we understand inflammatory and immune-mediated disorders which predominantly affect women. Before NGJ, Ridhi worked at the Broad Institute and at Bristol Myers Squibb. She earned her bachelor’s degree in science from Georgia Tech, her Master of Business Administration from Harvard University; and her master of science degree from the Massachusetts Institute of Technology; and she is both a Blavatnik Fellow and Ferolyn Fellow.
TRANSCRIPT
Swaril Mathur:Welcome to MedTech Talk. I'm your host, Swaril Mathur, and I'm thrilled to be joined today by Ridhi Tariyal, CEO and co-founder of NextGen Jane. Ridhi, thank you for being here.
Ridhi Tariyal:Thanks so much for having me.
Swaril Mathur:So I'm so excited for this conversation Ridhi because you've been working on something really interesting in a sector of healthcare that is so often overlooked and often really challenging to dig into. And before we get there, I really want to talk about how you got to this place in your career and what your most formative experiences have been. So can you tell us a little bit about your professional journey and how you landed in the world of women's health?
Ridhi Tariyal:Yes, absolutely. I am an engineer by background, so went to Georgia Tech, majored in industrial engineering, and actually did uh banking and consulting at the start of my career, if you can believe it. Um, did not like either, and really wanted to dedicate my time to something that I found worthwhile. And so joined Bristol Meyer Squibb for two years in their RD group and thought, this is it. This feels like the right home, but still too big, you know, um massive infrastructure, lots of bureaucracy, but doing the type of work that I found exciting. Um, and this was back in the day, um, I'm gonna time myself, but somewhere around 2005, 2006. And when I asked uh uh people, you know, what should I go into if I want to do some, you know, genomics and precision medicine and uh more startup type work. And they were like, yeah, you the startup's the right place to go. That's where a lot of the cool cutting-edge science is happening. Um, but you have to have an MBA, which, you know, I don't think that would be the advice today. I don't, I don't, you know, I probably wouldn't even take that advice today, but I was like, okay, great, I'll go get my MBA.
Ridhi Tariyal:Um, got my MBA at Harvard, and while I was there, I got a secondary master's in biomedical enterprise from MIT. Um, really uh, you know, wanted to double down on um healthcare, and MIT offer this great program where you go through med school classes, you round in the clinic, and the thought is if you want to be a medical entrepreneur, um, sure, go get your MBA, but you should also know the jargon in medicine and you should know the problems on the front lines. Um, and that will make you a better life science entrepreneur. Um, loved it. Uh, graduated uh from MIT, you know, after this three-year dual degree program, and took my thesis um and tried to turn it into my first startup. Um, this was uh around 2010. So it was still, we were all still recovering from the housing crisis. And um, you know, it was it was me solo sort of pitching this idea that was targeted towards um an a consumer base in India, genomics play consumer base in India, and uh couldn't quite get anyone to bite. So I ended up saying, okay, I know I want to do emerging market genomics. Um, and I got an opportunity to um do exactly that at the Broad, um, which is a genomics institute based in Cambridge, Massachusetts. I was uh leading the finance and operations for a large GWAS, which is a genome-wide association study looking into viral hemorrhagic fevers, specifically loss of fever in West Africa. And it requires you to be on the ground for like four months out of the year and you know, gave you access. I was managing like a $10 million budget. And I was like, this is sort of like a startup budget as well. Um, I loved it, you know, it felt like it was still a very entrepreneurial environment. Um, and uh did it for two years. And after that, HBS had this great opportunity. It was called the Blavatnik Fellowship, um, where they were bringing back people who had graduated with their MBA within the last five years and um giving them what they called a little bit of walking around money, you know, paying them some sort of salary, uh, giving them access to the entire IP portfolio across the university.
Ridhi Tariyal:So, you know, from the college, from the med school, um, and and saying, try to spin something out. You know, this is uh really high quality IP. There's a lot of PI that spent a lot of time um in on this basic research, but it's it's there, you know, all of this research encounters the Valley of Death, um, where it's not quite a product yet. So it's not ready for VC, and yet, you know, it's it's too far along for basic research, and so it just dies. Um, and I was looking at all these cool things, you know, very fascinating, um novel uh material for our uh warfighters in theater, um, you know, new interesting machine vision systems that were going to transform how we developed um psychiatry psych psychiatry drugs.
Swaril Mathur:Wow.
Ridhi Tariyal:Like, you know, was I I loved those projects. I worked on them. And at the same time, you know, I was in my early 30s and I I was uh talking to my OBGYN saying, well, um, how can I find out the state of the state in terms of my reproductive health? And um, you know, I had just as context come from the broad where genomics was just transforming everything. It cancer was a completely different field, right? Everything from how it's classified, diagnosed, how drugs are developed for it, how it's treated, um, was all being driven by molecular medicine. And um, even uh microbiome was next, right? There's so much research happening there. And you go to your uh OBGYN, everything is analog, not digital. Um, you know, at Papsmere, they're looking for morphological changes in the cell shape. Um, you know, fibroids, adenomiosis, they're looking, they're doing imaging to look for structural changes in the uterus. Um, endometriosis is probably the worst, where they're still doing surgery and going in with endoscopes, trying to identify ectopic lesions. Um, and none of it was really driven by molecular medicine. And it was evident not only in the tools that they had for diagnostics, but in the uh options women had for drugs.
Swaril Mathur:Yeah.
Ridhi Tariyal:You know, very blunt instruments. And so um I thought, oh, there's uh there's an opportunity here. Uh clearly this space needs molecular uh medicine. It needs that kind of uh underpinning to understand why, why we get these diseases, how to uh treat them in a more targeted way. Um, and that's really where I would say my career um, you know, bent towards uh women's health in particular. Wow.
Swaril Mathur:Wow. You know what something that strikes me about your background and kind of the first chapter or maybe chapters of your career is just how many different things you did. And I'm curious, you know, I think it's always interesting with careers when you talk about then you can look back and backwards justify why every transition was logical. But in a moment, it's not always, it's not always so seamless. But I'm curious across all these different things, consulting and finance, you know, rounding in hospitals, being an engineer, doing genomics in West Africa, were there any like specific kind of aha moments or any transformative learnings that you find yourself now applying in your in your current role?
Ridhi Tariyal:That's a great question. Um, one I would say that, you know, I I learned very early on that I don't do well in extremely constrained environments or where, you know, environments where uh that are so big that it takes um 15 decision makers to to reach a decision. And so uh I would say that a lot of my uh career decisions, you know, as they evolved and definitely today, are oriented towards how can you make how can you be nimble, how can you be um quick, how can you respond in a way that's that's um you know thoughtful and yet reflective of how fast the world is moving. And I would say that that, you know, giving into that impulse early on in my career and saying, oh, this is too slow, I don't want to move at this pace, um, has absolutely optimized me for the pace at which science is moving now and the types of decisions we have to make in in this start of uh next change.
Swaril Mathur:Yeah, yeah. That's so interesting. And and you know, like one of the things that comes to mind for me is one of the reasons things sometimes move slowly or decisions often take so many different seats at the table is because everybody's trying to mitigate risk and everyone's trying to um, you know, uh mitigate their own personal liability involved in making a risky decision. And so uh I'm sure as we talk about the NextGen Jane story, we'll get we'll get into all the different types of risk and things that you as the as a co-founder have had to take on and assess. Um, but I'm curious, just before we dive in, if that's if that's a consideration that, you know, at all for you.
Ridhi Tariyal:Um in terms of just to clarify the question and how to think through risk in this environment?
Swaril Mathur:Yeah, and uh, you know, you described that that you've intentionally pivoted your career towards things that can move faster. A trade-off of moving faster is often taking on more risk or making riskier decisions with less information or less input. Does does that actually does that assumption actually feel true to you, first of all? I'm just stating that as an assumption. And then second, how do you handle it?
Ridhi Tariyal:Yeah, it's actually very liberating. I think that part of the the um problem that's inherent in women's health is that there's a data gap. So you're just functioning in a lack of information, right? Inherently the risk profile is higher. Um, because you're, you know, will menstrual blood be the right aperture by which to understand uterine biology and have insights into inflammatory diseases that are female dominant? That's a question mark, right? It's it's been a question mark for a long time because you're not that not like you go in the literature and there's 2,000 papers that you can reference. There you go. That's your that's your benchmark for where the risk profile already is. Nobody can actually mitigate that risk. If you think that it's an interesting idea theoretically, you're going to have to take on risk to take a swing at it.
Swaril Mathur:Yeah, yeah. Well, I I mean, and it sounds like you're exactly the right person to be doing that, given how energized you are about it. So tell us so that we could dive into it, tell us a little bit about NextGen Jane.
Ridhi Tariyal:Um so the the best way to describe it is that is the core thesis, is that uterine biology is a singular aperture by which to understand inflammatory and immune-mediated diseases that that are overwhelmingly impact women. Um, and examples are autoimmune diseases and endometriosis, which you know is often thought of as a reproductive disease, but is a chronic inflammatory condition. Um, and fundamentally, um, you know, we believe that that part of the reason that there are not great tests to help you find out early on that you have these diseases and not great medical options to as to how to treat these diseases is because there is a gap in understanding the molecular underpinnings of these diseases. And so fundamentally, what we're trying to do is we we've we've put a stake in the ground to say um the uterine, the uterus is a singular organ. And if you could understand the molecular infrastructure of this dynamic biology, right? An organ that that goes through an entire developmental cycle every 20 to 32 days, right? Um, grows, sheds, you know, knows when to become placenta. Um, if you could actually understand what's happening in that uh uh dynamic catalog, then you have unique insight to be able to help understand what is actually causing some of these diseases and what are some novel uh insights that you can use to actually think about new drugs?
Swaril Mathur:Yeah, yeah. And that thesis is so compelling. I mean, that the the potential of what the applications could be, if all of that holds true, is really interesting. But you you called out a moment ago that it is a question mark. So how did you how are you tackling that, right? Why, why start a company? Why is this a company, not a research project in a lab? How are you de-risking this? What's your thought process around that?
Ridhi Tariyal:Yeah, I think there's two great questions in there. One is how? Um, and that's a really important question is how would you even begin to answer it? Um, and then there's a secondary sort of question is is a startup the right context to do this? Like why not do it, you know, just in academia, where that's the traditional way life science happens, right? There's years and years of basic research that happened in a university setting. And then you license that IP out, and there you go, you're off to the races building something um uh more productized. Um, you know, for us, um, maybe I'll answer the the second question first, which is um there when we started, which was a long time ago, you know, I was in this fellowship around 2012, 2013, um, there still wasn't that much of an appetite to take a serious look at this substrate as an undervalue overlooked uh medical specimen.
Ridhi Tariyal:And um uh, you know, the the context is actually the landscape's different now. I think that every month almost I see a new call out for menstruation uh in grants through NIH, as well as um, you know, funding opportunities through other nonprofit organizations and foundations. I hear all, you know, often hear of different universities having labs that are are beginning to evaluate this. Um, and so maybe if I was starting this company in 2025, I would have thought, oh yeah, this should just stay in a university setting for a few years before we take it out. That just was not the case in 2012. You know, we we had conversations with academics where they were very uh frank and said that that this is not something that we are interested in looking into, that labs are are not going to be friendly to working with this specimen type. Um, and so at the time it felt like there was no avenue through the traditional routes, right? Um, as well as um my co-founder and I were neither of us, we you know we were both at the broad and we had uh uh done research in that setting, but we weren't PIs in our own right.
Ridhi Tariyal:And so the thought of like, okay, we, you know, where how do we how do we set up the apparatus for writing grants? Um, you know, ironically, now, years later, we won millions of dollars in grants through SBIRs and uh, you know, our are find ourselves to be pretty adept at it and enjoy writing grants. But at the time we thought, okay, so you know, writing grants and going the traditional route uh through through how this should should work and public through from public funding is probably not for us. Um and so that that just left the only option, right? Which is we've got to get investors interested in this. We've got to get someone who who loves deep tech um to see the value in this and and want to be on the journey for it.
Swaril Mathur:Yeah, yeah, absolutely. And then going back to to kind of the first question, which was the the why.
Ridhi Tariyal:The how.
Swaril Mathur:The how.
Ridhi Tariyal:There's a why though. No, that's that's the that's the next good question. The why. The how is, you know, so we said, all right, um, you're gonna we're gonna collect this this specimen, we're gonna, we're gonna have to do it across many individuals, we're gonna have to do longitudinal collections, right? Because we can't, we can't begin to understand such a dynamic organ with a single time point analysis. Um, and so when we took all of those things into consideration, we landed on having an at-home um specimen collection kit, number one. Um, number two, we wanted to make sure that we were not um asking uh individuals to do like things like go get wet ice and dry ice and make an entire science experiment at home. You know, in general, the more um asks you layer on for a participant, the more you drive down activation energy. Um and, you know, we were very keen that we would only be able to solve this conundrum of like, is there value here if we could collect multiple samples across a single cycle, multiple cycles across, you know, a year and multiple years across a lifetime.
Ridhi Tariyal:Um so we spent a lot of time really optimizing how do you do all of the, if you can imagine everything from um the UI of like I have instructions for use that the patients can use at home, um, you know, the the intuitiveness of the design. Um, there were things like that we had to engineer around, uh, like um when women were dropping their tampon into the device in the early days, they were leaving the tampon string out and it created a wicking path. Um and so we designed a mechanism by which as they closed the device, the tampon looped it around and and was driven into the device. There, and this is like a single example. There were so many examples like this where you are discovering how the patient can is is actually using the device and way where there are natural places of misunderstanding.
Swaril Mathur:Yeah.
Ridhi Tariyal:And there are only two ways to tackle that really is you can try to optimize your instructions for use for more and more clarity, but there's a plateau there. Um, or you can design for them to say, I see that that mistake you keep making. I'm gonna actually design the product so you cannot make that mistake.
Swaril Mathur:Yeah, yeah, yeah. Well, and and that right there is just a great lesson in in like product development and and true primary user research. Um, not asking someone how they would put the tampon in it, but just seeing how they do it in real world. But just so take a step back. This is like back to the the broader how you decided, okay, we have to start a like venture-backed company to go and do this basic science research. And then everything you're talking about right now is the mechanics of how to get like study participants to give you samples of menstrual blood so that you can do the basic science research to see if the thesis holds true, that genomic data from menstrual blood can be used for diagnostic and potentially therapeutic indications.
Ridhi Tariyal:Correct.
Swaril Mathur:Wow. And what was the process like to get investors? What are the types of investors you were looking for? What story were you telling them? And what were they pressure testing? Because in in the same way that you just described, that, you know, the the university research environment maybe wasn't optimized for this when you started it. I am curious whether the venture environment was ready for it.
Ridhi Tariyal:Uh, more ready. As evidenced by like how they should be played out. Um, you know, I I don't know if this is would be a controversial statement, but I would say that when you're raising a seed round, people are willing to take risks. Um and and the further you go, like it's harder to raise the A because you need to have hit a certain proof point. It's harder to raise the B because you need to have reached an even higher proof point. Um, but at the seed stage, you know, having a uh really good thesis of what you're doing and why you're doing it, um, and having uh a really compelling sort of vision as to what kind of value we could unlock is almost sufficient to get investors that are sort of have the right risk profile interested in taking that small bet, right? It's it's not gonna be big money, like our seed round was $2 million.
Ridhi Tariyal:Um, but there were enough people around the table that said, okay, we get it, you know, um uh this, this, there's not a lot out here in terms of what's going on with the specimen. If you actually were able to diagnose some of these diseases, it could really unlock value in terms of both unmet clinical need um as well as shorter diagnostic odysseys, as well as, you know, obviously potentially making a lot of money because there's such a demand to have answers. And and women are extremely electrified uh individuals when it comes to wanting more information about their bodies. So that's enough of a value proposition that we're willing to take that risk at the seed stage. Um, and so that was, you know, our approach was making sure that there was enough of a really compelling thesis as well as a enough of a um the home run if we hit the home run is really big.
Swaril Mathur:Yeah, yeah. No, that resonates. And uh, you know, it in the seed stage, it sort of sounds like you're selling a story. And if that story resonates, they're willing to take the risk on the technology because that's by definition what what the seed is. Yeah, that's that's what it is. Yeah. Um, and you mentioned the value proposition, and there's there's multiple layers to that. But just speaking to kind of the business and financial value proposition, you know, having having spent some time in kind of the women's health arena of med tech, I've seen countless examples of solutions that are designed to address a legitimate unmet need, but are trying to slot into pockets of healthcare where the dollars have historically been small, either because, you know, the set reimbursement rate for a certain category is really low, um, or because the procedure volumes have historically been low. And all of that makes it really challenging to try to pitch a business case that's compelling either to investors or to eventual acquirers. Um, and that's a real limitation. I mean, I've I've seen firsthand from my time in in BD at Axonics how how you know a smaller TAM makes it really challenging to make a compelling investment or acquisition thesis. So how how has that come up for you? Um, how have you thought about the the business you know proposition?
Ridhi Tariyal:Um it's it's been a moving target. Uh and it sometimes in part depends on where you are in like the venture cycle of what they're interested in investing in. I would say when we started out, um there was uh an even more, and you know, it still exists to this day. I think everyone knows in Venture that um uh a pure diagnostics play is just not as compelling as a drug play at some points, as a data play, as a platform play, you know, in search or favorite um uh category. And the the reasons are sort of um understandable. You know, you you mentioned reimbursement and TAMS being small in women's health. Um, reimbursement is just sort of hardened diagnostics across the board, right? I mean, if you get a diagnostic FTA approved, there's no guaranteed you're gonna get it reimbursed. Um and that is uh a lot of risk for a VC to take on. First, they're taking on the scientific risk of like, does it will it work in the way that you assume that it'll that it will work? Then they're taking on the regulatory risk of like, will it make through make it through the appropriate regulatory bodies? And then there's still consumer and payment risk.
Swaril Mathur:Mm-hmm.
Ridhi Tariyal:Yeah, that's like again, that's just inherent to diagnostics, much less layering on that if you were to get reimbursement, by the way, if it's a women's health product, the reality of the data, data data show that women's health interventions are just uh more poorly reimbursed. And so it's not even going to be as lucrative as something that would be for um, you know, a non-women's health uh product. Um, so there are a couple of things like that have helped sort of thread the needle at the appropriate moment. Um, you know, one has been it's why you saw early on so many women's health companies having a fertility plate, because there are no known exceptions, right? Like if you think about um very successful businesses that sort of are at the intersection of healthcare and and um a cash pay, um infertility IVF is is a big one, right?
Ridhi Tariyal:Um and it it I don't think incorrectly in some ways, of course, family building involves multiple um parties, but like in some ways you could think of it as a woman's health business. Um, and it does really well. And so uh that's why there were so many startups initially that were, and you know, including us, to say, all right, this is this is a really viable market entry point. And it's something that the numbers show that it's a vibrant marketplace and and reimbursement so difficult that if you need to prove out that there is a demand um for the product that you're building um that's gonna have to be self-paid, that is the right, you know, uh proof point, that is the right call point to go to because there's already a willingness to pay. There are other trends that have changed over time. So clearly, telehealth um and DTC everything, like there's a lot of diagnostic companies, have also transformed how people think about this because there's now this sort of willingness to accept um that consumers for convenience and maybe privacy would pay out of pocket for things, that they could get in a queue with a specialist and wait for a reimbursement. And so there was a tension there for a while. And again, especially when we started out, um, there was this sort of fundamental belief in amongst life science VCs that, like, unless you're going enterprise, meaning like, you know, reimbursement through the clinic, it would be a tough slog if you went the alternative.
Ridhi Tariyal:If you were gonna go direct consumer, you know, sell this at whatever price point that the consumer was willing to pay, it would never be as attractive as a reimbursed product being sold through through the traditional channels. And I actually think, I mean, some of that still exists, but I actually think that over the last decade, we've actually seen a lot of transformation and proof points that maybe that's not always the case, right? People are buying birth control pills online and people are buying um hair loss uh pills online. And there's just this really uh vibrant market showing that people are willing to make a lot of these decisions, um, uh not necessarily through the traditional channels.
Swaril Mathur:Yeah, yeah. And those business models are interesting and I think have have probably contributed to some of the growth that we've we've seen and more med tech, more women's health med tech innovations actually getting out into the real world, um, which is a positive.
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Swaril Mathur:Uh a tension or a balance that I'm curious for your thoughts on is, you know, there's a pro to getting things into patients' hands more quickly by going the cash pay consumer route. Um, but there's also a trade-off of that's not going to be accessible to everybody, right? Inherently, there is a segment of the population for whom that will, no matter how motivated they are, that is just not an option. Um, how do you, how do you guys think about that at Nextgen Chain?
Ridhi Tariyal:Yeah, it's very important for us that we are on the path to reimbursement. I think the the way we try to um reach balance in that decision making is look, if we said we're gonna wait for reimbursement, investors would never be interested, right? They would be like, that's what is that? After you get the product uh working is that two-year clinical utility study? Like what you know, and what are the economics that you're convinced, convince convincing payers of? Like, and I've spoken to payers and uh, you know, they're they're um often transparent where they say, listen, uh, you know, I'm a commercial payer, I cover people for 12 to 24 months. And uh my expectation is that anything you offer actually has to save me money across my covered population within that time frame. And so anything like an easier way to diagnose a disease that is likely to cause more healthcare expenses in the year of diagnosis, um, that's gonna be a tough sum, right? There, and they're sort of honest about that.
Ridhi Tariyal:And I still think that there are clinical utility studies that can show them that that there's still ways to save money, that they're gonna take time, right? They're gonna take time to show exactly um at a statistically significant number and a well-powered analysis analysis to say, look, over X number of years, X number of patients, we were able to sell save you X dollars. You know, who funds that clinical utility study? Um, and so one of the best ways to do that is just to get the product on market and start with cash pay as you do that utility study and work with pairs to really get them to buy in and say that this is something that's worth reimbursing. Um and so that that's how we we tackle it. We say what we're just starting at at cash pay, you know, to make this attractive enough that it continues to be a fundable priority with the intent to uh reach a point where we can make this, you know, reimbursed. Yeah.
Swaril Mathur:Yeah, that makes a lot of sense. And I think, you know, it's a it's kind of the phase strategy of you solve for the thing you can solve for at the time, and you can't, you can't ever reach that giant population um that requires reimbursement if you if the company doesn't exist. Um the company has to do what it has to do to exist, which sounds so basic, but that's pretty important.
Ridhi Tariyal:You know what? One of the interesting phenomena, again, this is also context specific, is um obviously there's there is something happening in pharmaceutical, right? There, there are there's now a movement to sell drugs, DTC.
Swaril Mathur:Yeah.
Ridhi Tariyal:Right. We we we see the war happening for GLPs um in terms of who's gonna get access through what channel. I mean, I think my favorite headline recently was Costco's gonna start selling it. Oh my gosh. I was like, game over, black black, game over. Um, but the the interesting thing is gonna be that as and more and more pharma companies are signing on, right? Not just for GLPs. They're they are understanding the importance of this channel. Um, and so you know, if you have a DTC uh uh, you know, business arm um for your drugs, you will need a DTC diagnostic arm for your business, right? You can't prescribe a drug without having a diagnosis. Um and I am sort of waiting with bated breath. I think it's just an exciting movement for diagnostics to say, okay, now pharma is going to be compelled, right? To be like, we need a uh a companion diagnostic in a completely different way. We need a companion diagnostic that we can prescribe so that we can unlock reimbursement for the drug.
Swaril Mathur:Yeah. No, it's a it's a great point that if once you go consumer, the whole, the whole care journey actually kind of has to be compatible with that. Yeah. Yeah.
Ridhi Tariyal:It introduces a market dynamic that that is, I think, in net favorable for diagnostic companies.
Swaril Mathur:Yeah, yeah. And, you know, as a as a consumer, there's something very motivating about the idea that you could take control of all these things and and and really be empowered to, you know, to move the journey forward at your own pace and not be hamstrung by lack of availability availability of doctor's appointments or specialists or things. So um, I think there's a lot of really motivating aspects there. Um, I want to get to some of kind of the key lessons that you've learned in the Next Gen Jane journey. We've alluded to some of them, of course, but before we go there, can you just give us a sense of like where have where has the company come so far? What since from founding to now, you know, what have been the major milestones, the major kind of de-risking pieces? And then what's what's next on the horizon for you? What are you focused on right now?
Ridhi Tariyal:Yeah, I mean, I think there's been a lot of major de-risking milestones. I think the best way to understand it is this um stack that I always describe, which is the core asset of the company. Um, you know, I think that there's been a lot of focus over the last few years on, oh, you know, a smart tampon was like nice clickbaity title that they gave Next Gen Jane for a while, or um, you know, um a way to diagnose, you know, hardcore disease at as at home that often had surgery as the only alternative, which none of these things are wrong. Um, but interestingly enough, the the sample collection system and the fact that it enables longitudinal narratives is is the foundation of what we've built, but it's only the bottom layer. Um the layer you know, above that is great. You've got the sample type, you know, and it it you've got you've done some pre-analytical standardization, you've got the sample type in your lab. Now what?
Ridhi Tariyal:Um, and we we actually generate high-dimensional data from it. It's not like we're doing target uh sequencing, we're not looking at PCR, we're saying next generation sequencing. We're doing full RNA seq. We are um understanding 19,000 gene profiles from the host, so the actual woman, as well as the full metatranscriptomics, which is the activity level of the bacteria in that sample, um, which just is such key insight. Um And then we layer on DNA sequencing, right? And we we're doing that very deliberately because we know we've taken it with that, like one of the bets we're making is that in this environment where you know AI is going to transform everything, you actually you actually need high-dimensional data and you need matched RNA and DNA samples. And that is what makes your data extremely valuable. And so you know we've done we're deliberately going down that path. So great, you've got this high-dimensional data. It's your ability to do anything with it is only as good as your ability to understand who gave it to you. And so we try to do clinical grade annotations, which means we both extract valuable labels from EMR, so medical records that we get, as well as we we it um have instituted this proprietary next-genjane survey. It's pretty intense. It's over like a thousand questions.
Ridhi Tariyal:And over time we have found that, you know, the EMR is spotty. You never, you it's not like you have EMR from the last 20 years. You've probably gone to 50 different doctors. Um anything that they're you're getting from an quote-unquote EMR perspective is sort of a spot chuck of like what your latest doctor understands about you. Yep, that resonates. We ask, we've asked patients questions like, oh, do you have any autoimmune diseases? And they will be like, Yes, I was diagnosed with lupus and so and so. Not in the EMR. Nothing to anything records that they've given us, right? As you can imagine, really relevant information to know when you're thinking about like what data you're looking at. We've asked women who are like, have you ever had any miscarriages? We'll have women be like, Yeah, I've had four miscarriages in a row, not in the EMR. Again, really germane to uterine biology and and everything that we're thinking about and looking at.
Ridhi Tariyal:And so we have found that the annotations are extremely uh improved by just engaging patients themselves to say, we'd love we'd love to know things about your health. Um, and then finally, the most important sort of de-risking for us came through when we developed the what we call a female-specific ontology, which is, you know, especially so female-specific labels for the data that have everything to do with femobiology. The most evident one that everybody knows now is sex as a variable, right? You should take sex as a variable into consideration. It's a very important covariate in your analysis. Um, and and great, awesome, you know, most data sets that we know track that. What we found over the years is things like cycle day of when you did a sample collection, extremely important uh covariant. How heavy of a bleeder you are, extremely important covariate. And so I would say really in this journey, um, probably the most important invention that we have come up with are these the female specific labels that drive our understanding of the data.
Ridhi Tariyal:Um, and my, you know, in terms of your like, what why was that like a uh unlock in terms of de-risk moment? Um, we have this beautiful uh chart that we we show, which is uh two charts, histograms, that um plot out our what we call our endometriosis score, which is like a compound um score based on RNA-seq data. And it, you know, it spits out a score that essentially is uh our assessment of whether or not you have endometriosis, right? And we collect cases and we collect controls. And ideally, what you want to see is that there's this nice separation in those two curves, right? And so we we plot this data and on the left hand side um you see cases versus controls, and the curves are completely overlapping.
Swaril Mathur:Oh my gosh.
Ridhi Tariyal:Not ideal. And on the right hand side, there's like a five-fold separation. Beautiful, exactly what you would want to see. Um, and they were put through the same algorithm, same data points, like absolutely the same data. The only difference is on the right hand side, we actually told the algorithm all of the female specific labels. We told it what age she was in her cycle when we collected the sample. We told her what type of bleeding phenotype she had, et cetera. On the left hand side, we just didn't. We said pretend this is a data set exactly like everyone else collects. And you know, the curves were completely overlapped. And so for us, that was it. We we were like, this is the future of women's health. Wow. This is massive de-riskment, which is if you have these labels in place, you are actually able to see signal from noise. And that that to me is is the real value of NextGen Jane. Forget about the diagnostic piece of it, is this data architecture and this stack that, you know, if you have a belief that uh, you know, the most valuable thing in this, in this um changing, very quickly changing landscape is proprietary walled gardens of data that are well labeled and well annotated and are specific to very um you know, clear populations that you understand, that is what we are building.
Swaril Mathur:Wow. That is incredible. I love, I love that example of the uh, you know, the histograms. And I think what what it brings to light, you know, as a again, as a consumer who hasn't spent two decades in genomics, right? Who's who's trying to understand, you know, the impact of all this is conditions like endometrioses for so long, the talk track around them has just been they're multifactorial and it's so complicated, and you can't predict when you're gonna have a flare-up or what how significant the lesions are. There's all these things that the answer has just been it's too complicated. Throw your hands up in the air and just uh like brute force with the bluntest tools possible. We'll just rummage around inside your body and try to pick out weird lesions that we find. And that's not a commentary on like the wonderfully skilled physicians. It's a commentary on the lack of the basic science to support anything different up until now, right? Um, but the nuance with which you and your team have thought through what are all of the layers on top of the data and what are the ways they need to come together to make this data truly actionable and to differentiate and tease out these, you know, highly intermingled, um, you know, highly complex conditions is really interesting. This is really profound.
Ridhi Tariyal:Thank you so much. And I will just telescope out to make two other comments. One is is that um imagine, so you know, if if the way that you diagnose the disease is through surgery, right? Uh what is the clinical endpoint you're chasing in uh drug trials? You know, it's not actually degree disease regression right now. The clinical endpoint for endometriosis trials is pain. One of the most subjective uh endpoints you could imagine, right? And you know, people who develop drugs for endometriosis know this, that this is a weakness in the entire way we think about drug development for endometriosis is you need a molecular phenotype to change to comment on whether or not your drugs are making an impact on the progression of the disease. If you do not have that molecular phenotype, what are you assessing? Just reduction in pain, which again could be placebo effect. Like is this right?
Swaril Mathur:Right, right. Like the level of clinical risk in running that trial just increases tenfold because you don't have an objective, reliable metric.
Ridhi Tariyal:And and I'm just tying this to like this is why this is so much beyond data, right? Once you establish a molecular phenotype, great, sure, it can be used to diagnose, but think about how it could transform the small molecule options that women are going to have in the future. Yeah. Right. Now you're actually saying go up against disease progression. Like that's what you should be evaluating as to whether or not these drugs work. And then if you telescope out further, it's, you know, why not just endometriosis, it's not just reproductive disorders, it's immune-mediated disorders. You know, it is all these different conditions that affect women. And, you know, uh, there is there's this really interesting um comment I always make when I think about like what why would menstrual effluence be the right um uh uh aperture for thinking about all inflammatory and immune mediated diseases? The the biggest answer is that menstruation in itself is a programmed inflammatory event, right?
Ridhi Tariyal:Like women, female biology presents model systems you can you can use to study, you know, loosely good inflammation. So like ovulation is an is an inflammatory event, but it's not it's natural, right? You're you're gonna get inflammation during ovulation, implantation, inflammatory event, menstruation, inflammatory event. And menstruation is really unique in because it is, it provides you the opportunity to understand the kinetics of inflammation. What happens during menstruation? You have this huge inflammatory cascade that kicks off because your body is saying, shed, right? Kill these cells and shed the endometrial lining. And then you have this repair process where you now have growth of the new lining. And so over the course of three to five days, you have a model system by which to observe the natural cascade of inflammation to repair, right? And and we would offer up like inflammation to rep, well, inflammation is the consensus pathophysiology of so many diseases. If you could understand the relationship between inflammation and repair, you now have insight into so many diseases. Absolutely.
Swaril Mathur:And I just think, you know, as we as you zoom back out that way, the thing that comes to mind for me is we've talked before about the fact that so many other conditions that aren't women's health conditions, they are just human conditions, have been studied primarily in the context of men, right? The research studies, clinical studies have historically been mostly male because menstruation is a confounding factor. And be because that's it, you know, if you're if you're a scientist trying to maximize the cleanliness of your data to get a result, it's better to control for that factor by not introducing it. And um, and it makes me think that this could be a possibility to kind of catch up on that research and and use this as a lens into those chronic conditions that have been studied so broadly in other populations. But maybe there's a gap in the understanding for women. And this could become a tool to to catch up on that and maybe in a more accelerated way because of the ease of measuring it with a natural biopsy, like a a natural, a natural source for sample collection.
Ridhi Tariyal:Yeah, totally. I mean, even so, you know, again, I I tend to focus on like the scientific aspects because they're just so super cool. But even from a um compliance perspective, think about how hard it is to get patients to come back for blood draws. That is incredibly expensive. And it, you know, you lose a lot of patients from that. Imagine just mailing them a sample collection kit and being able to get them to regularly give you uh, you know, molecular updates in that way, right? Just just clinical coordination could be improved by integrating something like this. Imagine how many um phase one safety studies uh don't have women. Right. I mean, just just and and it, you know, we think that like the it's fine, but if you think about like the sheer number of drugs that have been pulled off the market are mostly for for side effects that they had on women, right? It's it's just it's the the the utility of it is just, you know, when you um when I have put my big vision hat on, I'm like the utility of it is just endless.
Swaril Mathur:Yeah, yeah, absolutely. You know, I think there's this is an incredible opportunity. Um, we've talked a lot about the NextGen Jane story, and I I kind of want to zoom back out now as we've as we've explored it and talk about your journey through this. I mean, as you look back um on all of this, what have been some of maybe the the more challenging moments for you, the moments that have really tested you and pushed you? What have you learned from that? And and maybe to summarize it all, like how are you different as a leader and as a person now than you were before you started this journey?
Ridhi Tariyal:Oh, those are tough questions. Um, maybe I will answer the easier one first uh about uh the challenges and in the journey. I mean, I think one big challenge is um, you know, women's health tends to get drip capital. Um and this science could have moved so much faster if there were bigger checks cut for it, right? But um I always say that, you know, when you give uh certain areas of science uh small checks, you are telling them to make incremental progress. And when you write big checks, you're telling them to shoot for the stars. Um, and so part of, you know, I will I will fully say part of the tenure journey that we've been on is really because there's been no foundation, right? So build we've been building the scaffolding as we go, right? Truly, truly being like, oh, this this is a really important feature.
Ridhi Tariyal:Now we have to go back and recollect and to understand exactly what the impact is. I mean, even to figure out all of this, like uh the kinetics of cycle day and how important it is, and some of these covariates, you have to collect multiple multiple, like day one, day two, day three from like 50 people across multiple cycles. Like, you know, that's it's like a huge undertaking to even set the groundwork. And so um, you know, some of that has been just this is just gonna take time because it's new, but absolutely some of it has been so frustrating um because it's there's just not enough capital that's gone into it, right? And you you can't, you know, again, once you get past the series seeds date, it's harder and harder to unlock bigger and bigger checks unless there is this clear path to commercial data, right? And this is this tension of if you're doing something that is more basic science oriented in a you know capitalistic environment, um, you are gonna face that pressure, right? To be like, when's this baby coming to market? Right. Love science, love, love the leaps and bounds, but like you got to show me the path to market. Um, and and that's been necessary and frustrating. And, you know, I've I've often wished to be like, uh, this needs a $50 million truck to go from um zero to a hundred. If you want the zero to a hundred and eighteen months, then I need a bigger truck.
Swaril Mathur:Yeah.
Ridhi Tariyal:If if I can't get a bigger truck, then you're just gonna expand the timeline from how we get to a hundred.
Swaril Mathur:Yeah. Yeah. Yeah. It's an interesting um relationship between between dollars in and timeline that I hadn't really appreciated. And and it's interesting actually to hear that in the context of kind of the basic science research, because those of us who maybe haven't engaged as deeply in basic science research might assume that it just moves at the pace it moves. Um, and basic science research in the university setting, you know, certainly isn't isn't always that quick. But I had never thought about it through the lens of there are probably pieces of that that are true. And then there are probably pieces that if you throw some accelerant on it, you could move more quickly.
Ridhi Tariyal:Let me tell you, I mean, like there are more money at product development, it moves more quickly. If you throw more money at clinical trial enrollment, it moves more quickly. Yeah.
Swaril Mathur:Yeah. Yeah. There you go. Well, okay. Um, and then what about kind of your your experience as a as a leader? I mean, there's just, I'm just imagining there's so much uncertainty that you are facing every day that you've been leading through. You are going after such an important challenge, but that also means on many days, I imagine you're just doing things that nobody has ever done before. How, how has that, you know, transformed your leadership or affected you?
Ridhi Tariyal:Yeah. I mean, and maybe two things that stand out is curiosity, persistence. Um, I think curiosity because like again to your point, it's everything's so new that you've got to be curious about it. Um, and you know, you can you can start to have conviction, but it better be loosely held. Cause the next day you will find a data point where you'll say, oh, oh my goodness. Um and so, you know, you you can't be uh again, when you're when you're when you are um traveling such novel terrain, you've got to be open to that to say, like, I am just gonna learn. I'm gonna ask a lot of questions. I am, I'm gonna try to hold off on assumptions um and be ready for wherever the data's gonna take me. Um and so I would say that is just that's a skill set I have had to hone to be okay with that. Um and I would say um persistence because you know, you do, you do want to quit, right? You do there's there's many opportunities where you're like, um, you know, I've been approached by uh like scientists that have really, again, really cool tech, right? That there's so much happening in the world that I've that have like actually asked me to say, are you done with NextGen Jane? And like this is I I would love for you to come run this. And um, you know, you're always tempted, like, because you're like, oh, this this is the new cool shiny toy. Yeah. Um, but but knowing that you are working on something that really is is super novel in it. It's it may you may have been working on it for seven years, but it is still super novel to the world. Um and saying just stay the course, stay the course. There there are breakthroughs happening and there are bigger breakthroughs coming. And if you can be patient with it and persistent with it, that that like that the you know outcome is gonna be way more than you anticipated. Um and that's that's it, that has been a like a skills, skill to hone in itself, to say, like, no, of course there's gonna be new shiny toys. You've just you you've got to finish this. Like there's something interesting here. And the reason, you know, be-- forget about the money for a second and the capital acquired to do something like this. Like the reason that these team things take a long time is because they're hard. Like, and if you don't have the patience for that, then you're never gonna get to that the Easter egg at the end of this.
Swaril Mathur:Yeah, yeah, absolutely. I love the way you articulated that. And I think your passion for this is so palpable in the way that you talk about this entire journey, this mission, and what's at the end of the finish line. And I am, I am just so excited to watch it come to fruition and to continue tracking the journey.
Ridhi Tariyal:Thank you so much.
Swaril Mathur:Ridhi, this has been a really wonderful conversation. Thank you for sharing your personal story and the story of NextGen Jane. You were tackling some enormous problems that will have transformative impact on a lot of people and excited to continue to watch it come to life. Awesome. I appreciate the opportunity to chat with you. Thanks for being on.
