Solving Patient Matching in Rare Disease Trials

Welcome to let's Talk Rare, a monthly podcast from Partners for Access, where we discuss news, views and the latest insights from the orphan drug and cell and gene therapy world. Welcome to let's Talk Rare. Today we are continuing our 2026 the year of the Patient. And we'd really like to concentrate on today's topic of finding and connecting the right patients to clinical trials. One of the persistent barriers in rare disease drug development isn't just scientific discovery, but it's identifying and reaching the small number of patients who could benefit from emerging therapies most. And today we are delighted to be joined by Dr. Jennifer Carter, CEO of MedZone, a platform redefining the healthcare ecosystem by improving patient access to advanced therapies and clinical trials for cancer, rare and complex diseases. Welcome to let's talk prayer. Dr. Jennifer Carter, it's great to have you with us. Thank you, Owen. It's great to be here with you. Nice to see you. Now, before we get into the nitty gritty, tell us a bit about your journey to CEO of medzone. How did you get there? Well, it's been a little bit of a circuitous journey, but it's been a fantastic journey actually. So I started off as a physician many, many years ago, really in internal medicine or as a primary care doc. Quickly moved into the world of startups and consulting and investing and got very involved with consulting and financial services. This was back in the early 2000s. It was just the beginning of some of the new cancer drug development and diagnostics really where we started to be able to look at biomarkers and drugs were designed to target those biomarkers in patients, cancer. We just had really individual biomarkers back then, even next generation sequencing. It was being developed, but it wasn't clinically available. I had a number of friends and family members back then who got sick with very bad cancers, and I was involved in helping them navigate their journeys just based on my career and my background. I was actually shocked with how fragmented the system was. Even for people who have access to the top cancer centers and the top doctors and could go where they wanted to and had the education to be able to ask questions and things of that nature. Yet they were still told different things at different places about essentially the treatment for the same disease. There was no underlying infrastructure or really data guiding that decision making that enabled a right or wrong answer, if you will, or even an answer that got you further ahead in making the decision. And oftentimes they were left to make the decision themselves without really even having the background to do so. And I found that shocking. And then when I was looking at the advancements in the way drug development and also diagnostics were kind of barreling forward, it became clear to me, and this was really, back in like 2005, became clear to me that there was going to be a whole new paradigm for the way we diagnose disease and the way we treated it, that there was a whole new way of developing drugs to treat these diseases. So back in 2008, I started one of the first personalized medicine or precision medicine companies called N of 1. And we started the field of what today is known as molecular oncology decision support. And that basically meant taking the genomic information from patients tumors and turning that into treatment strategies. Yeah, it was super cool. It was really cool. And back then people didn't even know what I was talking about. Wow, this is crazy. This isn't going to work. We became the world leaders in that and ultimately sold the company. And it's still the core of a lot of the interpretation of next generation sequencing and molecular diagnostics in oncology. When patients get their tumors sequenced, n of 1 is the backbone of how that data is interpreted and helps doctors know what to do with that information. Really exciting journey, you know, Then I did a startup, you know, in the clinical trial space, which was acquired by a pharma company. Spent time there running Precision Health. And most recently I was a managing partner at Blue Venture Fund and Sandbox Industries, which is a venture firm for Blue Cross Blue Shield. And I got very interested in basically how do these drugs and diagnostic testing and how do we use the data and how does that enable the payers to basically figure out how to get their members better access to treatments. So from there I looked at a bunch of the solutions in the market that were supposed to solve some of the real challenges with the cost and risk associated with cell and gene therapies. And you know, cell and gene therapies are just the tip of the iceberg of specialty drugs, right? And there are thousands of these drugs in development and they're fantastic drugs, but they're very expensive and they'. Esoteric. And we have to figure out how do we get patients access to these drugs in real time, but how do we do it in a way that's affordable for the system? You know, I was looking around for other solutions to potentially invest in. You know, quite frankly, I didn't think any of those were really going to solve the problem in the way that would benefit, truly benefit patients. So I decided to Start Medzone. So here we are. There we go. So funny. You've got a real pioneer yesterday. Starts one thing, success sells it does something else and so on. And so that's an amazing story and it's absolutely great to have you with us. You know, I was so excited that you were with us, Jennifer, that I completely forgot to introduce my co host and I will never get into it. So also joining us today is the wonderful Georgie Ratt. Georgie, how are you doing? I'm very well, Owen. Great to be here as always. And I'm really looking forward to recording. Yeah, definitely. Now, we've heard a bit about your journey there, Jennifer, but what I'd love to do is to just flesh out your story a little bit with. With our listeners and ask you a few either or questions. Not many, but it helps people give a little flavor of your likes and dislikes. So if, if you don't mind, I've got a few for you. So first one, and we always ask the same question to our guests is do you prefer the town or the countryside? Well, how big is the town? Any town. Any town. Your local town, let's say. I love both, actually, but I prefer smaller cities or towns that have a little bit more of that natural feel to them, if you will. Fantastic. So that was an amazing answer. You kind of a bit of both there. Okay, what about walking or running? What do you prefer? Well, at this stage, I prefer walking, but I once was a runner, but not a really great runner, so I'll go with walking. So sweet or savory? Oh, sweet for sure. A scary movie or a comedy? Comedy for sure. Email or teams message? Oh, email A pets or no pets. I'm a no pet person. Going away or coming home? That's a hard one because if you go away, you want to always go home, right? Like, I'm not really sure I like to go away, but I like to come home. So that's a tough one. I guess I'll have to. I guess I'll have to say coming home. And finally, it's not really neither or. But what's the strangest place you've ever been to? I think we're gonna have to come back to that one at the end of the podcast, I'm afraid. Well, we're gonna. We'll put that one on ice. Thank you very much. Great answers, by the way. And I feel I know you really a little bit better from those, which is kind of the reason we like to do them, but really the reason you're here. Is for us to talk about finding, connecting the right patients to clinical trials. And as we know, in rare diseases, everything is a bit more complicated than in normal medicine. So really, let's start with again, I guess, difficult question, what makes rare disease populations so difficult to find and diagnose? Well, I think, you know, this in some ways is a bit of a tautology, but based on definition, they're rare. Right. And a lot of the rare diseases in many ways have been ill defined. Right. I mean, there are certain buckets of rare disease where, you know, there's a clear genetic definition of them. And those are in some ways, you know, obviously they have a more clear etiology and definition associated with them. And yet because of just the numbers and often, and also sometimes the different presentations, even in well defined diseases, it takes a very long time for patients to get diagnosed. It depends where they are. Right. Because sometimes in less sophisticated systems, it takes a lot longer for them to get diagnosed or for people to have access to the technologies that allow them to be diagnosed with certainty. And then based on the definition, which is they are rare, and depending on how rare the patients can be anywhere, finding those patients, being able to engage all those patients, finding them at the right course some time in their disease is very challenging. It's interesting, you said about sometimes the actual disease itself is badly defined. Yes. Can you elaborate on that bit? Can you give us an example of one that you've come across? Yes, I mean, I think, you know, without really honing in on a specific example that comes to mind, but even if you look at, you know, some of the rare neurodegenerative diseases or autoimmune diseases, it takes years and years and years for people to even get close to a diagnosis. You know, I think that's even when people have access to good medical systems and they really are getting the right, a lot of testing done, they still can be very ill defined. I mean, I think that we don't know a lot about different diseases. And so it's very hard to pinpoint how to treat them for the more well defined diseases. I think, you know, it takes years even for, you know, coming to mind things like Ehlers Danlos or, you know, some of the neurodegenerative diseases. You know, there's lots of, there's lots of overlap in symptomatology from disease to disease. People often will get a diagnosis, they'll live with that diagnosis for quite some time until someone says, well, I don't really think that's your diagnosis. And then they get Another diagnosis. I think it makes it really hard for patients with these diseases to get treated. We see it even in oncology, where they're rare cancers. And it turns out that about 25% of all cancer is rare. Right. And so, you know, it can take a while for these cancers to get diagnosed or they get diagnosed as a certain cancer type, but the treatment for those cancers is still poorly defined. Right. So absolutely. And just looking at kind of the diagnostic odyssey, as we say, just just looking at some stats here. So kind of on a global level, the average time for a diagnosis for a rare disease is roughly around four to five years. That's incredible. The typical range could be between four and eight years to actually get a diagnosis for a rare disease patient. And in some cases, around 25% of the global population, that's over 10 years. What kind of impact do you see this in trial readiness, for example? Well, I mean, I think that, you know, more and more and happily, these diseases are, well, become better defined, But a lot of the newer drugs are focused on a particular mutation or biological change. And I think that's where there's been the most success, generally, because you're not sort of taking a broad sort of physiologic approach. You're taking a really, you know, specific approach to the etiology of the disease. So if you can define the underlying mechanism, the disease, then I think, you know, that really impacts the ability to develop specific drugs that could impact the outcomes of endless symptomatology of the disease. Right. I think when we have the, you know, when people are on this diagnostic odyssey and their disease is, you know, relatively poorly defined, it's very hard to think about what is the appropriate therapy for them. And there's a little bit more of that trial and error that goes on in terms of trying a therapy that impacts inflammation, let's say, or impacts a symptom of the disease, but it's not really getting at the underlying etiology of the disease. That's part of the challenge, I think, on these diagnostic odysseys that you're still looking for what actually is the disease or what is actually the etiology? For a layman like myself, sometimes I think, gosh, you know, there's been, you know, at least over a century of medical diagnosis of these. Of these diseases. Don't we know all about rare diseases yet? Don't we? Can't, don't we? Haven't we categorized every single rare disease there ever is? And if we haven't, how long would that take? Well, I think I Think, number one, we haven't. And number two, I think that, you know, that's a large place where, you know, technologies and, you know, enabling technologies like AI are really having a tremendous impact because we can use AI now to put in the right prompts around symptoms and response to therapy and other kind of variables and then be able to search all of the literature and all of the studies that have been done and kind of collate that information much more quickly and much more expansively to get to information that may lead to a diagnosis. And that's really exciting. And I think it's early days for that. But I think that, you know, hopefully, Georgie, like to you, the statistics that you just quoted, you know, we'll see that, that those numbers, you know, the time that it takes to make a diagnosis and the diagnostic odyssey being shortened, that would be, that's, that would be really hopeful. I mean, there's a natural thing you'd imagine would happen. But let's, let's talk about a bit more about the role of technology and data innovation. Tell us a bit more about what you do at medzone. Yeah, so at medsound, what we're doing is basically we are working with any organization at risk, health plans, et cetera, to identify, basically come in as a benefit to the members and identify those members who have those patients really who have really complex diseases, cancer, rare disease and other complex diseases who are likely to need help from cutting edge treatments that are often in trials and find those patients and really be able to get them access to those cutting edge treatment. And you know, we apply lots of different data and technology to be able to help find them and work with them. But we also provide a first and last mile high touch approach to working with the patients. But the real underlying pieces around data and technology is data and technology are really powerful tools for being able to identify patients and being able to understand where they are on their journey and how to get them access to the best, best treatments that are most personalized for them. And are you finding, Jen, that the tech that we're using now to gather this data is really helping to improve the patient identification for the right trials for them? Oh, absolutely. In the real world. Yeah, yeah, absolutely. I mean, you know, being able to use the technology is, you know, the types of technology that we have today with, you know, all the different types of LLMs, et cetera, it's huge, right? I mean, it just, it's a huge enabler of being able to process a lot of information and data much more quickly. I Feel like it's table stakes to be able to use technology in that way. I think that there's still a lot of domain expertise that is required to really solve the rare disease and these complex disease problem and figuring out how to get patients access to treatment. Because the technology is really only as good as the data that we put into it. We see that across the board. It's this whole concept. You could put a ton of data into one of the large language models and come out with an answer, but if the data is not good or it's not enough or there's not enough to compare it to, the answer is not necessarily going to be the right answer. You have to really think about it as a tool that we use, I think, to enable, to speed up discovery, to open the opportunity and aperture on answers and progress and other options that are out there. But the domain expertise and I think the conscious questioning of that data and what the answers mean and what is the best approach is really a requirement across any of medicine really to really find patients the right treatment. And I suppose what can really help there is patient advocacy groups, patient registries. I'm really using the data from that and plugging into these AI kind of tech databases to really like you say, find the correct patients that you can then combine with the right trial, I suppose. How important are patient registries, Jen, and patient advocacy groups in this? I think that anything that helps move the needle forward for patients is high value. I think that one of the big challenges that exists across any system really is a fragmentation that exists where there's data barriers and data sharing barriers and barriers on information and how patients receive that information. I think that's a little bit of the challenge that there's a geographic challenge, there's a business challenge. You know, there are lots of challenges to that. So, but, so I think any effort, however, any effort that's trying to move forward, that move the needle forward for patients with rare disease and improve discovery, improve access is highly valuable. Definitely you touched on this earlier actually, Georgie, about the, hopefully the time for diagnosis coming down for rare disease generally. So in practical terms, Jen, what does this actually mean for the patient, the patient with a rare disease? How is their journey, do you think, going to change with the event of technology? Well, it's been huge change, I think, Owen, when I think about when I started n of 1 back in or even began to think About n of 1 back in the mid early 2000s, around 2005, between 2005, 2008, if you look at it none of the drugs that we have today for cancer, well, almost none of them existed. Wow. Really? In the last, what has it been, 15, 18 years, the whole field of oncology and the way we treat cancer has changed with targeted therapies, with immunotherapy, now with CAR T cells, et cetera. And now we've the development of gene therapies for these rare diseases, monogenetic diseases, where we can actually really replace a piece of DNA that is not working in the right way for the patient. That's huge. That's one aspect of technology that has vastly changed the whole treatment of cancer and rare disease already. That's next generation sequencing. The data and the knowledge that we've laid on top of that, the ability to process that with bioinformatics and the type of work we did around oncology, decision support and things like that, have completely changed that aspect of using genomic medicine to drive forward on the clinical side in parallel. If you look at it in terms of drug development, our ability to use AI and these advanced models to really test out, you know, binding sites and configuration around proteins and genetics and using the different types of CRISPR technologies and whatever, to define new drugs and develop new drugs. Phenomenal, right? I mean, for the rare disease population, not all these drugs work, but there's. There are many that do. Look at sma, right? Look at Duchenne's, look at hemophilia, right? And sickle cell now, right. I mean, the progress is massive, right? So over the last 15 years, when you think about how technology has changed the whole paradigm of drug development and diagnosis, I mean, it's massive, right? Yeah, it's got a long way to go. But when you think back, I mean, I've had the great fortune of being riding this wave all the way from the beginning and being able to be at the cutting edge of it. And it's just been phenomenal to see what's happened. Even though it feels like we're just taking baby steps, if you look back, it's like it's massive change and massive benefit for the patients. So that's a really good point, isn't it, Georgie? You know, sometimes you think, oh, you know, we haven't moved that far. But when you actually look back what Jen just said, the change has been unbelievable. Unbelievable. And Even in the 12 years that I've been working kind of in the rare disease space and working on this podcast, you know, we've had many different guests and many different podcast episodes on talking about the patient, the patient voice, patient Engagement, patient involvement in clinical trials, and really making sure that you're building your trial around the patient and understanding that that patient signs symptom, you know, what they date, what they live through daily, even from the caregiver perspective. Because a lot of rare diseases affect children, very young children, and not so much the adult population. So it's really the whole family dynamic that is impacted. And for drug developers, I think it's really, as we've always said here, to really integrate the patient voice into their clinical trial before they even start to think about it and develop it. Actually speak to the patient and listen to the patient, because they are the experts of their disease. They are the ones that have to go to these trials and making sure that it's really sustainable for them to stay in the trials right through the end without impacting their quality of life to a certain degree as much as possible. There's financial burdens, there's all different sorts of burdens. So how are these changes? Sorry, I've gone on a tangent there, but how are you so passionate about it? It's like at the core of all of this, Georgie, it's so important. Absolutely. So are you seeing this having an impact in drug development and in kind of the speed to develop drugs, Jen, or just the speed enrollment for rare disease patients in clinical trials? You know, it's hard to know. I mean, I think that we've. The needle has moved a little bit, especially in oncology. I think there's just more awareness as these new drugs have come to development and there's been some really amazing impact. I think people are generally more aware, but I think the stats on that are still. It's maybe 6% of patients get into clinical trials. I've heard it may be as high as 9%, but really, on average, I mean, that's shocking, right? It's really shocking. And I do think, you know, we really, I think it's so important to, you know, technology is a huge enabler, but at the end of the day, it's got to be all about the patient. And that's why we really believe in that first and last mile too. You know, we, you know, deep in the data, deep in the science understanding, but it really all comes down to how do you help the patient really, you know, and their families really access those treatments? And that's, you know, absolute critical variable for sure. We've talked a bit about, you know, the things that are going on, and there are huge strides being taken at the moment and really encouraging things happening out there. Harnessing technology for really great reasons and using it really smartly, but we're not there yet, as you've just said, you know, and change in these things does take a while to filter through all the mechanisms. So from your point of view, Jen, what needs to change? What are the biggest gaps that need to be addressed in finding the patients and getting these things speeded up? Well, that's a hard question. You know, I mean, I actually think that we're really. Med Zone's really addressing many of those real fundamental issues. But, you know, I think as it comes down to, you know, it's really just such a fragmented system. And, you know, it's. It's fragmented in every way. It's, you know, around information and data and technology and access and knowledge and finance. You know, that each piece of that has its own silos. And, you know, and even within the silos, there's fragmentation. Right. So, you know, and I think each in a, you know, I like to say that, you know, we're looking. I'm looking at things from a health solution perspective. I think having been in this market from long, long period of time, but a lot of times technology or applications are developed looking at a sliver of the problem too. And, you know, but. And that's the way that, you know, I mean, pharma looks at it from the drug development side. Providers have to treat their patients. They have to. They function under the world of reimbursement, and there's variable variabilities in reimbursement. And, you know, I think that all these challenges and all these infrastructure challenges, if you will, all of them create blocks in the system for patients to get access. We see that in every aspect of. It's not just in rare disease or cancer, you know, it's even in much more common diseases. You know, in getting a, Getting an mri. You know, it's like, oh, first you have to do this and then you have to do that. And it just, I mean, there's one. There's one infrastructure barrier after another for people really getting access to care. So I think it's, it's really. We have some systems challenges. Yeah. And you, you raised a really good stat there. You said 6% of patients actually are unable to. To access a clinical trial. I mean, I was just sitting there thinking about that, and you said, may, maybe it's nine. But, but if we kind of go in the middle, you're talking 6 or 7% of patients actually are able to access a clinical trial. How can we ensure that we get More patients in these trials and effectively getting the treatments that they need. Absolutely. Well, again, I think that gets to some of the things I was talking about before is thinking about how do we change a little bit around the infrastructure that creates the barriers all along the way. I think it's also a data problem. Right. I think it's an education problem. Providers need to be educated, patients need to be educated. You know, so I think addressing all those different variables, infrastructure, access, education cost, you know, there's a lot of different pieces to it, Georgie. And, you know, I think again, that's been my work since, over the last 15 years and I hope we're going to be changing the paradigm now. But, you know, I think there's, if I could say there was a magic bullet. I'm not really sure there is one magic bullet to change, to change all of the challenges there usually ever is, is there? No, no. This magic bullet that we, we often talk about, but it just doesn't exist. It's just a lot of hard work, a lot of effort and a lot of patience as well. Absolutely. But what we, you know, we at Med Zone really envision is, you know, it's not really about the technology per se, or that trials need to be done differently. It's fundamentally more about creating a more connected, basically ecosystem healthcare system. You know, and that's, that's really, you know, our focus. And I was going to ask you just to close. Jen, you know, if you, if there was one change you could make for disease patients, but I think you've answered it there to make things more connected, to take away the fragmentation of the system. And with technology, we're on the road to that. Right, Right, exactly. Take away the fragmentation, but layer in the domain expertise, the understanding of the need for precision medicine and creating diminishing fragmentation and creating cost of sustainability as well. All those variables have to come together so that we can get those patients the therapy when they need it at the right time, make faster diagnoses, you know, all these pieces, bring them together and create a sustainable system around it too. Dr. Jennifer Carter, it's been a pleasure to spend some time in your company. You're doing fantastic work and I have to say it's been really, really informative what you've discussed today. Just finally, that strangest place you've ever been to. Well, this has been such an engaging conversation. Let's see. I'm not sure that I have a great answer. I can't leave this conversation without a really good answer for that or just a place that you just think, wow, that's interesting. Okay, wow, that's interesting. All right, how about. You know what? I just did one of those Formula one virtual races and I was like, I was like, you know, you bounce around in the car and everything. I'm like, wow, how do people, like, do this for real life? Like, how do you, you know, it was, that was. I never expected it to be quite so. So virtually in such an all around experience. That was pretty crazy. So that sounds fun. Do you feel the G's in the simulator? You do? You do? I got a little car sick, Georgie. I was like, this is crazy. It's been one of my ambitions to. To get in one of those cars and try it out. I might have to have look this up and see if I can find one in the uk. That was pretty. Yeah. Well, that's a fantastic answer. It gave us much more than I wanted, which was just a quick, we're gonna go away and look at this Formula One thing now. Jen. I 100 now. I'm gonna look at it now. It's been. Like I said, thank you so much for spending your time. It really is just an amazing, exciting point. We are at, in. In. In medical history, really. So check out Med Zone. They're doing great work and we hope to have you back on the podcast sometime in the future, Jennifer, to tell us a little bit more about these amazing innovations and how they're improving patient access. Thanks so much. Thanks so much, Georgie. Great to talk to you today. Thank you, Jen. Lovely to meet you. Take care. Okay, thanks. Bye. Bye. Thank you for listening to the discussion. You can find more information about this subject and other matters relating to rare disaster and cell and gene therapies on the Insights section of our website, www.partnersforaccess. Com.