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Built This Week is a weekly podcast where real builders share what they're shipping, the AI tools they're trying, and the tech news that actually matters. Hosted by Sam and Jordan from Ryz Labs, the show offers a raw, inside look at building products in the AI era—no fluff, no performative hype, just honest takes and practical insights from the front lines.
We we strongly believe that clinical trials that could bring life saving therapies to patients need to move faster, need to be more efficient, and need to be cheaper. And if we do that, we'll be able to get faster life saving therapies to patients.
Intro:Built this week, breaking it down. Built this week, we show you how. A fresh idea, a clever tweak you locked in. You built this week.
Sam Nadler:Hey, everyone, and welcome to Built This Week, the podcast where we share what we're building, how we're building it, and what it means for the world of AI and startups. I'm Sam Nadler, cofounder here at Rise Labs, and each and every week, I'm joined by my friend, cohost, and business partner, Jordan Metzner. How are doing today, Jordan?
Jordan Metzner:Yo, Sam. Another new episode. Exciting week. Great new guest. Lots going on in the world of AI, like, every week.
Jordan Metzner:I mean, some crazy news, both in politics of AI and just, you know, a lot of new a lot of new AI features and products coming out of Frontier Labs. So exciting new episode, looking forward to chat.
Sam Nadler:Absolutely. And I'd love to introduce our guest, doctor Chadi from Write dot ai. You know, Write dot ai is an AI platform that builds digital twins. Doctor Chadi, welcome to the podcast. Tell us a little bit about yourself and what you're building.
Dr. Chadi Nabhan:Thanks for having me. Great to be with you guys. I'm a medical oncologist and a hematologist by training. I practice on the provider side for two decades, for about twenty years, and then I transitioned after that to the to industries. So I held several positions.
Dr. Chadi Nabhan:One of them was with Cardinal Health as chief medical officer and then Kerris Life Sciences as the chair of the Precision Oncology Alliance. Kerris Life Sciences as you know focuses on genomics and multi omics. And then I joined Ryght AI about two years ago as Chief Medical Officer and Head of Strategy. What we're doing is right, we strongly believe that clinical trials that could bring lifesaving therapies to patients need to move faster, need to be more efficient, and need to be cheaper. And if we do that we'll be able to get faster lifesaving therapies to patients.
Dr. Chadi Nabhan:So we are focused on enhancing and accelerating clinical trial operations by matching any clinical trial of any therapeutic area against the most precise and the best sites that are going to execute on this clinical trial at scale and globally. To do that we have built digital twins for every clinical trial site in the world that have done any kind of clinical trial in any therapeutic areas. We have a secure platform that really allows us to match the clinical trial against all of these sites using, again, AgenTeq AI and and generative AI platform. So that's what we're doing. We'll go into more detail, I'm sure, with that, but that's really very high level.
Sam Nadler:Perfect. I love it. And we will go into more detail. But before we do, don't forget to like and subscribe. We have new episodes out every week with great guests like we do today.
Sam Nadler:Hit that button and be reminded on every Friday. And the docket, we're gonna demo a little something we built with in mind. And, you know, like we do in every episode, this may be totally off base. I did my best to try and kind of capture maybe something that would be interesting for Ryght. But as you can see, this is a a digital twin dashboard and and could show the difference between manually selecting a site versus using AI.
Sam Nadler:So let me kind of walk you through this trial trial strategy snapshot, and let's start a tour, actually. I think that would be really helpful. So, you know, first, the digital twin. This dashboard simulates the clinical trial network using historical performance data and predicts enrollment velocity, diversity, and risk in real time. Obviously, you know, these trials, the goal is to, I'm assuming, finish on time and either under or at cost and with the right markers involved.
Sam Nadler:So the status quo problem, we're currently simulating a standard manual site selection strategy. Most sponsors over index on tier one academic centers where enrollment could be slow and diversity could be below target. With that, there could be financial consequence. So inefficiency has a price. You know, you could run over time.
Sam Nadler:You could run over in terms of cost. There could be regulatory risk, and with that, we can have AI optimized output. So the strategic advantage is, you know, we can recover the two month delay and hit diversity targets. So, you know, with this AI optimized output in terms of site selection, maybe, you know, Emory Healthcare could be a great option versus, you know, a tier one clinic that's ranked a little bit lower like the Mayo Clinic. So is this somehow you know?
Sam Nadler:And you could, like, trigger these simulation parameters that have, you know, biomarker complexity. How does that change the ranking of these sites, which could be a better fit for the clinical trial? You know, overlay the census overlay. You know, you have the potential strategic tension with equity. Is is this somewhere in the realm of, like, how your business is thinking about site selection and and why it matters?
Dr. Chadi Nabhan:Yeah. I mean, I think I think somewhat. So, you know, for the sites to execute on any clinical trial, they need to have qualitative capabilities for their specific study or quantitative capabilities in terms of what they can actually do in terms of enrollment and getting patients on. And these vary between sites. And to your earlier point, there are large academic sites, there are also the smaller community sites, there are sites in The US, there are sites in Europe, Australia, and so on.
Dr. Chadi Nabhan:Our goal is to help rapidly identify the best sites for this specific study. If I step back, Sam, I will say, why do clinical trials fail? First of all, they're costly. It takes ten to fifteen years to get a clinical trial to enroll. These are the trials that go to change standard of therapy, standard of care.
Dr. Chadi Nabhan:And 1 to $3,000,000,000, and by the way, 90% of drugs and trials don't really, you know, get you a drug to market. But trials fail because either the drug doesn't work that you are studying or because it's toxic so you cannot give it because it's really it could work but it's just too toxic, or simply because the trial did not enroll, so you never really got to the yes or no, you never got to that point. And when you look at the statistics, the statistics don't lie. 80% of trials run behind schedule, 50% of sites enroll just zero to one patients, and from a sponsor perspective, time is money. This is a lot of money to activate the sites and then don't enroll.
Dr. Chadi Nabhan:So we wanted to disrupt this by focusing on the third element. We're not making drugs, we're not really reducing toxicity, but what we can do, we can help sponsors identify the sites that are best for this particular study. And we also connect them with the right principal investigator, with the right person who's going to bring that trial and champion it internally because that's to help with enrollment. Subsequent to that, we also automate a lot of the mundane work. So we allow actually the exchange between sponsors, between sites, and so on.
Dr. Chadi Nabhan:So there's really this end to end solution between the two major stakeholders in that space. So your point is well taken that you have all of these sites, but maybe the site that is ranked in this particular list as number 20, it could be the best site for this specific trial that is going on there. And the only way to do that is by linking the trial and the specific needs of that trial against the capabilities of that site. And I'll just say one other thing is there are nuances. So you're talking with a sponsor that have a specific interest of having that particular trial enrolled in Europe because they have a regulatory goal in Europe as an example, strategically.
Dr. Chadi Nabhan:Well, where do you go in Europe if you have a specific regulatory component that you need to actually achieve? So we select the right sites that are able to execute on that. So I I like what you've built here. I think it's pretty easy and you certainly picked up on what we're doing. We're literally I mean, that's what we're doing.
Dr. Chadi Nabhan:We're trying to make that link and and be able to really rank these sites. So when whenever we get these sites, we end up having a score. We we tier the sites into three tiers, tier one, tier two, tier three. And the tier one usually the ones that are most likely to succeed in enrollment, tier two less, and tier three the least.
Sam Nadler:Incredibly interesting. Tell me a little bit about, we talked about it on our call, but how does diversity and the biomarker complexity kind of influence the results and or just the trials themselves?
Dr. Chadi Nabhan:You know, it's a really important question. You know, when you look at existing clinical trials in The US and, you know, cancer takes the lion's share of these trials, but even cardiovascular, metabolic, neuro neuroscience and so on, most patients that are enrolled in these clinical trials do not represent the demographics of The US. So you see often ninety to ninety nine percent of patients enrolled are Caucasian, while twenty five percent of patients in The US are considered non Caucasian. You see a lot of folks who are enrolled who have good socioeconomic status, they're able to travel, they have good psychosocial support and so on and that's really not what you see in real life. So what we do because we have the digital twins globally, at least in The US, we have the ability to link that against The US census and I think you have that, the census overlay, which is which is really interesting.
Dr. Chadi Nabhan:So you're able to actually tell in the using The US census and API into The US Census, what are the demographics of the patient population each particular site serves. So if you have a particular study that requires 20 or 25% underrepresented minorities, then that becomes actually high on the list when you are deciding to tier these sites and you're able to recommend sites that serve this patient population so the denominator is higher. The biomarker overlay is really critical and as you know at least in cancer, in cancer all of the trials now have biomarkers or mutations or things that you have to actually look at. The way we do that is several ways, but as you know, we have ability to look at every clinical trial that each site has done in the past because we are linked to clinicaltrials.gov where you have the repository of all clinical trials that have been done at each particular site. And if you know that a specific site has conducted prior studies that required biomarker testing, then at least you know they have that capability.
Dr. Chadi Nabhan:If you know more granular details that this particular site has conducted studies in the EGFR mutated tumors, then you know that at least they have that patient population so you actually rank them higher because that information is available through clinicaltrials.gov. So we basically look at past experience of these sites that allows us to predict also future success If you have a sponsor that have come back and forth to this specific site many times before for their particular studies, then that site must have been successful in enrollment and so on. So that census and biomarker is key, in the cancer world and I think it's going be beyond cancer as well. But that's how we do it for now and we're able to try to partner also, we're trying to form strategic partnerships with a lot of entities out there that we can layer out the genomic data on the digital twins. That's work in progress on the roadmap.
Jordan Metzner:That's awesome. I guess, I think kind of following up on what Sam has said, I'm sure a lot of like kind of site matching has like always been a problem in this circumstance. How has AI specifically I mean, you started to talk about like the ability to leverage like, you know, the DNA markers, etcetera. But how has AI kind of like pivoted the business in the sense of like giving it like kind of acceleration or ability to kind of make these twins, you know, and how is it mean, obviously previously it was done with like, I guess like SQL type data, right? You would like run these kind of data queries and try to find, you know, some type of data information, but I guess with a with a larger data set, obviously AI becomes incredibly more powerful, but yeah, maybe how has AI made it like a really big impact?
Dr. Chadi Nabhan:Yeah. I mean I I mean, as you said, Jordan, I mean, the mass of data just you can't really do this, any of this manual at this point. But but a couple of things are really important just to explain maybe a use case. Some of the you know, there are there are ability there are AI agents that we actually have built that allow us to find the right contact individual for each particular downstream after you select the sites. But before that, the AI is able to infer a lot of the capabilities of a specific site based on prior studies that they have conducted.
Dr. Chadi Nabhan:An example, if site A has conducted a phase one trial in whether it's a basket trial, umbrella trial, or one tumor trial, just because they've conducted a phase one trial and the trial has opened, We know that they can conduct pharmacogenomic studies, pharmacokinetic studies. We know that they're able to do x, y, and z. So the AI infers the information from prior experience and gives us the capabilities of this particular cycle. The other thing where we leveraged AI is reading the protocol. So when we upload a particular study that could be 200 page study in any therapeutic area, we have 13 AI agents that dissect and parse out, read the entire protocol.
Dr. Chadi Nabhan:We have an AI agent that reads the title, an AI agent for the schedule events, an AI agent for the biomarker, an AI agent for the endpoints, and so on. So by parsing the protocol in a matter of seconds, by the time you upload the protocol and click on the AI and so on, it just within seconds, the AI read all of the protocol and what it requires. What does it actually require to what does this trial require? It requires a site that has an MRI machine, they did a CT scanner, all of these things. And then it matches that against digital twins.
Dr. Chadi Nabhan:So reading the protocol is an example, inference is an example, and the third example is the AI agent that brings you the best contact person for this specific site for this specific trial.
Jordan Metzner:That's awesome. You know, this is the second or third, I think, healthcare focused AI enabled guest we've had on our podcast and in both in wildly different areas, but just showing how AI becomes like a super enabler even for industries that are obviously like, you know, more traditional like healthcare. Sam, what do you think? We go to the news.
Sam Nadler:Yeah. No. Actually, I have one more question, if you don't mind. Like, I can and maybe this highlights my unfamiliarity with the space, but, you know, I can totally see why CROs and sponsors are coming to you for the tool. Do sites themselves also who may be, you know, less recognized and who who want to do more of these kind of are they reaching out and saying, hey.
Sam Nadler:Like, these are our capabilities. Like, how do we is is that something that happens?
Dr. Chadi Nabhan:I think Sam should be working with us. I think he probably was think I think you were on our call last week or you called or something. The the the answer is absolutely yes. But as you know, Sam, I mean, you know, we have just to be strategic and we have to think what we could do today versus the roadmap and so on, but absolutely we have a site strategy, and one of this is exactly what you said. There are so many sites out there that have certain capabilities that they could be forgotten because nobody really has reached out to them and know them.
Dr. Chadi Nabhan:So we are building an entire platform for the sites where the sites actually go in and they're able to, a, you know, update the information, tell us the information that they have because maybe they can add more information we cannot get. I mean, we can only get information that is available out there, but there are certain proprietary information that I may not be able to have unless the sites volunteer that, and we're building this. We're also connecting the sites with the sponsors to make sure that if a site I was having a conversation with a site just about last week, and they said, you know, one of our interests is studies in colorectal cancer. And for whatever reason, we haven't had a lot of trials in colorectal cancer because the investigators that we have are not necessarily well known. We'd like to build their clinical trial portfolio.
Dr. Chadi Nabhan:So a site like this would come to our platform and show that they have a lot of interest in colorectal cancer, they have capabilities, they just have not gotten the chance, and then they get ranked higher because we have that information and we're able to link. So the answer is a resounding yes, and that's actually happening. Hopefully by the next time we meet again, you'll see a lot of this progressing. I mean, this is very, very close actually where you're gonna hear about what we're doing on the side. I would say in less than a couple of months, you're gonna hear on a press release for that.
Sam Nadler:Alright. We wanted to choose something a little bit health focused. Obviously, you know, sleep is really important. I think there's been a lot of recent trends in in health care pop culture news about how important sleep is in the last couple years. Maybe it's always been important.
Sam Nadler:Maybe it's always been trending important, but I feel like lately in Eight Sleep, this nothing too familiar about the product, and then this it's really this high end mattress where you can personalize it with cold air, warm air, you know, elevation, etcetera, just raised 50,000,000 at a $1,500,000,000 valuation. So, obviously, doing doing pretty well, I'm assuming. In a, have you either of you used Eight Sleep? Are you I believe it's a subscription model. Are you subscribers?
Sam Nadler:Have you sat on the bed? Have you tried it? And what do you think in general of of this news?
Dr. Chadi Nabhan:I am not. I was I read the article, and I was a bit fascinated by the valuation. I'm like, oh my god. But clearly, there's a huge market for this. I I need something like this.
Dr. Chadi Nabhan:I don't sleep well at all. Seems like, know, yeah, I mean, I don't know what Jordan thinks. I I was a bit fascinated by the technology and more fascinated honestly by the not the market valuation, but more of the there's such a huge market for this. Like, didn't I didn't I didn't appreciate that much until I read this.
Jordan Metzner:Yeah. So I I don't have an Eight Sleep, but I've read both sides kind of like customers that are fanatical about it and saying that's changed the way they sleep, and then also heard like horror stories of like water leakage in their house and kind of not having a great experience. Maybe that's, you know, both are kind of like vocal minorities. But yeah, I mean, I'm not a doctor, so I think that was like it would be interesting to get your take on it. But you know, I think the idea of being able to lower your body temperature while sleeping for people who sleep hot and and I guess maybe the same the opposite direction, but you know, in an effort to kind of, you know, improve the quality of sleep for the time that you have it is an interesting idea.
Jordan Metzner:I think this is I'm not exactly sure how the subscription aligns, like what happens if you stop paying the subscription, but does your bed stay
Sam Nadler:sleep on your own bed? Yeah. You have to stay hot at night. You have to sleep on the couch. Yeah.
Dr. Chadi Nabhan:I mean, sleep is important. I think this would be a perfect infomercial at 2AM on all the channels when you're, like, trying to flip through the TV at 2AM and and sleep and you get the infomercial for this.
Sam Nadler:Yeah. I wonder I wonder if they have a solution for my, you know, anxiety that keeps me up at night. I don't feel it's like a comfort issue. It's more of a a mind issue. But, yeah, just a fun article.
Sam Nadler:I I need to, like, see a store can you see these in a store, or is it just an ecommerce solution?
Jordan Metzner:I don't know if they have a retail location. I don't believe so, but, yeah, it's ecommerce mostly.
Dr. Chadi Nabhan:But that actually what's what what you said, Sam, is really important. I mean, when people have insomnia or don't sleep, how much of this is really because of the posture and the actual comfort versus whatever? I mean, all of these things, anxiety, work, burnout, there's so many things and that's not gonna be fixed with the mattress. But the market is telling us otherwise.
Sam Nadler:Yep. Totally. Well, speaking of retail, you know, one of our, you know, arguably one of the biggest retailers in the world, if not the biggest, like Apple just released a low cost or lower cost Mac Book, a May version. I think it's, like, a competitor to the Chromebook. I'm personally having two children.
Sam Nadler:Really excited about this. But, yeah, I think it was a long time coming to get an Apple computer at this price point.
Dr. Chadi Nabhan:But what's the I could I mean, I think the the power and the memory, like, I I didn't get a chance to finish the whole thing. Like, I wasn't sure what the it's probably I mean, obviously, it doesn't have the same capabilities as the larger ones. No?
Jordan Metzner:Yeah. I mean, they have smaller hard drives and memory for for RAM, but I think the key is that they're using the a series of chips that's available in the iPhone versus using the m series of chips that are historically in the iPad and in the Mac the rest of the Mac series. So I think that's like the biggest step down. Whether that has like a significant performance impact is to be seen as this is like a new series of computers on on on untested yet. But to Sam's point, you know, it competes with a Chromebook, and I probably have a prefer a low powered Mac than a Chromebook just because you get kind of the access to the entire operating system.
Jordan Metzner:But, yeah, I don't know. I haven't tried them yet, but, you know, $600 is a pretty good entry entry price point to get someone to use a Mac computer.
Sam Nadler:Chadi, before we wrap up, a thank you for joining. I also wanna plug that you're an author with multiple books, and a new book coming out is or just recently came out or or coming out?
Dr. Chadi Nabhan:Yeah. It's coming out in in a couple of months. It's AI in Cancer Care, and it's it's not a tech book. It's not a medical book. It's really a book that's written for everyone who wants to understand a bit about AI, to have an intelligent conversation, not to be intimidated by all of these AI jargon that they hear everywhere but more importantly how does it affect the cancer journey and their cancer care.
Dr. Chadi Nabhan:So it's really written in a very simple conversation, so I appreciate it. Yeah, it should be coming out in a few months.
Sam Nadler:What's the name of the bot?
Jordan Metzner:Yeah, how can people find you?
Dr. Chadi Nabhan:Yeah, it's called AI and Cancer Machines Meet Modern Medicine. I have a website www.shadynabhan.com and I think people will have information on my prior books and my upcoming books as well on my podcast which is very healthcare focused, healthcare unfiltered.
Sam Nadler:I've got a last question. So I've always heard that Google is a doctor's worst nightmare because the patients would come in saying, I googled all my symptoms and I got this disease, I got this thing. Is that now 10 times worse with ChatGPT? All the patients are calling in pre diagnosing themselves, or is it actually helpful?
Dr. Chadi Nabhan:I think it's very helpful, and I actually write that in the book and the prior book which is called The Cancer Journey. I think having an informed patient and family is 10 times better than having someone who is not informed. And I really don't think any physician is ever going to meet a patient or a family today, at least in The US. Right? You know, it's like in under in different countries, maybe different, but in The US, people are going to look things up.
Dr. Chadi Nabhan:They're gonna talk to their family, their friends. They're gonna be advised. So there's no the idea that somebody's going to come to you and they're going to hear for the first time about a diagnosis or a prognosis is just not practical. So a lot of times what's really important for the physician is to help patients and families really separate the signal from noise, the myths from facts, and guide them into online sources that are really more reputable and more, you know, you can trust them, more trustworthy as opposed to not. You know, you go on Twitter, you go everywhere, there's no filters, no peer review.
Dr. Chadi Nabhan:I could tweet anything I want. I could put a video on YouTube and so on. When I have time, sometimes I go in and I see some of the videos that really drive me crazy and I feel I have to really counter that and put it on my channel just to explain to patients and families some of the information that is really incorrect. But people are going to use online. I personally embrace it.
Dr. Chadi Nabhan:I just guide people and say, you know, you're gonna do this anyway. May as well do it differently. I'll just say one more thing is I think in the future, the Chad GPT and all of these LLMs are going to be 100 times better. I think we all agree to that. But also they're gonna really be attuned to every specific patient.
Dr. Chadi Nabhan:They're gonna almost know that patient and know what they want and so on, and the information is gonna be really custom made to this particular individual. And I think it's gonna help a lot of patients, and that's what I project. So I think it's gonna be net positive as opposed to net negative.
Jordan Metzner:Yeah, totally agree. Obviously, there's a lot to come with AI, it's just the early days, And, yeah, it seems like definitely in healthcare, it's gonna be a net positive for for patients, for doctors, for the system overall, and that's that's super exciting. Alright, Sam. Great episode. Great to meet you, doctor.
Jordan Metzner:Great. Thanks for joining us today. Thanks, everyone. See you all next week. Every week, we got a new episode on Built This Week, and thanks, doctor, for joining us, and see you soon.
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