Harsh Thakkar (00:03.455)
All right, we're live. And today we're going to be talking about the world of clinical trials. I tried to research before this episode, approximately how many stakeholders are involved in a clinical trial. I was hoping to get a quick number by a Google search, maybe 200, 300, 1000, but I couldn't find any tangible number of people. our my guest today is Rob Freistadt. He is the president and co-founder of

Rob Freishtat (00:15.866)
Yeah.

Harsh Thakkar (00:33.055)
uncommon cures. He's also a professor at George Washington University School of Medicine and Health Sciences. And he is one of the most sought after experts in the field of clinical trials. And we're going to be talking all about this topic, how to get all the stakeholders aligned and how to run a successful clinical trial end to end. So I promise you that's what everything we're going to cover is going to be for that topic. So stick around and let's dive in and chat with Rob. Welcome to the show.

Rob Freishtat (01:03.241)
Thank you, Harsh. It's a pleasure to be with you. It's funny that you Googled that and I'm curious, I'm going to have to do that myself. The number of stakeholders in a clinical trial, gosh, I mean, I think of it like somebody's making some soup and everybody gets to come put whatever their favorite ingredient in to the soup that they want to. And you end up with so many things in there.

Harsh Thakkar (01:26.135)
Yeah.

Rob Freishtat (01:32.529)
Sometimes maybe it tastes good, but a lot of times, who knows what ends up in the final product. And so I'm not surprised Google didn't know how to give a number to that.

Harsh Thakkar (01:39.713)
Right.

Harsh Thakkar (01:45.695)
Yeah, and I think of it like, you know, if you even look at sports, right, if you look at a basketball team or a football team, sure, you have, you know, 10, 12 players or 53 man roster on a football team. But when you actually count the number of people that are impacting the team, you know, the training staff, the ground staff, the stadium staff, like you add all of that, the number just keeps going, right? So I feel like clinical trial is sort of

Rob Freishtat (02:12.543)
moving.

Harsh Thakkar (02:13.899)
Yeah, clinical trial is that kind of, know, yeah, we have patients, we have sponsors, we have investigators, we have regulatory agencies, we know that, but there's so many people behind the curtains that nobody ever hears of, they don't know who they are, and that's why we wanna talk to you.

Rob Freishtat (02:33.317)
Super. Yeah, there's definitely a lot of people behind the curtains and, you know, many of them are playing really important roles in getting a trial off the ground. mean, the amount of attention to detail that's required is astounding. And so, you know, the trick, of course, is to not let all of the various stakeholders drive the process because then you've got

Harsh Thakkar (02:38.338)
Yeah.

Rob Freishtat (03:03.572)
Everybody's in the same boat rowing in different directions. You don't end up going where you think you want to go.

Harsh Thakkar (03:10.175)
Right, so to pick on that analogy of going in different directions, when did you, because I know you have a lot of content on this topic and you talk at other events about misalignment in clinical trials and getting everyone to that one North Star. When did you realize that you wanted to sort of devote your career into this field of clinical trials?

Rob Freishtat (03:39.027)
or, you know, it's kind of interesting. I grew up as an emergency medicine physician. So I'm very familiar with, you know, focusing in on the one critical problem and doing what you need to do to solve that problem or get that single answer and try to shut out all the other noise. And I did a lot of emergency work around rare disease and a lot of emergency

patients in clinical trials. And what I noticed happening in the field is that clinical trials, first of all, are super expensive. You know, often more than a billion dollars to bring a drug to market. Sometimes even more than that. And the reality is that this whole ecosystem has grown up around clinical trials. All the various components

of financing and patients and CROs and pharma and all the different departments within each. And it creates a very expensive structure. And that structure is actually quite good at getting things like hypertension medications or your cholesterol medication to the market or ozempic, whatever it is.

know, that are used commonly, that system is, you know, they're not exactly efficient, but the cost is spread over so many patients that at the end of the day, it's really decimal dust on a per patient level. However, when you start to get drug development for less common diseases, rare diseases, all of a sudden that...

cost, that carrying cost of a drug when it comes to market, that financial value that needs to be made up in the commercial phase is spread out over a much smaller group of patients. And now that drug cost, that development cost per patient is substantial. And that's why you have drugs that are a million plus per dose for a patient.

Harsh Thakkar (05:46.925)
Hmm.

Rob Freishtat (06:00.617)
with a rare disease. And in that scenario, that system, that same system that we use for a hypertension drug, those inefficiencies that contribute to that overall price tag, those all of a sudden matter a lot. And so when we talk about inefficiencies, going back to that boat analogy, anybody not rowing in the right direction, as far as I'm concerned, is not helping the process. Right?

Harsh Thakkar (06:17.804)
Hmm.

Rob Freishtat (06:30.419)
that their incentives may be different than what the rest of us are looking at, which is, is this drug safe? Is it effective? Can we get it to patients who need it? And so as an emergency physician, know, that truly I like to simplify things. And that's really how I boiled down my thinking around why the system wasn't working. And if you look at a rare disease drug,

You know, so you're developing a drug for say, you know, 250 patients in the US or less. And the cost on average is more than half of what it would cost to develop a hypertension drug for several million patients. So again, that process, the inefficiencies, all the rowing in various different directions drives up that carrying cost and makes it a burden.

Harsh Thakkar (07:15.063)
Mm.

Rob Freishtat (07:26.673)
on the back end for patients and payers. And if the payers stop paying for the drugs, the investors are going to stop investing. And that beautiful pipeline we've got of gene therapies, cell therapies, really great science coming out of academia, that pipeline's going to dry up because nobody's going to invest in that front end for fear that it never gets paid for on the back end. So to me and my co-founders,

Harsh Thakkar (07:54.21)
Hmm.

Rob Freishtat (07:56.649)
We felt like something had to change, something had to give before we squander this scientific opportunity that we have as a field.

Harsh Thakkar (08:07.969)
Yeah, and for a of the audience that's listening or watching this, if they're in life sciences, they're familiar with the different phases of drug development or different phases of running a clinical trial. And maybe there's others in the audience who are not from life sciences, they're just here to learn. But if you were to pick one area, so like let's say if you're starting a new clinical trial, you're setting up

all the parameters, you're setting up the protocol, you're looking at sites, you're building out your investigators, researchers, all these teams, figuring out how you're gonna qualify these sites to run these studies. And I'm sure there's tons of other stuffs, I'm not by any means expert in this space, but when you look at the start and the end of a clinical trial, can you pick one or two areas where you feel like the industry is quote unquote,

squandering a lot of either time or money into this.

Rob Freishtat (09:10.719)
Yeah, so I mean, I don't know that squandering is necessarily the right word, but it's pretty close. And there is one area that stands out above all else. If you look at the, so there's been a couple of good papers in recent years looking at the approvals and failures at the FDA, know, drugs that made it through versus drugs that didn't. And if you break it down by,

Harsh Thakkar (09:15.287)
Okay.

Rob Freishtat (09:39.167)
class of disease, know, there's a bunch of cancer, bunch of cardiovascular, et cetera. And the success rates for drugs coming into the FDA range anywhere from 8 to 25%. So already you've got a pretty poor success rate. And actually rare diseases are the 25%. That's the best at the FDA, although in the last couple of years, all the gene therapy is getting pulled, has driven that number down some.

Harsh Thakkar (09:53.475)
Mm-hmm.

Rob Freishtat (10:09.213)
But if you then look at the failures, what's the reason that these drugs don't make it? Is it bad science? Well, unfortunately, no, it's not bad science. That's a perfectly appropriate reason to fail. What it is is they can't recruit enough patients into the trial, or they can't keep the patients in the trial. 55 % to 57%, depending on which paper you want to believe that's pretty close.

Harsh Thakkar (10:30.467)
Hmm.

Rob Freishtat (10:36.937)
drop at 55 to 57 % fail at the FDA at some phase along the way because they can't get the patients to do the trial. Now, so to me, to answer your question, the one spot where we can make the biggest impact is by focusing more on the patients, making the trials easier for the patients to participate in. Often these folks have a lot of burden in their lives anyway.

And so a trial can be very tricky to make it fit into someone's daily life. So you have to go all the way back to the design phase and frankly even how the drug is administered to effectively begin to address the patient's concerns about trials. So will patients do everything you're asking them to do in a trial? Often,

You know, as a scientist in my former career, I remember the days where we were designing things and we wanted to measure, get as much data as you possibly could, measure everything. But that takes a lot of time and effort on parts of patients and on parts of investigators. And it may be that patients just opt not to participate because there's too much work. The other big part of the patient recruitment piece is for some reason,

In drug development, are still, a lot of us anyway, are still stuck in the mindset from the mid past century that double blind placebo controlled trials are the way to go. When you do want to trial with 10,000 patients, sure, you can do that. Again, you're spreading the cost over, know, millions of patients on the back end. But when you start looking at

patient groups where there's relatively few patients, so rare diseases, things like PKU, cystic fibrosis, one of more common rare diseases, sickle cell, whatever it is, you're already starting with a limited pool of patients who could participate. And so you need to use creative, newer statistical methods to be able to reduce the number of patients you need. So instead of doing a 200 patient trial,

Harsh Thakkar (12:50.412)
Yeah.

Rob Freishtat (13:01.107)
you can do a 15 patient trial. We've had several clients come in where we're redesigning the trial to be more efficient, means you only need 15 to 30 patients to get the same information that's perfectly acceptable to the FDA, but all of a sudden, it's much more feasible to do the trial. So focusing on the patient really is a critical piece, and that's where you're make the most impact.

Harsh Thakkar (13:20.172)
Right.

Harsh Thakkar (13:25.315)
And I can speak just from knowing people like my wife was in the physician assistant field in clinical trials. Right now she's in the period of transitioning to a different role, but she worked for a company and they did two trials for the time when she was working. One of them was, I can't remember the name of the trial, but out of the two,

the one that stopped was because they couldn't get enough patients, right? So you said 50 % or around that data, and I know she worked at two trials and out of two, one had to stop because they couldn't get patients for that trial.

Rob Freishtat (14:08.339)
Right, and the other part of it is, if you're a patient, whether you're a patient with hypertension or a patient with a rare disease, the idea that placebo is an option is the higher risk of the disease, the less attractive getting placebo is. So perhaps if you're in a vaccine trial or something, maybe placebo is OK. But if

your child has a rare disease and every day they're getting worse and worse, are you going to sign up for a trial where you could get placebo? It's not going to happen. So, you we have to be creative about the ways that we provide the opportunity to participate so that, you know, everyone gets drugged. So we answer our questions, but there are ways to design these studies. at some point in the trial, everybody's getting...

Harsh Thakkar (15:02.955)
Yeah, I mean, this might sound like a philosophical or very loaded question, right? But it is obvious that as an industry, everybody that's involved in the trial is shooting for safe and effective medication for that end user or patient. Then what are the difference in priorities for researchers, regulators, people involved in the trial?

And how do they start from like a very small level to snowballing into derailing the trial? Can you walk us through an example?

Rob Freishtat (15:42.577)
Of so it is a very philosophical question, so I'm going to answer it very philosophically. So, you know, ultimately, this is where misaligned incentives comes into play. So these are humans designing, conducting, participating in these trials, and they're going to first and foremost act like humans. And, you know, so a lot of the mid-level and lower down folks at

Harsh Thakkar (15:45.25)
Yeah.

haha

Harsh Thakkar (15:56.035)
Mm.

Rob Freishtat (16:12.275)
various trial infrastructures, they know that if they do exactly what they've always done at their company or whatever, then their job is safe because if it doesn't work, it's not their fault. So the risk aversion in trials, we want to avoid risk as much as possible, but a trial is a trial and it's inherently risky. And so...

When you've got folks who are incentivized in other ways, a good example not to throw the financial folks under the bus because I love the financial folks, but you know, I deal with pharma companies all the time where when they're in their contract negotiations and figuring out the pricing, the financial folks are paid bonuses based on how much they negotiate down the CRO. you know, while cost savings are important,

Harsh Thakkar (17:04.353)
Hmm.

Rob Freishtat (17:09.311)
that we want to be efficient, they may be skimped because they're not scientists. They may be skimping on things that actually really matter. And so in addition, it adds complexity and time to the process. And let's face it, time is perhaps the most important factor in a lot of these trials for just about everybody. The patients, if they have a degenerative or progressive disease, time is really important.

Harsh Thakkar (17:19.158)
Right.

Rob Freishtat (17:38.073)
The sooner there's a drug available, the better it is for them, effective safe drug. For the pharma company, the sponsor, from the time they file that first patent, the clock's ticking. And their ability to recoup their R &D expenses becomes more more limited. Even in rare disease cases where that patent window is extended, typically the trials for root disease take just as long as eats up that additional window.

you know, and, you know, regulators, they, you know, they, they want to see good safe drugs come through. and they want to see it happen quickly, but the, you know, so, so getting to the finish line with good data so that the regulators can make good decisions, on approval or not, it's all about time. It's all about doing things efficiently and getting

getting to the finish line. And in many cases, the, you know, back to the philosophical answer, in many cases, the different components aren't efficiently moving the ball down the field.

Harsh Thakkar (18:40.727)
Right.

Harsh Thakkar (18:53.347)
Yeah. I want to switch gears and talk about Uncommon Cures. When I was reading about the company, was like, is this a CRO? Is this a consulting company? Is this a trial program? So can you just expand a little bit about what your team does and what's the mission of Uncommon Cures?

Rob Freishtat (19:19.581)
Yeah, so the answer to your questions are all yes. So really what we are, mean, the simplest way to do this is to explain where we started. So there were four of us who knew that especially in rare disease, clinical trials were a major problem. And like I mentioned before, that investment was already starting to dry up on the front end. People were getting much more cautious.

Harsh Thakkar (19:31.715)
Hmm.

Rob Freishtat (19:49.159)
even though the science was more promising than it's ever been in our history. And so what we decided is the system had to change. And so we assembled what the process is, every step in drug development from preclinical through clinical trials, through post-approval marketing, everything along the way. We broke it all into its component pieces and any component that didn't add value

or wasn't required by regulators, we deemed to be superfluous and throw it away. And then what was left, we reassembled into uncommon cures. And essentially we are a very streamlined clinical research program. Our ideal is to work with companies, we always joke, two guys and a drug.

Harsh Thakkar (20:29.367)
see you.

Harsh Thakkar (20:35.075)
Okay.

Rob Freishtat (20:42.047)
And that's what we see a lot. These are early stage companies. Before they've made the mistakes, we like to be thought partners and to help guide them through the process so that they're efficient with their investors' money and they're more likely to find out if their drug works. That's really our goal is to answer two questions. Is their drug safe and does it work? And so everything we do drives toward that and we don't like to waste time. And I always say we don't.

how to crawl or walk or how to run. So once we start, people gotta keep up with us. We interact with the regulators early. We are very big on having discussions with the FDA. It's not like a lot of folks think the FDA is where it's like this Kabuki theater where you bring a whole pack and a paper and throw it through a window there and then run away as fast as you can.

Harsh Thakkar (21:18.944)
Right.

Rob Freishtat (21:38.655)
We like to engage with them early, get their feedback, encourage them to help us think through alternatives to what we may be thinking, and really get buy-in to build a clinical development program for these drugs that make sense. Now, we like working with the early stage companies because they haven't gone down to dead ends yet, but we definitely work with companies who are further along who

maybe have made some mistakes or just need to get things done quickly and right. And so they come to us and so we do pick up programs at phase two and phase three, even phase four for some, where we're brought in at those later times. So we are not a CRO, but we do everything a CRO does. We're not a site, but we do everything the site does. We actually are a site.

Harsh Thakkar (22:34.688)
interesting.

Rob Freishtat (22:37.801)
global site, have multiple locations around the world, but essentially we've boiled everything down into one contract for sponsors. use central IRB. We have everything in our control that one would need to conduct a study. We don't work with academic medical centers per se because again, misaligned incentives, the processes there often add a minimum of 18 months to a development time.

And so we prefer to work directly with the key opinion leaders, engage them in the process. We like to say that they get to be part of the trial design, which they love, and they get to be part of the publications on the back end, which they love, and we'll eat the vegetables in the middle. We'll do all the parts that are giant headaches for academic clinicians to do. We'll take care of all that and we'll treat the patients really well and, and, and

Harsh Thakkar (23:08.995)
Hmm.

Harsh Thakkar (23:25.571)
Hmm.

Rob Freishtat (23:38.527)
hopefully get the drug to the point where there's enough data that the FDA can make a ruling one way or the other.

Harsh Thakkar (23:45.793)
Yeah, you mentioned about working with different types of clients. So early stage companies where you are involved from day one working closely with the founder, co-founder or the scientists that are behind the science, so to speak. And then also mid-size to big pharma companies where they have something going on, but there are a lot of inefficiencies and they need an expert like you.

So I want to focus on the second side. So imagine something is already going on, but there's misaligned and sent, you know, misalignments and stuff going on. How do you or your team come in? How do you, how do you, you or your team come in and diagnose where to sort of pull the levers?

Rob Freishtat (24:19.967)
Sure.

Rob Freishtat (24:24.541)
Of course.

Rob Freishtat (24:35.101)
Yeah, that's a really good question because we don't do, so we don't have a recipe. We look at every single project separately. What is best for that patient group? And we evaluate things from the start. And frankly, we're developing the reputation of being brutally honest. We will tell you if you're a company and you come in and your drug is terrible, we're going to tell you.

Harsh Thakkar (24:43.885)
Mm-hmm.

Rob Freishtat (25:04.383)
And we have, and we've declined to work with some companies because there's big problems that they're not prepared to address. However, there are, I would say more often, a lot more often, there are companies, mid to larger companies who have been stuck. They've gotten stuck either with a poor trial design, they can't recruit patients. Sometimes it's...

that the patients aren't available because they've got too many exclusion criteria. We see that all the time. You can't be too perfect with a rare disease, for example. Or they've got the wrong indication. For some reason, companies especially, they all want to study the same diseases. There's something like 13,000 and growing rare diseases, lots of choices, but everybody always wants to study the same ones. So sometimes it's a matter of

Harsh Thakkar (25:46.371)
Hmm.

Rob Freishtat (26:01.599)
doing a deep dive on what they've done to date to see if they're, the road they're on goes anywhere. It may not. We've had companies come in because they're stuck and they're working on a disease where four other companies are further along in that same disease. And that, in that case, the disease only had like 150 people in the U S. So how many companies are going to have a drug for that disease? So sometimes it's a matter of steering them to other indications.

Harsh Thakkar (26:10.595)
Mm-hmm.

Rob Freishtat (26:31.153)
And sometimes it's a matter of just redesigning their study. You you can't have all these exclusion criteria. Let's try to get away from using a placebo. Let's try a crossover design. There's various ways we can help companies reboot their process. And several of our clients have been and are in that.

Harsh Thakkar (26:55.871)
Yeah, no, that's a very important point because it sounds like from what you explained is that you would understand all the different stakeholders and all the different steps in that clinical trial, what was already accomplished and what the company or the team is trying to accomplish before you come up and say, this is what you need to fix, right? Because on a surface level,

The steps are the same in every clinical trial, but when you go deep into the trenches, they're all very different. At least that's how I read it by talking to others in this space.

Rob Freishtat (27:34.847)
You're absolutely right. And, it doesn't do any good to just apply a sort of general approach to a trial and expect it to work. Every patient group is different. Their burden level is different. the, their geography is different. You know, we've got diseases that occur in some parts of the world and not others. And maybe you're just looking in the wrong place, but having fresh eyes.

Harsh Thakkar (27:44.397)
Hmm. Yeah.

Rob Freishtat (28:04.573)
I find is very helpful. And having us coming in, we completely respect the people who have worked on the project to date and respect their expertise, but sometimes just having some fresh eyes. Maybe they're an expert in a slightly different area of life sciences and their expertise doesn't totally translate. They just don't know the disease.

Harsh Thakkar (28:27.607)
Mm.

Rob Freishtat (28:33.523)
they don't have the experience in the disease that they're working with. We've seen cases where people from who've been very successful in common disease clinical trials have moved over to less common disease clinical trials and struggled. Because the same principle, it's just a completely different animal. And so when we get pulled in, we like to respect what's been done, but look at everything just.

Harsh Thakkar (28:54.079)
Right.

Rob Freishtat (29:01.661)
very honestly and with open eyes.

Harsh Thakkar (29:05.943)
Yep. Right now, I think one of the big buzzwords in the industry is artificial intelligence, generative AI, machine learning. No matter which area of pharma you go to, everyone's talking about it. What is going on in the clinical trials world? In the kind of the trials that you're involved in, are you seeing like...

every other company adopting AI or are you seeing companies trying to dabble but not going all in? What are you seeing with adoption of AI?

Rob Freishtat (29:43.113)
So it's kind of funny because for the last several years, anything that had AI in the name was getting money thrown out. So there's a lot of AI in clinical development. However, I would say most of it's not actual AI. There are some areas where we're seeing AI actually provide value. There certainly is value on the

molecule design side on designing, you know, some of the gene therapies that are coming out that we're seeing some of the newer technologies that are, the next generation, AI has played a role, in, you know, cancer as a field is typically ahead of others. It's just so much more investment there. So there's certainly is some on that end. we're also seeing it.

come into play around real world data, where I mentioned phase four, that post-approval marketing phase, especially for the cell and gene therapies where the post-approval marketing period is often 10 to 15 years. In the current system of collecting medical records and calling up patients and doing visits and labs and things like that, it's extremely cumbersome.

And so it's ripe for, and there are a of companies doing this using AI, you the key in that area, which has always been a challenge is getting access to the data. But I do think that we're going to see significant advances there. And it's especially important in this day and age because what we're going to see as the regulatory process evolves.

The safety trials will happen as they always have, but the efficacy trials for some of these rare diseases will move into more of a real world setting, where maybe you're using historical controls, or you're doing the trial in the real world and measuring efficacy in the real world. so collection of data in the real world is different than it is in the classic clinical trial. Maybe you're using smartwatches or things.

Harsh Thakkar (31:50.787)
Hmm.

Rob Freishtat (32:07.519)
other digital technology becomes possible. And so, you know, I definitely see AI emerging in that space as well. As far as the, you know, the nuts and bolts, bread and butter, or clinical trials, we're seeing less of it there. I think it's more of a tool in terms of document management and some of the other.

sort of mundane tasks that AI can do better than we can as humans.

Harsh Thakkar (32:39.329)
Right. And it's only right, given that we've talked for 30 plus minutes about spotting misalignments in clinical trials and getting all the different stakeholder priorities onto one track. It's only right that I ask this question just because I'm curious. Do you think AI, if it had access to this real time data capture and data sharing, have you seen AI spot

these misalignments before they happen or do you think it has the potential to do that?

Rob Freishtat (33:14.985)
So, I mean, honestly, I thought you were going a little bit different with that question, but the spotting the misalignments, I think right now we're at the point where the things that most impact the process are fairly obvious to someone who doesn't have, know, isn't in the mix of everything. Someone who's sort of looking from the outside, they can see, that's...

Harsh Thakkar (33:20.221)
Ha ha.

Rob Freishtat (33:42.643)
That's slowing us down. We don't need that. We do need more of this. Ultimately, I could totally see AI replacing a lot of the processes, streamlining other processes, and frankly, facilitating patient interaction in a way that is more amenable to the patient. There are things they can do with their phone instead of having a video appointment.

Harsh Thakkar (33:45.943)
Mm.

Harsh Thakkar (34:02.147)
right.

Rob Freishtat (34:12.243)
Things like that, measuring physical exams by video, measuring muscular function, for example. You could envision where AI gate tracking and things like that could be quite useful. So I do think that it's going to continue to infiltrate all parts of the clinical trial process, where I see it

most proximate to where we are right now is in that patient interaction phase and in the drug design phase. That's really real life. The rest is sort of a little science fiction-y, but we're not that far.

Harsh Thakkar (34:50.37)
Okay.

Harsh Thakkar (34:56.363)
Yeah, yeah. What, I know you said that you thought I was going in a different angle. What were you thinking? Was I gonna ask you that? Because now I wanna know.

Rob Freishtat (35:03.795)
No, I was thinking you were asking, think, yeah, I was thinking you were going to be asking about patient interactions. So rather than having a whole bank of people like, you know, a call center essentially for a clinical trial for tracking patients and interacting with patients, you could easily see where some of the AI technology now interacts with people in a very

Harsh Thakkar (35:14.125)
Mm-mm, okay.

Rob Freishtat (35:34.719)
human way, but rather than sticking to the script, it sort of has the ability to adapt and learn. And that's one of the things we need to do. You we can ask questions about things we know about, but what about the things we don't know we don't?

Harsh Thakkar (35:52.641)
Mm-hmm. Yep.

Rob Freishtat (35:53.971)
Right. And so an AI tool can help us can help spot patterns emerging where before we can.

Harsh Thakkar (36:02.531)
True, yeah. For any of the companies or organizations who are running clinical trials right now, maybe they're working with you or some other professionals or experts like you, can you share what are some of the metrics that they can track so that they can ensure that their trial is running smoothly?

or maybe the metric gives them an insight like, wait, wait, hold on, something is not right. Let's figure this out.

Rob Freishtat (36:39.271)
Yeah. So I think the best way to answer that is to sort of give you some examples of areas where we see, they're unforced errors. know, so, you know, our, our unofficial motto is don't do stupid stuff. and sadly we see stupid stuff happen all the time. you know, one of the biggest things that comes up is a lack of a manufacturing.

Harsh Thakkar (36:50.915)
Hmm.

Harsh Thakkar (36:59.139)
Yep.

Rob Freishtat (37:07.367)
If you don't have drug, there's no study. So companies sometimes will think about manufacturing after everything else and either due to COVID or various factory shutdowns. We're seeing a lot of companies have a hard time finding someone to manufacture their drug. And when they do find somebody, it's going to take a very long time.

Harsh Thakkar (37:08.087)
Hmm.

Rob Freishtat (37:33.307)
And so especially for an early stage company that doesn't have a long runway, an extra 12 to 18 months for manufacturing, especially for biologic, that can kill a company. Doesn't matter how good the science is, if you're wasting runway, wasting an extra 12 to 18 months, not to mention that that's patent time, it will kill the company.

Other things are just the pace at which companies are used to doing things is honestly, it doesn't have to be that way. So if you are a company and you're partnering with a bunch of institutions and you know from experience it's going to be a year and a half, two years to get these folks online, that should be a red flag.

because that's a waste of runway. It's also a delay that's unnecessary. And then finally, the other thing that I see often in unforced error is my business partner likes to call it the rule of additive optimism. So companies will go talk to the key opinion leaders and they'll say, hey, you know,

we're going to do a study in this disease, how many patients do you have and, you know, can participate in this study. they, they think back, you know, in their, or check their records and they're like, I have, you know, 10 patients with this diagnosis. And so those 10 patients get added to the total and then maybe risk discounted say to five. So they're counting on five patients from that truck, from that site. But the reality is, that.

three of the patients moved away, one died, two others are in other trials, somebody's on a medication that isn't compatible, and so all of a sudden you're left with one to two patients. So now your trial needs way more sites, and so I just caution people to avoid that additive optimism.

Harsh Thakkar (39:30.563)
Yeah.

Rob Freishtat (39:56.307)
to under recruit at all of these locations. Just because they know that a patient doesn't mean they have the patient.

Harsh Thakkar (40:07.491)
Yeah, no, those are some really good examples, especially about the last one that you mentioned. I've seen that with some of the clients and companies that I worked with. And it turns pretty fast because at the start of the year, you're extremely optimistic. You have all this data. And then six months later, it's a complete turn of events.

I've seen that firsthand. Yeah. Yeah.

Rob Freishtat (40:37.319)
Absolutely.

Absolutely it is and it's unnecessary. Frankly, if you engage with the patients and the key opinion leaders ahead of time, especially where there's patient advocacy groups, you will often have a much better idea of who is willing to participate and what kind of numbers you're going to get. Just a de-identified example, we're doing a trial right now.

Harsh Thakkar (40:51.522)
Mm-hmm.

Rob Freishtat (41:09.843)
the company and the patient group have worked very closely together. And the moment we announced we had 30 patients within an hour had reached out to us to participate. And not all of them were eligible. But it can be like that if the ground is properly laid.

Harsh Thakkar (41:22.647)
Yeah.

Harsh Thakkar (41:30.165)
Right, All right, I know we're up on our time. I really appreciate this discussion and everything that you've shared with us. Before you drop off, do you wanna share where the audience can reach out to you or where can they learn about your company? Do you wanna share your social media credentials?

Rob Freishtat (41:36.095)
Thank

Rob Freishtat (41:52.393)
Sure, sure. We obviously have a website on www.uncommoncures.com, one word, uncommon cures. And we're also very active on LinkedIn. We post a lot of think pieces, usually try to, you know, every couple weeks have something there about rare disease or clinical trials. We are present at a lot of meetings and reach out to us anywhere. We're happy to talk.

Harsh Thakkar (42:23.459)
All right, and any final word for the listeners about anything related to clinical trials or anything else you want to share?

Rob Freishtat (42:34.823)
Yeah, I just, so my final thought and sort of this goes back to your question about mission. For all of us here, we try to remember that at the end of everything we do is a And in many cases, the patient who needs a drug to survive. And as long as we keep that front and center, there's really no one along the process who wakes up in the morning and says, ha ha, I'm going to keep patients from getting this drug that they need.

Nobody's saying that. What we want to do is just keep those patients at the front of what we do, remembering that every decision we make has some effect on downstream, on the drug, the drug development, the drug timeline. And so we try to always remember that, and I encourage others to as well.

Harsh Thakkar (43:05.729)
Right.

Harsh Thakkar (43:28.407)
Yeah, that's very powerful. Yeah, I don't think that anyone in life sciences is going to deny keeping that perspective in front. So thank you, Rob, appreciate your time. And I will stay in touch and keep learning more about what you're doing at Uncommon Cures.

Rob Freishtat (43:47.647)
Super, thank you, Horace. This has been a lot of fun.

Harsh Thakkar (43:49.837)
Thank you.