The Peter Attia Drive - #409 ‒ Inside modern drug development: the science, economics, and regulatory hurdles behind bringing new medicines to patients | Lloyd Klickstein, M.D., Ph.D.
Episode Date: September 28, 2026View the Show Notes Page for This Episode Become a Member to Receive Exclusive Content Sign Up to Receive Peter's Weekly Newsletter Lloyd B. Klickstein is a physician-scientist who has spent more t...han 20 years at the intersection of drug discovery, healthy aging, and preventive medicine. Drawing on his experience in academic medicine, translational research, and biotechnology, Lloyd walks through the full arc of modern drug development. He explains how scientists identify an unmet medical need and decide which diseases and therapeutic targets are worth pursuing. From there, he takes us through the process of engineering a drug, testing it in animals, and navigating clinical trials and regulatory approval. Using bimagrumab as a case study, Lloyd explains the rationale for targeting myostatin and activin signaling to increase muscle mass and strength and describes how the antibody was engineered and screened. He then walks through what was learned from early clinical trials. Unexpected effects on fat mass and type 2 diabetes helped reshape bimagrumab's development as a potential treatment for obesity, including its use in combination with semaglutide. Along the way, Peter and Lloyd explore the differences among drug modalities, including biologics and small-molecule therapeutics. They discuss the roles of patents and capital allocation in drug development, along with the requirements for IND submission and GMP manufacturing. They also examine why developing a new drug takes so long and costs so much, and why identifying failures early is critical. At the end of the episode, the conversation turns to mTOR inhibition and geroprotection, as well as Lloyd's current work on a novel pharmacologic approach to cancer prevention. This episode provides a rare behind-the-scenes look at how new medicines are actually created and the scientific, regulatory, and economic decisions that determine which ideas ultimately make it to patients. We discuss: Lloyd's path from academic medicine to translational drug development [3:15]; Drug modalities, patents, and the economics of innovation [11:30]; Choosing sarcopenia as a target for drug development, and confronting the problem of measuring falls [23:00]; The rationale for bimagrumab: improving muscle mass and strength by targeting myostatin and activin signaling (and why follistatin failed) [36:45]; Engineering and screening the bimagrumab antibody, and the cost of developing a new drug [43:45]; From candidate antibodies to animal proof of concept (impressive muscle hypertrophy) [54:15]; Toxicology, capital allocation, and the path to an IND [1:02:45]; IND requirements, GMP manufacturing, and gray market peptides [1:14:45]; First in-human study design, patient selection, and protection of healthy volunteers [1:22:00]; Phase 1 dosing, pharmacodynamics, and global trial strategy [1:33:45]; Phase 2 lessons on muscle mass, function, and nutrition [1:43:30]; Bimagrumab's effects on fat mass and type 2 diabetes [1:50:45]; The BELIEVE trial of bimagrumab plus semaglutide [1:59:30]; Selective mTORC1 inhibition and the challenge of testing geroprotection [2:11:45]; A new pharmacologic approach to cancer prevention [2:15:45]; and More. Connect With Peter on Twitter, Instagram, Facebook and YouTube
Transcript
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Hey everyone, welcome to the Drive podcast.
I'm your host, Peter Attia.
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My guest this week is Dr. Lloyd Klixstein, a physician, scientist, rheumatologist, and drug developer
who has spent more than two decades helping discover and develop new medicines.
After beginning his career as a physician scientist at Harvard Medical School and the Brigham
and Women's Hospital, Lloyd joined Novartis, where he helped pioneer translational medicine
and led the company's new indication discovery unit, identifying entirely new disease and
therapeutic opportunities. He later held leadership roles at several biotechnology companies,
including Versantis Bio, where he led the development of BEMA, before,
the company was acquired by Eli Lilly. Today he serves as the CEO of Cost Lap Therapeutics.
I wanted to have Lloyd on because very few people have had a front row seat to every stage of
modern drug development, from identifying the unmet medical need to the discovery of new
therapeutic targets, to navigating clinical trials, regulatory approval, and even commercialization.
While we use BEMA as a case study throughout this conversation, the real goal is to pull back
the curtain on how new medicines are actually created, why the process takes so long and cost so much
and how scientists decide which areas are worth pursuing in the first place. In the episode,
we talk about how new drugs are discovered, developed, and ultimately brought to patients,
the science and economics behind choosing which diseases and therapeutic targets to pursue,
the differences between small molecules, biologics, gene therapy, and other drug platforms,
why drug development takes so long, costs billions of dollars and so often fails.
The story behind this one particular drug from its discovery at Novartis to its development
as a therapy for muscle loss and obesity, what clinical trials, FDA approval, and patent
protection actually involved, and how the next generation of obesity and muscle preserving therapies
may reshape the treatment of metabolic disease.
So without further delay, please enjoy my conversation.
with Dr. Lloyd, ClickStation.
Lloyd, thanks so much for coming out to Austin.
Great to see you again in person.
It's been probably six, seven, maybe eight years since we were last in person.
It might well be that long, yes.
So, look, for folks who don't know you as well as some of us do,
tell us just a little bit about your background.
You're a physician and a scientist, but talk a little bit about how
those two paths came together. Right. So my original plan when I finished college was to go to medical
school following is basically the family business. But between college and medical school, I worked in a
laboratory at Brigham and Women's Hospital in Boston and found two things. One that I love doing
science and two that I was pretty good at it. And I ended up doing an MD PhD degree. And that is
the training not required but helpful for becoming a physician scientist. And from there, I did
medicine training. I was a rheumatology training, and I practiced rheumatology for maybe 10 years,
and also had an NIH-funded research lab doing very basic science on adhesion molecules in the immune
system. And that was also at the Brigham? Did you stay there after you finish your training?
I have a high activation energy.
from moving and doing other things.
Okay.
So I stayed there
my whole academic career.
Yeah, that's right.
Medical school, MD, PhD, the whole thing.
The only job I ever had
until I left and went to industry,
which was a little over 20 years ago.
And I went to Novartis Institutes,
which was founded by Mark Fishman
when he was recruited by the then CEO
of Novartis Dan Vesela
to reimagine how research
in early clinical development
are done in industry.
And they basically brought the whole concept
of translational medicine to industry.
Now, that term, I think, was coined at Oxford,
somewhere in the UK, for sure.
And this was the first industry manifestation of it.
So, Lloyd, there are a lot of specific drugs
and indications, pathways and targets
that I want to talk about today.
But I think before I go there,
there's a black box that exists that is the world you occupy that I really think it's unknown
by the public, but I think it would be very insightful if people understood it. And it is the
process by which a drug is discovered. The first person who I ever read articulating this was
Steve Rosenberg, wrote one of my favorite books about science called The Transforms Cell. This book
is over 30 years old. I probably read it cover to cover 10 times.
during the course of my life.
But he starts with a question, which was,
hey, he's at a party one day,
and someone says, hey, how do you discover new drugs for cancer?
Do you just go into the kitchen sink
and kind of grab things and experiment?
So, again, it's a very intelligent person
can still have an enormous blind spot
to what it is people like you do.
So take that any way you want,
but I think it might be a great foundation.
Let's start from a very broad area of medicine,
not just focus on cancer,
because cancer is a special case
of a more general concept.
So I personally, and this may be different for different people,
but I personally start with the patients and the clinical indications.
And essentially, you're looking for what's not there.
So you're looking for a drug that doesn't exist or a therapy that doesn't exist but is needed.
And then there are two broad categories.
There are incremental improvements, and then there are quantum steps in the concept of drug discovery.
incremental improvements are making a drug that you have to take less frequently, or as we've seen a lot in the press recently, an oral drug instead of an injectable drug, or the same kind of drug, but works better. And there have been great examples of that. Think atorvastatin and resuvastatin in a mevokorzokor world. And those have been enormous commercial successes, and there's a strong bias throughout the drug development infrastructure to do those kinds of.
of things because they're relatively low risk and there's not so much uncertainty.
On the other hand, to see indications that may not even have been described yet and don't have
ICD 10 or 11 codes and have to deal with the whole complexity of making physicians and patients
and payers and everybody else aware of this and then creating a regulatory path for it, it's a
heavier lift, but I think that's where the biggest value comes to society and individuals and
patients in creating new therapies. And that's kind of what I do. And there's a lot of failure
involved in there. And the things that we can talk about are how do you get a new regulatory
pathway established, been part of that once soup to nuts. And then how do you sort of create new
indications. That's also a challenge. Maybe it would be informative to think about how my team and I
started something called the new indication discovery unit at Novartis. So Mark Fishman,
who was the president of Novartis research at the time, had a few of us come into his office and
said, we need to make the most needed medicines and find out what we're not doing that we should be
doing and get it started. And we had a budget for that. So super. As I mentioned, I start with
patients and indications and medical need. So starting there, we made a list of about 7,000
clinical indications that were unmet. All clinical indications. We just made a list of all the
clinical indications. It didn't have everything there. It only had the ones that people had recognized
at the time. But it gave us a framework in which we could start thinking. And then it sounds like a lot,
but surprisingly it isn't. It's maybe 10 or 20 pages of paper at the time. And we grouped them
into things that we were already working on, things that were rare genetic developmental things
that would be difficult to approach. And the remainder fell into maybe seven or eight different.
buckets. And then we started working on those. One of them was healthy aging, and one of them was
E&T, and one of them at the time was renal diseases. And we should talk about that some more,
because that's the regulatory endpoint. Novartis wasn't at the time working on liver diseases.
One of them was those, sort of fibrodic diseases in general. And there were some others. And we
started our program, and it eventually grew to have dozens of projects and became a bit of a
And then we had to sort of whittle it down a little. But some really interesting studies came out of that.
One of them, which I know we're going to get to later, is mammogramab for muscle diseases.
It's a long story there. But again, it came out of a medical need of frail elderly people. And I was
very mindful. As a rheumatologist, I saw some of these people. If you, at the time, I haven't
looked at the data recently, but at the time, if a patient is, you,
had to go to a nursing home, not wanted to go or whatever, but had to go. The three-year mortality
rate approached 90%. So being a frail elderly person who has to go to a nursing home was
worse than cancer. Worse than cancer. And there are a lot of serious diseases in medicine that are
worse than cancer in terms of clinical outcomes, but we don't treat them the same way, and I think
we should. But so we really embraced the concept of being a frail elderly person. And what
we do to number one treat it, but then prevent it down the road?
Yeah. I didn't know that it was that. I didn't know the three-year mortality for frailty
in that specific indication was so high, but that's a staggering. It was terrible.
Again, it might be a little better now, but it's not good. Yeah. Okay. So let's now talk about that
next leap. So let's assume you or the scientists and the team have decided we have an
indication. There's a target we want to go for, an unmet clinical need. And there's not an
incremental opportunity, right? The example you gave is a great one. I have six statins already.
I'm going to come up with the seventh. Let's take that one off the table. How do you begin
the thinking around what we're going to do? And maybe, by the way, for the listener, can you explain
some of the different classes of molecules? I also think we talk very quickly and,
casually about monoclonal antibodies, small molecules, biologics.
But I think that that nomenclature might not be clear to everybody and maybe provide a
little bit of that as well.
Sure.
So let's start with what we call small molecules, which is industry jargon.
It basically means a chemical.
Historically, the companies that became our biggest drug companies started over 100 years ago
as dye companies, because the chemistry is very similar for making a dye as for making a
drug. So these are just chemicals. The other class are biologicals, which is pretty much everything
that's not a chemical. Within that broader group of biologicals, and actually there's a third
group, let's say devices. So for biologicals, that could be an antibody. It could be some other
protein like a peptide or a soluble receptor. And I think we're now creating a separate category
of gene therapies, which themselves can be complex based on how they're delivered or targeted.
And then let's talk about devices because that's a completely different animal.
And it's regulated by its own group called CDRH in the FDA.
And that could include things like a gadget you make in a workshop.
It could be an app.
It could be something simple like a syringe that you use to inject a drug
or an auto-injector, which are very common nowadays,
or some combination of those things.
And include all the way up to implantable?
Yes, absolutely.
And we don't have to go into it,
but are there differences in the IP treatment
of small molecules and biologics?
Are there longer patent lives or anything like that?
So patent law, I think, is the same for anything,
but there are other regulatory conditions
that apply to one kind of,
treatment or another. For example, there are different exclusivity periods for a small molecule
versus a biologic, and they change periodically. And all of this is something that's considered
as you're working on how do you protect the drug you're making. This is a really important point,
and it's very topical now with the concern about expensive new drugs and how do we make them
available for people. And I don't think it's well understood or adequately understood how
patent law works about drugs. Maybe we could take a few minutes and talk about that.
I'm going to preface my remarks by saying I'm not a lawyer. I don't play one on TV. And I wouldn't
if I were asked to. But you've been to the rodeo many, many times. Yes. I was the clown.
So the way this works is if you think about at a very high level,
making a new drug that's used by many people takes longer,
is more expensive and takes as many people as building the biggest skyscraper in the world.
I think that the Burj Khalifa.
Just think about that.
for a minute. That's thousands of people, many years, more than a billion dollars. And unlike
a building which can ultimately pay for itself and pay all the bondholders and provide a return to the
investors over decades, patent law gives a very limited term in which all of the investment and potential
profit can be recovered, and at the end of the drug's patent life, it is freely available for
anybody to make for the rest of eternity. That's the deal you make with getting a patent.
The patent is essentially a monopoly on being able to make, use, and sell the drug in exchange
for telling everybody how to do it. That's basically what a patent is. Now, the term of the patent
from the time you file it is 20 years.
And there are a few little things about extending it for a small further period
based on how much time it took to work on it.
Practically, you get 10 to 15 years of exclusivity from the time it can be launched.
So a couple points I'll add just for you to expand on if you chew if you like.
Some people might also be aware of the idea that not everything has to be patented.
So for example, the classic example is Coca-Cola.
had they patented the formula for Coca-Cola hundreds of years ago, I guess I don't remember when Coke started, but call it 150 years ago or something like that, we wouldn't be drinking the same thing today. So they chose a different route, which is we are never going to make this secret public. And in exchange for that, we will have no protection. That's correct. So you're describing a trade secret. Correct. That's another form of intellectual property. Now, I assume that is not an option in pharma. Well, surprisingly it is.
Interesting. There are some specific drugs where they were protected by trade secrets. So a couple of my favorite examples are armored thyroid, which was a thyroid place. Desiccated thyroid hormone, yeah.
It was the thyroid hormone for people who needed replacement therapy, and it was before we could make it synthetically. And the process by which that was made was kept secret. Now, it didn't stop other people from trying, but they had to copy again.
exactly the composition of all the peptides, as well as the impurities and the final preparation,
in order to be able to use the clinical and filing package that Armour used at the FDA to get
FDA approval.
Turned out that was technically really hard.
Another one I really like is actar gel.
So this was purified from pig pituitaries, and it was ACT-T-H, basically.
That's the AC-T-H-A-R.
Jim. I used to love it. I used it in the emergency room a lot because it was a rheumatology smart missile.
Patients could come in with acute gout and be miserable. You give them one shot of that and it gives them endogenous steroid taper over a period of several days. It was great.
Totally unaware of that. Yeah. It was a funny story behind that one too. It was it was cheap and widely available until the BSE scare, the bovine
spongiform encephalopathy scare happened. And then because it was purified from pig pituitaries,
the company was worried that it was going to be, there's going to be something similar in pigs,
and we know pigs have endogenous viruses. So it was pulled off the market. And then it was bought
by a very small company who eventually re-commercialized it for infantile seizures. And they jacked
the price up 100 or a thousandfold. And so it hasn't been available for rheumatologists to use since
then.
It's stupid, bad pharma trick.
Yeah.
Well, I'd like to actually talk about a few more examples of that because there are
several.
Going back to the patent in classic pharma, are patents primarily issued only for
decomposition of matter or are companies trying to get patents for process manufacturing
and other things?
Or is the playbook that, hey, if there's a really complex.
process required to make this drug. I'm going to file my patent on composition of matter.
I'm going to keep the process as trade secret. So even when this thing runs off patent,
you might know what the finished product looks like. You'll never figure out how to make it.
So both of those things happen depending on the drug. Exactly. So one good example would be,
let's say, Ab v. and Humaira. They patented every single little thing around that drug that they could.
It was a huge winner for them, and they wanted to keep it protected as long as they possibly could.
And they would stagger it.
So they would first patent composition of matter, wait 10 years, patent this step in process, wait five years, and you just keep doing it, doing it, and you sort of effectively extend the patent life of the molecule and process.
Exactly.
And that can be abused, I think, personally.
Okay.
But exactly, they'll patent the drug.
They'll patent the formulation.
They'll patent the salts.
They'll patent the auto injector.
They'll patent the, of course, the indication right at the beginning to the extent that they can, which is sort of method of use.
And they'll patent the dose.
They'll patent the route of administration, everything.
Yeah, combining it with something else.
Okay.
Going back.
And the method of manufacturing.
Yes.
going back to the clinical team, the scientific team that is beginning the exploration of what to do,
are you at the outset completely agnostic to whether you're looking for or entertaining small
molecules or biologics as targets? Do certain disease states lend themselves for you to go looking
in one path versus the other? I think there's two considerations. One is that there are some conditions
that might suggest one router the other.
But there are also sometimes companies
or infrastructure that would make it better
to use one format or the other.
I think big companies are format agnostic
because all the big drug companies
are now doing small molecules and biologics
and many gene therapies and even some now cell therapies,
which are sort of the frontier of complex medical.
therapeutics. For example, if you're treating a childhood disease, then you need to make something
that is oral and taste good. All the parents out there are going to remember, you know, the grape
and the cherry flavored. Tylenol or Edville or something. Grape, Scepter, was a particular favorite
of mine when I was given my kids drugs. Yeah. So that's one example. Others are, there are
inhale drugs for specific lung conditions.
And so some formats will make sense.
And there's a medical rationale for that.
So then how do you begin the screening process?
How do you begin to identify molecules?
And again, I think we should assume that our listeners who are otherwise well-informed
won't know the details of what an IND is, what we use phase one, two, three, four,
and what has to happen prior to the IND?
Like, let's just start from the very beginning.
Right.
So with a preamble, that this would be about a year-long course.
Yes, if we did this as a seminar at Harvard, this would take you a year.
But to cover it at a high level, starting from the idea and the medical indication,
and it might be useful to think about one specific example.
And we can, let's think about muscle weakness and which can be described as sarcopenia or,
and the definition of that is still evolving, frankly.
I've gone to some of these specialty meetings like the Kakexia Consensus Conference.
And it's a topic of discussion every year.
But I think one, we seem to be converging on the concept of decreased muscle mass with impaired muscle function as a good definition of sarcopenia.
And whether the function is grip strength or date speed or stare, climb, or people use different ones.
Okay.
So we'll talk about that as a specific indication. So impaired muscle function with low muscle volume.
Which to your point, by the way, nobody listening to this doesn't care about this. So this is a very topical consideration. It's not esoteric. It's something I've personally been working on for 20 years, as you know. So what should be the drug format? Well, the patient population are likely to be older adults. So it needs to be a drug format that'll be suitable to them. And,
shouldn't underestimate the importance of this, it's what's most likely to work. Because in a drug
development program, especially with a new target and a new indication, there are so many unknowns
and all of the risks multiply across a drug development program. So if you have, if you have, say,
20 risks you're taking in a drug development program, whether it's target and format and bioavailability,
toxicity, the whole thing. Everything. And all of them,
have maybe a 90% chance of success.
You multiply all that out 10 or 20 times, it's zero.
It's a huge failure.
Yes.
Yeah.
So you have to minimize risks at every step other than the ones that you sort of identify
and accept.
This is the big question that we don't know and we have to answer early.
So we want to fail fast.
If you can.
Yes.
Yeah.
Absolutely.
The worst outcome in drug development is failing in phase three.
Oh, yeah.
Actually, that's probably not true.
The worst outcome is succeeding in phase three and failing commercially.
But failing early, super important.
Now, let me just ask a question about this specific indication.
So you've already made a decision, which is we're going after sarcopenia, and you've decided to do that as opposed to say, we're going to go after muscular dystrophy.
So are you doing that because sarcopenia is a much, much, much bigger market, which is the obvious choice.
or are you saying it's easier to get approval there,
and then ultimately we can also demonstrate
that this will work in Bouchain's muscular dystrophy.
How would you think about those two ways to proceed?
So my personal bias is,
I have a limited amount of time on this earth
to develop medicines and help people.
I want to help as many people as I can.
So I mostly do large indications,
and that's my personal choice.
Now, in that situation, regulatory pathway might be harder for sarcopenia if it is not yet identified clearly as a disease.
No question. No question. Whereas Deshaines' muscular dystery, that's an orphan disease. You would probably get a quicker regulatory pathway to approval. Yes. Yes.
And so a different strategy might be we go after Deschains because we can get there faster. And then once we have demonstrated a drug that works in that category, we then chase the approval pathway to help as many people as possible.
Would those just be two different strategies?
Yes.
And frankly, I've done both, depending on the circumstance and the mechanism of the drug and so forth.
And frankly, I'm doing that right now with one of the two companies that I work with.
Okay.
So let's go back to your example, though.
Let's get back to sarcopenia.
The very first thing that I tried to do in sarcopenia was prevent falls.
Now, how do you measure a fall, Peter?
Well, I was going to ask a harder question, which is which are the muscles that are most responsible for a fall and maybe that's part of what you could test. It turns out, I think it's very complicated, right? I've had a guest on this podcast who presented data that suggested something that's seemingly as innocuous as great toe strength is an enormous predictor of falls. Now, there's a very objective way to measure the force that a person can generate with their great toe. And as that force gets below certain thresholds relative to their body weight,
the probability of falls just starts to go straight up.
Balance, obviously.
I would argue that they don't really know that.
Okay.
Because I asked the question, you know, what, first, what causes falls?
There's about 11 different things that cause falls.
Then people can think, think through themselves.
They're the obvious ones like weakness and dizziness, which dizziness itself is very complicated,
but also vision, also attention.
Lots of things can cause false.
Yeah, I mean, I think another big one that we see clinically, Lloyd, is loss of reactivity. So footspeed and reactivity. So you and I, if we went for a walk today around Lake Austin, so there's a 10 mile beautiful loop around Lake Austin, the probability that on that 10 mile loop, you and I wouldn't stumble once, at least once, and miss our footing is zero. But I would venture that neither of us would fall. And so the question is why? Why? Why? We don't.
wouldn't we fall despite being challenged at a great level, you know, stepping on a twig,
missing a branch or a root or something like that. And the reason is we have the reactive speed
of our feet to catch ourselves. And that, to me, is one of the things that's missing. And that
tends to come down to the type 2A muscle fiber, right? Like that's a very explosive. But also
proprioception. Yes, absolutely. Vision, all the things that we're talking about. But maybe maybe the
broader point is this is multifaceted. There is an atrophy that is beginning of various systems in the
body and it's creating this perfect storm where when you watch an elderly person fall,
you realize that that's a situation where they would have saved that fall. It's not the insult
that's the problem, whatever caused the perturbation in the step. It's the inability to catch it.
I think that's exactly right. So let's get back to the issue of measuring,
I mean, if you're trying to, yeah, but this becomes a very hard problem.
So I tried to do that because in a clinical environment, the only falls that are ascertained are those that cause injury, right?
From our perspective as physicians, those are the patients we see.
And patients are reticent about reporting falls because they know they could potentially be taken out of their home environment if they were felt to be unsafe.
And frankly, I would do exactly the same thing if I were in that circumstance.
I want to stay home.
Yeah.
So we developed a study to try to measure falls.
And so we worked with a large company that manufactures triaxial accelerometers.
And we made a research device for this effort.
And I designed a wonderful study.
So the study was we were first going to put the device.
on bad ice skaters in Boston in the winter,
and videotape the rink.
And so the videotape results
are the positive controls for actual falls.
And then we would look at the device telemetry
and look at the sensitivity and specificity
of the device for aspirating.
It's worn on the ankle, the wrist, where we do it?
This was going to be a pendant.
Okay.
And then the second part of the study is
if the first part worked
and the device worked on falls that were real,
we were going to put it on elderly,
nursing home residence. And there, and there, the positive control was little old lady found on the
floor because the people were old and frail and unable to get up themselves. So when the nurses or
the staff found them on the floor, that was a, that was a fall. However, they got there. And then we
look at the device telemetry and see. And sorry, was the purpose of that exercise, Lloyd, to see if
the ice skating telemetry could predict a fall on ice? And was it offering the same insight that you
were seeing in the actual field with the elderly people?
Well, it's a little bit that falls are like the Supreme Court in pornography.
You know, you say you know it when you see it.
And so we wanted to see it on the ice skating rink.
And then look at the device telemetry and see, was it reporting falls when they actually
happened?
Was it reporting falls when they didn't?
You know, was it missing things?
Basically to see if the device worked.
So I put that through the institutional processes for funding.
and I was told, cut the first part out.
And so just put it on the older adults.
So I worked with a really good geriatrician named Lou Lipsets.
And we did that study.
Kieran Dole was the clinical operations person.
And it was really a good study execution because working with patients
and research subjects, participants in their 80s up to a little over 100 is challenging.
And these were all into.
individuals in one living environment or across multiple?
Yes, they were in one living environment.
We wanted to make it as, we wanted to minimize the variables.
How many subjects were?
We had 60 subjects.
And you followed them for how many months?
We followed them for six months.
And these, these are people who had fallen at least once in the prior six months.
So we, we knew they're at high risk for more falls.
And remember, this institution has a lot of protocols and procedures in place to try to prevent falls.
And they're still falling now and then.
So Lloyd, 60 subjects followed by six months.
How many falls did you capture?
Well, we ended up 117, I think, was the number of events that actually happened based on someone found on the floor.
However, the device was awful in that I think it had about, it detected 17% of the real falls.
And only 17% of the device actuations where it said somebody fell were false.
So it was just not useful.
And it was the best we could come up with.
And just to be clear, you weren't asking it to predict antecedent movement pattern of fall.
No.
You were just asking, once a person has fallen, do you know?
Yes.
Very simple.
I would have guessed that you would have been higher.
So did I.
But we were wrong.
This study is actually published now.
But then we couldn't use it for measuring falls.
Yeah.
We tried one more thing.
There is a Massachusetts Institute of Technology professor named Dina Katabi, who was using
Wi-Fi-type devices to measure people's movements in their homes.
And it is a little scary.
It could measure wherever you were and whatever you were doing.
And so we thought that would be a great way to assess falls.
But ultimately, I don't remember the issue, but we could end up not being able to use it.
So we had to stop our whole program for making drugs to prevent falls because we couldn't measure them.
Now, let me play devil's advocate for a moment.
Wouldn't you have just said, we want everyone involved in a study to report if they fell
because it's going to help us get better data for the study?
And, I mean, given that you're going to capture all the reported falls and really all you're
trying to do is capture the signal of unreported falls. But if you ask the people, say,
look, we're not taking away your driver's light, you know, whatever it is that you're afraid
of losing. We are just trying to report this as an AE or as an outcome. I mean, it seems to me
you'd have a much higher chance of capturing it than any sort of device at this point.
That would be true. We were just worried about the data quality because people, remember,
these are older adults who were frail. And we were worried.
about the, you know, recall bias and we were worried about whether they would have something
to write it down with and people generally weren't device savvy at the time. I think that might
be better now. Anyway, we didn't. I have to think there's some AI way to do it. Like,
there must be, I mean, were these accelerometers using any AI? This was a long time ago.
Okay, got it. Got it. Okay. Or more. So there was no AI in those days. Well, some people would take issue
with that. Yeah, yeah. But not the way we see it today. Not the way we see it.
Yeah. Anyway, it was an interesting example of a lot of ideas are conceptualized and we have to be able to objectively measure things ideally in drug development. And we tried and we couldn't. And we moved on. So this kind of brings us to sarcopenia and muscle mass and strength, which was the genesis of bimagromab and active and receptor antagonists in general. Now, we knew at the time about myostatin.
So, Seijin Lee is sort of the father of myastatin.
He discovered the biology.
And in rodents, myastatin is kind of amazing.
You can turn a mouse into an Arnold Schwarzenegger mouse by blocking myostatin.
This was in the mid-90s, right?
I think so, yeah.
I mean, this was, when I was in medical school, I remember in 97 seeing the images of the mice.
the chickens, the dogs, the cows.
I mean, we, we couldn't get enough of these myostatin knockout animals.
We thought it was the greatest thing we'd ever seen as students.
There were no people who had that, though.
No.
So, so at the time, the people who led the discovery project, so this is the laboratory research,
where, so Chris Liu and his team and David Glass and his team.
And that's where the original code,
of pymagromab was BYM-338, and that's where the VAT came from. I was part of that team
on the clinical side, and if they made the drug, how would we test it? Do you want to explain how
myostatin inhibition would lead to enormous muscles? Yes. So the broader question is what
governs the size of your muscles. And we know it's nutrition and we know it's use. And then there are
biochemical things that regulate it. And myostatin is an inhibitor of muscle growth. So if you
inhibit the inhibitor or block myostatin, muscles get larger up to another point where there's
something that regulates them and we don't know what that is. And that's most of the inhibitory effect
biochemically in animal species. In humans, it turns out that it's more complex. It's myostatin
plus activants, mostly active in A. And this is the advantage of inhibiting myostatin and active in A together
or blocking the receptor, which is what the magromab does. What is the evolutionary, I mean,
I'm asking you as though you were there during the design phase, but what is your best guess for
what the evolutionary reason was to limit muscle growth.
Was it simply a nutrient management system, which was like, hey, we grew up in a nutrient
sparse environment.
We can't just have muscles demanding all of this protein.
I would have to guess that based on everything else about people, there were times during
our evolution when resources were very scarce and we had to conserve.
Yeah.
But I don't know.
Your guess is as good as well.
But it is interesting because the other way that nature could have solved that problem was
just to make it completely supply limited and just say, yeah.
But anyway, okay, so we don't really have a great teleologic reason.
That's kind of the way it works without a post tissue.
Yeah, yeah, exactly.
That's right.
So we don't have a great explanation for why, but regardless in humans, myostatin plays a smaller
role than it does in these less, presumably slightly less complex mammals.
And what is the actual mechanism by which myostatin is?
inhibiting? Is it doing something in actin myosin filaments? What is it doing to prevent hypertrophy?
Complicated. But to summarize it briefly, the receptors are part of this larger TGF beta
super family of receptors, and there's dozens of them. There's type one, type two, type threes,
and they all signal via mostly a common pathway called smads, which was named by those
whimsical Drosophila geneticists.
It stands for similar to mothers against decapentoplegic, which people don't need to know.
But, and those are transcription factors, and they govern a whole lot of gene programs.
Some of the more important ones are muscle, so muscle size is regulated by nutritional availability
and then muscle protein synthesis versus muscle protein turnover.
And the proteins that turn over muscle are MRF-1 and MAF-Box are atrogen.
And David Glass was one of the discoverers of this pathway, who I mentioned earlier.
And myostatin signaling via the active in receptors suppresses the proteins that are involved in targeting muscle proteins for degradation.
So before we leave myostatin to talk about bema, do you want to say anything about falastatin?
And I don't even know if you're aware, but falustatin became a very popular recreational sort of gray market agent that was sold for research purposes only in quotes.
And the marketing material suggested, look, if you take fallostatin, fallostatin inhibits myostatin, you're going to get really big muscles.
and so people were pumping themselves full of pholostatin.
Actually, that's not really true.
I think the pholostatin was so expensive.
They weren't doing that.
They were doing some attempt at fallostatin gene therapy.
So do you want to just explain what fallostatin is
or why it may not be as holy grail as it was made out to be?
So pholostatin, and then there's folostatin-like proteins
are endogenous inhibitors of this pathway we've been talking about.
And it does if you do a gene therapy,
and rodents result in larger muscles. But it's a small protein with a relatively short half-life,
and I don't think dosing it systemically now and then would be successful.
We did the math on this, and you would need to give it several times a day. And given the price of
Falostatin, you'd be spending above, I don't know, you'd be spending a million dollars a month
on Falostatin. But also, it wasn't clear that it would do anything in an adult.
In other words, it seemed that there might have been a critical window during which administration of fallastatin or fall statin gene therapy would have an impact.
But it had to be pretty young.
It had to be during the development of the muscle more so than a mature phase of the muscle.
I think it would work in adults if you could solve the half-life.
And I know there are companies working on this with FC fusion proteins and other half-life extended versions.
That's a good point.
Can you tell people why an FC fusion pro?
I mean, I think we have to talk about some of this technical stuff, unfortunately.
I almost caught myself as I was asking the question, but explain what an FC fusion protein is and why that might be able to, like, keep it in place longer.
Sure. You can, you can edit this out later if it gets too technical.
I'll try to make it, it's trying to speak in plain English.
Well, yeah, just think about it through the lens of like how you manipulate drugs.
Like, I think of this as part of the story.
Right.
So if I remember correctly, the technology that we use now for FC fusion proteins was originally
developed by Brian Seed at the Mass General.
And the very first drug that used it was Enveral, which is etanercept, which is itself a
really interesting story because this is a TNF inhibitor that's now approved in rheumatoid arthritis
and psoriasis and some other things.
But it was first tested in sepsis.
I didn't know that.
And it made people worse.
Well, because physicians and scientists at the time knew that sepsis,
was an exuberant inflammatory reaction to an infectious stimulus,
and by tamping down the inflammatory component,
you might be able to have better outcomes,
and it turned out it made people worse.
But ultimately, it was then tested in rheumatoid arthritis,
and it was amazing.
And you know the story after that.
But a company called Immunex at the time
licensed the technology from Mass General to make a tannercept.
And essentially what it does, it does two things.
So the soluble receptor, which was the low-affinity regulatory TNF receptor, I think, at the time.
Got to double-check that.
I haven't thought about a 10-Rcept in like 20 years.
I had a relatively short half-life just as a protein injected all by itself.
And doing the recombinant DNA technology to attach it to this part of an antibody called the FC region did two things.
One is it extended the half-life of the protein in the circulation by allowing it to recirculate the way some blood proteins are recirculated normally.
So you're sort of hijacking an endogenous mechanism to preserve proteins in the bloodstream and doing it the same way.
And the second thing it did is it put a hook on the protein to allow you to purify it easily because the protein G and protein A columns were well estuble.
at the time and easy to use to purify proteins.
So that's what it did for the drug developers.
And since then, the technology, this is a great example of going back to our patent discussion.
Originally, that was patented technology and only Immunex could use it or some other licensee
of the Mass General, but the patents expired.
And now it's, the technology is freely available to the rest of the world for the rest of
eternity and many, many, many companies use this technology to make drugs and we're all better off
for it. Okay. So how did you guys discover BEMA? How did you create it? So again, the earliest
biology was done by Chris Loo's team in the Pathways group at Navartheist Institutes. Jeff Porter was the
leader of that group. And the idea was we wanted to inhibit the receptors, not go after all the
possible ligands, because we knew that myostatin wasn't the whole story in humans. We didn't know
which activans it was. Thought it was probably active in A, but it could have been others too. And
that story and that thinking has panned out subsequently, as we can get into later. And
at the time, therapeutic antibodies were the best technology to do this.
Remember, the affinity of the ligands, myostatin and activans for the receptors,
was nanomolar, low nanomolar, baby high picomolar.
So we needed an inhibitor that could bind down in the low picomolar range
in order to effectively prevent ligands from binding.
Can't really do that easily with small molecules.
Okay, this is a great example of the importance of understanding that distinction.
Yes.
I'm going to explain what you just said, and then I want to have you state that last point again.
So people, when they're talking about pharmacokinetics, they're talking about affinity.
You have to talk about a concentration.
So what concentration of this hormone or this ligand is necessary to get into this?
And when you start talking about, you know, we can talk about millimoles, micromoles, nanomoles,
as we get smaller and smaller and smaller, as those numbers get smaller and smaller and smaller,
it means you don't need very much of the thing to get in the receptor.
And therefore, if you're trying to develop something to block that, it becomes a harder problem.
Because you better figure out a way to usurp this guy getting in and this guy gets in very easily.
Yes, exactly.
Okay.
And you're saying to get a small molecule to have that degree of sensitivity is very challenging.
Yes.
And therefore something that's biologic makes more sense.
Yes.
And is that due to just the physics of the conformational fit?
Yeah, I think you could describe it that way.
It's essentially this, it's more complicated than this, but think about it as the surface of interaction of the two molecules binding together.
Essentially, we need, if the ligand, myostatin, inactivin for the receptor is sticky, you need an inhibitor that's even stickier.
Yeah.
And that would be very challenging to do with small molecules.
So in this case, we went with the biologic route, sort of ran a therapeutic antibody project
in collaboration with morphosis, with whom we had a collaboration at the time, and had a bunch
of candidate antibodies and then ran through the usual developability, maturation, improvement of
what we get in the screen until we have what we think could be a therapeutic drug.
How many molecules enter the top of that funnel?
Oh, there might be thousands of antibodies that get tested initially.
This is done with something called phage display technology.
So I would say for the past 15 to 20 years, we don't make antibodies in mice anymore.
It's all done in by recombinant DNA using these viruses.
And I think back, I've been in the business long enough.
You know, I've made antibodies by immunizing mice and fusing cells and growing them up.
and putting them back into mice's acides tumors to get enough to anybody to do experiments with.
I mean, it was terrible. It's much better now.
So you're literally running a screen with all of these antibodies and you're screening for two things,
but, well, basically one thing. What is going to give me the lowest concentration that binds to this ligand?
It binds to, sorry, to this receptor. Yes. So knowing that you have to be below a certain concentration.
We knew we needed really high-affinity antibodies.
There were some things we didn't know.
So in the laboratory, most of the time you can measure a cell surface receptor on the surface of the cell pretty easily using things like flow cytometry.
The active in type 2 receptors are actually expressed at such low levels.
You can't see them by flow cytometry unless you somehow very artificially manipulate the cell.
So we had to create a screening assay.
that was essentially a reporter assay.
So we couldn't measure the receptor
on the surface of the cell.
We could have developed an assay to do that,
but it would have been very laborious,
radioactivity, not necessary.
So we put in a reporter gene,
which is, and basically made the cells glow
with firefly luciferase
if the ligand-bound myostatin or activate.
And then we were looking for decrease in the glowing
with therapeutic intervention.
And we also didn't know whether we needed to do inhibit active in receptor type 2A or B or both.
Most of the work in vitro's suggested for muscle hypertrophy, most of it was driven by 2B, but we weren't sure.
And we ended up getting a 2B preferential drug, but it also hits 2A.
And this has nothing to do with muscle fiber type.
No, this works on all fiber types.
Oh, okay.
And then we looked for antibodies that worked in that cellular assay where we wanted to prevent cells from glowing when we added myostatin and activin.
It had to work on both of them.
So there was it shouldn't matter which ligand you put in.
The antibodies should block their activity.
And the affinity of the antibodies had to be really good.
So it had to be much stickier than the ligands for the receptor.
And so we had that. And then the real important experiment is could we block the activity in an animal?
But just that first step, Lloyd, until you could identify candidates, how many months was that?
Years. That was years. So again, just going back to the analogy of building a skyscraper, that's the planning phase of the skyscraper. That's the excavation of the hole. That's probably the laying the foundation. You haven't actually put any of the big pillars up yet.
It's the permitting. It's securing the funding. It's the, it's sort of the site planning. It's all of that from your building perspective.
And, by the way, I assume that the standard estimate 20 years ago was every approved drug is approximately 10 years and a billion dollars. That's got to be pretty low today. What's the, do you have a sense of what the more accurate dollar figure is? It's got to be more than a billion today per approved drug.
Oh, yeah. There's a, there's a Tufts organization for the study of drug development,
and they think it's, I know, two, three, four billion, something like that.
Yeah. The part you're doing now is time consuming. Luckily, it's not that expensive,
correct? Right. You're spending millions of dollars, but not necessarily, you know,
tens of millions at this point. Okay. Yes. So you finally identify a candidate or several
candidates that you now want to take to the next step, which is, hey, in vivo, does this thing work?
Yeah, so we would typically have two to ten at this stage.
And it's taken years because we have to work through the biology
and make sure that we understand what's going to happen,
not because we want to save the cells in the petri dish,
but because we don't want to start something
unless we have confidence that will succeed if we pass each step.
So we have to work through the biology.
We have to make all the tools we need,
which are these glowing cells.
in response to myostatin, for example, and there's plenty of other tools that we need to.
We need to make the reagents.
We need to make the myostatin in the active in A, and all the tools we need to do these experiments.
So, and then run the experiments, and we have to make the antibodies, and that takes quite a bit of time,
as well as developability on the antibodies, which means we need to, at the very earliest stage,
have high confidence that we're going to make an antibody that we could,
give to people and it'll be stable and it'll have predictable physical properties and it'll have
a shelf life and all of these things are what we build into the antibodies that is at this very early
stage how confident are you at that stage lloyd that the antibody won't elicit an immune response
in a human it's still one of the biggest unknowns and the best way to do it is to use fully human
Humanized.
Not humanized.
Human.
Human.
Full.
Straight up human.
Yeah.
Can you explain to folks the distinction there?
Yeah.
Well, there's humanized is used to describe taking a mouse or other species
antibody and replacing as much of it as you can with human sequences based on what we
know about human antibody codon usage and amino acid preference and so forth.
Whereas fully human means you're starting with human.
genetic material antibodies.
But ultimately, it still has something in it that's foreign.
As little as possible.
Part of the sequence. I mean...
As little as...
Well, there's going to be something new because antibodies have this intrinsic ability
to recombine and create new sequences.
Yeah.
Now, in vivo, in people, so if you make some brand new antibody and it's not suitable
for some reason, it gets selected out.
Whereas when we do this in vitro in a test tube that doesn't happen, we do the best
we can and try to end up with sort of common codon usages, common antibody sequences,
even pairwise and so forth. But you don't really know until you put it into people.
There are some Ensilico screens you can do by looking at what peptides are likely to be
generated in a lysosome and are they going to have high affinity binding to an MHC molecule and
so forth and we do all that stuff. But you still don't know until you do it.
Now, it's an interesting historical perspective because I'm getting old enough to be interested in history now.
The very first antibodies tested in humans were mouse antibodies.
And there's still one that's used to this day as a therapeutic.
So it's OKT3.
So this is an antibody used to prevent transplant rejection.
It's an anti-t cell antibody, human T-cell antibody, and we still use it to this day.
And what is it targeting?
Is it literally targeting CD3?
Yep. Wow. So it's broad. Yes. It's going after every T-cell.
Yes. Right. And there's there's there's there's there's there's there's
thymocytes globulin too that's still used clinically. That's a blast from the past.
It's still used. Yeah. And these were the first antibodies used in people and of course
the other antibody the other foreign antibodies that are still used are antivens. Most of them are
horse serum. As you can imagine you only want to get bitten by a snake once and need that.
Because when you need it the second time, you have kind of a ferocious serum sickness response.
Great point.
So you identify BEMA plus a few others and you start now running these into the mice.
Yes.
Is there another chance that because you've gone to all the trouble to make sure you have a human antibody,
it won't work in the mice when it otherwise would have worked in humans?
We test that beforehand.
Okay.
Got it.
So this is, again, there's an enormous amount of detail in drug development.
And one of the things is that your drug has to cross-react, I mean, work also in at least one of the two species we're going to use later for toxicology.
And it has to work in a species we're going to use for pharmacology.
If it doesn't, then you need to make surrogate drugs to do that.
But in our case, we made one that worked in rodents.
Now, it turns out that bimagromab is pretty immunogenic in mice, but not in rats.
Although, how common is that?
It's kind of idiosyncratic.
So the construct we ended up using in mouse experiments was something called CDD-866,
which was you talked about humanizing antibodies.
We muranized the magromab so that we could use it in mice.
So you could go back and use it.
Yeah.
That makes sense.
And to make a long story short, we were able to give these antibodies to mice and
see if it caused muscle hypertrophy or not.
And how much did it do so relative to the pure myostatin knockouts that were enormous?
Probably more so than the myostatin knockouts.
Wow.
It was really impressive.
Again, we're going to link in the show notes to what these images.
look like, but it is it is truly a caricature.
It's impressive in the mice.
Look at also the whip at dogs, the Belgian blue cattle that are double muscles.
Yeah.
It's, it's impressive.
Did you do anything else, Lloyd, at that time?
So when you demonstrate that Bima is making bodybuilding mice, was there any assessment
of muscle function?
Yes.
Okay.
And what did you find?
The mice were stronger and can run fast.
Okay.
But remember, they had perhaps a 30% increase in their muscle mass, I mean, which is, which
is a huge.
And people can look at the pictures online and see it's quite obvious.
So it doesn't work this well in humans, because just skipping all the way ahead and we'll
come back.
Humans get about 4 to 8% increase in muscle mass.
Most of the people we've tested have been older people, which is one caveat.
whereas...
Did you do it in old mice?
Not in old mice.
I think David Glass did some experiments in older rats.
And it still worked, but not quite, not as well as in younger ones.
And remember, when people do these muscle experiments in rodents,
they almost always do males because it works better in males and females.
Cool thyself.
It would be interesting to know as you ran it across a continuum of escalating,
age what the what what what what accounts for the reduction in efficacy right is it is it
is it a muscle protein synthesis problem i mean what is you know i don't think i don't think
that's been studied formally by scientists it might be known in the in the bodybuilding community
and just just a heads up to the the listeners who might be bodybuilders the first thing that
any company does when they're working on a drug that has the potential for abuse is
we work with WADA, the world anti-doping agency, to make sure that they can screen for these
things. So where in the pathway of BEMA did you begin notifying WADA that we're working on
this thing? As soon as we had a therapy, soon as it worked in the mice. We started that process.
And basically they've they've had an assay for more than 10 years. Have they ever caught it?
Have they ever seen? I have no idea. That's funny.
Okay, so after the, you get the home run in mice, do you want to go into a primate?
Where do you typically go from mice?
So for therapeutic antibodies, often it includes a primate simply because we want to have one of the two toxicology species in whom the antibody has the expected pharmacology.
so we can look at sort of on-pathway and off-pathway toxicity of the therapeutic.
So we typically use non-human primates for this.
When you're at the mouse stage, Lloyd, how are you screening for talks besides the most obvious, right?
Obviously mortality or something catastrophic is obvious.
But for non-apparent or non-mortality-based toxicity, what are you looking for?
And is any toxicity at the mouse level disqualifying to go forward, or are you evaluating it case-by-case and saying,
look, okay, this ended up being pretty bad for the mice despite the efficacy.
We don't think that's going to be an issue or we think we got the dose wrong or do you
basically keep going back and perfecting it in the mice until you get the dose response
right before you move up or do you just sometimes say, no, we're going to go to the primate
or whatever other model we're going to look at and reassess talks as we get closer to our species
of interest. Yeah. So with the caveat that I'm not a toxicologist, the fundamental
principles are you use a weight of evidence approach based on all the data that accumulates.
From a clinical perspective, we've tried to balance risk and benefit with new medicines in
general. So if it turned out that pomegramab had some, and pomegromab has some talks that we'll get
into, but if it were unsuitable for use on a big population that we then think about
higher medical need patients. That's when you would go from maybe sarcopenia to
Duchenes, muscular dystrophy.
For example, yes.
If we could, yep.
And where whatever the adverse effects are would be outmatched by the potential benefits.
Yep.
But secondly, we want to know precisely what the toxicology is.
And the two big things we look for are whether it's monitorable, whether it's reversible.
So if we have irreversible cardiac toxicity with a therapeutic, that's usually the end, for example.
or neurologic.
If it's serious organ toxicity.
But there's enough of a prodrom.
So for example, if it's, well, you look at a drug like lamassil, right?
Something is supposedly benign as lamassil.
I mean, that can destroy your liver.
But there you can stop the drug.
So that's your point.
It's monitorable and reversible.
Yes.
If you stop it and you get a long enough warning.
Yeah.
Because otherwise, if it would just automatically,
destroy a person's liver at a frequency of one in a hundred people using it, you can never
justify it. So you're describing idiosyncratic liver toxicity, which is the most common
reason drugs get pulled off the market still. And I personally have killed drug programs for that.
And it's hard to, can't predict it preclinically. Yeah. Yeah. So let's get back. You get BEMA into
the primates? Yes. And how does it, how does it perform? Well,
In order to do toxicology studies, you have to know how much to give them and how long it's going to last and what it's doing.
So there are preliminary studies in a small number of animals.
And so we did those, but we did them long enough so that we could see the muscle hypertrophy of what were going to happen.
And it did work, not as well as in the rodents.
But it did work.
So it gave us confidence that we could move ahead with the rest of the activities.
Now, manufacturing enough antibodies for use in larger animals is time and expense.
And so all of that was going on in parallel.
And each of these decisions, so you're doing this all inside of Novartis, is there an, I see, is there an investment committee that basically revisits every time there is a new allocation of capital to move from one thing to the other where everybody presents?
And how does that typically work in a large company?
All big drug companies work kind of the same way that there are typically two or three or four,
depending on the company, major checkpoints where all the data are assembled and made into a slide
decks and presented and feedbacks obtained and programs, courses adjusted.
And so that happens.
And I think it's more frequent but faster at small companies.
But things are constantly being reevaluated and reassessed.
Yeah, and what's interesting for folks listening to us is we're talking about this in the context of a large company that doesn't have to go out and raise capital every time it does this.
But the exact same idea that you just described, everything you just said could have been done by a startup.
But now it would have a totally different look and feel in that, hey, we're going to go raise some seed funding to go test this idea.
Okay, guess what?
We were able to find the antibody.
We're going to have to go raise another, you know, $20 million and boom.
And now they'd be at the stage where they'd be probably raising a series B or, no, probably
this would still be an A, I think, as they go into the primate.
Whatever you call it, you.
But give folks a sense of how much you'd have to raise for this next stage, which is basically
your pre-IND.
So if it includes many, so you have to manufacture.
Yes, it's going to include the primate through manufacturing.
You have to run the I&D enabling studies, which is,
oxygology and some other things. And frankly, investors want value creation for their money,
and reasonably so. So I would think for Bumagromab, if this were in a small company,
the value creation step would be showing muscle hypertrophy in the very first clinical study.
So the funding that I would raise would be I&D enabling plus phase one.
Plus phase one plus a runway to raise the next round.
Yeah.
And you would structure your phase one to demonstrate efficacy,
even though technically you only need to do talks.
Yes.
You would have it long enough, big enough.
Not talks, but safety and tolerability.
Yeah, yeah.
So, okay, and then just for using BMA as an example,
how many dollars would that be from where we are now
to give you that runway into 2A?
In today's dollars, probably $20 million.
Okay, yeah.
So series.
They're about, yeah.
Okay.
Maybe a little.
That's lower than I would have guessed, by the way.
Maybe a little more.
Okay.
It depends on where you do the manufacturing.
So for Novartis, this is nothing.
For a startup, this is everything.
You're betting the farm.
Well, not enough.
I don't want to make light of it inside of Novartis,
but the point is Novartis doesn't have to go back to the public market to say,
I need to raise another $25 million to fund this.
They're doing a lot of these in parallel.
Big companies, though, have, their resources are stretched too.
too. It's kind of funny thinking about it looking from the outside, but having been inside a
big company, people are competing for a fixed amount of research dollars, the people within
the company and resources are allocated based on company strategy. And ironically, sometimes
there's more project capital available in a small company than in a big company. Because the small
company's got one or two or three projects. Right. They're taking fewer shots on gold. All the money's
going there. Yeah.
whereas there are hundreds in the big companies.
So, and I've seen it both ways.
I've seen some big company projects get high profile, high importance, well funded.
So, yeah, so we'll say $20 to $30 million maybe at this stage.
And the magromab at that point made it through rodent and non-rodent toxicology studies.
and what we call DMPK, which is distribution metabolism, pharmacokinetics.
It's knowing that when you give a participant or a patient a subject, a medicine,
does it get into their body?
Does it go to where you want it to be?
Does it do what you expect it to do?
You have to know all that stuff before you go into patients for the first time.
And we assess that in animals.
You asked earlier, what do you actually do to measure
the toxic effects of a medicine. And animals receive courses of therapy. And we do blood tests just
like we do in people. Sometimes we would do x-rays if it was warranted. And then they get
autopsied to look at all the organs and look for microscopic changes that you might not perceive
clinically. And we know, we have to know all of that before we give people in experimental
medicine for the first time. So any red,
flags whatsoever as you, or anything that is of concern, not necessarily a red flag, but
anything that's still an unknown as you're going into the phase one? Lots, lots of unknowns going in.
And there are always things of concern. I've never seen a drug development program that couldn't
be stopped for some reason. And you have to balance the unknowns and the uncertainties and the
risks with the potential benefits and make a decision about whether you move forward or not.
It's kind of a joke in the industry that every really successful program has been almost
killed or killed several times before it eventually makes it out into humans and then eventually
commercialization.
What's the approximate attrition from that first candidate drug discovery to the
the IND filing. That's a winnowing down of what to one.
It's hard to put in an aggregate because it depends based on the format of the drug.
And then there's other factors like strategy and funding and everything else.
But for biologics like Bumagromab and a therapeutic antibody, it's pretty low, actually.
Five to one? Six to one.
I would say maybe 30% of them actually you could get into humans.
Okay.
Yeah, more than I would have thought.
Yeah.
It's simply because there are no off-target adverse effects with antibodies in general.
There are some specific counter examples to that.
But in general, an antibody is not like a small molecule that could have liver talks or some other talks that you can't predict for reasons that you don't understand.
That's a great point.
Yeah.
So maybe I'll restate that so folks get it because because the antibody is so specific, by definition, it can't bind to many other things.
And in fact, we screen to make sure it doesn't.
Yeah, yeah.
Whereas the chemical can do lots of things off target.
You know, I had on recently, we had a podcast talking about CETEP inhibition.
And, you know, the very first version of that drug lowered LDL cholesterol.
But raised blood pressure.
and that was a completely off-target complication of the drug.
Exactly.
So that doesn't generally happen with biologists.
Got it.
So that's why you have the higher throughput.
Yeah.
Okay.
Let's skip.
So you file the IND and you're now ready to start a phase one.
So an IND is requesting regulatory permission to administer the drug to people.
And you've already filed your patent at this point?
Yes.
Yeah.
Where in that process did you file?
Patents typically get filed.
Again, there's a...
You want to do it as late as possible, but while still protecting.
Exactly.
So typically around the point where you have a group of candidates from which your final
drug will be selected, that's typically when we would do it.
Okay.
Wow.
Because you want the patent to last as long as possible, but once information about what
you're doing is getting out, you want to have it protected.
Okay.
So from the time you file the I&D with the FDA until, and you have to show them everything that we've talked about, do you also have to, at the IND show them that you can manufacture in GMP?
Yes.
So the manufacturing is a core element of the common application that you do for an I&D.
And this is U.S. specific nomenclature.
IND stands for investigational a new drug.
In Europe, it's called a clinical trial application.
CTA.
There are other countries that have different nomenclature,
and companies can do the first in human study anywhere in the world
that's got a proper regulatory environment
and suitable investigators and clinical sites
and with adequate quality and so forth.
But maybe we'll be U.S.-centric for this discussion.
Sure.
Can you explain to folks what the,
hurdle is to
GMP or good manufacturing
processes and why it's so important.
And again, I'll,
I call this out to listeners because we live
in an era now where these peptide therapeutics
are very prevalent, these sort of
gray market peptides. And
there are people out there that think, hey,
I'm buying red at trutide.
Yeah, no, they're not. Yeah, exactly. Maybe
use the GMP
process as a way to explain why, when you think you're
buying red at trutide peptide,
peptide for research purposes only, you are definitely not buying what Eli Lilly is going to
eventually sell if they get FDA approval. Right. So GMP stands for good manufacturing process.
And it's basically a commitment by the manufacturer to use high quality standards with extensive
documentation to be able to prove what they've made so that everybody can have confidence that this
is a good quality material and they know that what's on the label is what's in the bottle,
basically. And that there's nothing in the bottle that's not on the label. Exactly. It's purity,
it's activity, it's contamination or lack thereof, it's sterility, if you will. It's all of those
things, it's that the material that's being purchased eventually commercially is the same
material as what was tested clinically, and we can have confidence in it.
Basically, the factories are inspected and the factories that make it have, and typically
there are many manufacturers involved when you buy a, with the exception of saying buying a
bottle of terseppatide from Eli Lilly, but typically when you buy a drug from somebody,
the drug substance, the chemical, is manufactured by one company,
and then it is formulated or put into a mixture
that makes it predictably absorbed or administered
is done by another company.
And then it's put into a package by a third company
and then it's distributed by a fourth company.
So there's a lot of people involved.
And this whole manufacturing infrastructure and pipeline
is well controlled and well documented.
And you can buy online peptides
that may be the same as Reddit Trutide.
They might not.
You have no way in knowing.
Yeah.
And in many ways,
that's the premium you're paying
when you're buying the drug from Novo Nordisk
or Eli Lili or Novartis or whatever is
part of the premium is it's very expensive
to manufacture under GMP conditions.
Yes.
So it's a bit of a buyer beware when you decide not to.
I think it's a big mistake to buy these peptides from fly-by-night manufacturers.
Conceptually, it's no different than going in a drug user, going and buying some opioid from a street corner drug dealer.
You have no idea what's in that.
Could it have fentanyl in it?
Could it have car fentanyl in it?
Which is even worse than fentanyl?
Baking soda, you have no idea what's in there.
It's the same thing with these peptides.
You have no idea.
I think it's a mistake.
And plus, even if you were to have confidence that those peptides,
were what they're saying they were, the data to support what they do are almost non-existent.
I've been reading in the popular literature about this one that's, I think it's called BP 197.
BP-157.
157, yeah.
All of the data for that peptide come from one investigator, who's the only person published on it.
And remember, the fundamental tenet of science is if it's real, it's reproducible.
This has not been reproduced.
what the hell is it? It's not encoded in the human genome. So it's not a human peptide.
And it has no known receptor. Yes. So we don't even know how it works. There's so many red flags for this.
No, it's the it's the poster child for what I would argue is the absolute greatest grift of the entire health and wellness industry.
There's a lot of, I'm sorry if I'm insulting you, Peter. There's a lot of grift in the health and wellness industry.
you're not insulting me.
But that's my point.
Despite how much grift there is in the health and wellness industry,
I'm putting BPC 157 on the podium at least.
I would too.
Yeah.
I would too.
Okay.
So we've made bimagromab and it's made it through all of the I&D enabling study activities
and we're ready to give it to people.
Who do we give it to?
And this depends on what we need to measure.
and what the expected safety and tolerability issues are in people.
Again, we talk about toxicology in animal species.
We talk about safety and tolerability in humans.
And again, most antibodies, including bimagromab,
won't have safety and tolerability issues
that are off the pathway that it's working on.
And didn't really see any safety and top,
any toxicology to speak of in the animals.
The only thing that I was a little worried about that we saw was in the rats, they had cardiac hypertrophy.
However, remember the animals had enormous change in their body size because of the muscle hypertrophy.
And if you normalize the heart size to the body size, it was normal.
So does that mean that you didn't know if the cardiac hypertrophy was in response to more?
more resistance that the heart had to work against,
or whether the antibody was working directly on the cardiac myocytes
and increasing hypertrophy there as it was in the skeletal muscle or both.
Exactly.
We didn't know.
But we could make an argument that rats of the size that they became should have bigger hearts.
Should have bigger hearts.
And that was the argument we made to regulators.
And so we didn't think there was any specific cardiac toxicity.
And typically in toxicology studies,
you have something we call a recovery period
where the drug is withdrawn
and some of the animals are followed
to look and see whether any toxic effects
that did occur are reversible.
And in fact, when you stop giving the animals
mammogramab, the muscles got smaller
and the heart got a little smaller.
How often was it dosed?
So the way you dose in the toxicology studies
is you want the exposure,
which means the amount of drug in the blood
to be ideally higher than what we ever expect to get in humans.
And then when you got to the humans?
So that was the preamble to the answer to your question, which was weekly.
So we gave the animals the drug weekly.
And the half-life of the drug presumably is short, but...
It's shorter in animals.
But again, you drive the dosing in the toxicology studies
to make the amount of drug in their blood
ideally higher than we will get in people so that we have what we call a safety margin of exposure.
Now, how do you know at that point, Lloyd of toxicology is driven by peak or trough?
Because some drugs are...
You don't.
You don't.
You make a best judgment, but...
Is there a general rule of thumb?
You measure both, and you want both of them to be higher in the animals than what you get into people.
Okay.
Now, this is in general medicine therapeutic indications.
in some nasty oncology drugs, toxic effects and therapeutic effects are at the same exposure
or even lower sometimes.
But the medical need is so great that you accept the toxicity.
Well, I was going to actually use that as an example.
We sort of skipped ahead a little bit on the phase one patient selection.
We rushed through that.
Or actually, we didn't answer it.
We went off topic.
We're going to come back to which patients do you select for the phase one.
And that really depends on the drug.
Because in an oncology drug, you're going to test it on the most recalcitrant cancer patient, right?
You're going to test it on a patient who's progressed through every therapeutic.
They have stage four version of whatever cancer you're testing, and this is the Hail Mary,
and you're not just testing for tolerance and side effects.
You're hoping to get a sliver of efficacy through dose escalation.
That's the most common scenario on cancer.
But here, what are you doing?
Are you going out to the most frail, sarcopenic elderly?
person or are you going to test it in?
So what I do personally and a very experienced drug developer named Bob Schmutter taught me this,
and I think he's right, is ideally you'd like to test this, a new medicine in the cleanest
population you possibly can where anything you measure is related to the drug and not
some underlying disease or other things.
However, we do not want to expose healthy volunteers to risks if we possibly can.
Right.
So we use our best clinical judgment to say that I don't want to expose people to a risk greater than that of a lightning strike in a year.
Is that literally a probabilistic formula?
That's what I use.
Interesting.
Yeah.
So the risk of being struck by lightning in the U.S. in a year is about,
one and 100,000.
That's actually higher than I would have thought.
Me too.
That's a little scary.
But that's what it is.
Okay.
And so I don't want the risk of something bad happening to one of my volunteers to be greater
than that.
And that's frankly how I explained it to him.
So if I can have some confidence that that's true, we will test drugs and healthy volunteers.
If we're worried about a toxicity or a risk, then we will go.
into people who have a potential benefit from the therapy so you can make a risk-benefit
argument. And this is all laid out in plain English in the consent forms.
But I mean, so first of all, that's a great framework, Lloyd, which is if the risk of adverse
event is greater than one in a hundred thousand, we must move to a population that is going
to potentially get benefits to justify it.
Serious evidence.
Is that a Lloydism or is that a truism across the entire industry?
Is that something the FDA would ask of every company?
It's a schmouterism.
But Bob, if you're listening, thank you.
But the FDA doesn't force that?
The FDA doesn't force that, but the principle is still there.
Okay.
But it's a great standard.
Yeah.
Again, and if you think about the industry as a whole, how do we do in bringing new medicines into healthy volunteer populations?
I've been in this business, partially in academia, wholly an industry, for maybe 30 years total where I've been watching this.
And about once every 10 years, we see something serious happen to healthy volunteers.
Once every 10 years in a study.
So that's pretty good.
And we learn something when those happen.
So we're talking about therapeutic antibodies.
The one that comes to my mind and maybe to others is the degenerate.
incident. Say more about that. I don't remember that. This was a therapeutic antibody that was directed
against CD-28. It was an agonist antibody. Now, CD-28 is an inhibitory receptor on T-cells,
and the idea was, I'm sorry, is it an activating receptor on T-cells? And I forget the actual
therapeutic indication they were going for, but they tested the antibody pre-clinically. Everything
was fine. And then they started at a very low dose in humans. And what we think happened is they
cross-length the CD-28 receptor, and they had extremely strong T-cell activation and an acute
cytokine release syndrome in healthy volunteers. Some of them died. It was terrible. I mean, why did
more than one of them die? In other words, why didn't they figure this out the very first time they
administered this? That's super important. So that study, which that happened, boy, more than 20 years ago,
that experience is why ever since we typically have sentinel patients and dosing cohorts
when we're bringing something brand new into people.
So they dozed, I think, six people at once with the active drug.
Oh, my God.
We don't do that anymore.
Yeah, wow.
The other one, there was a example with a small molecule, bi-al, I think, was the example.
B-I-A-L, people can look it up.
But it's extremely uncommon to have healthy volunteers,
have anything bad happen to them in a drug study.
Extremely uncommon.
If you think of the...
I remember there was one at Hopkins when I was there.
It was an in...
Oh, no, no, no, you know what it was?
I'm sorry.
That was not a...
It was a woman that, a healthy volunteer that underwent a bronchoscopy
and I think had a horrible bronchospasm.
That...
So it was, if I'm remembering it correctly,
it wasn't a drug that caused the issue,
but it was a horrible adverse event to
But anyways, but she died.
Procedures can't have
adverse consequences, which are known and disclosed
in the consent forms.
This gave me a lot of, when I was in medical school,
I was, I was so broke
and doing anything I could to generate a buck.
I was probably one of the most volunteered people
for studies at Stanford.
And like if there was a study
they'd paid $1,000, it didn't matter what it asked of me, I would do it. And I remember coming
away from that. I mean, I had radial lines in my, I had, you know, as you know what a radial line is,
but arterial lines into my radial arteries that to this day, I still have scars over my wrists.
Can you imagine that I subjected myself to that? That seems a little much. My, I think many of us,
as medical students, volunteered for this stuff. My personal favorite was, there was a study
called brain electrical activity mapping
that children's hospital was running
when I was a medical student.
And essentially they
attach electrodes to your head
and then you go sleep in the lab
and they monitor that in video you
while you're sleeping.
They loved me as a subject because
I was bald as a medical student and it was really
easy to put electrodes on and off.
I loved it because all I had to do is go in
and go to sleep. But there
were some others like inhaling radioactive
microspheres. I used to
donate plasma via plasma fororesis as often as I could when I was at the NIH. And on one occasion,
I was in there. And this was like a lymphocyte plasma phreasis. It's a four-hour procedure.
And again, it probably paid $200, which seemed like when you're a medical student, that is,
that's infinite money. And then at one point, somehow the nurse stepped out and the lab locked. And I was
stuck in their lock and they could not find a key. So they couldn't get back in. And,
They were losing their minds, but I didn't know it.
I was just in there watching whatever movie was on the thing.
It turned out to be like one of the most stressful moments in the, in the NCI history, you know, trying to figure out a way to get a spare key to get into the lab and, and I was completely oblivious to it.
Oh, yeah.
Okay, so back to patient selection.
Yes.
So ultimately for Bima, you pick what?
Ultimately for Bima, a healthy volunteer study.
You did go with healthy volunteers?
I'm older volunteers.
Okay.
So people...
What was your criteria specifically in terms of muscle mass?
So I actually didn't run these studies.
The clinicians involved were Dan Rux and Ronan Rubinoff at the time.
But the principle here is healthy volunteers doesn't necessarily mean you're 20-something year old with no problems.
It means people without typically diagnosable disease or concommodent medications that could
confuse any assessments. In the case of BEMA, because we were thinking older adults,
these were older healthy volunteers and people in whom we would be able to measure some of the
effects of BMA, we hope. And again, what you measure in a healthy volunteer study depends
on what the drug is expected to do and what adverse effects you might expect. So there's some
things you always do, like a set of standard blood tests. But in the case of Bima,
we were assessing people's muscle mass.
Via dexa?
And strength.
This is almost archaeology at this point, thinking of what, you know, what we measured,
but we would have measured muscle mass and at different times we used MRI and we used Dexa.
Okay.
I don't remember what that study had.
Got it.
But we would have measured muscle mass who measure soluble muscle proteins in the blood like
K and Aldelaus and LDH and so forth.
Did you see any adverse effects in the phase one?
Yes. So the three adverse effects that are evident with BEMA that we think are on target,
that were assessed in that study where muscle spasms were cramps, acne is rare in older adults,
and it was rare in this study because those were older adults. But skipping ahead, when we've tested younger people, acne is more common. We don't understand why.
And then there are GI symptoms of diarrhea that happen.
They tend to be first dose related and less common subsequently,
but they're reproducible and we think they're real.
And we saw that stuff.
And how many steps of dose escalation did you do in that study?
By the way, if that's too much detail to remember, don't worry about it.
But just I'm wondering if you remember how high you got relative to what was an efficacious dose.
So there's some principles here.
I personally like to dose as high as we can in the first in human study to understand if there is going to be any safety or intolerability issues in people, while at the same time never exceeding the exposures we've tested in animals.
So the study designs include the opportunity to go as high as we can. Typically in antibodies, that ends up being as high as is feasible.
And there are a lot of technical details here we don't need to get into, but when you're,
antibodies are made from cell culture, and they're highly purified, but there's still some measurable
contaminants in them. And the amount of contaminants are, of course, they're also tested as part of
the toxicology studies because they're in the drug we give the animals. But we can't
exceed the exposure to the contaminants either in the clinical study. So sometimes that, sometimes
it's the volume we can administer, the mass we can administer, and so forth. So I think the highest
This dose that we ended up doing in bimagromab was something like 50 to 100 milligrams per
kilogram, but I don't remember.
And in that study in humans, you're administering once a month?
Initially, you administer once, then based on the emerging results for how long that lasts,
and we knew what exposures we needed to reach in order to get maximal efficacy based on the
culture data.
There were a lot of cell culture experiments we did that we haven't talked about.
Like you can culture muscle cells in a dish, and we did that and looked at the ability of the drug to cause hypertrophy of those cells.
So we knew what exposures we needed to get to and how long we wanted to do it.
But again, we don't exceed the exposures that we get in animals.
So I think after the single dose study, we probably did three doses.
And that was it for the first of human study.
And typically, you need multiple doses in order to be able to.
see the technical term as pharmacodynamic effect. So the effects on the body that the drug causes.
So the end point for the phase one, before you move to phase two, where you're really going to
actually look as your primary, and you're always looking obviously for safety, but now you're
really pivoting to efficacy being the thing that you're trying to chase. Yes. What did you need to
submit to the FDA to say, okay, have we checked our phase one box? Typically, you're in
reasonable communication with regulators, whether it's the FDA or whether you're overseas elsewhere.
And you provide them with a report.
And Novartis is a European company, right?
They're based in Switzerland.
But this work was being done in the U.S.?
I think we did do the first inhuman study in the U.S., yeah.
Any reason for that?
Are European and U.S. regulators so comparable on this point that it's really just a question of where your teams are?
So every country is a little different.
Europe is somewhat homogeneous, but not completely so.
Every country is a little different.
And I think it's true both for large companies and small companies,
that you go wherever makes the most sense.
It's where you can, remember, the three biggest challenges of any clinical study
are recruitment, recruitment, and recruitment.
So you have to be able to get the subjects or the patients or the participants.
You need qualified, experienced, reliable clinical
investigators. You need a regulatory environment that's supportive for what you're trying to do.
And then you think about cost of the study. They're different in different countries. And so you
integrate all of that stuff. And that chooses, at least personally, where I would go to do a
first in human study. Countries that are often used nowadays are Germany. Australia is pretty
popular. New Zealand is very popular now. Things are.
have really changed, I guess maybe in the past year or two about China being really popular
because China has a regulatory environment that's become more favorable, and they can do
investigator-initiated studies with less supporting data than we require for a typical I&D,
so it can often be a faster way to test something.
And, of course, China has a lot of patience, so that's something that's being done now.
out too. I personally
love doing studies
in the U.S. and Taiwan.
Taiwan has,
they have wonderful investigators. They speak
English better than we do.
They have a very centralized clinical
environment, so they have many patients at
a limited number of clinical
sites. The regulatory
environment is very similar
to the U.S.
Australia, New Zealand is
favorable because they have a, especially
this is Australia now, they have a
different regulatory construct where safety is assessed by the ethics committee and
CMs drug quality is assessed by the regulators. So they have a clinical trial notification process
rather than an approval process. And plus the exchange rates favorable now. So if we get back to
what is the trial going to cost, that's useful. And how much reciprocity is there between
agencies? So if you, well, I should clarify the question.
You can conduct the trial in Australia, but under the auspices of the FDA where they're issuing,
or does it have to be in the U.S. if the FDA is overseeing?
If the FDA is overseeing, the study's done in the U.S.
Okay.
So if you do a study in Europe and get European approval or you do a study in Australia and get Australian approval,
how much of an additional hurdle is there for the FDA to typically approve a drug?
So it's, let's talk about running a study versus marketing approval, very different.
So for running a study, if you're doing it in, say, Australia, you apply to the Australian
regulatory authorities and the Ethics Committee for the study, and they do the review and
request modifications and eventually approve.
And then the studies run in Australia.
If you want to then do a study in the U.S., you have to apply for an I&D, just as you
would if you were doing it any other time, but you include all the data that you got in
Australia as well. And if you were doing it the other way around, it would be the same thing.
And it's true for any two countries. Meaning, if you had a drug that went all the way to the
equivalent of a phase three ready for approval in Australia, and you come back to the U.S.
from scratch and say, we want to be able to sell this drug in the United States, they're going to
say, submit an I and D? The FDA. I think so, yes. Yeah, wow. And, but how much do you get the
shortcut? Would they still make you do a phase one and a phase two, or would they let you go straight
to phase three? I would think you could. I would think you could.
go right to a regulatory study. I mean, do you have registration study? Okay. And in fact,
this kind of thing is often done. Because typically you do the phase one study somewhere,
but rarely in more than one, two, or three countries. And then you can use that data to go to
many countries for a phase two and then use that data to go globally. There are a few specific
examples where you do have to run a phase one study before you go into that country. Best examples,
the best defined examples are Japan.
So to run a large study in Japan,
you need to have run a phase one study in Japanese people.
And there is a formal regulatory definition
of who is Japanese from the Japanese regulators.
And you have to provide that data
before you can do a larger study in Japan.
They're called ethnic sensitivity studies.
And scientific rationale for this
is that the genetic background of Japanese people can be a little different.
Average body size is often different from people in the West,
and you want to make sure that the dosing and exposure will be safe and tolerable.
But because the Japanese are so well organized and specific about what a Japanese person is,
you can do these ethnic sensitivity studies in Hawaii, for example,
or even California, or you can do them in Japan.
and I like to do them in Hawaii.
China generally requires an ethnic sensitivity study also for the same reasons.
And there are some specific examples of where there's toxicity of drugs and people on Chinese ethnicity.
But they have a less specific definition of who's Chinese.
Easiest way to do it is in China.
All right.
So let's go back to Bima.
Bima.
You go into phase two now.
By the way, at some point, doesn't Novartis sell this asset?
Yes.
So Novartis had strong confidence in Vamagramma.
It was first in class, had really obvious biology in humans.
And basically, Novartis ran maybe, I think, 16 phase two studies of one sort or another,
or phase one, phase two study, different indications?
Tried very hard.
So the drug reliably and predictably increases muscle size,
but not performance assessments in a major way.
And I think that's because, remember in the rodents
in whom we saw both, size increase and performance increase,
the mass increase was large, 20 to 30 percent or more.
In humans, it's 4 to 8%.
And 8 is the absolute max.
Were those differences based on dose or starting mass?
Biology.
People are just not mice.
Oh, sorry.
I mean, the difference between the 4 and the 8,
how much of that is dose dependent versus other demographic dependent on the patient?
Like, you know, do you get more muscle mass in younger people, more muscle mass in people starting with more muscle mass?
There's a trend to more in males versus females, a trend to more in younger versus older, but there's a lot of variability.
Do we know if other variables such as resistance training, nutrition, protein consumption, would have augmented these findings?
And how much were those variables controlled in these studies?
So we know some of that. We try to control as much as we can.
There was one study that has not been published in peer-reviewed form yet, but there is an abstract for it.
If people want to find it, they can look at it.
So the belief study of Bimagromab in obesity was just published a few months ago in nature medicine.
If you look in there, this nutrition study is referenced.
But there was a—we'll link to it in the show notes.
Yeah.
There was a study of Bmagramab in patients who,
were dosed at three different levels of protein calorie nutrition.
And the bottom line is the more pro, and it was the recommended daily amount, half of that,
or one and a half times that, I think.
And basically within those boundaries, the more protein you ate, the more muscle you
build.
Probably shouldn't surprise anybody.
The other really interesting finding.
And by the way, twice the RDA is only 1.2 grams per kilogram.
Yeah, maybe that's what we used.
it was 1.2.
Yeah, I would argue had you gone to 1.6 or 2, you probably would have seen more hypertrophy.
It's not been tested.
I think you're probably right, but it hasn't been tested.
It's interesting.
So it suggests that in humans, you might have been substrate limited.
Amino acid limited or protein synthesis limited.
It's a possibility.
And not drug limited.
I'll tell you a funny story about that in just a minute.
But just to finish that study, the other very cool thing we found is that, as you would expect,
if you have half the recommended daily amount of protein calorie nutrients, you lost muscle mass.
But bmagramab prevented that.
So there was some biology working there for sure.
No question.
No question.
So the really interesting story is that when the bimagromab project, when it was still in the research stage,
moved from Chris Luz lab to David Glass's department, which I was part of is the clinical
side of that. One of the things we really wanted to do was co-develop a nutritional component to this
therapy for the exact reasons that you brought up. Yeah. And at the time, Novartis had a nutrition
arm. And so we were working with them to develop a specific nutritional supplement for what became
mammogramab. At the time, it didn't even have a code yet. But then Novartis sold their nutrition unit,
I think, to Nestle. And so got the rug pulled out from under us.
on that side, and we were never able to fully pursue that.
But in retrospect, I really wish we had.
You think this is a blind spot for Big Pharma, just the role of nutrition and other
behaviors that can potentiate drugs?
Big Pharma tries to control it, but they don't see that as their core mission.
Yeah, but I'm saying a blind spot, I appreciate that they want to control it, and that
makes sense.
But I'm saying, like, it's an opportunity lost, right?
Probably.
Like, here's a great example, right?
Yeah.
Like, BMA could have been more of a hit if maybe, and maybe not, but a drug like that could have been a hit had it been appreciated that, oh, by the way, like, you actually have to kind of do something to reap the benefits of this.
We would have figured this out many years sooner if we had kept that nutrition element.
But again, one of the challenges of big companies is there's so many people involved.
They don't all know what the others are doing, despite everyone's best efforts.
So basically...
It was a missed opportunity.
And so did Novartis then spin it out after the less than expected findings in humans?
Yeah.
So what happened was we saw muscle mass get larger, but not stronger.
And parenthetically, that's the same as was seen with IGF-1 agonists and with androgen agonists.
Remember the SARMs were extensively studied.
Is that you can make muscles larger, they don't get stronger in the absence of resistance training.
So it's not unique to the active and receptor antagonist pathway.
And in a meta-analysis of the Novartis studies, where they looked at muscle hypertrophy and sarcopenia,
the meta-analysis showed an increased six-minute walk distance, six-minute, nine meters, so a small effect.
That's my least favorite test in the world.
It's surprisingly hard to standardize.
why wouldn't they just do something like a wall sit or you know something that really tests strength
many other things were done the timed up and go test the short physical performance batteries
but six minute walk was included in multiple studies so you were able to do a meta-analysis of that
got it so the an academic group did this and they published it and so the the four to I don't know
8% increase in muscle mass that these older adults got yielded a 9-meter-meter increased in 6-minute walk
distance.
Yeah. I'm not convinced that's going to help anybody not fall.
No, I don't think it will either. And Novartis didn't think so either. I guess. I wasn't an insider
at the time. I don't know why they out-licensed it. I was the recipient to that.
Yep.
We were on the outside pulling. But the very last study Novartis did was a study in type 2 diabetics.
Because we had had data that hemoglobin A1C's decreased in patients given Bimagramap.
And that study, which ran for 48 weeks, so it was 10 miggs per Kig monthly for 12 doses.
Okay.
So a lower dose than you were giving for hypertrophy?
No, this maximized the...
Oh, why did I think you said earlier 50 migs per Kig?
In the phase one, we went out.
You went up that high, got it.
We went up as high as we could because we wanted to know what would happen if people were overdosed later.
Got it. Okay. And the answer was nothing. Okay. So at 10 migs per kig monthly over 48 weeks?
Yeah, was a was a maximal dose in terms of effect size. And they saw the expected muscle mass increase.
Interestingly, they saw a substantial fat mass decrease and hemoglobin A1C and these type two diabetics
decreased by about 0.7 or 0.8%. Absolutely. Which is a pretty good effect. Yeah. And do you think that
that was on account of just more insulin sensitivity or was it a larger reservoir for glucose disposal?
Both of those things, I think. And these patients didn't have to do anything else. It wasn't like,
in addition to that, they changed the way they ate or they exercised more. You gave them a drug that added
muscle mass took off fat mass and lowered A1C by 0.7%.
Yep.
And they had standardized dietary advice to...
Yeah, both.
So who?
Did Novartis run that study?
Navartis did the whole study.
And then they made a strategic decision that the effect size wasn't big enough.
I mean, actually, I don't know what their strategic decision was, but they decided...
The output was we're going to spin it out.
Yep.
The output was to spin it out.
And at the time, I was working with Joe Jimenez and Mark Fisher.
in Pravina Kandula at Adidem bio as an advisor.
And we really wanted Bumagramab.
What year is this approximately?
That it spun out was 2021.
I think it was 2021.
Yeah.
Discussions had been ongoing in 2020, but I think it finally happened in 2021.
Okay.
So you guys acquired the asset, obviously, for a lot less than you could have produced it.
Yeah.
still wasn't cheap because it was a phase two ready program.
But we acquired...
Did you guys raise money for that acquisition?
No, did it and all themselves.
Okay.
To their credit.
And the plan was we were going to develop it in older adults with low muscle mass
and impaired muscle function because we thought who were also obese,
because we thought this was the patient population most likely.
to benefit, losing fat and building muscle and maintaining muscle in the context of weight loss,
we thought would be super important for those people. And remember, all of this happened in the
context of nobody being interested in obesity. Everybody thought it was a wasteland for drug
development. Every drug that had been developed and obesity had failed commercially. I mean,
there are some that had been registered, right? But by 21, you're saying pre-21.
This was before Novus semaglutide data came out.
Okay, that's right.
Yep.
And I'll tell you, I...
Because that was 21, wasn't it?
Later in 21.
Okay, so it's November of 21, if I remember.
February 21, we started Versanis Bile, which is the company that licensed
Bimagramab from Novartis.
So at that point, so I was the founding CEO, I was working with Elon Zipkin, and we went
out to raise money from investors, because now, all right, great, we had this.
asset, we needed to run a big phase two study and we went out to raise money. I think we talked to
53 investors. Almost none were interested. Because you told them indication sarcopenia still.
Well, it was it was sarcopenic obesity. Yep. And obesity was just not a successful area for drug
development. So people weren't interested. How much did you need to raise? We ended up, how much did we
need versus how much we got are different issues.
Yeah, I know. That's why I asked.
But we ended up raising 70 million.
And what was your, if you could have had your wish list, what would you have raised?
About 100.
Okay.
However, Atlas Venture and Medici liked the story.
And I had worked with Atlas before.
And Michael Gladstone was the partner.
And it was Vonie Marigi and Nick at Medici.
Nick Williams, and we then built a investment syndicate and they funded the company and then everything
changed when Novo's data came out with semaglutide, which was amazing. It was the first really
effective obesity medical therapeutic. But then when you're doing drug development, you skate to
where the puck is going to be. It's a Jay Bradner's favorite saying, but the puck was going
someplace else now.
Some of gluteide was going to become the standard of
Claire or some in Creight and agonist.
We knew it.
So what we did is we
quickly repositioned the company
to think about
what is Bumagromab going to do on top of that
because that's going to be the standard of care.
So I quickly ran a bunch of mouse studies
and the efficacy
was additive.
When you took Bumagromab
with semaglutide or terseptide or lyraglutide,
it did them all.
And the efficacy was sort of unprecedented,
never seen anything.
For both fat loss and obviously for preservation of lean mass.
Exactly.
For weight loss, especially fat loss and preservation of lean mass.
It was amazing.
So the opportunity became much larger.
And the board then brought, and I was part of the board,
the board then brought in a super experience.
experienced CEO, this was Mark Przansky, to lead the company then because we had a really big
opportunity and we knew it. And we brought in a CMO, Ken Addy, because I had been serving as the
CMO also. And then I stepped into president and CSO role just in terms of company organization.
But we all kept working on the program. We ultimately ran what became the belief study.
and the story here we spent a lot of time thinking about what we would name our studies.
The plan was believe was going to be phase two, become was going to be phase three,
and behold was going to be post-registration studies.
And then you actually have to come up with what those things stand for,
knowing only what the B stands for when you start.
I mean, this is so funny how drug name studies were.
Yeah, you know how it goes.
I know the drill.
But it was all, they all became with B for Bagramma.
Yeah.
Now, you haven't asked me where.
Magromab came from. So this is another interesting, wonky drug development thing. So the generic
name is called the I'm in NN name for, I think, international nomenclature. I'm not sure what it's
an acronym for. Which is why it ends in MAB, obviously. So the suffix of a drug generic name is
pre-specified based on the class. If you're the first in class, you know, pick a new one. But the
company gets to recommend the prefix and sometimes the infix. So Bima is the Indian god who's as strong
as 10,000 elephants. And that's why Bumagromab is Bimagromab. And then ends in Mab monoclonal
antibody. The grumab is a monoclonal antibody suffix. So any other drug that comes along in that
class, what would be the nomenclature naming options? Antibodies are just
complicated. There's a lot of different criteria for naming antibodies and you have options for
infixes and suffixes. And what was the, what was the GLP1 before Lira Glutide?
There's Xenotide. Exenotide, right? So the tide became the thing that everybody had to link
to going forward? Tide is peptide. So any, but they, they, they, were they forced into
Lyraglutide, semaglutide, tersepid? The tide is the, is they had to do it. They had to do
for that class, but there are other peptides that end in tide.
Okay.
So you guys ran Believe.
Yes.
So Believe, it was originally planned to be a 24-week study in patients with sarcopenic obesity.
That was what we were going to do.
But then when Novo's data came out and we got super excited about obesity, he said, oh, my God, we've got to do a bigger study.
We're going to do it in combination with semaglutide.
And this was during the pandemic.
So there was a lot of complexity in supply chain disruptions.
And remember with semaglutide, it was a proprietary drug of Novo.
We couldn't get the drug substance.
So we had to use the commercial presentation of semaglutide, which is expensive.
Which is expensive, and it's an auto injector.
We couldn't make a placebo for that.
So the study design included semaglutide as open label, but we did a
we did placebo-controlled bmagramab because we had control of that.
We used bimagromab intravenously just because it was the fastest, most straightforward way to get into the clinic.
Not public was that we were working hard on an auto-injector, and we would have been ready in the next study for an auto-injecture,
but it was intravenous for bimovet.
And then what combination should we use?
we ended up doing something called a full factorial design.
So we did all possible combinations of low-dose,
semaglutide, high-dose semaglutide, low-dose spomagromab,
high-dose pomegramagromab and placebo.
So it's a nine-arm study.
Why?
Because we didn't know in humans what would happen
with those different combinations.
We didn't know if there would be adverse effects
of the drug combinations or not.
They did have a couple of adverse effects in common,
diarrhea, for example.
And this is in part why I did that pharmacology study in rodents, because if there was anything
unexpected that would happen with the drug combination, I wanted to know about it.
Technically, actually, we, and we had to do this because we weren't using the semaglutide
in its intended population.
I think it wasn't registered yet, I guess, was the issue.
We had the data, but it wasn't registered, so it wasn't indicated in obesity.
So if you're using an...
And so, yeah, you were using
Ozempic, not Wagovi.
You were still using...
We used them both, actually.
Oh, you did?
Whatever we could get.
Remember, they were in short supply.
Yeah.
And to the regulators' credit,
they recognized all of this
and were willing to allow us to substitute
interchangeably Osepic and Wagovi.
Yeah.
So what were the findings of this six-month nine-arm study?
So it was originally going to be six months,
but we changed it from the original plan with Bumagromab alone to the combination,
and it eventually became 72 weeks of treatment, 48 weeks was the primary endpoint,
and then we had a six-month follow-up period, so 104 weeks total study, two years.
Did you have to raise more money?
We did.
Yeah.
I was going to say, that's a hard study to do for 70 million bucks.
Yes.
We did, and it was 500 people enrolled, roughly, 570.
was the exact number.
So we found, so I guess number one, and one of the things I'm kind of proud of is I got
the doses right, because you wanted to see a partial response with the low dose, a full
response with the high dose for both of the drugs and see those kinds of dose responses
in the combination arms.
Remember, there's four combination arms.
Yep.
Right?
There's low dose, bema, high dose bema, low dose, sem, high dose, samma, four combinations,
and then placebo.
And we saw the dose effects in all the arms.
So that was good.
And the primary endpoint was body weight.
Wasn't what I wanted for a primary endpoint.
I wanted waist circumference.
Why couldn't you get DECSA too expensive?
We thought that since the registration decision is made on the basis of body weight loss,
we wanted that as the primary endpoint.
We included DXA in every single patient.
Yeah, it's crazy to me that you would be held to the standard of weight loss when in reality,
a better outcome might be less weight loss.
That's true.
If you're preserving muscle.
We were acutely aware of that.
Yeah, this awful.
But it is not what the field was thinking at the time.
No, I know, but it's just, I mean, it's good biology abuts regulatory simplicity for Lutton.
Yeah.
Yeah.
That would be a charitable way.
I personally wanted waist circumference.
And I wrote a long white paper about this because
waste circumference is more closely linked to important
clinical outcomes than is BMI or body.
For sure. Yeah.
So body mass index is, if you're following longitudinally,
is essentially the same as body weight because height doesn't change.
Exactly.
Yeah.
For a short term.
Just for listeners.
So we ended up using body weight as the primary input.
And it wasn't just regulatory intransigence.
It was also what do investors and potential acquirers think?
Everybody cares about what the approval endpoint's going to be.
We wanted that to be the primary endpoint.
But we measured all these other things.
And to sort of zip ahead to the end, in the high-dose combination group,
the body weight lost at 72 weeks was 22, 23% of starting body weight.
High-high.
Yeah, double positive.
The high-high combination.
And what was the high...
But the fat loss was 45.7% of starting body fat.
Now, that's what you get with bariatric surgery.
So this, to me, this is the first medical therapy that gives fat loss equivalent to
or superior than bariatric surgery.
That's amazing.
Did you do any functional testing in that study?
We did.
We did.
And we even did a proliferation.
preliminary observational study in overweight adults at different age cohorts, and we tested a few
different things. We tested essentially timed up and go for short physical performance battery.
We tested the 30-second chairstand test, which is my personal favorite, and we tested grip
strength. But ultimately, we went with grip strength in the believe study because it was the one
most closely linked to clinical outcomes. And did you see an improvement in
strength? Small, but also it was a variable assessment. Okay. And it's in the published study that came
out a few months ago. Now, Novo bought this asset from you guys, right? No, Lily did. Oh, Lily did.
Yeah. Okay. So we were super excited about the study. It was ongoing. We were enthusiastic. We closed a
Series B in two tranches, and we called the first tranche, and then the company got bought
by Yila Lilly. And so they have Bramagramab now. What are they doing with it? You have to ask
Lily. But they made some noise last fall that they were pausing the program or?
No, they just, they, they paused one study, but they still have other studies in clinical
trials.com. Okay. But you got to ask them. I see. So publicly,
the only thing we know is they're still doing something with it,
presumably testing it with terseptide, I'm guessing, or retitrutide.
Yeah, the study that's in clinical trials.gov is a complex combination study with
terseptide.
I do think it's fair to mention the one adverse outcome that happened in the belief study
that we weren't really expecting, which is an increase in LDL.
Yeah, how much I remember that.
Now, I thought that was actually something that Lilly saw,
but that was in your study.
Yeah.
And how much of an increase was it?
It's about 20%.
Why do you think that was biologically?
It's a direct effect of the drug in the liver.
So interesting.
Again, you wouldn't expect this off target, would you?
This is on target.
But because remember, there's active in receptors everywhere.
Oh, I didn't realize that.
Yeah.
Ah.
So it's doing something to interfere with LDL clearance, presumably.
I guess, but I don't know what the biology is. It hasn't been studied tonight. Or no, maybe. I mean, what would be a more plot? I mean, that would be studyable, right? Is it is it impeding LDL clearance or is it increasing LDL synthesis? I know who knows the answer to this. So Chris Liu, when he left Novartis, eventually founded a biotech called Lakna in China. And he's made therapeutic antibodies to active in receptor type 2A, type 2B, and the combination. And he studied them. So he knows the
answer to this. And I assume he'll publish it at some point. And Lloyd, were there any adverse
effects on glucose in the other direction? Did glucose ever go up? No. Okay. And did you continue
in the belief to see glucose go down the way you did in the diabetic studies? Yes.
Independent of what you would have seen from SEMA, I mean. Yes. So we have all of that data
and it's published in the Nature Medicine paper. At EASD in September, which is a European meeting,
we're going to publish the results of the six-month off-drug results.
So that's-
That's off both drugs.
Yes.
And so the real issue is what's going to happen when you withdraw the drugs?
And we know what happens when you withdraw semaglutide, right?
Everything goes back towards where it was.
It doesn't quite get there.
And we're going to find out with pomegramat.
I expect some things are going to reverse.
Like, we know that muscle mass with every muscle
anabolic agent reverts towards baseline when you withdraw the therapy.
I expect that's going to happen in the humans.
It happens in the rodents.
In Believe, we deliberately included patients with metabolic syndrome.
So these are people who are pre-diabetic.
So we can measure diabetic endpoints in these people,
and it's going to be super interesting to see what happens there.
Personally, if we had kept Vomagromab in,
In Bursanus and there have been a standalone entity, we would be well advanced into phase three by now.
And the reason is because I believe, even with those LDL effects, which are not favorable, LDL predicts adverse cardiovascular endpoints.
But I believe that-
You can monitor it and you can treat it.
Yes.
Which, as an aside, since my personal interest is making drugs to prevent the most common causes,
of morbidity and mortality in older adults.
Side effect of that is healthy longevity.
That's what I do.
I am not making cardiovascular drugs,
even though it is the number one cause of morbidity and mortality
in adults in the U.S.
and in many developed countries around the world.
The reason is we've already got a lot of good drugs
or just not using them for primary prevention,
which we need to be doing more of.
So with that aside,
I would be well advanced in developing
bimagromat in phase three,
But I think the paradigm for managing obesity is going to be induction and maintenance of remission,
probably combination and injectable therapies to get people to their, you know,
to move them categorically from obese to non-obes.
And then they need something for maintenance, which might be something like,
or for glopron or some oral GLP1 agonist to maintain appetite and satiety.
And you don't think just a lower dose of this.
the injectable could do?
Absolutely, you could.
Yeah.
You're just saying economically, it might be easier to make it or earlier.
Exactly.
Yeah.
Exactly.
Okay.
I want to pivot and talk about one other thing, which is also an area where you know a lot
about it, which is selective mTOR inhibition.
We're not going to spend as much time on it, of course.
But again, talk to me about where your head is at these days on that pathway in general.
Do you believe that there are
that this is gyroprotective in humans.
I mean, it's been well established how
geroprotective this is in mice,
almost assuredly,
I think it'll end up being gyroprotective in dogs.
So it might be safe to say that
inhibiting mTOR in everything from yeast to dogs
and maybe even primates extends life,
we don't have a clue if it's going to in humans.
We'll never probably get to directly test it.
There are really good compelling arguments
on both sides of why it may,
or may not be the case in humans, including the longevity quotient argument and things like that.
What are your thoughts?
I think it probably will.
It's highly conserved biology across evolution.
So I think so.
Reductively, if you envision mTORC 1 as a master regulator of sensing, sort of integrating nutritional inputs
and then deciding to grow or not grow.
and not grow means circling the wagon upregulating autophagy and recycling pathways.
I think it probably would.
I think the effect size is going to be modest.
Is it just as it has been preclinically?
And I think it's torque one.
I haven't seen a lot of new data on that.
Well, there was that study somewhat recently suggesting that rapamycin impaired,
I don't know if it was impairing MPS or some other metric.
a physical performance or something.
Obviously, you're familiar with the agents you've tested.
You know, we're still at sort of the infancy of these drugs, right?
What do you think is standing in the way of more drug development on more and more selective,
potentially higher efficacy, but potentially lower side effect burden versions of drugs that can
inhibit mTOR complex one?
The selectivity is the big challenge because with,
Rappalogs, as you know, there's
torque one selective, but there's
a downregulation of torque two with
sustained exposure. And I don't know
that we, you know, so in
restore bio, we tried to manage that by a
combination of a catalytic and an allisteric
inhibitor, which seemed to do it.
And I know there are other companies that are working on other ways to get
torque one selective inhibition, and I think that's what we need
is a real torquine selective inhibitor,
and then we can test the biology.
And do you think that just intermittent dosing of everolomus
or serolomis gets that?
Maybe.
Again, it's hard to tell in healthy people
because, you know, in cancer,
when you study mTOR inhibitors,
the cancers have a highly upregulated pathway,
and it's easy to see the biology.
You can't really see the active biology
in humans measuring blood.
It is not necessarily the tissue.
you want anyway. When we do this in rodents, we measure their liver activity. And I think we mentioned,
you and I discussed this before, that in young rodents with fasting, they downregulate EMTOR,
as you would expect. In old rodents, they didn't. So it makes me call into question the whole
concept of intermittent fasting in older people, because I don't know if it will do the same thing.
Yeah. Again, imminently testable. Nobody.
He's lining up for liver biopsies, though.
No.
And we can't get that with MRS or anything else.
I don't think so.
It's just.
Yeah.
Again, the price of admission is so great on that.
Okay, final question slash topic.
As you think about drug discovery over the next decade, I'm not going to ask you the
question everybody's thinking.
How is AI going to help?
We'll punt that for now.
Thank you.
Yeah.
What are you most optimistic about in terms of,
of pathway, disease, where are you most excited?
Where do you think we're going to be in 10 years
where there's been a step function change?
I think we're starting to wake up to the concept of real medical prevention.
I mean, this is something I've been saying for years.
You've talked about it a lot is that we need to get away from being a sick care system
to a health care system.
And the way you do that is with preventive medicine.
And the way to implement it is you need better primary care and you need codes for preventive visits.
Because right now, if I wanted to see a patient for prevention of cancer, for example,
so my new company is cancer prevention, there's not codes for that.
So you can't bill for it.
So there's a lot of institutional hurdles that we need to get through.
But I think people are waking up to the concept of I want to stay healthy rather than get sick and get treated.
Say a bit more about your current company.
And how could one develop a drug for cancer prevention?
Yeah.
So this is conceptually difficult to wrap your head around.
But again, where do new drugs come from?
They come from reading the literature and thinking, which is sort of what I did after Versanis ended for me.
or it's still ongoing in Lilly.
And there are some papers published over the past five to ten years about drugs that cause cancer.
So if a drug causes cancer, it must be most likely inhibiting a cancer-protective pathway.
Most drugs are inhibitors of things.
The prototype for this is seraphanyb, which is a multi-kinase inhibitor that's used to treat
renal cell carcinoma and hepatocelular carcinoma, primarily.
primarily. If you give that drug to people, about 10% of the patients, of the older patients,
get skin cancers. Why is that? And are these melanomas or are these squamous or basal cells?
The cancers they get seem to be the prevalence that's reflected in the normal population.
So almost everything that's ascertained is basal cell and squamous cell. And more recently,
we understand the pathway biology of that. These are, seraphinaib is a multi-kinase inhibitor.
it's a lot of kinases.
But one of the ones that it inhibits
is the sensing kinase
that triggers something called ribotoxic stress.
And this is a pathway
that causes cell death.
That pathway, if you turn it on
irreversibly and covalently,
is the target of some of the nastiest toxins
that you know about,
like diphtheria toxin.
Sarsin, ricin.
It's a very, very potent pathway.
My innovation
is putting together different parts of the literature,
I came up with a way to turn it on in a gentle and controlled fashion.
Remember, it's on constitutionally in people
because if you turn it off with these multi-kinase inhibitors,
you get cancer.
So the hypothesis of the company is if we turn that pathway on a little more,
we'll prevent cancers.
Not all of them, but maybe 50% is what I'm hoping.
and since skin cancer is almost as common as all other cancers put together, we've got to start there.
But in a phase two study of older adults, and older adults in this context means 50 and up,
sorry, Peter.
I'm in that category squarely.
Don't worry.
I have been for a while.
And who have had at least five skin cancers in the past, those people have a 50% chance
of having another skin cancer within a year.
So if we recruit a cohort of 100 or 120 of those, we would be able to test a low-dose, high-dose, placebo,
and actually measure cancer prevention in a phase two study.
Now, is there a risk that it will only work in preventing squamous cell and basal cell carcinoma,
but will not progress in epithelial tumor?
Or prevent, I'm sorry.
That's possible because the only data we have are for skin cancer.
but even if it only prevented skin cancer, that's a really big medical need.
But I think it will work on multiple cancers.
But it's going to be almost impossible to test that before approval just because cancer incidence is a really rare event.
Yeah.
I guess the next thing that would be an interesting question, Lloyd, would be you take a bunch of patients who have successfully undergone adjuvant therapy for a state.
three epithelial cancer. So I would think colon cancer or breast cancer. They're
NED, no evidence of disease for the listener, but there's a 50% chance they're
going to have a recurrence. You know, you stratify it in a way that you basically
find people who have a very high risk of a cancer recurrence and then you you
treat them. I think that's one way to do the other study. What I've done in
Koslap Therapeutics is a collaboration with the Broad Institute where we took our tool
compound. Now, we don't quite have a development candidate yet, but we took the tool compound,
which is good enough, and run it through their panel of a thousand cancer cell lines to see
what tumors are sensitive to it. So this would be a treatment mode rather than prevention mode.
And you think it could have efficacy in treatment as well?
That's the question we were asking.
Okay.
And melanomas emerged as by far the most sensitive tumor.
Now, I'm not sure why, because my hypothesis, the thing about skin cancer is it's got a heavy
mutational burden because of all the UV exposure.
It's the highest mutational burden organ we have in normal people.
And I thought that was going to be it.
And there was a correlation between mutational burden of the cell lines and susceptibility to
this mechanism.
but it wasn't great enough to explain the tumor susceptibility.
So it's something else.
That would be good news.
Yeah.
It's there, but it's not good enough.
So I don't know why melanomas are so sensitive, but they're enormously sensitive.
So I'm very confident this will be a therapeutic for melanoma as well.
And it augurs well to the idea of preventing melanoma, which is also testable and has been
proven with a therapeutic intervention in a wonderful study conducted in Australia.
The intervention was intensive sunscreen use compared to usual practice.
So it's going to be testable in a large phase three study, but not before that.
So, yeah.
So that's what I'm doing.
And I think preventing cancers.
That's a very interesting idea.
I mean, talk about a new, a whole new playing field, right?
Pharmacologically.
Yep.
Nobody's made a drug for this mechanism.
Because we usually think avoiding cancer or preventing cancer can.
down to avoiding carcinogens.
Which we should definitely do.
Yes, yes, absolutely.
So don't drink alcohol much.
Yeah.
Don't smoke.
Don't smoke.
Be as insulin sensitive as possible.
Yes.
Yeah, all of these things.
All of those things.
Lose weight if you're overweight.
We know that successfully treating obesity prevents a bunch of cancers.
And we know that from the Swedish obesity study, which is an observational cohort of Swedish
patients who've undergone bariatric.
surgery and these people are being followed for decades. It's doing all the good things you'd expect
of successfully managing obesity. Well, Lloyd, this has been great. This has been kind of a
a wonderful education on drug discovery using, I think, a very interesting drug in BEMA as a
case study for the complexity and the nuance of the process. And by the way, I don't think I realize
that the BMA story is still ongoing.
So that's great.
So we're going to continue to follow this biology,
and it'll be interesting to see where Eli Lilly goes with this drug.
But it sounds like, based on what's showing up on clinical trials.gov,
they're following in your footsteps in that they're probably testing this in parallel
with the newer generation, GLP1 agonists and the...
As best I can tell, that's what they're doing.
And it's not now just Eli Lilly because many other companies,
you know, who have seen the believe data,
because we've been presenting it at national meetings and international meetings, for that matter.
There's a lot of other pathway inhibitors that are under development.
Yeah.
Well, really appreciate your time, Lloyd.
It's been a pleasure to chat again.
Great efforts, yeah.
Thank you.
Thank you.
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