And welcome everyone, to another Smart Money Circle episode.
I'm Adam Sarhan. With me today is Martin Brenner,
who's the CEO and the CSO, the chief scientific officer at
IBIO. Martin, thank you so much for
taking the time and welcome to the Smart Money Circle.
Thank you, Adam. I really appreciate being here
today with you. It's a pleasure.
So, Martin, I always like to begin.
Can you please tell us your story and how you got to where
you are today? There's a a long story and a
convoluted story. So I my CV is not exactly what
you would call linear. I started actually out trying my
hand at becoming an electrical engineer and wouldn't this
didn't work really well. I studied veterinary medicine
and halfway through my studies I met my professor for
pharmacology who ignited kind of a fire in me for drug discovery
and making medicines. And ever since I've been
pursuing that career, first in large pharma.
I was in R&D departments of four of the major companies, Ileli,
Pfizer, AstraZeneca and Merck, and then jumped into biotech at
which at the time sounded like a, a more, you know, exciting
opportunity for me after 15 years in big pharma.
And have, you know, ever been in biotech since trying to actually
combine novel technologies with a very empirical field of drug
discovery, which is always a challenge.
It's a job that is very humbling because every experiment around
the corner can be the last one for your program.
So it's not for the faint of heart to be in biotech.
I love that and I usually that's it's a good Darwin type wedding
out the weak and the strong and the ones that can adapt and
survive. So I'm glad that you're here and
thank you for the work you do. So Martin, next question for you
is tell us about your business please, your story, your
competitive advantages, anywhere you want to go?
Absolutely. So Ibio is first and foremost a
really cool turn around story. When I took over the reins of
Ibio together with my CFO, Philippe Duran, the company was
a CDMO. We actually had a plant based
expression system. So we literally grew tobacco
plants or you know, cousins of the tobacco plant in in a
facility extracting molecules, among other things antibodies.
And I was originally brought on to build a biotech arm that
would feed programs into this manufacturing site.
While it was really challenging to do the manufacturing and we
ultimately decided to to walk away from it, the biotech sector
actually has taken off quite nicely.
We were in a lucky position to acquire the assets of a a
company called Rubric Therapeutics.
It was a pioneering company that one of the first companies that
used AI in antibody discovery. And the only downfall for Rubric
was they were a few years ahead of their time.
And so funding got really complicated.
And so we brought this outstanding team down to from
the Bay Area to San Diego and we started to kind of build upon
what they've done. So we are staying far, far away
from calling ourselves an AI company.
What we are is really we're very, very good in integrating
AI technologies in the current lab flow.
And as you might know, there's two sorts of companies, one that
are more focused on the developability of drugs.
So we make antibodies and you know, if you want to make a
medicine out of this, they have to fulfill certain requirements
that make them drug like. And there's some companies that
are good at that and there's other companies that are going
full in silico. So they design molecules by AI,
but they usually run into a ball when it comes to developability
because they don't look at all as drugs.
And we have found a niche for us in between there.
So we can make really hard to make molecules, but at the same
time they look like developable drugs.
And we're a few months away from moving the first molecule into
clinical development. Our initial focus is cardio
metabolic disease and that's a little bit of a coming home area
for me. And that was my research area
for the 1st 15 years of my career.
It's a pretty complex space, but we have focused on that.
And what makes us so different in the space is we have not like
everybody else gone into the GLP ones.
We have actually accepted the GLP ones will be a cornerstone
of obesity treatment. And from that point on, we
actually looked at what do they leave open in patient care and
these are the areas we're trying to cover with with our
antibodies. Wow, I love that.
So for the audience, just to help them understand what you're
doing is that you're using AI to develop molecules to help
antibody discoveries and create a platform that can really help
accelerate that that discovery. Is that a good way of
summarizing? It that that is a really good
way of saying this. And you know, you have to solve
multiple problems on that way from an idea to having actually
an antibody that works in in an animal model or in humans.
And So what we've done was we created multiple layers that
will help us, right? I, I hear a lot of people
saying, oh, we made an AI drug. It's, it's a little silly to say
that because it takes about 10,000 steps to make a medicine
and we enable three to four with AI.
That doesn't really make it an AI drug, but it actually allows
us to do things we couldn't do before.
And I think this is where, where I draw the line.
If you can create a molecule with the help of AI, you
couldn't imagine before, then you have something if you just
make a molecule that I can find with my traditional way of
making drugs, what good is it to use user model, right?
And so we have really focused on can we create antibodies against
targets that are usually considered undruggable.
And we have two great examples where we are, at least to our
knowledge, the only company in the world that is has an
antibody against two of these targets.
That is important. And we have also proven, like
you said, the speed of of development.
We have our our first program, we moved it from a paper
exercise where we just strategize what that molecule
would look like all the way to a so-called development candidate.
That's when you make the decision.
Yes, that's the molecule we actually want to move forward in
clinical development. That took us seven months.
That is a process that can take up to two years.
So it is helpful, it does help, but you know, AI is not yet
there to help us in assessing safety, not yet there in helping
us to assess efficacy in humans, but we're likely going to get
there at one point. But so far we've really focused
on this early part of discovery where AI really can help us and
has demonstrated really clearly that it can help make you make
better drugs or make drugs that have been impossible to make
before. Wow, I love that.
OK, Thank you for your work, by the way, and it's a good segue
to my next question, Doctor Brenner.
Let's talk about risk management.
How do you handle risk and what are some mistakes you see people
make with respect to risk management?
So we're in biotech. So we're anyway a high risk
environment if you will. What is what is really
challenging is making the right decisions, not throwing good
money after bad. And we start to de risk our
programs, if you will, in a way where we we always start with
the final product at the end. And that means is there a
patient that will benefit from the molecule we're designing?
If that's the case, that's step one.
That's the most important one. But you also have to think
about, is there a physician that will prescribe this drug?
Is there a payer that ultimately will pay for this drug?
And so then we work our way backwards through phase three
development. Is it feasible?
Are there endpoints that we can register?
And this is basically how we're working all the way back to the
very beginning. So we're never starting a
program unless we have a clear path of this could actually
become a medicine that helps people and that de risks you a
lot. There's always risk in in, you
know, the mechanism might not work.
The molecule in itself might have, you know, a part that is
toxic that we don't know upfront.
But if you clear that path to to a ultimately a product, a
medicine, it de risks you dramatically.
But I would lie if I if I'd say, you know, we have this all under
control. Luck plays a large role in what
we do and that's why we use an attrition model as well, right.
So if you start three or four programs, up to six programs,
you almost guarantee that one will hit the clinical
development. But it it could be up to 60%
attrition in, in early preclinical models.
So far we had zero. So our model is a little, we're
now in a in a good position to not have enough money, but many
programs that are very successful and very positive.
So it becomes a luxury problem. Which ones do we actually
prioritize in this case? I love that.
OK, next question for you. Let's go towards the timeless
advice here. What is What are some timeless
lessons you've learned along the way that you'd like to share
with the audience? I think the, the one thing
we've, we've learned over the last four years, if you will, is
that resilience is an absolutely necessary factor for a team that
works in biotech. We were multiple times close to
having to shut down. None of us gave up, neither the
board nor the leadership team nor any of our team members in
the R&D team. We all believed we we have
something that is really valuable and that actually
brought us through these really dark times.
So it's a, it's a fact of biotech life that you have to go
through these dark times. If you do not have the
resilience, if you cannot take punches on a daily basis, this
is probably not the right environment.
So this resilience is kind of the key part.
There's a lot of other things, you know, you need to have the
right like minded people. You have to rally behind one
common mission and goal. All of these are important, but
ultimately, if you can't sustain these assaults on on on your
programs on a daily basis, you're not going to make it.
Yeah, that's a great point. OK.
Other side of that would be timeless mistakes.
What are some timeless mistakes you've learned along the way,
and how do you learn from them so you don't repeat them?
So one of the biggest misconceptions and, and mistakes
that our industry in general has made is trying to de risk
programs by going after things that they already we already
know and, and know as a fact. What this breeds is a is a
so-called me too environment where everybody's doing the same
thing. And then ultimately you
differentiate your molecules not because they're helping patients
better. You're differentiating because
you have a better marketing team.
To my knowledge, this has never worked long time for any
pharmaceutical company to be really kind of that the risk,
right? It is very hard for larger
companies to change, you know, tracks and reinvent themselves.
And sometimes it's necessary, right?
If just because one mechanism works doesn't mean you have to
do the same mechanism all over again and try to kind of make
things fit. That's usually the time when you
have a successful truck out there that you should reinvent
yourself. Really kind of think about
what's the next big challenge you want to solve and that
inherently has not been done. And, and I think this is one of
the biggest mistakes we have. Once you have basically money
coming in from a successful drug, that's the time to really
kind of put your eyesights on the next frontier.
And it is very hard because that usually requires change, and
change is is hard for everybody, and specifically the larger the
organization. Yeah, it makes perfect sense.
OK, let's talk about leadership. As a leader used to work at big
pharma companies and that had other leaders there, and now
you're the leader here. What makes a great leader, and
what are some lessons you'd like to share with the audience about
leadership? So first of all, in my eyes, a
great leader always trusts and relies on the team.
I have never seen a single smart person making a better decision
than a whole group of really smart people.
As smart as the individual might be, a group of smart people
always makes better decisions. I think that is a cornerstone of
leadership. The second is that you need to
invest into your team, into mentoring, into developing your
team. We have a huge effort at Ibio.
We literally built the R&D team around 3, pretty junior, but
absolutely brilliant talents. And our job is to actually kind
of grow them into vice president C-Suite roles over time.
And yes, we do share a lot with them.
There's a strategy should be owned by the entire company, not
just by a leadership team. So they're part of devising the
strategy. They're part of devising our
messaging to the outside and by including them in the scenario
planning in how does AC Suite make decisions?
I wish somebody had opened that treasure chest for me when I got
for the first time in AC Suite. And and you know, I had to learn
the hard way, but you know, if you have smart people that
actually soak up information, why would you withhold that?
So there's a huge effort and I bio to really kind of develop
talent. And this is independent of
level. We always hire people that have
the potential to grow significantly in their careers.
And it's our job to kind of provide them with the right
folder, if you will feed the right information so that they
can actually utilize that to, to further their careers.
And if, you know, two or three of our team members go out,
start their own companies at one point because they're all
entrepreneurial thinking, then we know we've done our job well.
OK, I love that. And then let's talk about
adversity being successful. You have to handle adversity
different overcome obstacles. How do you handle adversity?
What are some obstacles you had to overcome along the way?
And anything along those lines please.
So I think you know, as a, as a small company pivoting into a
completely new area, you have to overcome the, the notion that
you know, you have no credibility, you have to
establish your credibility. And I think one of the key
points for us to be successful was that we never over promised
things, right? So if, if people can hold you to
your word, if you deliver what you say, you will deliver, that
might not initially be something where people say, oh, you could
do this faster. Of course, you know, if if all
the stars align, you can do things faster.
But being realistic about this is really important.
It's also important to be realistic about science, right?
So a lot of people just misinterpret or misrepresent,
not in a, in a negative way, not in the way that they want to,
you know, manipulate, you know, public opinion.
But sometimes we just don't know enough about the science to make
big assessments of, of how things work.
I get asked all the time, how much weight loss do you expect?
How much this do you expect? Well, if I knew I would
probably, you know, not working, I would be retired by that time.
But it's, it's really important to kind of remain true and
remain actually sticking with the facts that you have.
Yes, people ask us to speculate and, and, but it's important to
kind of mention at this point, we're speculating.
We don't have the data to support this.
So there's issues that if you overplay your hands, that can
backfire very easily. So we're always trying to remind
ourselves what our messaging is so that we're not basically
giving guidance that that we cannot support with facts.
Yeah, that's great. Thank you for that.
I take notes as people speak and I was taking a lot of notes as
you're speaking. So thank you for sharing a lot
of great stuff here. Final question for you, Doctor
Brenner, what is the best piece of advice you'd like to give the
audience or your 30 year old self?
Go into biotech, Foster. No, I think you know, what is
absolutely critical is that you love what you do.
I keep telling people I have the best job in the world.
Doesn't mean that 100% of the tasks I have to do are bringing
me pleasure, but I truly have the best job in the world.
I can interact every single day with people on a Sunday night.
I don't feel bad coming to work Monday morning.
I'm excited to come to work Monday morning everyday.
I'm not here because I have to travel a lot and can't interact
with my team. I feel a little sad because I
really enjoy working with smart people that have a goal that you
know, have the same passion that I have.
And I, I can highly encourage people if if making medicines is
your passion, it's a greatly rewarding job.
If your passion is more on the financial side, if, if money is
your main driver, don't go in biotech.
You're going to be disappointed to run a hedge fund that's
that's way more, way more conducive for your goals.
But it is a fantastic job if you can live with kind of the
setbacks. But you know, if you hit it one
time and if you make a medicine that changes people's lives,
this is all over what we're working for.
Yeah, I love it. Congrats on your success.
Thank you so much for coming on the show.
Hopefully we'll have you on again soon.
This is absolutely fantastic. Thank you so much for having me,
Adam.