Speaker 1:

From the New York Stock Exchange at the corner of Wall and Broad Streets in New York City. Welcome Inside the ICE House, our podcast from Intercontinental Exchange is your go-to for the latest on markets, leadership, vision, and business. For over 230 years, the NYSE has been the beating heart of global growth. Each week, we bring you inspiring stories of innovators, job creators, and the movers and shakers of capitalism here at the NYSE and ICE's exchanges around the world. Now, let's go inside the ICE House. Here's your host Lance Glenn.

Lance Glinn:

Breakthrough medicines aren't just discovered, they're engineered with precision. Thanks to advances in computational power and molecular modeling, scientists can now design small molecules that strike at the heart of disease. This next-gen approach is reshaping treatment and offering the potential of higher efficacy. It's drug development that's faster, smarter, and deeply personal. Nimbus Therapeutics is a leader in precision small-molecule design using advanced computational chemistry to craft therapies that target disease with exceptional specificity. Their structure-based approach allows for rapid iteration and optimization, dramatically accelerating the path from discovery to development. Our guest today, Abbas Kazimi, has been CEO since March of this year. And while his tenure is young, he's already positioning Nimbus for great growth in the years ahead. Abbas, thanks so much for joining us Inside the ICE House.

Abbas Kazimi:

Great. Thank you for having me.

Lance Glinn:

So I want to start with just a brief overview of Nimbus. How would you just describe the company in broad strokes and what do you see as the core problem you and your team are trying to solve in the biotech world today?

Abbas Kazimi:

Now, thank you again for having us. As a privately held biotech company, rare to come down to the stock exchange, so great to be here. I would describe Nimbus honestly as a 16-year-old biotech case study. We were formulated 2009 out of the financial crisis of how do you get a more capital-efficient biotech? And it was built on multiple theses. One was purely in silico drug discovery, meaning taking all these computational chemistry tools that existed and really putting them to use. And so Atlas Ventures and Schrodinger, which is as down the street here, had that idea, incepted it, and put it together. The other hypothesis was can you create a more virtual organization? So we're 85 people at max. Today, after 16 years, you would probably come to our offices and it feels like over 150, 200 because we've globalized CRO usage. And that was really taking off in that 2009 timeframe.

And then the third piece is probably more well known about Nimbus, is our business model. Kind of this build an asset, get to a value inflection, exit, return capital, recycle, raise money, and do it again. So for us, the challenge was always not really thinking about can we go after novelty and novel targets? I think there's really big challenges, even till today on validating new biology for us was can we use some of these computational tools and really advance the ability to get differentiated chemical assets. So going after programs that are fairly well known, but overcoming those chemical challenges, finding a differentiation pathway, and developing that asset and taking it forward.

So it's been, I would say, various forms of success are measured. I think one way that we look at it is we've put four molecules into the clinic. All molecules are active today. And for us, that's probably the hallmark of success I would say. What we did in 16 years was really refine and perfect what we think are gaps, what we're doing now, it's being pragmatic as we've always been. So integrating all these tools and we'll talk about it, I'm sure about AI and where that has fit in for Nimbus. But now I see the next couple years being more accelerating. So if it was four molecules over 15 years, we're already projecting we'll have three first in humans over the next three years. And that's just a scale of just more efficiency and then thinking through how to overcome limitations.

Lance Glinn:

So it's been a little bit over a decade and a half and you speak to that business structure. We're going to talk about that a little bit later in our conversation. But what I see that differentiates Nimbus from traditional biotech firms is how it blends that cutting edge science with that innovative business structure. So you stepped into the CEO role relatively recently, but you spent a few years within the company in various leadership positions leading up to it. So from your vantage point, how has the company transformed and really its vision evolved since you joined in 2014?

Abbas Kazimi:

When I joined, I think the business model even then was still very early, meaning the belief was get early chemical matter. The tools that we have can really dissect and say, "Hey, we have novel chemical compounds," and then exit those assets. When I joined in 2014 and the previous CEO around the same time he came from GSK, really successful career. Both of us were kind of wondering how sustainable really is this model in terms of actually creating a lot more value? So what we started seeing was an evolution in terms of let's take these assets a bit further and I think getting more conviction from investors.

I ran business development in the CBO role, corporate development strategy, and it's not a process at Nimbus, it's been an evergreen style. We're always talking about our assets. And so what I've seen evolve, it's taking one probably deeper conviction on certain targets. We take those programs much further into the clinic. Equally, and I think this is probably still a big gap that a lot of my colleagues and I talk about, but as a privately held company, we can talk about this pretty publicly, we take a lot of attrition. And I would say in my over a decade here, we're probably averaging around 70% attrition. We celebrate that. Creating a culture to celebrate that was a challenge, but I'm going to continue perpetuating that. Killing a program is probably the most fastest way to get investors to reward you by double downing on the winners. And I think that's something that with tools that are coming around, we're going to take a look at those tools, but one aspect of those tools is actually how to make a decision and kill a program.

So that evolution, it takes time, it takes building the right people, the right mentality. It takes pure entrepreneurship, figuring out, wow, I have a PhD scientific team that's gone deep on a certain program. But to ask them to lead the question of should we keep investing different value ownership? And so every employee at Nimbus is an owner. I mean, you have individuals who are going to recommend programs that will shape the future of the company in four or five years.

And that just speaks to the third piece of just culture. We've really created this culture that has every scientist feeling like they're part of the future and I would say you've never had one individual, be it a C-level suite executive or a CEO saying, "We're going to work on this program." It's always come from bottom up. And I think from a business model, from a being pragmatic on how to kill programs and creating a culture, I think those three pillars are probably the most important for us. And I would say they continue to evolve, but we continue to really hold those true and let everything else come to place.

Lance Glinn:

So you mentioned the 70% attrition, and you talk about how there are these tools now that help you make decisions, and we can't talk about these tools without first mentioning AI. I'm sure that's probably the main tool or one of the main tools that not only companies in biotech or in pharmaceuticals or in really any industry are using, but it's a buzzword that's just taking over the business world as a whole. So starting just big picture here broadly, from your vantage point, what's the most meaningful change in the industry that AI has caused that you've seen? How is it really influencing so far? Again, still not a new technology, but it's being used in new ways over the last few years. How are you seeing it change biotech as a whole?

Abbas Kazimi:

Yeah. Look, I think we're somewhere, to your point, we're kind of in the messy middle, this adoption curve. I think everyone's trying to figure out where are we? I think last year or two years ago, the question was hype versus reality. I think today we're all going to talk about it's reality, things have changed. From our vantage point, there's some phenomenal tools. I think it's acceleration. And when I say acceleration, I'm be really clear. It's not about speed of moving a drug from six years to two years. It's an acceleration to actually go into more challenging spaces. And I think you said it really well, these are tools. And for us, we cannot be behind the curve. I think it's healthy to be a skeptic. And when I say a skeptic, not a skeptic of is AI a buzzword or AI is not a buzzword. It's a skeptic of saying, "Where can some of these tools really integrate?"

And so for us, it's always been computational chemistry. That's the foundation. Within computational chemistry. For us, it's always about can we elucidate structures, for example, and structure-based drug design? Where AI comes into play for us already in one aspect is more generative AI. Can we actually learn more about these protein structures? Can we inform the medicinal chemists on what are better routes to synthesis? What chemical matter can we further explore? So we're already integrating. I think if you take a more rudimentary conversation around it, pharma produces and biotechs produce thousands of patents on a monthly, yearly basis. An individual PhD JD can go through one or so of those patents in about 10 to 15 minutes. It'll have a cost associated with it. We've built out tools that can actually analyze those patents, look at the chemical matter, look for differentiation within seconds, and the cost goes down.

So I think we're at a point where it's still a tool. I think we're at a point where we're integrating those tools much more in depth. If you talk to colleagues within Nimbus who've been around for decades, computational chemists and medicinal chemists were always separated. I think today you'll physically see it in our offices. They're sitting next to each other. And so you're having one way, a predictive tool to help inform the medicinal chemist on which compound to take forward. Why the skeptic of us occurs? I think you still need the individuals to make decisions, right?

Lance Glinn:

It's that balance. Yeah.

Abbas Kazimi:

It's that balance, right? We're able to optimize potency, we're able to optimize selectivity, but when it comes down to certain questions of do you want a QD dose? Do you want a BID dose? Do you talk about indications? Do you talk about stratification and strategy? Individuals can make those conversations happen of do we kill this program? I think that goes back to my first point. I don't know if these tools are unable to say, "Stop this program." If these tools are going to say, you might be at a multiple factorial component of saying patent competition, clinical differentiation would say, no, I would believe the tools today want to continue giving you an answer that's going to say, "We'll find a way forward." So again, is it an engineering problem that we overcome with time? Sure. I think at the end of the day, for us, it goes back to as a small molecule player, fundamental biology. So we're going to watch generative AI, we're going to integrate it, but to elucidate these new biology pathways, that's a big challenge.

Lance Glinn:

Yeah, absolutely. And you mentioned the word acceleration earlier in your answer, and I think that's sort of the big hope when it comes to AI and biotech and pharma is can it accelerate something like drug discovery or drug development or molecule discovery, so on and so forth? I think the hope is that it could bring something that normally takes years and at the very least, shave six months off of it, 12 months off of it, 18 months off of it, so that we can get these molecules and these drugs to patients faster and obviously ultimately save more lives. How realistic do you think that is right now, and what do you think may stand in the way of realizing it at scale?

Abbas Kazimi:

I'll be honest with you, I don't think we look at time as the most important factor. So in one way, if you do a quick analysis, even if you go from six years to two years, what have you really saved? Time and money. But if that quality of that compound isn't great, and now you're investing a hundred, $200 million, you get to a phase 2B or phase three and you fail, you saved maybe a couple years, but the cost that you've lost, and now if you put time in there as well, you've taken a lot of investment to go forward. So I don't think the conversation for us within Nimbus's walls is around can we go from six years to two years? I think honestly, the way we're using AI tools is can we go after harder targets, the challenging ones?

So our president of R&D, he comes from a very simplistic conversation, but a really impactful one to say, Let's look at what we've done with KRAS, what Amgen and Mirati have achieved. That was fundamental drug discovery. 10 years, 12 years, we couldn't get there. And fundamental drug discovery, even though it took years to get there, you'd have a breakthrough drug. You look at now the ability to the chimeras of the world and others who are looking at stat six, that's another breakthrough. So I do believe time will be a factor. I unfortunately, on the skeptic side of me says, when you're pitching to certain investors or pharma partners, they're going to diligence you less about your timeline and more about the quality of the product and the asset that they want to take forward.

Lance Glinn:

So as these AI tools do become more advanced, I think there's a belief that platforms could one day suggest new targets, design new molecules, even propose entire therapeutic programs. So do you envision a future where AI has a seat at the strategic table or has a strategic seat at the table actually helping shape the direction of not only Nimbus, but just biotech as a whole?

Abbas Kazimi:

Absolutely. I think we're already there. I think the novelty that it is able to actually help in terms of discovering. Now, then you go down to a more philosophical question, discovering a novel target that may not be in our business model. I think there are a few that need to spend time. I think right now, if you look at the space, the challenges biotech is going through, there's a lot of noise. AI has been able to synthesize so many compounds against so many targets, but how many of those are actually validated? And I think that is going to be a question of are those actual breakthroughs?

I think the way I look at it, candidly, it's someone would argue, "Well, if we had AI implemented, maybe we wouldn't have waited 10 to 12 years for GLIP1s to really emerge the way they've emerged." I don't think that is how we look at it. We look at it from a perspective of you need patient capital, a little bit more investment. So my fear is that we're at a point where we're dismissing novel ideas too quickly. My hope is that with all these different multi-channel processing tools of AI to actually give you more confidence of this target or this pathway is worth investing. So rather than dismissing it early, you have more information on why you can go forward. And I think internally, we see this now.

So a big part of our culture is this new target jamboree that's been Nimbus's evergreen list of how do you survive for 16 years? For us, the first sin is always target selection. AI has fundamentally advanced how quickly now at this point, we're looking at these new targets, how quickly we can actually get more input. So a couple of years ago it was more about can we get a structure up and running? Are there chemical ligands? Now we're doing multi parameters of patent escape, patent landscape, competitive landscape. How do we actually incorporate that? And so we're actually able to look at more targets on a faster basis and kill those.

To your question, there will be a space at the table for individual companies to say, "How can we novelize or find new targets?" We need that in their industry. I think patients still need novel breakthroughs, and I would hope that that seat at the table is approached appropriately. I think right now we're dealing with a lot of hype, and I think individuals are placing AI kind of in a revolutionary perspective. I think our view is it's a natural evolution that you need to integrate intelligently.

Lance Glinn:

So you bring up a lot this idea of killing programs and noticing and making a decision on what to continue to pursue, what not to continue to pursue. Now Nimbus, and I want to ask you more about it, this fail fast strategy, admittedly can sound sort of counterintuitive when you hear it. When you think of drug development, you think of longer timelines, you think of perseverance. But what does fail fast really mean at Nimbus and why has it become such a cornerstone of your business model?

Abbas Kazimi:

Yeah. I've come into this role even before this role with a big balance between conviction and discipline, and it's a really narrow line to walk on. You have to have the conviction on a target. You have to fundamentally believe we're going to change the course of medical practice for a patient segment, for a therapeutic area, but you also have to be careful of not chasing false positives. And what is a false positive? False positives could be we have an early signal in one patient, kind of like a biotech curse. And now you're going to spend money and time and keep going because we have changed an individual's life. The question becomes was that a one-off case? How fast can you go? How much longer should you go? And that is where I think the false positives happen. You have a lot of companies that can really speak about chasing that false positive and capital gets burned. And that's why I think right now investors are healthy skeptics of how much conviction do you have, but do you have the right discipline?

Before a clinical program, same concept. Great target in our hands, we look at the landscape. If I can't get to a proof of concept in an intelligent way, if I look at lupus, lupus patients deserve better medication. Is Nimbus the right one is the first question, right? There's a huge graveyard of failed drugs. Phase II will be very expensive. These patients are highly immunosuppressed, it's a heterogeneous disease, regulatory still needs to be worked out. Within our budget, within our focus and landscape that might not be the right program. So we might have early chemical matter, but as the teams get sharper about what's the clinical path to success, we'll pause that program.

We did this a couple of years ago. We had a program for AMPK, 30-year target, Merck, Pfizer multiples had gone after it. No one was really able to get AMPK beta or any isoform activators. We worked on it. We actually had activators in our hands. The landscape had changed. We were going after NASH. NASH had some challenges. Going after a cardiometabolic trial would've been really expensive. So you know what? We decided that even though we have the only activators in the industry, let's park this program. A few years later at a conference, met some friends, colleagues from Eli Lilly, talked about that program, talked about the clinical challenges for Nimbus, not the chemical challenge. We'll get there. And we did a deal with them in 2022. And that deal was to enable Nimbus to finish out the chemistry, get to a clinical candidate. I can't speak more about it, it's in their hands now, but a clear example of what we knew we could do well. Get that clinical program to an asset and now they can run with this forward, broaden their franchise.

So a smart play from a BD perspective, a smart play from a internal portfolio management perspective. And I hope what we're all learning, and again, I think about Nimbus, it's a 16 years of a case study, as I call it, because we're always being pragmatic. Now, pausing that program allowed us to also allocate resources to a few other winners, and I think that's why our pipeline doesn't look that big. I don't think it should look that big either, because I can actually truly now go to investors and talk about the one, two, or three liquidation assets that's going to change not just our cap table and balance sheet, but it's actually going to impact an industry and a patient, but yet also have an evergreen list in the background. I think that's hard for people to achieve that. To your point, it goes back to fundamentals, conviction. You got to have belief or you have to have discipline to say, "When have we gone too far? When should we actually stop and put resources somewhere else?"

Lance Glinn:

So as we begin to wrap up a conversation and you look ahead now to the short-term future for Nimbus, the next couple years from a scientific, strategic, even cultural perspective, what do you think will really define the company's next chapter?

Abbas Kazimi:

I think we're going back to fundamentals. I think this is a very humble period we're going through for the past three years, past two and a half, three years, you've seen a lot of companies give a lot of over-hype, over-hope. I think investors are cautiously sitting on the sidelines and letting companies unfortunately close doors, the ones that aren't able to deliver, ones that aren't able to actually fulfill that promise. I do get worried because within those, there's some great, great science, great assets, and most importantly for us great scientists. And I think that's going to be probably the most foundational component for Nimbus. We always start off with talent. At the end of the day, even I talk about AI and ML, I think the most powerful teams within Nimbus are our head of computational chemistry and structural biology paired with our medicinal chemists.

So what I hope the next five years is we continue cultivating talent, we continue challenging ourselves on keeping this conviction and discipline balance. We equally see other companies find that right cadence on, know who you are, know what you're good at. And I think there's been a lot of chasing. At one point, we could have easily thrown our hat in the ring and said, "We're going to go after a small molecule GLIP1." That wasn't the smartest move for us. I think others can do it well. I was trying to predict where do we want to be in five years? What's going to happen when most patients are on GLIP1s and they're losing both fat and muscle? Can we look for assets that's going to actually preserve muscle and yet still have an impact on weight loss?

And so we're trying to be a little bit sharper with all the industry information that we have. I think for now, I want to keep on building this culture of great science first, use the right tools when we need them, and still think about the winners. And so I'm proud of our portfolio today, it's trimmed. I think we're being a little bit more cautious about how much we're disclosing publicly given a lot of global challenges in terms of competition. But again, as a privately held company, our audiences come down to the investors that back us, the partners who are going to take our assets forward and ultimately the patients we really want to serve.

Lance Glinn:

So to wrap everything up, just when you think about long-term success for Nimbus, what does that look like for you personally? Not just in terms of obviously your bottom line, your top dollar. When it comes to drug approvals, valuation and how the company influences the biotech industry, the scientific community, and ultimately patient populations, what does success look like for you?

Abbas Kazimi:

Great question. On many spectrums, Nimbus has achieved success. People defined it by the amount of dollars we've raised, the amount of dollars we've returned back to investors. If you ask almost every employee at Nimbus who's celebrated in all that success over the years, their defining moment has been each time we hang a banner about a new IND, it's been approved. I think the calls that we get from clinical sites about a patient's family that's A, decided to take our drug as a trial basis and more importantly, to be able to hear about an endometrial cancer patient who was given a diagnosis and all of a sudden his back of the gym and fundamentally re-enjoying life. I would say our success comes down to the molecules.

So that I think we're pretty authentic about internally, we all share about, everyone has a story with a disease. I think we're pretty open about, and I have voiced that a lot. I come from a lot of medical challenges in my family. I'm open about sharing those, about cancer, how it's played a big role in my own influence, and yet how critical it means to me that I want to talk about individuals on a basis. These side effect profiles, if you see it in your own family, you actually appreciate them in a different way. So for us, success ultimately is going to be these molecules making it forward. Business will happen along the way. I think all of our pharma colleagues, that's what they appreciate about us, the candidness about how eyes-open we are about why we're doing what we're doing, and ultimately delivering for them a molecule that they're going to be better at putting into patients' and prescribers' hands.

Lance Glinn:

Well, Abbas, we appreciate all you're doing, all the science you're doing, and we thank you so much for joining us Inside the ICE House.

Abbas Kazimi:

Again, thank you so much for having me. Appreciate it.

Speaker 1:

That's our conversation for this week. Remember to rate, review and subscribe wherever you listen and follow us on X at ICE House Podcast. From the New York Stock Exchange, we'll talk to you again next week Inside the ICE House.

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