Episode 55: Alex Federation- Co-Founder at Talus Bio

Embark on a quest to unravel the 'undruggable' genome with Alex Federation, Co-founder of Talus Bio. Explore challenges in targeting transcription factors in cancer with Talus's innovative Marmot platform. Discover potential breakthroughs in rare diseases and pediatric cancers, and glimpse into the future of studying transcription factors within live human cells.

First In Human is a biotech-focused podcast that interviews industry leaders and investors to learn about their journey to in-human clinical trials. Presented by Vial, a tech-enabled CRO, hosted by Simon Burns, CEO & Co-Founder. Episodes launch weekly on Tuesdays. To view the full transcript of this episode, click here.

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Chapters

• 0:06 TALIS Bio
• 14:56 BIO Podcast

Transcript

Speaker 1: 0:06

You are listening to First In Human, where we interview industry leaders and investors to learn about their journey to in-human clinical trials presented by Vile, a tech-enabled CRO hosted by Simon Burns, ceo and co-founder. Featuring special guest host Rich McCormick, evp of Clinical Strategy and Head of Oncology. In this episode we sit down with Alex Federation, co-founder of TALIS Bio. Stay tuned to learn more about TALIS' journey and their groundbreaking approach to drugging the undruggable genome using the revolutionary Marmot platform.

Speaker 2: 0:45

Hi, I'm Rich McCormick, executive Vice President of Clinical Strategy here at Vile. Joining me today on our First In Human podcast is Alex Federation co-founder of TALIS Bio. Thanks for joining us today, alex. Yeah, thanks for having me. Awesome, so we'll jump right in. Can you share use your personal journey that led you to co-founding TALIS?

Speaker 3: 1:05

Yeah for sure. So for me a lot of this goes back to my earliest training in grad schools. Talis' focus on this problem of the undruggable genome. I still remember one of the first days I trained at Harvard, walking into these big, fancy buildings they invented the field of organic chemistry. Go into class and one of the first things they say is, oh, we have all these drugable targets and then 90% of the genome is undruggable, which was stunning and hard to believe that they just had resigned so much of biology to this area that they didn't want to touch. So I was lucky enough to find a lab there where I could train, that was not afraid to go after this undruggable space, and we did some cool stuff there. And then really since then, my whole career has been trying to find the right technologies to plug in at these different parts of drug discovery to really try and tackle this problem of undruggables, and eventually that all led to what we're doing at TALIS.

Speaker 2: 2:03

Yeah, I love your company's philosophy of nothing is undruggable, so heading in that direction, can you guide us through that approach to developing those therapeutics for transcription factors?

Speaker 3: 2:13

Yeah, so transcription factors are one family of proteins that are in this undruggable space. They're some of the oldest proteins we know about. So even before we knew what DNA was, we started to learn what transcription factors were, because when they go wrong, the problems they cause are just so massive Like a fly doesn't grow its wings or a mouse doesn't grow a tail, and, as you might imagine, when these go wrong, which their jobs is? To find DNA, interpret the information in that DNA, interpret the information inside of the cell and outside of the cell and make decisions about what genes should be on or off. You might imagine that in cancer or in other diseases, when that decision making process goes wrong, it's really easy for these proteins to lead to a state where they will just tell the cells to grow and grow and grow and keep the growth gene done forever, and that's what often happens.

Speaker 3: 3:05

So the problem for these proteins is that, since their jobs are so complicated, when you take them out of the cell, out of the nucleus where the DNA is and RNA is and all of their collaborative partners, they don't fool their function properly. Most other drug targets. You can take them out of the cell, put them in a test tube and do all sorts of things to find molecules, and they still maintain their function. Transcription factors don't. So what we had to do at TALIS is bring new technologies forward that let us understand and observe how these proteins work in the natural, unmodified human cell and then use those technologies to find molecules that combine to these proteins and block their activity. So often in cancer these proteins are hyperactive for finding molecules to stop their activity, get off the genes for growth and cause these cells to either die or stop growing.

Speaker 2: 4:01

That's interesting. So then, how does TALIS bridge that gap between the high number of transcription factors and then the limited number of approved drugs?

Speaker 3: 4:12

Yeah, so you're right. So there is this huge gap. There's about 200 or so transcription factors that we have found in the field to be associated with at least one type of cancer. It's about 10 approved drugs to target those. So huge gap.

Speaker 3: 4:29

The way we approach this at TALIS is in a data-dependent, a data-driven way and also an unbiased way. So our technology uses something called proteomics. You're probably familiar with genomics, sequencing DNA in order to understand biology. My co-founder, lindsay, is really a leader in how do we do this next step? How do we sequence proteins at scale? And that's what we use at TALIS to try and bridge this gap.

Speaker 3: 4:55

So when we look at a molecule, we're actually, since we use proteomics, we sequence all the proteins. We see what that molecule does to every transcription factor in the cell. So, unlike the traditional approach where you have one target and you test many molecules, we actually can test many molecules against all the transcription factors at once to really let us rapidly iterate, discover and optimize the molecules that we find. So the sort of two-dimensional approach to drug discovery can be a lot more efficient from a discovery point of view but also a lot more challenging on the back end, because then when we have all this data, we have to use computational tools to kind of wade through it and prioritize what we're going to do next.

Speaker 2: 5:38

Interesting. So then maybe that's where you were headed. So I was going to ask about the validation process for the newly discovered TF inhibitors.

Speaker 3: 5:46

Yeah, and it's just a problem that's really top of mind right now. We just finished one of our biggest discovery efforts and have literally hundreds of molecules that all look interesting, and triaging and prioritizing how we approach that is a new problem for us. So the process right now looks a lot like what I was mentioning. So how do we use computational tools and machine learning to help essentially rank all these molecules based on all the data that we have? How potent does it hit one of these transcription factors? How selective is it? Do we see what these molecules do to every TF in the cell? So we want to start with something that's pretty specific and only modulating the TF that's contributing to the cancer growth. And there's other things too, like the actual chemistry we take into consideration, the commercial viability of these molecules going forward, how many other people are trying to work on these targets. So it's really a multifaceted approach and really leading on the computational side of it to help us make those decisions.

Speaker 2: 6:47

How does your marmit platform factor into that drug discovery?

Speaker 3: 6:52

Yeah. So the marmit is the way we think about it is essentially letting us do that first step, as well as the follow up that we were just talking about. So marmit lets us take a molecule, see what it does to all the transcription factors and then allow us to really sort of turn the crank. So when we have an initial molecule, it's still pretty far away from being a drug. But, like we mentioned before, these targets don't have structure. They're really hard to purify outside of the cell. So we really need to use these advanced technologies while we're optimizing these molecules as well, and that's what marmit lets us do. So we can take a molecule, we can synthesize all sorts of analogs, see how those changes to the molecule affect the potency of the drug, see how they affect the selectivity in the cell and other parameters that we're trying to optimize for, like pharmacokinetics and stability and other drug like properties.

Speaker 2: 7:51

So you mentioned cancer in an earlier answer. What about challenges in developing therapeutics for rare diseases like Cordoma?

Speaker 3: 7:59

Yeah, there's pros and cons to every sort of decision like this and markets can change. So the obvious con from a business point of view for a small disease is that there's a small number of patients. So it's harder to sometimes justify the investment from a venture side or from a strategic side in a rare disease like Cordoma. But, that being said, we've seen some massive successes in the rare disease space, even just in the last few months. Spring works comes to mind. They just had a drug approved in a rare desmoid tumor and there's other folks now pursuing an indication because they kind of paved the way. And that's really one of the pros for going after diseases like this is that the development path can be pretty streamlined. The resources can be pretty rich.

Speaker 3: 8:43

We are lucky to collaborate with the Cordoma Foundation, who's really not just built out a lot of support for people like us on the preclinical side to help us optimize our drugs faster, but also on the clinical side to help set us up for efficiency and success in first clinical trials for the molecules we're making. So that's the way we think about it. There's also the obvious thing that I didn't even mention, but there's really a huge unmet need and that really is what drives the decision at the end of the day. There's no approved drugs in Cordoma. Even chemotherapy is ineffective here. So it's really a disease that's managed by surgery, radiation and then waiting until the cancer inevitably recurs. So we're eager to bring these molecules forward as quickly as we can for these patients.

Speaker 2: 9:32

So how might a breakthrough with rotisserie inhibitors impact treatments beyond Cordoma, especially in other cancer types?

Speaker 3: 9:40

Yeah, that's a good point. This is an interesting transcription factor. So brachyuri is only normally expressed in very early embryonic development, so in essentially all of the tissues. In adults and children, too, anyone that's been born, brachyria is shut off. So in Cordoma in particular, when brachyria is turned on, in these particular cells that are around our spinal cord, that drives these tumors, these Cordoma tumors, and it's really the sole driver of those cancers. But that being said, if we look across many other cancers colorectal, triple negative, breast cancer, lung cancer, even some other rare cancers like ewing sarcoma brachyuri is also reactivated there and we think it's less well studied there. And it's not the sole driver but seems to really play a collaborative role in metastasis and resistance to chemotherapy. So it's something that we're starting to explore. Now that we have more advanced molecules, where is the next best place to start looking at brachyria inhibition to help other indications as well?

Speaker 2: 10:48

So you mentioned pediatric cancer in that response. I think if you have some grants that have come available to TALIS, so how do you plan to use those grants to tackle the unique challenges with childhood cancers?

Speaker 3: 11:00

Childhood cancers are really interesting.

Speaker 3: 11:02

So if you think about lung cancer non-small cell lung cancer it is often a disease associated with smoking or exposure to some carcinogens.

Speaker 3: 11:12

It's really people have decades of time being exposed to these mutagenic substances to accumulate all these mutations that eventually, once enough hits, happen and lead to cancer.

Speaker 3: 11:23

That's not the case with kids. They haven't been alive long enough to accumulate that many mutations. So really what tends to happen in pediatric cancer is that there's essentially really bad luck. They get one mutation in something like a transcription factor that can get them go and regulate the activity of thousands of genes downstream and sort of make up for the fact that they haven't had time to accumulate this genetic damage. So they get one mutation in a TF that can have widespread effects. So the way we're approaching it, the thing about this is that since these mutations are so profound and essentially they're also recurrent, they tend to happen over and over in different patients. We know what they are, so we can now go into models where we have these new mutations that happen in pediatric cancers and use the platform like Marmot to try and find molecules that are very specific at modulating these mutated forms of transcription factors, and that's a big focus of our grants is how do we do that, Especially these childhood tumors, these solid tumors where chemotherapy is not really a solution yet.

Speaker 2: 12:34

So I know we've mentioned the Marmot platform a couple times. Maybe could you just elaborate on what sets it apart from the competition and maybe what do you see as the vision for future impact of TALIS in the realm of transcription factors.

Speaker 3: 12:48

Yeah, absolutely so. The traditional approach to the undruggable space, and one that's had some success, is essentially bringing forward different methods that allow us to find molecules that stick to undruggable proteins, and in the past, some people have done this. They take these proteins. They either take them out of a cell and in vitro they still are into a test tube, or they engineered the cell in some way to allow them to study those proteins For transcription factors, though both of these approaches just inherently stop the transcription factor from being able to do its job and being able to be in the right confirmation, in the right shape to do its job, and, as a result, the molecules that you'll have found using these traditional approaches have just tended to be ineffective.

Speaker 3: 13:38

They're binding to an irrelevant confirmation of the protein.

Speaker 3: 13:42

So what we do instead, and really the fundamental hypothesis of what we do, is that we really need to be discovering these molecules in the most native system that we can.

Speaker 3: 13:53

So unmodified life, human cells and that's really the differentiating factor, for Marmot is bringing new technology to the earliest age of drug discovery. To let us do that, and we've been mostly focused during this conversation on discovering molecules. But if we take a step back and one thing that we're starting to look at more now is we can use these technologies to really measure any sort of changes in the transcription factor at proteome or the transcription factor activity in human cells. There's a lot of interest and activity now in cellular reprogramming or tools to try and slow aging. These are all phenotypes, these are all things that are driven by expressing new transcription factors. Same with cell therapy Can we figure out new transcription factors to help us manipulate cells to have new behaviors that we want as clinicians, as biologists, and tools like this can really help us understand what's going on under the hood in those sorts of applications as well.

Speaker 2: 14:55

That's great. So, Alex, it's been a pleasure meeting with you today and thank you for being a guest on BIO's first in human podcasts. The team here at BIO wishes you and your team at TALIS BIO nothing but future success.

Speaker 3: 15:08

Yeah, thanks so much for having us and being interested in our science.

Speaker 1: 15:19

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