Alan 00:10
Welcome to Healthcare Insights by KYBORA. Today I’m very happy to host my good friend David Apelian, who is the CEO of a company called Theolytics. I met David a couple years ago, I think almost when he was the CEO of a company called Eiger BioPharmaceuticals, where we did a little bit of work together. And I thought it would be great to invite him to talk about his background, but also since he’s a serial biotech CEO, to ask him more question about what it’s like to be a biotech CEO. So David, welcome to the podcast. It’s great to have you. As I said, you know, we’d love to learn a little bit more about you. So if you could start by telling us a little bit about who you are and history.
David 00:54
I, I started my career in science as a PhD scientist in molecular biology. I trained at Rutgers University and kind of early on, I, I got the itch to, to transition to a more clinically focused career. I kind of knew that as much as I enjoyed molecular biology and experimentation, that I wanted to move my career more towards a healthcare patient focused direction. And I could see some of my colleagues that were struggling to get academic positions in pure science. And it’s kind of a monastic life. I mean, you can make great discoveries and it’s very challenging intellectually, but it’s not the same as when you can directly help people. And I kind of sense that.
So instead of doing a postdoctoral fellowship and and getting an academic position in science, I ended up going to medical school. And I think it was one of the best decisions I ever made it it really gave me a way to leverage my scientific aptitudes towards patient care and patient focused endeavors. And I ended up going to UMDNJ, which is University of Medicine and Dentistry of New Jersey, which I believe now is part of the Rutgers system. And I actually did my residency at Columbia Presbyterian New York Hospital on the Upper East Side and, and trained in Pediatrics and was really close to doing a pediatric heme-onc fellowship at Memorial Sloan Kettering, but decided to make the leap right into industry.
And I thought it was a great way to combine science and medicine in pharma. And you know, I was really fortunate to land in some really good groups and big pharma to start, kind of cut my teeth and learn the trade. And I started out on the in the hepatitis C group at Schering-Plough in the late 90s during the race between Schering and Roche for the hepatitis C interferon based therapy. So it was a great place to learn development and learn business environment and the, you know, the pharma matrix team set up and learn development and regulatory fairs and all those things. And after leading the pediatric Rebetron sNDA for Schering, went to BMS and Co chaired and and was the medical lead on the Baraclude program.
And that was my first taste, I think of a program level responsibility with a big matrix team, you know, like 35 people. And it’s funny. And back in those days as a senior director in clinical, you didn’t have any direct reports. But I was running a big team of people from six different functions. And in a way, it taught me how to really manage people and lead people without explicit authority. So you had to motivate people and inspire them. And I think those soft skills have helped me a lot as I advanced my career to learn how to lead and motivate people. And then when you actually have the direct reporting authority with people, it, it makes it a little easier, but still it, it teaches you the importance of the soft skills and how to inspire people and lead people in a different way.
So I’ve always valued that experience at, at BMS and it was great programming. Baraclude was a great drug. I was really fortunate to work on that. And you know, so I learned a lot of great lessons in development and Reg affairs and had to run a big program. And then I took that and entered the biotech startup world and been taking on either cheap medical roles or now CEO roles, my third CEO role of Theolytics.
Alan 03:54
What what made you decide to go from big pharma to to biotech?
David 03:59
I think it was the desire to be in a more agile environment as as much as I enjoyed the experience in big pharma and it was a great place to learn early in my career. I mean, it is a pretty big bureaucratic system and there’s a lot of committee levels of decision making is very regimented, at least it was in those days. And the speed at which we can make decisions and move was a bit frustrating at times. And advancing your career to the areas that you had interest in was often gated in a way in a big organization like that, that was very kind of departmentalized. And so I just kind of knew I would have more opportunities if I enter the startup environment.
Of course, there’s more risk, but it was worth to me, it was worth the risk to to make the leap into the smaller and more entrepreneurial environment. And I’ve been in that space now for better part of 20 years now.
Alan 04:46
And So what was the the first company that you joined after Big Pharma?
David 04:52
I joined GlobeImmune, which was one of the really early cancer vaccine companies or therapeutic vaccine companies back in 2004. And this is back in the day when people thought we were crazy for thinking that the immune system could treat cancer. So, well, you know, I think back in, you know, we know a lot. Just think the wrong the wrong. The wrong generation. But you know, now that we understand checkpoint inhibition and the tumor microenvironment and all these things in a different way, I think we would have had more success if we had appreciated the complexity of that. But the idea was, hey, take the immune system from the patient and and enable that to fight the cancer.
Early on, even as a scientist, like I kind of was drawn to this idea of complexity theory. You know, the most challenging diseases are the most complex and cancer represents to me the most complex adaptable disease there is. The emperor of all maladies, as was actually coined in in a book a few years ago. But so to combat diseases like that, I kind of intuitively knew we had to create complex adaptable treatments to combat something as adaptable as cancer. And I think chronic hepatitis kind of falls in that space, high burden, you know, like hepatitis C, for example, kind of behaves like a cancer because there’s so much diversity. There’s so many quasi species that evolve when you try to treat a disease like chronic hepatitis C.
That’s why I learned a lot of valuable lessons about disease evasion and treatment and combination therapy and how we approached chronic hepatitis C. And hepatitis B taught me a lot of valuable lessons about oncology. And it’s amazing now like 25 years later, after being in grad school and thinking about complexity theory and how we can treat these diseases, we’re in fact using complex adoptable therapeutics, you know, autologous engineered T cells, immune checkpoint as a way of leveraging the immune system by taking the brakes off it. So the whole idea of leveraging immune system, using viruses to treat cancer, I mean, these are things that sounded like science fiction 20 years ago and now we’re actually doing it.
And I do think this is the level of therapeutic that can actually cure cancers. I mean, I say cancers 1 by 1 because it’s really a multitude of diseases. But I do think we’re going to get to the point where we can start really getting some big wins in the field of immune oncology.
Alan 07:11
Interesting, since you’re working on cancer virus or virus to treat cancer, you know, that’s an area though that became hot and then became very cold and it’s kind of coming back a little bit. So what what are your thoughts? Is it because the immuno oncology, PDL one, PD one were so successful that nobody wanted really invest in this space? Or was it that the technology at the time wasn’t developed enough to really be effective?
David 07:41
I think it’s probably a combination of those things. But you know, when you think about the early oncolytic virus programs they were using like the standard strains, they weren’t really being developed and like discovered and selected like we would do for drug discovery or for other kinds of therapeutics. I think that’s one of the limitations. And then, you know, oftentimes they were being infused IV in the early days and they were just being neutralized immediately. And so we weren’t really probably delivering those viruses the way that people thought they were. So I think there’s an appreciation for how to better develop and utilize these oncolytic viruses and for example, theolytics, the main thing we’re doing differently.
And the team from Oxford and you know, Margaret Duffy and the She’s CSO and one of the founders, they took the 50 standard adenoviral strains and diversified it to 100 million variants. So through systematic mutation and recombination, they developed this massive, massively diverse library. Now when we interrogate that library against patient tumors, you can then select really unique variants that have features that you could never design top down. You just have to it’s a Darwinian process that allowed us, for example, to say like the variant that’s got features that are pretty striking. Not only does it affect the cancer cells that we tested it on a primarily ovarian cancer, but also killed some CAFs, the cancer associated fibroblasts, which is a unique and distinct feature and it’s amenable to IV infusion because those were the features that were selected for.
So here I think, you know as an example, theolytics is taking oncolytic viruses to a whole nother level of rigorous discovery and selection and drug development that in the past people were just using the kind of the garden variety strains of virus that were in the labs and didn’t really do any effort to diversify them. I really select them. know,
Alan 09:29
you, you mentioned the autologous nature of you know, some of the work that is being done, the car T and cell therapy and things like that. Do you foresee a similar kind of process like it called and like treatment process using oncolytic viruses and you know, using the different variants to making sure that you’ve got the best solution for a specific patient or how do you see that evolving?
David 09:56
That’s also really neat because the oncolytic viruses work not so much based on a target selection in terms of receptors on the cancer or highly specific or personalized features of the cancer. So it doesn’t require personalized approach in the way that some of those other approaches do. What it selects for is the malignant phenotype. So the cancer, by being a cancer and being promiscuous and being able to invade and and to break the rules so to speak of the normal biology of the body, that also makes it permissive to viral infection. So we can actually select viruses that are attenuated and wouldn’t have any real risk of infecting a normal cell.
But now the cancer is vulnerable to that. It’s really selecting for the deranged phenotype of the cancer and not doesn’t require a personalized level of selection like you would with neo epitopes and the really refined ways of targeting T cells, for example, which is what I was also working on that BlueSphere Bio we were doing TCR-engineered T cells, which is highly personalized. What I think is exciting about an approach like what we’re doing at Theolytics is that it’s targeted because it’s targeting the malignant phenotype of the cancer. We also have selected the ability to kill the TME component, the CAFs or the cancer associated fibroblasts, which as we now know create a huge barrier and create a big problem for most therapeutics in terms of treating solid tumors.
So that’s a unique feature we were able to select and it’s really scalable, so. I think, you know, there’s a recognition that the personalized autologous cell therapies can be highly effective and select indications, but it’s not very scalable, it’s fairly expensive and the vein-to-vein time and all these other challenges are there. So I think we have to start as an industry moving to scalable practical approaches. And and this is one of the examples of antibodies are a great example of a scalable approach bispecifics, much more scalable than autologous cells. If we can ever get to an allogeneic solution for some of these cellular approaches, that would be a huge breakthrough, right, Because then they could be mass produced off the shelf.
So I think that’s another consideration that’s going to require some very good thinking and drug development and manufacturing expertise.
Alan 12:05
Now that’s super interesting because to your point, I think it’s a certainly, I would argue even within a developed world, those therapies are, are very expensive and not always, you know, readily available to patients. And it’s almost you use them in the last resort. And then when you go to the developing world, then they’re almost not present at all, right? It’s just too expensive. Only the rich people who can then fly to Europe or to the US and get the treatment to get them. And so if you can have a solution that can be produced at a larger scale, then hopefully you can kind of make it available to more patients around the world. And so that’s exciting.
David 12:48
It’s personalization. That’s cost and expense and time, Yeah. And the need for an autologous cell just by its definition requires intensive. It’s like you’re doing a manufacturing run for each single patient. So right, yeah, it’s the personalization, but also the unity manufacturer of a unified single product for a single patient just inherently makes the scale. Yeah, incredibly challenging. Yeah. know,
Alan 13:13
in my prior podcast with various people, I always ask them this question related to how the advent of what you can call medicine precision if you want, or individual medicine could potentially impact what the industry end up looking like. You know, do you end up with a series of smaller biotech that deliver value for a narrow set of patients instead of, you know, very large multinational as you have them today? Because it becomes kind of difficult for a very large organization to target a narrow segment of the population. And that’s that’s why you’re seeing. So for instance, in the ultra rare disease, big pharma is not interested. You know, it’s like, OK, what is going to make $200 million?
I’m not interested. You know, I need a 1 to $5 billion product before I can really start to pay attention, right? Because the scale of the operation that I have requires you to develop very large products, right. So if we’re going towards more individualized medicine, then how does that meet the large pharma business model?
David 14:22
I mean, I think there might be some segmentation where the therapeutic approach for a given indication, if it requires personalization and if it requires that level of precision may not fit the model of a bigger company that’s trying to hit a certain target of, you know, scope and scale. And that’s OK. I guess you know that that will always be served by, I think by by really good scientists and really developers that want to still advance that for either a rare disease or a small indication in cancer, high unmet need. And you can justify the resources that go into that. I think there’s always going to be translation of those initially personalized approaches and non scalable approaches to another version that from the learnings of those approaches become scalable.
I think an example of that will be if we can get to allogeneic engineered T cells like so taking what we’ve learned from the CAR-Ts and from like from other approaches and then saying, OK, it’s not scalable enough, but here are the few things that we could figure out would make us scalable. And then this is next generation of treatments that become more widely available, more cost effective. I think the the bispecifics are kind of another example of that. You know, there are examples of TCR bispecific. So instead of making autologous T cell, you can make a bispecific or one end there’s a TCR and one end there’s a isic antibody and that is much more scalable and much more affordable than an autologous T cell.
So I think we’re always going to see these evolutions of things. You know, those initial treatments are, you know the ones that are the first ones out that break make the breakthrough. Yes, they’re probably not as scalable and they’re probably more expensive, but they will eventually. These findings do lead to improvements and more scalable solutions for broader categories of indications.
Alan 16:02
It’s interesting, I think because you know, I remember talking to someone who was pretty high up at GSK and what she was telling me about the portfolio of big pharma is that because of the the scale of their operation, they need products that really make a different. So what they’re looking for are almost product platform or you know, like to take the example of a PD one, this is becoming the base of any cancer treatment, right? So you can add a bunch of things, but everybody’s getting a PD1A PDL one, right? I mean, so that’s becoming the new chemotherapy if you want, right? That’s the kind of product that you want that is going to be used in any cases almost.
So you stopped by Eiger as well. And so this was more in the hepatitis virology type of organization, right?
David 16:52
Yeah. I mean, Eiger, the lead program was the hepatitis D program, but there was also an interesting rare diseases. And so I think one of the really interesting programs there was the Progeria program that actually evolved from the same therapeutic that was being used in HDV. The whole progeria story with the Progeria Research Foundation is kind of inspirational one. I mean, Leslie Gordon, she was in physician at Mass General, her husband Scott Berns as well. When they realized their son was born and diagnosed with progeria, they basically stopped everything and set the Progeria Research Foundation. And it’s truly inspiring when you see how apparent the motivation of a parent, you know, could lead to identifying the point mutation that causes progeria in a few years.
And then they find lonafarnib, which is what we were using to treat HDV, but they figured out that that should work because it’s a farnesylation aberration in progeria that causes the disease. So lonafarnib, which was developed as a Ras therapeutic by I think Merck back it’s an antique, you know, farnesyltransferase agent. They tried to use it in these kids and they did a investigator sponsored trial and showed that it extended their lives. They published it in JAMA and then Eiger collaborated and cooperated with the PRF because we were developing the drug for HDV and we had all the manufacturing set up and we have the infrastructure to do it.
So we partnered with them and got it approved. That’s the like the rarest, I think maybe one of the most rare diseases in the world. 400 kids worldwide are believed to have this. And now, right now the survival advantage with Zokinvy, which is the, the product is 4 years and counting. And the more we treat the kids, the longer we watch the kids, the better they do. And so at Eiger we had the Hep D program, which was a rare disease, but on a bigger scale, probably a couple 100,000 in the US, but other ultra rare diseases and other rare disease programs as well. Yeah,
Alan 18:44
Now I remember that. And it’s interesting because you got a PRV for this as well, right?
David 18:51
We. Did yeah, we shared that with PRF. It was it was just one of those like win, win situations. And you know, in the end we ended up selling the asset, you know, Sentynl. And so it’s in the hands of another entity that can provide the infrastructure and provide the drug. I mean, it’s hard for a foundation to find a way to manufacture a drug in long term setting for these kids to have access to the drug. So it was recognized that by collaborating and cooperating and getting it approved and generating some revenue from the product, it would give these kids a much better chance of having this for many years to come and future kids with Progeria will have access to the drug.
Yeah, that’s great.
Alan 19:30
Switching towards a, you know, a little bit talking about what is happening right now in the industry. You’ve been a CEO for what, 10 years now? Maybe more? Yeah, it’s about 17 years, I guess. And so you’ve seen the, the, the recent evolution around funding environment and certainly the latest data is does not look great, right. I mean, I think even VC’s are having trouble and the smaller funds have difficulties raising more capital. What are your thoughts on, you know, where we are in the industry and and potentially why you we are here today? What’s what’s happening?
David 20:11
Yeah, it’s a, it’s a challenging environment, probably the longest I’ve in duration in terms of facing these challenges in the 25 years I’ve been in the industry. You know, even in the past year or two you’re seeing that most of the financings are the majority are inside bridging rounds. There’s very few syndicated rounds with meaningful influx of new capital happening right now, very few IPOs. It’s super challenging in terms of the traditional ways of private companies getting funded. There’s intense pressure on public biotech companies too in terms of meeting expectations and and what it would take to have a positive readout in a clinical program that bar has gotten really high in I would say the private and public side.
So it’s just a super tough environment. I think as CEO I really look to like building a really strong relationship with the syndication. We have to to make sure we have, you know, really a lot good alignment with our current board and our current investors and looking creatively at other sources of funding, whether it’s grant money that we could pick up to advance the program to a meaningful inflection point. Looking at partnering, you know, maybe earlier than you might have, which is challenging, right. But that bar’s pretty high too in terms of what will drive a partnership. So it puts a lot of pressure on us as CEOs to be focused, do really good science so that your early clinical readouts are as supported as possible by good science and understanding the biological mechanism of action, the the proof of concept you’re trying to demonstrate with that Phase 1 result or Phase 2A result or so on.
So we look at it that way like we need to really deliver really high value quickly with good science that will translate well to partnering, translate well to investors and that looks all the way ahead to the commercial opportunity that it represents. And that’s that’s kind of a high bar early like when you’re normally just doing safety studies in phase one. Well, we’re finding creative ways to really generate a lot of meaningful scientific and potentially clinical data to show where this could go and where it could be useful, what indications, what combinations and so forth. And it also, you know, when you have a platform in the old days when money was available, you take a few shots on goal.
You know, you would try to pick some diversified targets and advance them in parallel to a certain point, kind of de risk the platform with revenue and the access to capital. What it is right now, it’s really hard to do that. You know, it’s hard to take multiple shots. You got to pick your best shot, do it really efficiently and get really good answers really quickly. That’s what we’re facing right now.
Alan 22:41
And what do you think has changed fundamentally for the finance to dry out? I mean, sometimes I, I believe that there’s for me the way I’m looking at it, there’s certainly the fact that interest rates have gone up. And I did a quick analysis that looking at the relation between the number of biotech IPO and the federal interest rate. And what you see which is really interesting is that the number of biotech IPO continues to go up as the federal interest rates goes up up to about two and a half 3%. At that point it starts to stabilize. And once it goes above 3, three and a half, 4%, the number of biotechs IPO started to dry out and you know, and so there’s no more exit.
Is that a direct correlation or not? I’m not certain. You know, investing over a long period of time into a biotech, you know, 10 year life cycle or something like that, the difference in interest rate may have an impact on that. Is it that, you know, over the past two or three years, investors, I’ve had the choice to say, well, I can invest in AI or I can invest in biotech. And therefore I’m going to put my money into something that is going gangbuster. And within three years I’m going to know whether I’ve got an exit or not. I don’t have to wait, you know, 10 years or something like that. Is this whole discussion around price control that in some ways I feel the pharma kind of shot themselves in the foot a little bit when they open the door to this.
And it seems like the the horse is out of the barn now and you know, it’s not coming back. So is it that we’ve created an environment where and then you’ve got the cost also, right? I mean, not that long ago, you know, people would come to us and to raise preclinical foot talks and they’d say like I need a couple $1,000,000. Now they ask for 10. Are all these contributing factors where, you know, all of a sudden if you’re an investor, you’re looking at biotech and like the risk reward equation has kind of shifted a little bit?
David 24:39
I think it’s a combination of those things of course, like you pick up an interesting trend, but the interest rates and these things probably drive some of the directional things that are happening. But then you you mentioned a few things that are, are tangible perceived risks of especially these newer, more complex and expensive therapies that are being developed and biotech is high risk, high reward in a way that’s different than IT or different than some of their other areas. Now people can invest in and get a quicker turn more identifiable risk in those settings than you have when you’re treating patients and trying to cure cancer or trying to treat cancer or other complex diseases.
So I think all those things together do probably change the risk profile and there’s certain investors that don’t have the appetite for that. Now the wins I think are enormous and I think immune checkpoint inhibitors kind of show like, wow, like what was starting out as a few programs that looked pretty risky at first. If you remember the old days with anti-CTLA-4 and the CNSC&B problems, everyone was going, Oh yeah, this isn’t going to work, it’s too dangerous. Well, look at the products that are out there right now that are having a huge impact and it’s becoming a foundational part of how we treat cancer. Some people have an appetite for that and, and are willing to invest in those, you know, really big wins and other people probably find other ways to invest that are less risky, you know, and, and more predictable.
And look, cost that’s never going away. I think that’s going to be a challenge for us going forward, which is why, you know, the focus on scalability and efficiency and, and feasibility of delivering more efficiently to a broader, you know, market is going to be, I think with us for the long haul. So I do think it’s a combination of these things. I think there’s this shifting of the cost benefit profile that investors are looking at now. And then you on top of that, which is already complex enough, some of the political and economic other things that are happening and people are asking is the FDA as predictable as we used to think it was? You know, you had a certain package that riding guidance from the FDA and you followed it and and you know, since some recent cases have shed some questions about that, you know, with the Replimune outcome and it’s still evolving, you don’t really have all the answers yet there.
But that’s also something that investors look at and say, well, I used to know what an approvable program looked like. Yeah.
Alan 26:52
So now it’s. That just adds another level of complexity. And we have China now and that’s also bringing a bunch of products and competing. I had the, the CEO of Hansel Pharma here on the podcast and I was asking him about this and it was interesting because, you know, I said like, well, but you’re, you’re, you’re not going to be able to continue to do these cheap deals and things. Like he was like, no, you don’t understand that. First, we’re going to continue to do that because we can #1 and #2 we have to compete against our peers. So we’re not only competing against U. S. companies, we’re competing against other Chinese companies. So to the extent that we can do, you know, this early clinical and and I think really the difference over there is that they have a very strong investigator LED type of trial, you know, investigator initiated trial.
And so they can get into humans very quickly much, much faster than we can and get some initial results and things like that. And I think that does make a big difference in terms of competing. You talked about partnering maybe sooner than you want and I think that sometimes biotech companies think of partnering in the wrong way. They think about licensing commercial rights when they should be thinking about leveraging technology, leveraging manufacturing capabilities, leveraging ability to do clinical trial in different countries and things like that. And they’re not pursuing that at all. And you know, working with a partner to really extend every dollar you theolytics is based in the UK, right?
That’s correct. So how do you manage this? You’re doing global clinical trials. Are you looking at global partnering for the development that you have?
David 28:36
I mean, our trials are currently we have two studies. We have an IV version of our of therapy called THEO-260 for ovarian cancer and we’re on a dose escalation first in human trial in platinum resistant ovarian cancer in the UK, but we’re broadening to Canada and Spain. So we’re broadening that footprint and we’re launching about to launch a study that delivers IP. So it’s THEO-260 for platinum resistant ovarian cancer and that’s going to initiate it. MD Anderson Amir Jazaeri as the lead investigator and expert in ovarian cancer. And so we’re having like a counterpart study that’s IP delivered. And so we are we are slowly building a global footprint.
I do agree with you that partnering can be a really positive thing. You can bring capabilities into your program that would take years and years to develop internally and to to build yourself. So I think there’s an openness, I think not only me, but other CEOs of companies in similar situation are open to like leveraging that, especially because of the capital constraints we’re facing. It makes sense to go to companies that have the funding, have the half, have the infrastructure to, to leverage that to advance your program. And then you maybe can get some bandwidth to start taking multiple shots, right? So there’s still a value there. I mean, there’s very few small companies that start out that could actually fully leverage a platform.
I mean, just there’s just not enough resource to do it. So in my view, partnering can become like a multiplier and you could still have plenty of value that you could then start advancing because now you’re freed up to to add more things to the clinic. Our platform, for example, could be used for multiple cancer indications. It’s just a matter of running that really robust selection process against the 100 million variants and picking the winners, right, for different categories of cancers or different situations. It could also be used for vaccine therapies. It could also be used for gene therapies. So there’s all the slim tap value. That short partnership could free up staff and resources to start leveraging all that value.
So in the end, it’s a win no matter what. Yeah.
Alan 30:39
And you get some, depending on who your partner is, you may get some clinical validation or R&D validation. When you pitch to potential investors and, you know, looking to raise capital, do you drive with a science or do you drive with the value that could be created for the investors, you know, having an understanding of the competitive environment and what a potential exit might look like at a specific evaluation?
David 31:07
I mean, I think early platform companies always start with science because this whole thing is based on that. So I think Theolytics is no exception like early on before we were in the I’m sure that was the whole story. Here’s why our science is so much of an advancement thinking differently about how to build an ad of our library, how to select it, how to use the natural selection of 100 million variants to pick the one that out competes the other 99 million, which is kind of amazing that we can do that. And now that we’re transitioning to the clinic naturally, we want to start shifting our focus to the patient centric, you know, importance of the clinical work we’re doing.
But the science is always like the beating heart of what we do. Like it’s going to make what we’re doing in the clinic better, is going to make our biomarker strategy better. It’s going to make the way we understand how to use our therapeutics better in the clinic. So there’s always a really important science part to what we tell people. And you know, if we’re doing it right, people hear the message differently. Now they’ll say, yeah, now they’re leveraging that good science to do the smartest clinical program they can and get us the best answers as quickly as possible. And also build the team that is savvy enough to enable commercialization to know when they need to start doing XY and Z in the on the manufacturing side and knowing when they have to start engaging payers and knowing like so these are the kind of stumbling blocks for early stage companies where you know, if you don’t have the right experts at the right time, you can lose years of valuable time because you didn’t get some of those things done.
They’re a long lead time. Like manufacturing campaigns sometimes take 18 to 24 months to, to plan, right. Some of the payer research that you may have to be doing so that your endpoints are appropriate not only to prove to the regulatory authorities that you’re approvable. What’s that payers are actually willing to pay you And once you launch your pivotal study, if you haven’t done the endpoints the payers need to see, it’s truly there’s no deal orders you could try. But to get back to the initial question, I think science is still a really important part of our story. It’s just now showing people how that good science is leading to good clinical programs.
And this is still driving the best understanding and the best usage of our assets in the clinic now. So science will always be a huge part of what we do, but we’re very much focused on patients now. And that’s the heart and soul of our company. Like every person in our company and the board included, we all really want to make a difference for patients. When I came in, you know, 8 months ago, I didn’t have to try too hard to create like this sense of urgency or sense of mission. It was there, but it’s, it’s palpable. And I think that’s the case in a lot of start up companies. Like people really want to be there to take all the years of training they’ve done in science or in medicine and, and they want to like put it into a place in their career where they can kind of know that they’re trying to make a difference for patients.
And they want to, I want to look back on my career and think about the different patients that have been helped by the programs I contributed to. And that is the, you know, so that if science is the beating heart of our company, right? That mission is like the spirit of like why people go to biotech and why they taking on these huge odds to like make these really impactful treatments. It’s it takes a special kind of person to do that.
Alan 34:12
How do you as a senior make sure that you’re aware of the competitive environment? I’m asking you the questions because, you know, a few years ago, I remember we worked with an oncology company that was developing a, a KRAS product and they had, the product was licensed by a big company. Evaluation went to like $3 billion. You know, everybody was happy. They did a very large study. This was in myelodysplastic syndrome. The study failed that they had basically taken all MDS patients and then looking, you know, after the failure, looking at the details, they realized that, you know, maybe they made a mistake. They should have only selected high-risk MDS patients and you know, the product would have worked better.
They raised more money. They didn’t phase three trial in there. Eventually the product phase three finished showed that the product worked, but by that time the standard of care had moved and the difference wasn’t big enough. So total investment, five, $600 million into that company, nothing at the end of the day, right? I’m not naming who they are, but. No, I. But, you know, what do you do to make sure that the science, as you said, that everything that you’re pushing remains relevant?
David 35:23
Yeah, I mean, you’ll have to, you can never de risk it completely, right, because there’s always a chance of a transformative event and another program that could derail everything. I’ve lived through that with Hep C, right. When I was at GlobeImmune, we were developing combination therapies for inter interferon based therapy. And at that time, everyone believed that interferon was the backbone and that antivirals, because of the variations of Hep C, would always, would always mutate and you’d always need that interferon immune backbone. And then somebody comes out And it was one of the rare moments where I’m in, I’m at the AASLD meeting, I’m looking at a presentation and they showed a cohort of only like 12 patients with a ribavirin combo genotype 3, I believe SVRs.
At that moment, I turned to my then boss and said, we program. So we pivoted to HBV and we ended up having a program that we advanced pretty far along with Gilead actually, in a partnership to one of the first Cure B programs. But you can never predict completely whether someone else is gonna have a breakthrough that throws the whole field upside down, right, Right. So, I mean, you have to do your diligence and be monitoring the space. It’s a little easier now. I think honestly with access to information being it’s never been better. You can query things like get great information pretty quickly. So I think it’s about being diligent about not only the technical breakthroughs that are happening and identifying, looking around the corners of, hey, could that derail what we’re doing?
And if so, what do we need to be doing and what options do we need to preserve with our program so we can still advance and, and meet this need? Or, you know, so I think that thinking has to always be there. I mean, you just start, you have to start building the team that owned that like that really will monitor that and own that and be constantly on the alert for those kinds of threats to your business and threats to your program. But there’s, there’s no guarantee. There’s always, I think every 10 years or so, there’s going to be a Sovaldi moment where something has a breakthrough that’s so big it will turn things on its head and there’s people win.
I mean, it was a great thing for patients. And then the space still evolved and there were still a lot of other competitors to Sovaldi. I think there were two or three other programs that still were able to be in the interfere on free hep C world in that new world of, you know, post Sovaldi. But I have to say, like it’s less likely that’s going to happen in cancer. Hep C is a singular agent. Yes, it’s a very complex disease. Cancer is really hundreds of diseases, right? So I think it’s less likely that there’s going to be a singular diamond bullet moment that all of a sudden turns cancer on his head. I wish there was. I just don’t think just knowing the science of cancer, I think it’s going to be multiple breakthroughs that evolve over time.
And I think 1 by 1, we’re going to get better at treating major cancer indications and making them at least effectively curable or manageable. That kind of discontinuous risk to like the oncology space just because of the nature of the complexity of the disease itself is pretty unlike likely. That doesn’t mean in your space and your indication that there’s a competitive event that could derail your opportunity and that indication, absolutely. I think every company at this phase has to be super vigilant and be looking at that all the time. we,
Alan 38:34
we spoke about the difficulty raising additional funds, but there’s still a lot of biotech company out there that are sitting on a portfolio of assets and they usually only have enough money to really push one, their lead compound forward. What’s your hypothesis as to why so many of them just sit on these other compounds and don’t, you know, try to partner them out or sell them or, you know, like I was talking to 1 my colleague, he was telling me and, you know, whenever they were having conversation about streamlining the portfolio, the medical team would say, oh, we’ll do something with them sometime. It’s almost like when you have to declutter your house, you’re like man, I’ll still use this sometime you.
David 39:19
Know, I guess there might be something to that. I mean, you generally don’t have that in the starved environment, like it’s rare that you like, but I don’t understand why those wouldn’t be moved into like partnerships or programs that would be, you know, at least advancing those assets. There could be IP reasons. I don’t know it it’s if you don’t have the bigger companies that portfolios and think a lot of things sit on the shelf, a lot of things don’t advance. It’s it’s hard for me to appreciate why they might do that. Maybe it’s just that it’s hard to give away your babies something that was developed and you’re maybe waiting for an opportunity for that to become something important or have an opportunity to leverage that into some of your programs.
But yeah, I don’t. Or you don’t want someone else to make it a that breakthrough that we were talking about and you missed there. Probably is some of that like it like if it gets, if you do something and all of a sudden there’s a breakthrough five years later you’re like, why did you give away our compound so that it would become breakthrough? Right, right, right. I guess there’s some of that. So like.
Alan 40:12
When you join you, you, you join Theolytics about 8 months ago now and you come in as a a new CEO. What do you do? What do what do you look at where you know what’s kind of like your approach to taking charge of an organization?
David 40:26
I think it’s, it’s not really rocket science in my view. I, I really spent a lot of time with the team and the foundational team to understand the people, understand what they had done to get to the point we were. And I really spent a lot of time understanding the platform to really understand how we could best leverage it. And so the first few months was really just digging into the the science of what we had developed, understanding how it would represent potential, not only in this indication we had already selected, but potentially in the future. And then digging in really hard and really deeply to the clinical program. And having been a former CMO and several different roles, that was a bit easier for me to do as jump right in and assess the program and work with the team to identify some gaps and to make some modifications while we could and really hone in on the lead indication, but also, you know, start to look at where where we could go from there and think differently.
And when you bring a fresh perspective, sometimes it changes the way you might approach a platform. I’ll give you one example. You know, the the Felix platform initially was designed As for each type of cancer, you could select this 100 million bank library and pick the perfect or the best suited variant out of 100 million for each cancer. And then, you know, when I joined, I said, you know, that makes complete sense, right, Because you’re doing a Darwinian experiment and you can do it differently for colon cancer and differently for every cancer and you’re probably going to get a variant that’s different. But when we saw the CAF activity, no one would have predicted the CAF activity that, you know, cancer associated fibroblast killing in addition to the ovarian cancer cell killing or elite product THEO-260.
To me and some of the core members of my team that represented a very differentiated feature and there’s a lot of stroma rich solid tumors that are very hard to treat with any modality. And my interpretation, and this is a view that’s shared by some of my team members, is in treating intact ovarian cancer samples with the library and selecting THEO-260. the CAF part might have been one of the primary things being selected for because the fibroblast caused the barrier, caused the TME barriers, not only physical, but chemokine and cytokine barriers in the tumor. And so we said, you know, that we, we shouldn’t ignore that like this could be useful beyond just ovarian cancer, right?
So we, we, I know the model that the platform was built on was a certain thing, but but now you have to always take a step back and reassess things. And so of course, we’re looking now at at THEO-260 being perhaps more broadly applicable than ovarian cancer because of this unique feature of the CAF killing. And there are companies developing just stroma targeted agents, right? And here we have that as a built in feature to our lead oncolytic virus, right. So interesting it, it just was a fresh look, a chance to take a fresh look with the scientists and with the, the, the senior leadership of the company and say, let’s take a step back and maybe, maybe there’s a lot more value in THEO-260 beyond just ovarian cancer.
And maybe we can think differently about maybe it’s categories of cancer types we would select for. Maybe it’s a newer endocrine tumor behaves differently than epithelial tumor like. So we’re going to figure all this stuff out and really leverage the platform to the maximum. But that’s one example of.
Alan 43:43
And then do you then think about I need to raise additional money to kind of investigate to accelerate development into these type of of cancer that you know have that particular feature and.
David 43:56
I think if the access to capital was more free flowing, that would be a natural way of like taking multiple shots, right, right. I think in this environment, we still think the discipline of demonstrating in a lead indication how all this works and figuring it all out. And then that still naturally translates to other applications. And so there’s some preclinical work we can do right now on other tumor types and be as ready and then disabled as possible, right? So in this example, we can take THEO-260 and look at other tumor types and, and, and really interrogate that. So we understand the wheel indication footprint of THEO-260 before we have to spend like large amounts of capital and large amounts of our people’s time on it.
But be ready like so that when we get a good signal in ovarian, we’re that much prepared to go, OK, well, it actually can work in this indication as well and this indication and be ready to start leveraging that value. But right now, the temptation, it’s always for the platform company, the temptations to bowl the ocean because you there’s so many ways you can use the platform. So it does take some discipline to be really focused and really make sure you’re getting the answers. Not only that, demonstrate proof of concept for what you designed the therapy to do. You always learn things along the way about how to better apply the regimen, how to better do the manufacturing better do like you’re learning all these things.
And so instead of having four products in the clinic that you’re learning at the same time that you have to do things, it’s nice to have a lead program that’s a step ahead. And then you can start bringing in these other assets and or, you know, other indications with learnings you have. So there’s a there’s a cadence to it. I think that makes sense, especially with access to capital being as challenging as it is.
Alan 45:33
Do you see any AI models or tools that can help accelerate at least that that early evaluation that you’re talking about where you know you don’t have to do animal model, you can just use the AI model to give you an answer or help you to a certain extent?
David 45:51
I think AI is going to become increasingly useful in certain discovery aspects, like putting together the features of a data set that then could help you predict like where else something will work, really complex data sets that can be really interrogated by AI in a way that’s different than what you could do with like what I call the non artificial intelligence. So I do think there’s going to be a lot of leverage there. I think that’s one of the staffing challenges we’re going to face, I think and it’s not just on the science side. I think AI is is starting to become part of everything. I think I think we really need to start having some AI expertise in house to start managing AI not only for managing the science projects and making scientific decisions or development decisions, but also in the way we’re capturing information from meetings.
I mean, there’s all kinds of implications of having this automated AI kind of underbelly in all the applications we’re using. So it strikes me that there’s something that was on our radar. We have to start getting ahead of that a bit better. But I do think there’s no substitute for the non artificial intelligence of the human brain. I tease my team sometimes they say, hey, like if we have a really creative question on the table, like where we really have to think outside the box, I’m like, let’s use our non artificial intelligence to. Think about this like. This is not something you’re gonna solve with a query, you know, You know, I know. And when it comes to nuance things and really thinking creatively, I still think there’s no substitute for like what you have between your ears and, and I think it’s really apparent if you query something using AI tools in an area that you’re an absolute expert in, it’s when you can kind of see it, oftentimes it’s not really quite right.
It’s close, like there’s gaps there that. So I think we have to respect the fact that it’s not gonna be like a fantasy of really.
Alan 47:35
Yeah. I mean, I guess the the beauty about it is getting better and better and better, right. And so one of the thing that I agree with you, I mean, I think that people are saying that the way you need to look at it is it’s not meant to replace the human. It’s meant to enhance your ability to deliver value, right. And and how much quicker you can do it. You know, there’s a lot of the menial task that would take us forever before. And now you just say like it do this, right? I mean, like there was the latest the agent, for instance, you could ask it to make a hotel reservation for you and it goes and does it right. And after. I mean, it’s crazy that.
Yeah.
David 48:19
But, but I think for us, often we’re looking at correlation, you know, so you take two data sets and you interrogate and you say, can you find any relation between and it comes up with things that you would have never thought about. Sometimes you look at it and you’re like, makes no sense. But sometimes there’s one thing where you’re like, interesting. And I didn’t think about that. I think maybe there’s something there. I think for grinding to lots of data and factual information and delivering and like certain conclusions from it, it’s pretty powerful. I’ll give you an example. I just ran it today. I was thinking about the diversity of Theolytics.
I don’t know about a platform 100 million variants. And I said, I said that number. Sounds familiar to me. I think the TCR repertoire of a human being is around the same number, I said. But instead of going to pub Med and like looking up 50 articles and like or having someone do that and spend like a whole day, I typed that in and within seconds I told you I had the references and the and then I got into some really interesting stuff. The theoretical diversity of the TCR repertoire is 10 to the 15th power. But effectively, because of the constraints of an individual human being and various ways that that’s expressed in a person, each person has about 100 million, a repertoire complexity of about 100 million variants in their TCR repertoire.
I was like, well, that’s pretty cool. It also was like a moment where I said it’s also really cool that our adenoviral library has the same complexity level as a single person’s TCR repertoire, right? Right, right. So I said I want to, I want to remember that. But I was able to do that in 30 seconds, you know, today, instead of spending two days, like, looking up all these articles in Pub Med and like, you know, figuring it out. Yeah, I’ve trained my AI to give me a biotech company profile. So I basically say I want to do and you know, I have a folder and I want to say I want you to tell me all these things. This is how if you were to ask me, do you want to work with them, then I have a very specific way what I look, you know, I look at the cash position, the performance of the stock.
I look at the pipeline. I try to get an idea of the competitive landscape, you know, the latest news, deals in the space and things like that. So I’ve got all of that lined up as a template and all I do when I go to that folder I just put the name of the company and it gives me exactly. An abstract of all the key things you want to. Know everything that I want to know at the bottom, it gives me a best case scenario, worst case, you know, what are the risk? What are the potential advantages of this company moving forward? And it’s amazing because I used to go to this database and and then I would go to the website and you know, and it took me 1/2 an hour, an hour just moving around.
Now I’ve got it in, to your point, in like 3040 seconds. I’ve got the whole detail. Absolutely. And I think there’s applications that can take really dense, complex documents and extract really useful information quickly. I, I don’t think it’s 100% substitute for actually reviewing the document because you might miss stuff like you don’t know how much you’re missing. But but sometimes, like I’m amazed that when I run those things against my own documents, I’m like, yeah, I hit like all the key points in 40 seconds for 20 seconds. yeah,
Alan 51:23
are you familiar with this, this thing called NotebookLM from Google? It’s kind of interesting. You, you can grab any article, try it next time you you have a paper that you want to review. It was developed to to help students study. So you could take any publications or something like that. And of course it gives you a summary and then you can do flash cards and things of that. But what the the greatest piece is that you can have it, make it a podcast. And so it’s like you and I are talking. That yes. But you are driving home and it’s talking about it and you’re learning about this.
David 51:59
I heard a. Similar app that does that, it takes the document and it creates a podcast that in AQ and a session highlights all the key information from that. Yeah. Yeah, kind of. It’s also creepy the way it sounds like. You and me, right? Now, right.
Alan 52:15
And yesterday I was, you know, I joined the coaching from Dan Martell. I don’t know if you know him, but he he wrote a book called Buy back your time, which is really good book and very interesting. So I joined this this coaching thing. And so you’re part of the community and you can ask questions and things like that. And I was asking a question about, you know, how to effectively, as you, you know, category, we’re scaling, right? So how do you effectively capture all the processes in a way that can be easily taught to the next people coming into the organization? So you don’t have to do it every time, right? And and of course using, you know, recording and video and things like that is great.
But this lady responded to me and she said, we’re developing a tool that allows you to take any of the SOP that you have within an organization and make it an interactive conversation with the person who’s joining. So they can go in and they can read and they can ask questions. And the tool respond and say, well, this is, you know, how you should look at this SOP and, you know, pretty amazing.
David 53:23
It is pretty amazing. I think there’s, there’s definitely applications where it’s going to be a huge advantage. And then I guess my reservation is about like some of the, if you’ve been in this for 25 years, there’s always these like really subtle things like when you’re trying to analyse early phase data in the clinic, right? Sometimes you’re picking up really nuanced things that are different that I don’t think AI can can get you yet. And and a good example of that is the immune-based therapies and cancer, they don’t deliver the same kinetics of response for the traditional endpoints. And we’ve learned this for 1020 years. Like, you can actually have disease that looks progressive by RECIST, but then you still have an survival advantage, right?
Because RECIST was developed back in the day when chemotherapeutics killed the tumor acutely, right? Its mode of action was immediate. But we know that immune responses have a latency of effect. And even if it doesn’t have as big an impact on the primary tumor, it probably has other effects on the the cells that have escaped and are trying to set up metastatic lesions elsewhere in the body. So the, the whole idea that like you can just use data can fail miserably if there’s nuance differences of how something else is working. And the only way to figure that out is experience in doing the studies and like re educating yourself about what new endpoints are probably more applicable to immune based approaches on cancer.
And I think we’re starting to get there even with the imaging and and with how we think about how predictive is this traditional RECIST with long term survival using immune based therapy because I think the jury’s still out, we don’t we’re starting to appreciate the difference, but there’s still work to be done. know,
Alan 55:03
when I was a sales Rep, I remember going to and I was selling cardiovascular product and I remember having a conversation with the Ando at the time and I asked him or like my colleague asked him in your clinical experience and he got really mad. He said, what do you mean my clinical experience? Like, you know, I see patients and things like that, but that doesn’t mean that it’s not a representative sample. You know, it’s like it means nothing like it’s our anecdotal and you know, the studies are done at the large scale to try to prove something. But I wonder, you know, with this becoming more specific, you know, whether that anecdotal knowledge to your point of the physician having an understanding on how this could potentially work for that patient because of that, but maybe slightly different or it’s not because he’s not reacting immediately that is not working.
You know, I’ve seen that in that type of patients. more,
David 56:12
I mean, how do you run a clinical trial like this? You can take those nuanced learnings, right, the early kind of intuitive findings, but you still have to formalize them in the next study. And so it’s the initial finding is a hypothesis generating thing, right that you then have to start formally putting into your implement analysis and phase two and phase three to demonstrate, like you said in a representative sample, well controlled that in fact that’s what happened. And so one example of that, and this is in the early days of immuno oncology, this is back in like 2006 when we were doing the pancreas cancer trial at GlobeImmune. We knew our vaccine, if it was working should make lymph nodes light up.
But that’s also a form of progression the cancer patient, right? And we kind of and this isn’t a for pseudo progression. I think it was a widely known thing, but and we designed in the study because I was a young CMO and said if our stuff works, I don’t want these people being called treatment failures. And then you’re stopping treatment in the very patients that are supposed to start demonstrating what could be a response, right. So we had actually designed that into the study. And what we did was we said if a lymph node lights up on a scan, but the CA 19-9 levels are stable or dropping, which is the burden marker of pancreas cancer, we would call them a potential lesion and capture it and date capture it.
But then we would give the investigator two or three more visits to discern whether it was a true progression or whether it was a pseudo progression. And we weren’t using the term pseudo progression and we were just calling it a potential lesion. And in several cases, in fact, seeing CA 19-9 or stable or dropping node lights up, we see good immune responses. You see that node regressing over time, see CA 19-9 dropping, and it was never called a progression. We had to design that into the study and formally test it. And now over decades, many immune oncology programs, there’s an understanding and appreciation for pseudo progression. Like people have seen it in so many different settings that doesn’t.
We have perfect endpoints for it yet, but pseudo progression is the thing that we have to be aware of that the immune therapies themselves can create changes in the acute findings of scans that look like progression. Yeah. Probably aren’t, and you have to do the extra work now to show. How do you prove that? A big study.
Alan 58:25
What do you think of this whole debate around the right to try that we’re having now in the US? As you said, you’re a pediatric rare disease. You know, you’ve got experience in there. What what are your thoughts around around this?
David 58:40
I mean, I do think that in early stages of development, if there’s enough data that’s support that there’s a likelihood that something could benefit someone. And for diseases where people are really desperate to try something and you know, we’ve had vehicles like single-patient INDs who’ve used these in the past for different programs that have been involved in. I think there’s value to it. I think for people that really understand the risk and are willing to try something, you know, if they’re really have run out of options, I do think having an Ave. to that is ethical. I think it’s passionate. I think it should be done. It’s just that it’s hard to imagine like A1 size fits all like approach to that.
I think it really depends on the disease situation, how much data you have for that program that demonstrates at least some likelihood for benefit. I think there has to be some demonstrated proof of efficacy at some level where you do that. But I do think there’s value to that. I mean, I’m sympathetic to that movement. And in terms of like, you know, if it was my child that had no treatment options, wouldn’t I want to have? Three with ALS and yeah, I’ll try anything. I mean at that point. Yes, I mean and every, every program should have a benefit risk kind of maybe it’s or maybe a more formalized assessment that it’s a lower bar, but you still have to pass some level of credible benefit risk, not what it would take to get an approval.
Yeah,
Alan 1:00:05
as a CEO of an organization, what are the when you go to bed at night, you’re like thinking, what are you usually you’re like top three, five things that you really worry about.
David 1:00:16
It is a. Little different for the early setting versus the late stage and there’s different things that you worry about. But coming into a new company, you know, I really spend the first few months really making sure I’ve identified I think all the major risks that we face. Like do we really appreciate the risks of the given program we’ve selected or the the lead asset? Are we really looking around those corners to be prepared for something unexpected? Are we really getting as much out of the asset as we could be like? So I, I try to use that as a chance for a fresh thinking about things. Usually there’s some pleasant surprises and usually there’s some unpleasant surprises in any job, any first month or two in any company, right?
It’s just, you’re always going to start really getting in there and figuring things out. So I think, you know, initially that’s what I really focus on is like, you know, is the thesis by which we’re building value for the stakeholders and that includes everybody, investors, patients, the employees. Is it really based on a data set that I am, I’m fully convinced of? Are there gaps that we need to fill or are there assumptions I don’t really believe in or don’t really buy into? So it’s kind of like a chance to rethink everything and challenge things a bit. And then you have to manage operational risk and financial risk. And is the program executable and has the team really done the work to understand what it takes to get to commercialization?
So very early on, I think even at a phase one company, there’s a lot of value in doing integrated development plan all the way out to commercialization. It’s painful at 1st and especially for the first time a company does that, it’s like a huge task, right? But I always have found that you will always identify questions that people hadn’t thought about that required decisions much sooner than people realized. And I’ve always seen it add value like within a month or two, like we’ve identified a long lead time on manufacturing that we actually have to make a decision in nine months on that people wasn’t even on the radar, right. And now we have enough data to actually do a proper NPV model because now we’ve identified a few other costs and a few other delays.
All of a sudden, you find that, OK, now I really do know what it takes to get to like to get to commercialization 5 years from now, six years from now. And so then I start focusing on operational risk. Do we really know what we have to do as a team and do we have gaps in our expertise that we need to fill? And like then it becomes like an execution focused. Approach.
Alan 1:02:38
How early in in the the development do you start to talk to potential exit partner, like whether it’s licensing or you know, selling or something like that. Maybe not with the idea of selling at the moment, but at least to make sure you understand what is of interest to them.
David 1:02:57
I mean, I think there’s always a healthy level of outreach that could be happening organically through over time with investors, but also with potential partners. It’s not always about, I mean, I think it takes years of building relationships on the business development side, on the investor side. And that’s where those things lead to like the deal. So I think it’s worth the investment of time of having, you know, certain key companies that are in spaces that you think should have synergy with what you’re doing or have interest in what you’re doing and, and having outreach. And it doesn’t mean you have to have a deal like in three months, but it gives you a sense of what they’re looking for.
It gives you a sense of what they perceive the gaps are. It might help you actually fill some of those gaps by doing some additional biomarker work or doing some additional works. I, I think the idea that it has to be like a campaign where you say, OK, we’re going to partner this asset or, and that’s the only time you reach out. I don’t think that’s necessarily the way it needs to be. I think they’re going to be kind of like relationship building in a kind of selective way. And that I think that applies to either strategic partners or investors. And so and especially in this environment where like you just need to really understand what people are looking for now, like the bars I think a bit higher both from the partnering side and the investor side.
What, what kind of partnerships are you really, what kind of data in the clinic are you requiring now that might have been a little different than three or five years ago?
Alan 1:04:22
Do you have like a a career defining moment that that taught you something important about leadership or or business?
David 1:04:29
Yeah, I think I alluded to it before. You know, my first role running a big part of an organization was believe it or not, my second job at BMS running a really big form of matrix team for a global program. And honestly, I never managed anyone directly and sharing every small matrix team, you know, to do a supplemental filing. And that experience at BMS, like I said, really taught me like what it takes to manage people effectively. And, and those lessons I’ve carried forward because if you think simplistically about it, like, yeah, people report to you and you know, there’s this explicit level of like chain of command. And that’s it takes way more than that to lead an organization.
So I learned those lessons about how to inspire people, how to create a sense of mission, how to like and respect people. Like at every level of the organization, everyone should know why what you’re doing is important. And when you give people of that, you know that respect, not only do they appreciate it, they’re usually going to work twice as hard when they realize all the things that they’re investing all this time and is going to deliver a better therapy for a patient, an ovarian cancer patient, right, right. So I think that was one of the formative experiences I had, you know, in terms of being in industry and running teams and and leading people for sure.
I mean, it was one of those things that I will never forget. Yeah, that’s a great, great skill to have.
Alan 1:05:48
If you could give one piece of advice to someone stepping into their first biotech year role, what would you, what would you tell them?
David 1:05:59
I, I really think it’s building a really strong relationship with your board and your chairperson. And you know that at the officer level, you see some of that, like when I was a chief medical officer and I was involved in a lot of the board activities. But it’s very different thing when you’re the CEO. And I think it’s really important to have a really strong relationship with the board, a partnership to make sure that you have alignment, you know, across the board, and a strong relationship, a partnership with the chairperson. I mean, it works kind of, you know, the CEOs role is to manage the executive team to execute and deliver the programs and the assets, and at the same time to have the strategic support and governance support of the board.
And if you fail on either side of that, it weakens your relationship on the other, on the other side. So if you’re not executing well, right, the board’s going to lose confidence in you as a CEO. If you don’t have the alignment of the board and that the management team starts to sense that the board isn’t really behind the mission you’re selling to the whole company, then they’re going to lose confidence. And the CEO, the CEO has to kind of deliver both those things. So you really have to straddle that. So I think for a first time CEO, you know, you have to really just manage and make sure you are partnering with the board and not in any way adversarial relationship with the board.
I think that’s really critical. And sometimes the boards aren’t always fully unified when you join. And often times you’re joining because there’s been some turnover and some change. And so it’s not always the easiest thing to do in the first few months, but I think it’s super important to to have that alignment.
Alan 1:07:31
Who’s your biggest inspiration you know, outside of biotech?
David 1:07:33
I really, when I saw the story about John Crowley and, and how he started Amicus because his child, yeah, was afflicted with this genetic disease, I was super impressed by that. And the same, the same kind of story could be told about Leslie Gordon and. And that’s right. And the progeria story and what it showed me was when you really, really want to get something done, like when it’s your kid and. There’s no stuff those kinds. Of breakthroughs happen and I had the the good fortune of visiting Amicus at some point. You could not walk in that place and not be impacted by the patient focus. It was everywhere. It was absolutely the heartbeat of that place.
No surprise, right? You know, John Crowley did it for all the right reasons, like, and so it to me was a big eye opener. You have to kind of try to behave like it’s our kid or behave like it’s a family member. You know. I think people are naturally compassionate and empathetic and people use different terms for that. But I think if you can take a step outside of yourself and say like what we’re trying to do for ovarian cancer patients at Theolytics, right? That could be my sister, that could be my wife, that could be my daughter someday. Like I have to like use that as motivation and and inspiration.
Alan 1:08:49
I always like to to to finish my interview by asking a question around to get to know you a little bit better. But what did you want to do when you were growing up?
David 1:09:00
I always thought it would be scientifically driven because I just had that interest in that aptitude. And initially I thought I was going to be a pure scientist. I just, I was fascinated by science. And then I would say in college, I started to appreciate molecular biology as like biology and information technology all rolled up into one where the information that we need to do biology betters right there in the DNA. Like that was a mind blowing experience for me. And I was actually an engineering student from my first two years in college. And when I had a singular lecture where I had that moment in my biochemistry lecture at that moment decided to change my majors and I never looked back.
So I always knew it would be science based. And then midway through my Graduate School work, I realized it had to be clinically focused to really for me to have passion about it long term. And so, and it’s kind of amazing how scientific and how scientifically driven drug development is now like, compared to 30 years ago. It used to be kind of like screening large numbers of compounds and empirically finding out what works. But now there’s a way of understanding the information technology of life and how we can start, like, manipulating or, you know, targeting diseases in a way that’s like you would have thought of science fiction 30 years ago.
Alan 1:10:16
Awesome. David, thank you so much for your time. I think that was a great conversation. I really appreciate it.
David 1:10:21
It’s a pleasure. Yeah. Thanks for inviting me. You’re welcome. Take care.
