Patrick Short  0:03  
Welcome, everybody to the Genetics Podcast. I'm really excited to be here today with Dr. Dietrich Stephan who's the CEO and founder of Neubase therapeutics. Dietrich has founded or co founded 14 biotechnology companies, including co founding Navigenics, which is one of the first direct to consumer genetic testing companies, and, of course, Neubase therapeutics that we're going to discuss today. Dietrich, thanks so much for joining me. Great to be with you today.

Dr. Dietrich Stephan  0:25  
Such a pleasure to be here, Patrick, thanks for having me.

Patrick Short  0:28  
I'd love to just start with Neubase and the vision that you have for the company. How did you come up with the vision and the and the idea for the co mpany? And where are you at today? And what does the future look like? 

Dr. Dietrich Stephan  0:38  
Youknow, it's interesting, the key observation that led to the formation of Neubase therapeutics, was firstly, that every disease is genetic. And we know that from heritability studies and gene identification studies, you know, either they're Mendiola, and single gene disorders, which collectively affect about 10% of the global population are their cancer, a genetic disease of a single cell that causes those cells to grow uncontrollably, or infectious diseases where you are invaded by a foreign genome that replicates uncontrollably and or complex genetic diseases, often also called chronic diseases, where you inherit genetic risk factors that are often then triggered by the environment. And so every disease is genetic. Yet, the pharmaceutical industry has been waging the war at the protein level, two steps downstream in the central dogma. And I'm only more recently with the delivery of the human genome sequence Have we started to move upstream to nucleic acids in terms of dragging RNAs, but we aren't whole hog and with, you know, with full throated efforts, dragging the genome, and it just struck me as a non sequitur, and obvious issue in our strategy to impact those who are suffering and dying. And so that's what led to Neubase.

Patrick Short  1:58  
And you send your website and I think a big motivation behind the company is exactly what you just said there that most diseases actually are undruggable with biologic and small molecules, what why is that maybe you can dig into that thesis a little bit more?

Dr. Dietrich Stephan  2:12  
Yes. So the so I mean, first is the observation that for example, monogenic diseases of the five to 7000 monogenic diseases, only 5% of them have available therapies, which means 95% of the people diagnosed have no therapeutic option, and often suffer and die with no hope. And so just that statistic alone is data that says, at least in that category of disease, most of them remain undruggable. Now, when you go to oncology, half of us on this planet that are alive today, will will be diagnosed with cancer in our lifetimes and half again, will die of that disease or set of diseases. And there's another statistic that sort of speaks to the dramatic unmet need in terms of undruggable targets. And you can go forward, we're all aware of the issues and infectious disease. We've all lived through them over the last few years. And now we're on the cusp of monkey pox. And who knows what coming down the pike next. So, so that's the data. And then the question is, well, why do they remain undruggable. And my observation has been that as an industry, we started therapeutic development efforts by literally taking material from patients who are suffering from diseases cells, let's say, and engaging in high throughput screening, where with no a priori information, we literally poured 10s Hundreds, millions of compounds on to the cells and hope that some of them would positively impact the disease process and, and not cause a secondary toxicities that made them untenable as therapies and, and then we would go in and engineer those chemicals to improve potency and reduce off target effects for the next decade, until finally hopefully, we would arrive with a therapy. And so the process I outlined is really, I'd say, literally hit or miss very low probability of success, very slow, very expensive. And you simply even if you just add up the number of diseases and the time and money it takes to go through that process can't possibly develop therapies for all of the different conditions that folks suffer from. And so I think that that's sort of the core reason why there remains so many undruggable diseases today is a bespoke therapeutic development process and lack of scalability.

Patrick Short  4:39  
And maybe you could dig into your platform a little bit more and what is different I know you all are operating at the DNA and RNA level rather than the protein level what what are the key pieces of the puzzle what what you need to solve or others need to solve to actually realise this paradigm of trading much closer to the source rather than at the very end of the central dogma as you pointed out? Yeah,

Dr. Dietrich Stephan  4:59  
so So, as an industry, you know, there was a recognition that genetics are central to almost every disease process. And it led us to sequence that human genome and an industry has sprouted up that is nascent and fragmented, but has shown human proof of concept and being able to drug RNAs, largely one step closer to root causality. Another question is, well, why have DNA based therapies lag? Why Can't We? Or why haven't we really been able to drive the genome itself, as opposed to the messenger, and we believe it's very simply because the genome is double stranded, and has evolved to protect its information that's existential in nature in terms of a blueprint of life that has to be passed through generations in exquisite robustness, and fidelity. So so if that's the case, what one would need to do would be to open up the genome without breaking it sift through all 6 billion letters with a molecule that could recognise just the mutant gene, be able to once it's engaged with that mutant gene, increase, decrease, or even change gene function, because those are the three causal mechanisms that drive almost every human disease, and do so in a way where we could actually get the molecule to all of the tissues that are affected in these various diseases, as you know, were largely relegated to the liver after systemic administration with genetic medicines. And so get past the liver get into the brain, so forth, do so in a way with exquisite selectivity of sequence engagement, ideally, to the single base level. So you can see mutations versus wild type alleles, and certainly avoid any off target engagement with highly homologous sequences elsewhere in the genome. do so in a well tolerated manner. So for example, that you don't trigger the immune system. And we've seen issues with gene therapies and specific related to the concept of one and done and not being able to go in and give a second or third, or lifelong chronic dosing paradigm, ensure that these are manufacturable without needing to go build bespoke factories. And then finally, that they're truly scalable, so that we can print out drugs that engage with any genetic target that causes disease, and have sort of known performance around that molecule so that we can accelerate through the development programme. And so that's the problem that we started off solving. And after about three years of engineering work, I'm pleased to say that we've gotten to a solution that performs that way. And we'll be dosing our first patients likely early next year,

Patrick Short  7:48  
and is that I know you've got a couple of programmes on your website, myotonic dystrophy, Huntington's and a couple of really challenging to treat KRAS mutations and oncology's is that in one of those all three, maybe you could walk through one of those examples and just and just talk through what that process has been like from start to finish. Because I think in all of these cases, there's just no approved therapies that I'm aware of at all. So it really is kind of Terra, Terra Incognita that you're marching into?

Dr. Dietrich Stephan  8:14  
Yeah, well, I could start with our lead programme myotonic dystrophy type one dominant genetic disease caused by a trinucleotide repeat expansion in the three prime untranslated region of a gene called dmpk. And so obviously, the mutation is present from birth. The longer the repeat the earlier the onset of the disease, and the more severe the symptoms. Generally, patients suffer from muscle weakness and wasting myotonia and inability to relax after contracting their skeletal muscles, respiratory issues, particularly in the juvenile forms of the disease that often require going on a respirator cardiac conduction defects that can be fatal, and then cognitive deficits. So it's a multi system disease, there are no effective therapies. It's actually the most common neuromuscular disease that affects about one in 1000 individuals globally. So, what the pathogenic mechanism is that the, the gene, both the mutant and the wild type are transcribed and then the mRNA on them of the mutant gene forms an aberrant hairpin structure. So the repeat itself folds back onto itself in the three prime UTR and causes a hairpin and that hairpin inappropriately sequesters critical splice effector proteins, specifically a protein called muscle blind like protein mbN L, one that then decorates that hairpin and causes an nuclear aggregate. So now we have a double stranded nucleic acid target in the nucleus that we want to engage with. And so we've developed compounds and we'll talk about the chemistry If that can invade that hairpin, open it up and sterically displace the sequestered splice effector proteins. So now they're freed to do what they're supposed to do. And what happens is we, we resolve the characteristic splice Officee that causes the disease. So now the other component of this is that it looks like many features of this disease are reversible. So when you kick off that muscle blind like protein, and you rescue downstream splicing of hundreds or 1000s of other transcripts, you create healthy proteins from those transcripts now that can perform normally. And so what we see in the animal model is that we can rescue the characteristic characteristic myotonia, one of our collaborators in Paris shown Aviv, Gordon has shown that she can rescue aspects of the cognitive deficits and a bailar group has shown that they can rescue some or all of the cardiac dysfunction. And so that process can take between one and two months and in the animal models, and we believe that's transferable to the human condition. And so, fingers crossed. You know, once we start dosing our first patients, within a couple of months, we should see resolution of some of these major issues that patients have.

Patrick Short  11:20  
Yeah, that's tremendous. And you've anticipated one of the questions I had, which was, you know, at with many diseases, I suspect there's going to be a window of opportunity. But we may be surprised in many cases of just how wide that window of opportunity is. And I was also going to ask about delivery, it sounds like you'd need to get the correcting mechanism to the muscles, the brain, the heart, how do you solve that delivery challenge in this case, and more generally,

Dr. Dietrich Stephan  11:47  
yes, it's really two parts. So we have our pharmaco four, that's the active compound and the biophysical characteristics of that have been engineered to be low molecular weight, water soluble and neutral in charge. And so they're, you know, on their own there, they're very easy to traffic throughout the body. And that's juxtaposed against what I'll call classic genetic medicines that are often heavily heavily negatively charged, for example, antisense oligo, or SI RNAs are built on negatively charged backbones. And what happens is they get cleared by, for example, scavenger receptors in the liver and don't get past the liver, to other organs. So that's part one is, the second is that we have developed delivery technology that can be snapped on the end of these pharmacophores that allow them to interact with the plasma membranes of any cell and in any tissue of the body. And once they interact, again, in a non cell type specific way, they can be actively trans located across the plasma membrane via process whereby they form an emulsion with their partially cat Ionic, partially hydrophobic, and they can form an emulsion with a plasma membrane that's then pulled right into the cytoplasm and dumped into the cytoplasm, where they then diffuse into the nucleus. And so what we've seen after systemic administration, when we couple those to the delivery shuttles and the pharmacophores, is that we get access to every compartment, whether it's the skeletal muscle that's important in myotonia, the heart, or even the brain, which becomes very important in these multi system disorders. In particular, for example, in our Huntington's programme, where the primary pathology is neurotoxicity in the brain, and we need to turn off that disease causing protein. So you know, it's really the combination of those two modules together,

Patrick Short  13:50  
that so yeah, if we took the Huntington's as a as the second example, are the drug would be administered systemically? And then how do you actually set that delivery shuttle up so that it's only dropping the cargo off? If I can extend the metaphor into into the brain and muscle or whatever the couple of tissues that you're interested in? How have you worked out how to make sure it drops the cargo often in the right place, but not in the wrong places?

Dr. Dietrich Stephan  14:17  
So So our current strategy is to use a delivery technology that gets the compound everywhere. And so we don't discriminate as to which tissue we want to specifically target versus not target, and really rely on the exquisite selectivity of the pharmaco for payload itself to only drug, the mutant gene of interest and to essentially bounce off of the genomes of cells that don't have a disease gene that's activated and there's a nuance there were certainly your audience will recognise that if we're targeting the genome, every cell will likely have the mutation But in order for for our technology to work at the DNA level, we've talked about this double stranded RNA target, which is really an edge case, in terms of our core competencies, which are dragging the genome, the ability for the compounds to slip into the double helix and query for a perfect complementary match are really driven off of when a gene is breathing, or being actively transcribed, and the double helix is opened up that allows access. And so there you have a level of selectivity where by the gene must be being actively transcribed, which generally only occurs in the tissues that have or expressed the pathologies. And so that's an example of where sort of broad based delivery can be mitigated in terms of any potential off target effects, by the mechanisms by which the drug

Patrick Short  15:51  
works. Yeah, that makes sense, it's a very, it's a very elegant solution. Because if it's, if it's not breathing, if it's not actually active, then it's unlikely that that aberrant repeat or whatever it may be, is causing any problems in that in that tissue anyways, so we almost I'm sure there are some cases that that defy the logic where it may be expressed, and, and you don't want to mess with it. But it feels like a generally a good principle that if you can do the in the in vitro work to really understand what that is and how it works, then that that can give you at least some confidence that there aren't going to be off target effects before you go into humans or into animals.

Dr. Dietrich Stephan  16:27  
Yeah, exactly, exactly. And, you know, the mechanism by which we target the genome, I think is very interesting. So it gets to the composition of the molecules themselves. You know, what, from 30,000 feet, the molecules look very similar to a single stranded oligonucleotide. But when you zoom in on them, what you'll find is that the backbone is a synthetic polymer neutral in charge, and the nuclear bases while they can be natural ACS, GS and T's are also often modified to perform very differently than standard nuclear bases. And so the backbone is a poly a mite backbone. These are actually derivatized glycine subunits that are snapped together on a peptide sequencer. And then we can use standard nuclear bases, but also a class of nuclear bases called Hochstein binders. After the famous gentlemen that actually characterise the hydrogen bonding of the double helix, which can scan the outside of the double helix by peering into the major groove and finding sequence complementarity without the need to open up the genome. So that's a very interesting class of nuclear base. And then we also have further modifications with a class of nucleobase, called Janus faces, named after the Roman god with two faces on one head. And in that case, when these logos invade the double stranded genome, they can bind both the Watson and Crick strands in a sequence specific manner. And so you get this sort of interest in these interesting sets of structures that can be identified and formed and the entire mechanism of action once you've engaged a locus, however, you want to engage it with this, call it a naked oligo system, is that you interfere with or modulate machinery that runs on the rails of the genome. And so just one example, and this is how we develop our compounds for Huntington's disease is we put an oligo on to the mutant transcribed allele of the HTT gene, the gene that causes Huntington's disease, such that RNA polymerase can't read through that gene and create a mutant mRNA. And thus, no mutant protein is formed that causes the cell death in the brain, while the wild type allele can still output its healthy version of the protein, which is important for life. And that's actually the same strategy that we use in our K RAS programme.

Patrick Short  19:01  
And so is it fair to say that that general paradigm is one that can be used for many, many gain of function type diseases? Right, so that those are just two examples. But Is that Is that fair to say that many gain of function diseases could be targeted by essentially the same approach where if the one healthy copy is pumping out enough healthy copy, to do what it needs to do, and you just need to get rid of the unhealthy copy? The strategy that we've been trying as a field for many, many years is, is find the protein, engage it, get some machinery to degrade it, but actually, you can go to the source and just never, never printed off in the first place.

Dr. Dietrich Stephan  19:35  
Absolutely. That's that's succinctly said, That's exactly the strategy for gain of function mutations. And it's really, it's keyed off of the ability to, in many cases, sit right on top of the mutation, even if it's a very small point mutation and block transcription, essentially now, there may be cases where we need to tweak and tune that strategy. For example, Um, if the mutation is in a region, let's say that's not not transcribed, and one could imagine a functional polymorphism, let's say, in the promoter region that might or upstream somewhere that might impact gene output, then you start, you know, getting into things that you're an expert in, for example, you know, targeting something that moves, insists with that functional variant in the population, and allows you to still target the mutant allele and inhibit transcription, but but not precisely on top of the mutation, and we can go downstream and inhibit translation as well of the mutant mRNA. Although we think that's less practical, because there are many more copies, usually of the mutant mRNA than there are of the gene itself. And dosing and cadence of dosing and so forth become a little more involved. But yeah, in general, for gain of function mutations, we block transcription.

Patrick Short  20:58  
And how about strategies for loss of function? Mutations? What What can you all in the platform do in those cases?

Dr. Dietrich Stephan  21:06  
Yes, so for loss of function mutation, either, where one copy of the gene, it has ceased to output a functional protein. And that category of diseases, as you know, are generally Haplo, insufficiencies, or where both copies of the gene have ceased output. And those are recessive loss of function diseases, there are several strategies that we can use to increase healthy protein output. So in the case of a haploinsufficiency, what we've shown is that we can drive the healthy copy of the gene harder by opening up the double helix proximal to the promoter. And we've shown that we can boost the ability for RNA polymerase and the transcriptional machinery to engage with a locus and transcribe and we often get 2030 40% increased output from that healthy allele, which is generally enough to rescue the phenotype. So that's, that's the core strategy in addressing Haplo insufficiencies. Now, when we get to complete loss of function of both alleles, we can use established strategies, for example, at the RNA level to pop out truncating mutations and form a functional protein, you know, by inhibiting inappropriate early truncation of the of the protein itself or avoid nonsense mediated decay, complete loss of function, where both alleles, for example, are gone is the one use case that we can't address with our technology and where Gene replacement strategies either the mRNA, or the gene therapy level, I think become, or enzyme replacement therapy, become, you know, become the core strategy that that needs to be invoked.

Patrick Short  22:50  
You all have a very rare opportunity as a as a company that I think few do, which is you've got a platform that's potentially able to address 1000s of diseases. And yes, as you know, there are there are companies that focus on a single disease or a set of diseases because they have a small molecule and an understanding of biology that can treat that disease. But I think you have a very different opportunity in front of you, which is one of the challenges is how, how many diseases do you treat? And at what there is no, the sky's the limit. But there's there are really practical challenges to you can't do 100 At once, or 1000 at once, at least not yet. What what does that scaling process look like what you need to do now to get to the place in the next couple of years that you may be able to be you're having the impact that I think the the platform sounds like it could have?

Dr. Dietrich Stephan  23:37  
Yeah, so So the vision really is to create a single technology that can in a scalable manner, impact really any any disease. And, and so getting to that vision, let's say in 2030 years, where we can simply click together, Lego blocks, delivery backbone nucleobases, even for private mutations, where we understand the performance of the molecule A priori, the FDA is comfortable with, you know, the tox profile of, of this chemistry and how well we as a company can dial the molecules in bioinformatics way before we let them loose in a patient, for example, you know, that requires a methodical and strategic build out to get to that point of and some foresight, and so we think about them as achieving various sort of horizons or plateaus over time, the first is, obviously and move past this is establishing the platform chemistry, chemistry and proving that it works repeatedly in transgenic animal models with human mutations are built into them. So we can now take these molecules we've made administer them systemically either subcutaneously or IV They can get delivered to the tissue of interest, whatever that tissue is in therapeutic concentrations, get into the cell, get into the nucleus, engage with the target and resolve the disease. And so we've now done that with four different genetic targets affecting a variety of different tissues and so forth. And so that was the first VISTA that that we needed to meet. And I think, to convince ourselves that that we remain, you know, deeply convinced that we have a scalable platform. The second is getting our first patients dosed in our first indication, and showing that the compounds continue to be very well tolerated, but that we can also resolve the disease in humans. And it's, it's the reason that we picked a disease that we believe, can show clinical genetic disease, that that has aspects that are reversible in a very short period of time and weeks to a few months myotonic dystrophy type one. So if everything you know goes as planned by mid 2023, we'll have shown that this chemistry that's never been in humans before performs the way it performs in animal models, and that'll be our second Vista, then we would like to have three drugs in the clinic are in the market, five years from founding, so let's say by 2025 2026, and then our internal goal is 10 by 2030. So 10 drugs in the clinic are on the market by 2030. And that's not as a public company. That's not what we're promising. But that's our internal bullseye. And then once once we reach that point, we believe we'll have a level of understanding of the platform where we can begin to scale our output and do so with with partners where we share the load with a now validated platform technology. So that's the build out,

Patrick Short  26:50  
do you have a sense of that the stats are pretty clear in the industry, it takes 10 or 15 years, a billion plus dollars, some people say it's three or 4 billion to develop a new drug. And, you know, clearly that's, that's too long and too much time period. But it's certainly the case for ultra rare and rare diseases. What do you have a sense of what's holding us back there? And do you see a path where we could get that process down to three years and 100 million, you know, as as a as a goal number one, what would what would it take to live in that kind of world?

Dr. Dietrich Stephan  27:23  
Yeah, well, I think those stats are exactly the stats I'm familiar with. And the cost of developing drugs has not gone down over time, it's seems to have stayed static with with those strategies. And I'll call them the non scalable strategies that we had talked about before, where every drug development effort is a brand new bespoke endeavour. So what we have already shown in our first programme, is that we've gotten from target selection to the cusp of ind filing for let's call it about 50 million. And we think the clinical development should be let's call it another 50. And so our first compound with all all of the potential accelerated approvals, and so forth, for a completely unmet need, we think should take five years, and let's say 100 million. Now, the second programme, we've already started to see efficiencies, because it's the same strategy, you know, we can identify the precise sequence that we want to target. Now, we only have to make, let's say, 100 candidates to cover the chemical space of interest as opposed to several 100 in the first programme, because we've gotten better at the SAR and how to design these things. And we've gotten to hits much more much more expeditiously. And so there's the potential now to start shaving time and money off of each subsequent development programme with these increased learnings. And that's, of course, the promise of a platform. And we recently went through an exercise with a brand new target. And we believe that it's two years from target selection to ind, we think we can get there. And then we probably are stuck due to laws of physics at 18 months, as sort of the minimal time it takes but and then, you know, 30 million. And so you can already start to see in these early days, how the cost and and speed are changing and and then, you know, with parallelization and resources after full validation. We think that you know that then it starts to get interesting in terms of increased output. You all went

Patrick Short  29:42  
public much earlier than most biotech companies do. And you referenced this earlier, I was curious what drove the decision behind that because it has I'm sure its pros and cons. Being a public company. There's there's much more that you need to do but you've also got access to bigger, bigger capital markets and it forces is the level of maturity in a company that private companies don't always necessarily have? I was curious what drove that decision?

Dr. Dietrich Stephan  30:06  
Yeah. So. So ideally, it was about, well, just for context. And so in the introduction, you had mentioned that I've built some companies in the past and, and those had generally been venture backed for the traditional way of building a biotech company where you take VC investment and a Series A, and with that first investment, the boilerplate is you generally give up 40% ownership in the company, and the investor gains control of the board. And there are different classes of shares that are created that benefit the investor more than the people that are building the value in the company. And, and finally, investors have a portfolio based mindset in deploying capital, where, you know, let's say only one of many investments need to go through the roof to pay for the losses across the entire portfolio. And so all of those concepts are completely misaligned, I wouldn't say completely, but are misaligned with the incentives of the people that are committed to this one company and bringing all of their hard earned expertise and perspective to the table. And so in my pattern matching over the last 20 years, I've often seen management and the investor board, you know, representation goes sideways. And there's always this constant effort that's required to connect, keep those two connected in the best interests of the company. And it's quite frankly, exhausting. And for people that know how to build companies, it injects more risk, rather than less risk. And so that was the mindset that we went into building this company with, which was alright, if we really believe this is the final generation pharmaceutical company. And it's the culmination of everything we've ever done in our careers before, you know, participate in the Genome Project, you know, find causal variants help build the diagnostics infrastructure for the country, why would we inject additional risk into it. And so we went public, and have been building the company in the public markets over the last approximately three years have maintained complete alignment in terms of board and management. And so I've hand picked each board member because of their expertise. And so for example, there are people like Eric Richman on the board who founded MedImmune, which was acquired by AstraZeneca for 16 billion based on real success, and, and the list goes on. So they had to have done it before, ideally, multiple times. And they had to have emerged undamaged after that process. And that was that was the the type of people that that I wanted to call on. And it's worked beautifully. You know, we've made tremendous progress. There's no friction, complete alignment across all of our stakeholders, whether they're management board or investors in terms of upside. And yeah, I mean, I think we're poised to get clinical data in the short term, which will be transformational for the company.

Patrick Short  33:02  
Tremendous. I did want to ask what you learned from Navigenics and other companies that you've started over the course of your career, because you really have started a company and in many of the major parts of the genomics and precision medicine ecosystem, and you're involved in the early days of the Genome Project, how is the culmination of all that learning coming together? Because it seems from the outside Neubase isn't, you're not just innovating in one area, there's five or six big areas where you've made pretty significant innovations compared to what's being done. So what have you learned over these last decades that you're bringing together into this new company,

Dr. Dietrich Stephan  33:39  
I'd say that maybe there are two major learnings, and then a million minor ones, which we probably don't have time for. But I think the major learning is that it's there, at least for me, it's very important to have a macro perspective on the core opportunity. And, and, you know, we've seen so many people in this industry, you know, going after kind of a second, third, fourth me to sort of generation of, of technology that I think may be incrementally beneficial, while the big opportunity is sitting over here and everyone you know, because they're so used to it can't see it anymore. And so in our example, it's drugging root causality, as opposed to fighting the battle on the fringes. And it's just so obvious, but I think, you know, despite it being so obvious, the vast majority of people continue to fight the battle over here. And so I think that, and Peter Thiel put this so well, in his book from zero to one, it's really been inspirational, and he's an investor and another one of my companies and so I admire the ability to look at the world and not not sort of fall into the trappings of established ways of looking at the world. So that's number one. Number two is I mean, These are problems that no one has ever tried to solve before. By definition, that's what we do in biotech and, and, of course, other industries. But that necessitates I think, creative problem solving, and not just either getting emotional about a problem or thinking a problem is unsolvable. By definition, every day we come to work, it's another problem, it's just problem from a problem, right? And you have to, you have to look at it in a different ways, so that you get through it. But there's also this sort of weight in terms of, you know, not just getting overwhelmed with problems all day long, seeing them as interesting intellectual challenges and solving for them. And I think that's, there's something special in that, that that is important,

Patrick Short  35:46  
if you kept one foot in your academic research routes, or if you've gone two feet in because you you have had a very successful, more, call it true traditional 2030 years ago, academic genomics research career today, it's a lot more blended. And there are people like yourself and George Church who I think is on on your scientific advisory board who have one foot in one foot out in a bunch of different exciting companies, where did you personally fall on that spectrum? Do you like to have one foot one foot in one foot out? Do you go two feet in and then two feet out? On alternating years? Or how do you think about it?

Dr. Dietrich Stephan  36:23  
Yeah, I have, I have now gotten two feet in on the industry side. And there was a period of time where I tried to keep one foot in and one foot out, and, and wasn't quite frankly, very, very good at it. So I've decided that industry is the is the place for me, and, and have loved the that working environment. I mean, it's no nonetheless, excellent in terms of the people that are in that area of this industry. In fact, sometimes the people, you know, because of the sheer magnitude of dollars that are flowing into some of these efforts often have to, you know, have evolved in a different way, where there's a lot more on the line in terms of decision making, and so forth. The one thing I would say, though, and I think this is critically important in this macro environment is that I lean on my scientific training very heavily when I make decisions either about founding a new company, or about what path to take in this current company from a development perspective. And very often now what you see out there in the world are either very young folks, founding companies, which I think is great, and you bring that vigour of youth, but sometimes you do need the depth behind it. And I would urge folks to just surround themselves in that way. But also on the investor side, I mean, there is so much innovation, and so much of it is now being packaged up into companies and being put in front of investors that the sheer volume of it is overwhelming. And that complexity of it is dazzling as the only way I can think of saying it. And so how is it even possible for investors to make deeply insightful decisions these days? And I think that's probably one of the reasons why we're seeing this massive downturn in the biotech markets right now, as investors have just finally realised, it's it's really hard, and you can't just follow the pack. Because, you know, one, one person makes a bad decision on the front end of that, and then everyone jumps in behind it, and it collapses. And so I don't quite know what the answer is, except I think that investors should take a deep breath and really focus on the fundamentals when making decisions.

Patrick Short  38:40  
Yes. And I think for anyone else who hasn't been following this, it has been the last six, six months, maybe even nine months, especially small and mid sized biotech companies, the industry as a whole has lost 70% ish if it's on paper value, of course what that doesn't that is merely a as as I don't know who the was one of the either Buffett or Munger says in the short term, the stock market is a voting machine in the long term. It's a weighing machine, right? So it's, it's merely a voting machine right now we'll have to see in the fullness of time what actually shakes out but the reality is there are a mixture of companies that have you know, maybe to your point, not very transformative science mixed in with companies that have very transformative science and great fundamentals. And right now people are struggling to sort out the difference. And so you have a whole industry that is trading at probably significantly below what it's worth, but it takes, you know, somebody who's got an MBA and and years of experience and a PhD in genomics to figure out what the heck is going on under the hood, how has that impacted you know, you you personally kind of sitting there in the in the cockpit, so to speak, and seeing, you know, this slide happening all around you, but knowing that you've got a 3456 to 10 year plan that you've got to execute.

Dr. Dietrich Stephan  39:53  
Yeah, I mean, this is a marathon. It's not a sprint. And you know, it's it's fascinating the just the guts of building these medicines is so incredibly complex and intricate. And it's almost like building a Swiss watch is it's a good visual. And now you've got a macro environment that adds a whole nother layer of I wouldn't say similar complexity, but another layer of, of just work. And so from that perspective, it's annoying. But, you know, we have, and we have to do things that we wouldn't usually want to do like, turn down the heat on some programmes to extend the runway to make sure that the core value drivers, for example, our clinical data are fully capitalised and don't slow down and anticipate when the market comes back, and so forth. And so I'm just describing extra, an extra set of considerations that we need to bring to the table because of this macro environment. But at the same time, I think it's healthy for the industry. And in that, I think, a lot of fluffy stuff IPO and, you know, the crossover private investors behind that have cashed out and those companies are probably going to go away and not continue to create noise in the system and really focus on the true value creators, the innovators, hopefully allow investors to also focus because now there's a smaller set of companies and perhaps hopefully bring a new discipline to their thinking as to what to invest in. So there's some pain, but I think the quality as is most of the time, the case will make it through and, and continue to build value. So

Patrick Short  41:36  
yeah, I couldn't agree more. And I know we're running up against time here. I just like to say thank you so much for taking the time, it was a great discussion. I'm a huge fan of what you all are doing and working on it really great to understand in a lot of detail what's going on under the hood. So I'm excited to watch your journey for the next few years and hopefully see you all scale up and execute on that vision.

Dr. Dietrich Stephan  41:56  
Thank you so much for the opportunity to talk to you today. It was a real pleasure and and hopefully we can stay connected  moving forward.

Patrick Short  42:03  
Absolutely. And thanks everyone for listening to the podcast. As always, please share it with a friend if you liked the episode and we'd love it if you could leave a review on your favourite podcast player or just let somebody else know that you really liked it. Thanks so much again for your time and we'll see you next time.

Transcribed by https://otter.ai