SPEAKER_03 0:03

Good morning, everyone, and welcome to the uh Future Ventures podcast Scaling with Clarity. Today's guest is Dr. Henry Earle, co-founder of Go Kart Therapeutics. Henry is working at the intersection of biology and engineering focused on improving how we treat cancer using cell therapy. Before starting Go Kart, he spent years in research looking at how immune cells can be programmed to better recognize and attack tumors. What he's building now is armed, is aimed at solving one of the biggest challenges in CART therapy. How to make these treatments more precise, more controllable, and ultimately safer for patients. This is a conversation about what it actually takes to build in biotech where science, capital, and real world impact all collide. Welcome to the stage, Henry. Um super excited to have you on and talk about CR T therapy and your company. So um, and and my understanding is that you're visiting family now in Western Europe in Western Germany. So tell us a little bit about uh where you are, um, where you're calling from, and what's your origin story?

SPEAKER_00 1:22

Okay, so um I'm currently visiting family over the Easter holidays, so I'm in a small town in Black Forest, it's called Freudenstadt that translates into happy town. That's actually real. So, well, it got a it got a lot of nature, so uh spending some time, but normally I am based in Berlin, where I'm an alumnus of the Charity Medical School and the Max Sterlberg Center of for Molecular Medicine, which is a Helmholtz Helmholtz. And uh, well, that's how I got into CAR T cells.

SPEAKER_03 1:58

And uh why did you get into CAR T cells? Like, why do you decide to pursue the medical path? Like like tell tell me more as to what what's driving you.

SPEAKER_00 2:13

Well, so sometimes the I don't know, sometimes ideas kind of stick, you know. So um actually the first time I heard of the existence of CAR T cell, which is a specific cancer immunotherapy where you genetically engineer cells to hunt down the tumors. And the origin that uh actually in high school, where I did a presentation on uh gene therapy in in general, and then I read about yeah, you can like get cells, get immune cells out of the patient, then you make them have an artificial receptor with and then with that they can hunt down the tumors and kill the cells off. And that that idea was kind of impressing, and it's stuck it's stuck in the back of my head. And um later on uh I went on to study medicine, and uh from beginning on, I always was thrilled about research and wanted to do do uh more in research and have a big have a big uh bigger doctoral thesis in there. And then I remembered okay, yeah, that that that Cartisel stuff that that was so thrilling to you. Maybe you try try find and do something serious in that space. So looked around.

SPEAKER_03 3:33

Yeah.

SPEAKER_00 3:34

So looked around and uh found uh uh the research group of Dr. Armin Re at the Max Delbruck Center for Molecular Medicine, a sister institute uh that is also in Berlin University Alliance. I was studying at the charité, which is the local medical school. And uh so I got in, and uh that actually started off with how to design a chimeris antigen receptor, how uh how to tune it to a specific antigen. And I ended up with a project where I actually used an existing BCMA car on um on NK cells. They have some disadvantages and advantages, and the main advantage of those is you can use them allogenically. That means you can take donor cells and give them to a patient, and in that case, you can you can treat people with car NK cells even if their own T cells are destroyed by previous treatment, which is around 30% of patients, uh, and then fail to express car T cells, but you can use car NK cells for the uh for those cases. And uh did a project to better tune them into the tumor niche, make them migrate to the tumor, and also design the first car that has multiple targets. That time it was in a so-called OR gate where it kills either target, whatever molecule you want uh you have on there. And uh that's how the problem got uh got into my mind. So the OR gate is nice, it's a good backup mechanism. Should the tumor get resistant or lose one of these antigens, so an antigen is a protein on the surface of a cancer cell, and you want to train it down and kill the cell with it. But actually, there is a big problem. Most good cancer antigens cannot be used. We call them undruggable antigens. Why? And yes, that exactly is because you know, CAR T cells and any targeted treatment approach for that matter triggers all the cells that have this target. So you can only choose targets that are on the cancer, of course, and then on some tissue, some kind of cell, you could lose and still live somewhat comfortably. Okay, but but for example, like CD56 and most good cancer antigens highly expressed on tumors can be downregulated, a driving factor necessary for proliferation, so the tumor cannot easily lose it. That but it's on the brain, it's on like every every neuron, every nerve cell in your brain. And if you kill your cancer and kill your brain in the process, that that's kind of counterproductive. It might be a successful treatment, but I don't think your patients will thank you a lot for doing that. Yeah, so um, and that's actually kind of situation which is the normal case. So most good cancer antigens are in the nephron on the brain, uh hugely expressed on bone marrow or some kind of essential tissue, and that actually leaves 70% of all cancer types out of a specific treatment and also out of CAR T cells. So, yeah, that's basically the main problem uh we try to solve with GoCart, where we develop a system that recognizes two antigens again, but we can match them. We can match them, and our cells need both. We need both antigens to kill, and then we can combine them in a way that uh only the tumor has them. So we could use CD56 as said and C D38, so one is on the brain and the other one is on the bone marrow. Both things you'd rather not lose, but they're never together in nature, but they are together on the tumor, mainly on the acute myeloid leukemia and the multiple myeloma. So we started designing a CRT cell system that can recognize this and selectively kill off the cells that have both, but not the cells that have only one.

SPEAKER_03 8:15

Okay, so if only one of the antigen is present, then no good. If the two of them are present, then in this case using the the CAR T uh method, you're attacking just those cells because you know that those are cancerous cells. Yes, exactly.

SPEAKER_00 8:33

We can choose these, we can choose these in a way that we know for sure that this is cancer and not your brain.

SPEAKER_03 8:42

And then once you identify the cells, how do you attack the cancer?

SPEAKER_00 8:47

That's actually the normal system. So um we let we basically leverage the process your immune system uses for cancer cells and infected cells by standard. So basically, what we do, we take uh T cells or NK cells, these are killer cells, they normally roam around your body and uh recognize unusual or altered cells that are that express something that looks strange or that uh or for the T cells some specific pattern that uh the that is not in your body. Okay, so for example, a viral protein like the uh COVID uh S protein or uh a or a cat or a mutated or dysregulated protein or stress proteins, and if they recognize that they activate their intracellular killing mechanism. So a cascade happens that enhances the signal if uh these signals are on a cell the killer cell connects to, and then these cells have two steps. First, they try like knocking on that uh on that cell, if you want like so. They have a a receptor system like fast and fast ligand. So every cell in your body normally has FAS receptor, and the CAR T cell first tries to show FAS ligand, fast ligand to them. And uh if the cell somewhat works how it normally should, then uh this fast ligands activates the cell's uh self-destruct switch, if you want. So the cell then starts to digest itself and die. If the cell is already beyond repair and the virus has completely reprogrammed it, or it is completely mutated into a cancer cell that has no reaction to FAS whatsoever, yeah, then the uh the the CAR T cell uses its second weapon, which is actually like they have vesicles like bubbles of uh digestive uh proteins inside uh inside them. And if a cell does not respond to this suicide switch, then they throw out these digestive proteins onto that cell and actually destroy the cells on their own. So, this is how the immune cell normally kills off your cancer cells and virus-infected cells, and actually, that's the fascinating part about that. So, if someone has cancer, that means this process must have already failed at some point. There must be some kind of mutated form of cell, the cancer cells, that escaped this recognition and were able to avoid your T and un K cells that normally kill off all the cancer cells you produce. We produce around 100 new cancer cells every day and they get killed off. So if you have cancer, at one of those will have gotten through the through the screening.

SPEAKER_03 12:04

Okay.

SPEAKER_00 12:05

And with CAT cell therapy, we use an artificial receptor. We just put an artificial receptor on the cell that recognizes something on the tumor we choose to basically restore your your immune cell's own healing power to restore their ability to recognize and kill of this type of cell.

SPEAKER_03 12:27

So is this like the least evasive way of treating um cancer? Essentially, using your body's own immune system as the is the killer of the cells, kind of like how would you compare this to alternate cancer therapies?

SPEAKER_00 12:44

Uh well, depends on how you define invasives. So, in terms of change, okay, you genetically engineer a cell, but then it's your own cell. You could call it least invasive, but on the other hand, you we we must say this is a uh side effect-heavy therapy because uh high immune cell activation can actually uh create even life-threatening side effects. One example is so-called cytokine release syndrome, where a lot of tumor destruction and a lot of activation of killer cells floods your body with immune mediators, and you get like inflammation everywhere, so that actually uh the initial the initial the initial car T cell infusion always happens in in a hospital and cancer uh and cancer center settings, so you cannot do that at home. But basically, once you get past the first uh the first part, then you especially within T cells, have a long-term surveillance. So these cells form CAR T memory cells, they stay in your body and can find tumor cells that might come up later and have uh and still keep killing them. And that actually is an extremely effective kind of therapy. So when the first CAR T cells, CD19 CAR T cells came out, um we see one-third of relapsed and refractory uh leukemia patients, which I were on those study, uh cured. And these are patients that uh would be uh palliated otherwise. So there was no you we have exhausted all the kid all the chemotherapy and radiotherapy options, yeah. Uh, and normally we would say, okay, we we treat this patient to the best to the best supportive care we can, but they will they will ultimately die from their disease, and even in that situation, this kind of therapy could could cure one third of them, and uh another third of them was uh tumor-free for several years after that, so that actually is pretty strong results, so it's extremely powerful, and uh can can change the course of uh of the life of a person by quite a lot.

SPEAKER_03 15:21

So, Henry, does this mean that from a treatment perspective that um one of the avenues that um CAR T therapies are applied to to patients that are entering palliative care and all other alternate forms of treatments have failed? Or would you like to see CAR T as a method of treating patients uh earlier in their um in their career uh cancer progression? As well as would you I'm just trying to kind of understand from a market's point, or would you focus on um specific cancer types because this type of treatment would be the most effective?

SPEAKER_00 16:06

Yeah, so um basically a bit of all of that is the reality. So um at the moment we got approved ones for uh treatments of B cell cancers, and um on the one hand, myeloic cancers are easier to access for immune cells, so we see first uh results uh with adaptations of the cells. You need to engineer them more to be effective in solid tumors, but in blood cancers it uh we know it to work quite well. Um so we are kind of moving from a niche into a broad into a broader application, and we with GoCart want to help and accelerate that by abolishing the undruggable antigen problem. So, in general, we we started off with hematologic tumors, and we at Go Kart will do the same to prove the platform, but uh from there on relapse and refractory hematologic tumors, it kind of moves out the ladder. So we already see uh subsequent uh clinical trials using it earlier in treatment and still showing great results. So it uh I expect it to grow at least to a second line treatment uh within the next two decades. On the other hand, uh there is another issue that is raised by that. So the costs of this, at least as it as it's done at the moment, are rather high. That's also something Go Kart tries to tap into by using in-house production methods that can so we can uh have actually have the cells produced at the hospital and just send like the hospital the tools to genetically engineer the cells, lectovirus, for example, so that uh they do not have to have to send the cells to us, or fly them around the globe, fly them back, freeze and thaw them twice. So that actually is kind of a regulatory nightmare. So you it isn't it is necessary at the moment for uh regulatory purposes, but actually each free thaw cycles makes your cell product a bit more shitty. Yep, yeah, if if if the patient already is severely pre-treated with chemotherapy, the cells might be bad from the beginning on. I see these in-house production unit as a huge tool to on the one push down costs by quite a lot, and uh on the second one, improve quality of the cell product, and uh then push and down costs also what we see as a leverage is a modular approach. So, like for example, GoCart uses a common car T cell that is used for every indication now, so not one single car for every type of target antigen, but one for everything, and then we have a sandbox mode where you recombine specific binders, you give them subcutaneously, the patient gets an injection on a regular basis, uh and redirect the cells by this, so we can use the same vector, the same scaled cell products for all uh for all the indications, because that actually is the big cost driver, the uh the cell product. So there are different different leverages to uh push down costs from yeah, at the moment it's uh 400 to 500k in Europe and up to 800k dollars in the US. To uh, I think when we go to market, we could push it to 200k with uh uh with our platform approach, and maybe in the long term we can reach the lower uh double-digit thousands for uh for one treatment, which would be of course the ideal outcome, and that would help scaling into earlier stages by quite a lot. Yeah, yeah, the moment the bottleneck is infrastructure for cell product develop for cell product production.

SPEAKER_03 20:34

And so when you say getting into in in the future, get into double digits. Uh, like are we talking like 10,000, 20,000? How many treatment would a patient need? What do you think it's possible achievable? What would what would be a huge unlock on both? I mean, on the quality side, I get it from a cost and velocity perspective. What would be the huge unlocks for you um or or this type of therapy to get it down into really approachable territories where we're talking like single-digit thousands of dollars for uh for a treat per treatment?

SPEAKER_00 21:09

Uh single digit thousand, I think that's a the uh that's a bit unrealistic. Um because you have in the end you will you have to extract the cells from a patient, then you have then you have to treat the treat them, even though automatic uh semi-automatic units become available. You need the relevant staff to do that, and even without shipping, it takes like one to two weeks to do that. You need to uh you you need to culture, transduce, and expand the cells to reach a relevant amount of cells at a at suitable engineering levels, like we call the transduction rates. How many how much of this cell product is actually successfully genetically engineered and how much not? And you of course want something Ideally 40% or above before you want you want to give it back to the patient. And that's actually something that requires work and special and specialized staff in the end. But uh what we have what we currently have is like estimates of cost of goods, like the pure production costs of around$60,000 uh per one cell product for one patient.

SPEAKER_03 22:27

Okay.

SPEAKER_00 22:28

And I said by standardizing this and uh having like the same vector for all the indications out there, something like we can use with a modular approach. We can use economics of scale and push it down to maybe the the lower double-digit thousands, okay. And then these uh binders are are there to to redirect the cells over time. So uh this can make it uh more accessible in the in the long term.

SPEAKER_03 23:02

How would um how would you use AI to to drive velocity and drive cost?

SPEAKER_00 23:12

Yeah, actually, um we use AI for development of uh of an interface. So what we at Go Kart actually do is we have these end gate, these double recognition, and it works with our binders. So what we have is we have two different binders you choose, for example, CT56 and C D38 a set for AML and multiple myeloma, and that swims around in your body and attaches to its targets on the tumor cell, and if it's a tumor cell that has both of them, then they can heterodimerize. So we have a peptide engineered that kind of sticks together, so the two different of those can stick together, and our CAR T cell is engineered to only stick to these heterodimers, so only if they're stuck together, our cell sticks to that and gets activated. And if there's only one on a cell, then our CAR T cell does not stick to the single one, it needs both of these to stick together, and that actually is what is enabled by uh ML-driven uh protein engineering. So we we with the novel methods of binding prediction, we designed uh peptides that actually can do this with a high with a with a high fidelity and even obtained these artificial candidates in the first place. So something that uh with a high fidelity will stick together, like A and B, I call them, which are the two different on the binders on the tumor cell, and then C is on the car on the on the killer cell. And uh we need to design them in a way that first a and b stick together and only then c comes, and that's done by uh ML-driven uh binding prediction. So we uh what we have is a is an engine that automatically creates and mutates sequences of this specific type and then uh tests their affinities against each other, and then fuse out sequences that do what we want for what we want them to do. So uh at the moment we have screened around 180,000 uh individual trimers, trimeric sequences, and out of this, there is a lot of noise produced and like semi-useful stuff that well can be used to have the AI iterate on it, but could not be a candidate. And from these 180,000, actually, we identified 20 sequences that actually do what they should, and without AI-driven peptide engineering, that would just not be possible. Even the biggest pharma player could not could not produce all these different sequences for such a moons moon moonshot and uh test them in vitro, the costs would be astronomic. So testing one of those in vitro is around uh 1200 euros. Yeah, times 180,000. Uh that might that would probably get even big players in trouble. So these late advances actually are what makes this possible in the first place. So we can select these prime candidates and now we test these 20 candidates, yes, and that's rather doable.

SPEAKER_03 26:55

So, I mean, obviously, AI has been a huge unlock for you in terms of driving precision and quality. Um do you believe that cancer will be eradicated as a disease in the future?

SPEAKER_00 27:09

Uh what is eradicated? So I think we can treat it, we can treat it more. Actually, cancer is kind of like a a hiccup of your natural process, so it's not like a an infectious disease you could find a vector for and then eradicate that like uh that like uh like more bottom.

SPEAKER_03 27:31

But what I you mentioned that your body produces a hundred cancerous cells a day. Uh I are you able to it's actually kind of like you're German, and Germany's known for having some of the best performing automobiles. Can you get the engine tuned up in such a way that it just it's it's performing in such a way that like there's there's never um cancerous uh like that that indigents never surface in the first place, so you never exactly exactly exactly.

SPEAKER_00 28:02

Yeah, that that's that's kind of an interesting an interesting take, like having having pre-built uh CAR T cells in your body or having your immune cells tuned up to the max. But actually, that's that's that's kind of an interesting thing to think about, but um, you have to know the dirty truth about the immune system. The immune system can cause horrible diseases by being hyper-aggressive itself. Okay, that's the whole that's a whole field of autoimmunity, and actually, evolution put the immune cell immune system where it is in kind of a sweet spot between not allowing too much cancer, but also not getting everyone a horrible autoimmune disease, yeah. So, actually, um, kind of like engineering that meddling with that uh will probably need a lot of care if you try that.

SPEAKER_03 28:59

I just said so there's a fine balance, yeah.

SPEAKER_00 29:03

So actually, it's pretty fine balance, and what I see as a future is in cancer. Well, we see that in this case the the balance kind of failed on the cancer side, and and a can and a mutated mutated cell type, a can what we call cancer, got through. And then we can use our genetic our genetic tools like the CAR T cells to hunt that down. And with systems like us, like ours, we have a lot of flexibility. We can we can in the ideal future tune it down to exactly what this what this tumor is. So as we have these binder approach, these adapters, we start with these two binders and approve it in AML and MM to get on the market. We have like a clear path to market and an orphan designation, orphan approval, which saves a lot of money, which shouldn't normally be used on a phase three. We can use the orphan orphan designation to get around this, or at least already have a sellable product when doing the phase three follow-up. Um from there on we want to expand. So we are open to any collaborators. We already have three of those who develop antibodies, we h8 binders in the broadest sense. They need to be a single change, uh single-chain peptide binder, and they can step on our system. You can uh hang on our interface that we develop for a low emission, like five percent or something, and then they can start approve and sell of these binders that fit our system, or we buy the patent of them and develop it further develop it at some point, and then we deliver the CAR T cells, which are kind of like the operating system, and the treating physician of a cancer patient can phenotype this tumor. You can you take histology out of this tumor and really find out what is on this specific tumor of this specific patient, not only the statistic average, but this patient. And then you can recombine these binders and also backup binders if you need them for like for like tumors where half of the tumor has one antigen and the other half another one. Tumor cells constantly constantly mutate and change. Yeah, and then you can use R CR T cells, these binders, and have a system that backs that up and kills that kills them off. And also, modularity can be used to change the course of this treatment uh if needed. So, should should one of the antigens be lost? The tumor stops to express one of them, loses one of the targets. Normally the CAR T cells would fail at that point, but with us, you could look at look into the expression again, look for a new target, and then change to that new binder, and it should keep working. Interesting.

SPEAKER_03 32:04

So if I if I was translated uh into my own words for somebody that doesn't have uh PhD or doesn't have the medical biotechnology background, essentially we're going from one-to-many medicine, we're driving precision medicine, we're going one-to-one. We start with a phenotype analysis of the particular patient in mind, and based on this, we're reconstructing um what kind of binars we attach to this so that it's it's uh um unique and precise to the patient, and it depending on if it's work or it doesn't work, we kind of fine-tune it, we'd add back a binder, so we add different binars that help to attack the okay.

SPEAKER_00 32:48

That's yeah, that's actually the reason. So approaches like this are called personalized medicine. We always the same had the discussion how to make personalized medicines because when when the term came up, it was like designing a whole new therapeutic for one specific patient, and that's extremely expensive. Yeah, that's extremely expensive and not really feasible. So that's like kind of an idea to have it modularized, to have it recombinable, to deliver the huge advantages and that have been shown clinically of a personalized approach while still having all the components as an industrial upscaled product that can be delivered at sustainable costs for uh for healthcare systems.

SPEAKER_03 33:36

So, in essence, is is the vision for Go Kart to become the platform that builds out to to use your worst, build out the operating system, and all of these different partners that you have are just developing buyers and buyers and buyers, and then then you continue to provide that personalization and and precision, and then you have the partners that are kind of the ecosystem around you.

SPEAKER_00 33:59

Yes, so basically we want to be maximum open with the platform because that of course also enhances the value of the platform from a company perspective as well as from a clinical perspective, because the more the more binders out there, the more different antigens on the market, the more options for combination, the more backups a physician can give his patient with that specific uh treatment approach. And therefore, we we want to design an environment where we provide like the CAR T cells, the operating system that delivers the end gate with these binders, where you can use these two different antigens to kill to kill a cancer cell. So we can actually use the undruggable antigens that at the moment are you can use them for diagnosis, but not for treatment. With this, you can. And okay, everyone out there, so in theory, so first uh antibody development companies, of course, because uh we can collaborate on a uh on a project base uh with them and they can approve their own binders, but at some point uh we could also uh we we want to also expand to um to RD teams at universities or something. So also in the long term, the vision is that we offer collaboration like for low commission, where the where actually the partner does the validation and then the clinical trial for a specific binder, or at some point we would like buy off binders from academic labs, or uh we work together with academic labs to to further develop it than in-house once they found an interesting binder for a platform and we want to add it. So the more binders on the uh on the platform, the more powerful the treatment is valuable.

SPEAKER_03 35:54

The platform and so speaking of treatment, if somebody uh is it if if if if we have a um a patient or a loved one of a patient, uh, and somebody's hearing that part, like the podcast, how and when can they get this type of treatment?

SPEAKER_00 36:14

So basically at the moment, well, Go Kart, of course, is the uh is at the very early stage. We are moving from uh in silica to in vitro, so we would need until 2033 to get the orphan uh to proceed to the orphan approval, but you might you might want to look into other specific treatment approaches. Uh talk to uh talk to your oncologists. There are already approved CART regimens if you got like multiple myeloma, diffuse large cell B cell uh uh B cell lymphoma or uh or or ALL, acute lymph uh lympho uh lymphoblastic leukemia, then uh there are approved regimens out there, then you're uh an inclined oncologist should always uh look for clinical trials.gov because actually uh in many situations where standard treatment fails, and in some in some cases we already have very good standard treatment, so uh CHOP for um for lympho prolifer proliferative uh malignancies is actually rather powerful and has been developed over the last a bit more than a decade. Yeah, and yeah, sometimes it makes sense to enroll in in a clinical trial with something that's already that's all that's already being developed and uh is being tested against standard treatment. So some that's something you need to know about clinical trial. You always get at least the equivalent to the standard of care where it's tested against. And there might and potentially you you're getting something better, of course. You need to be uh to be aware that this is then like not completely validated dependent on the stage you are stepping in. Is it is it a phase one? Then even toxicity studies still have to happen. So that's kind of also like a a risk you take. But uh yeah, this actually generates data for us to yeah, for us as researchers to move these types of novel treatments into the validated space and onto the large public market, and also can potentially deliver better results for you as a patient or a loved one.

SPEAKER_03 38:42

So so Henry, you you said that that the data is a key component. What have been or what has been the biggest technical challenge that you have solved today, and what's the one standing in a way going forward?

SPEAKER_00 38:56

Yeah, the biggest technical challenge was to uh automate these uh binder bind uh binder prediction. Okay, basically, you know, 180,000 sequences, designing them by hand and then running them through a through a binding uh binding predictor is not so feasible. Yeah, so we need to automate that. So we what what what we have at the moment is we have this iterative approach that originally used a homo trimer template, so something that just sticks to itself and then run it through a side through cycles and cycles, and it was mutated and then tested against each other and mutated again. And if it moves towards our metrics, then uh that one is used as a template and mutated further and further. So building this engine actually is the uh the the thing that created our valuable candidates in the end.

SPEAKER_03 40:04

Yes.

SPEAKER_00 40:06

And well, big ones moving forward. The next one is of course uh closing our angel round.

SPEAKER_03 40:13

And how much are you looking to raise?

SPEAKER_00 40:16

150k. Okay, so that's act uh that's possible through our collaboration with the University of CADIS, uh, where actually configurations of CAR T cells plus binders are already being developed and tested, so we can use pretty strong synergies. Rather happy to have this collaboration. We could decrease the ask from 500k to 150k through that, and we are currently starting uh in vitro validation, so we express these binders in a human cell line, and we want to find the binders that actually do the same as predicted in silico, and from then on we express them as a car, and then we do my favorite experiment, which I've been done in all in the whole time I've been in car and k and car T cells. The co-culture you take a tumor cell line, throw it into a well, a bucket, if you want so, and then throw in your effector, your killer cell, and with the binders, we of course throw in the binders in the configurations we want, and then we want to see the effect plus both binders and both antigens killed tumor cells with only one binder or one antigen, they should not be killed because that would then be your brain. Yep, and uh that's that's that's the next exciting path uh validation parts. So from then on, we can move into NSG mouse validation, which is like a mouse that has no immune system, but uh, and that means you can uh test human cells in them. So that's kind of like one year in vitro in cell culture, and then two years in the mouse, and then we could move into the first clinical trial or at least file for moving into IND enabling, and starting a clinical trial with actual with the first actual patients.

SPEAKER_03 42:18

Understood. And from our prior conversation, you said uh you you have a great relationship in the University of Curdis, and one of the leading researchers, uh, I don't remember the name of the professor, is is collaborating with you on the development.

SPEAKER_00 42:33

Yes, so it's name it's the Institute of Francisco Garcia Kojal. He's he's department leader at uh Inibica Cadiz, so the Institute for Biomedical and Biological Research down there. And they actually developed like car plus one binder system, so where you could already have a car and then swap out different binders for different targets, like that. What I said, if a tumor gets resistant, you could swap out, or you could use two different binders, and then the car T cell will activate on both targets, and we actually fit in neatly with that. So we have our double binders, so we add the end gate onto this binder approach where we have like two different binders that must be together, and that's the new one, and we can use all the infrastructure down there. So uh we have the experiments established. There's actually only one that is new, that's the expression in human cell line, because that's necessary for our specific type of interface peptide. But all the other all the other validation experiments are already in there, material already in there, machinery already in there. We can use the laboratory. And uh, it's basically a very startup friendly university. So uh we have a sponsored research agreement in place, uh, questions around patents. Present or future are already solved contractually, even.

SPEAKER_03 44:05

So that's do they remain with you in terms of any kind of intellectual property that's developed?

SPEAKER_00 44:10

Or are they that's actually what it says? So uh intellectual proper property from this project uh will remain with GoCart Therapeutics, and we provide uh 125k in two tranches of research proceeds. So that's basically kind of like the use of this 150k, 25k stays within within the company for contingency, and in these two tranches, first 75k at the beginning for uh yeah, for the binder validation uh validation phase, like the in the the inhuman cell line expression and this stuff. And the second tranche when we move to uh the I think I think we lost each other for a short time. What was the last I said?

SPEAKER_03 45:25

Um I don't remember, but uh um we'll have to edit this part. So, in terms of um the research, um the how like the angel round a hundred fifty K, it primarily goes towards the University of Kurdis for furthering the research. Uh, how much of a runway is this giving you, Henry? Like, are we like six months a year? Kind of like, and and obviously we need to find a way to continue to fund you um to be able to scale the research. So, kind of give give me a sense on the capital side, kind of what are the requirements.

SPEAKER_00 46:00

Yeah, basically, that is uh even a one-year runway. So it funds a 12-year project, and okay, and it's possible because much of material and machinery is already there, and we do not have to pay for the uh uh yeah, for the uh for lab rent or something like that. So that's like already in the package, and we need and it's for research proceeds, material, and salary. So uh it's a one it's a one-year package, and the milestones are uh validation of the trimer, and that's the big pay the big patenting milestone. So the first uh that might even happen within weeks that we uh file the patent the the core patent for the whole system with this data that comes from that, and the second milestone is validation of cell killing in this co-culture experiment, and that actually is the major milestone. So, like the in vitro phase is covered by this, and then the next race that is a 5M race, probably a bit less if several grant applications that we filed get through. Yes, uh uh that will fund the mouse phase. Um, also perk is uh uh the the university already has a running mouse trial approval for car plus uh car plus adapter configurations, so saves a lot of bureaucracy to just expand this instead of filing a new one. And yeah, actually, that's also what uh our already interested investment funds in the second round told us. So basically, this Angel round funds us to the milestone where we already have soft commitment.

SPEAKER_03 47:52

Got it, got it. Okay, and yeah, I mean that that's pretty exciting. Um now I know we're coming on to time. Um, if somebody wants to pull out a checkbook and write a check, if somebody wants to follow your work, if they want to get in touch with you, what's the best way to do so?

SPEAKER_00 48:12

We have a website, uh gokarttherapeutics.com, where you have like a rundown on a project and on a tech. You could uh use the info at go cartherapeutics.com to write a mail to uh to us. We are on LinkedIn. I personally, Henry Erdley, um on LinkedIn, or you could reach out by henry.ertly at charity.de okay okay, which is uh which which is also possible.

SPEAKER_03 48:42

We'll drop those in the show notes, that's fantastic. Um kind of like uh a question that is a curiosity question for me. What's a belief you hold about the future of medicine that most people would disagree with? Kind of like where do you see future of medicine moving into?

SPEAKER_00 49:02

Well, I think genetic engineering will have will play a core role in it. Okay, two things two two things will happen. Well, or I think at least they should happen if we can get regulators to go with them. There is one that treatments are even are even more engineered to a specific patient needs. We modify we modify cells, cell types in vitro or uh yeah, ex vivo, like like the CAR T cells, or in vivo, like for uh for some orphan drugs that are that have gene therapies, and uh on this uh and it will get more modular, more patient individual, and actually it will move away a bit from like the the current standard of completely validated uh clinical trials. So we will, for example, with us in Go Kart, there will be clinical trials, of course, validating each binders for one disease. But I think doctors with this will get more freedom to recombine and use different, maybe more patient individual approaches. And that's also something I hope regulators will endorse because we already have clinical results that show that these individualized uh attempts have higher success rate, higher sustained complete transmission rates, then it might be the fully approved and um and guideline correct uh treatment line. We see first steps in the right direction in what I say is the um the FDA modernization act that uh has been started in the US and is currently being uh put into actual law. So with the um yeah, with the uh with a pathway-based approach for uh for compassionate use that actually gives uh gives individual physicians more more freedom to try and use patient individualized uh recombinations and uh treatment approaches. So that's actually something where where I think the future lies, but to get to that future, we need regulators to move with us. Uh we can we can help that with data. And on the other hand, of course, it will get more modular because uh because the modular approach is necessary to deliver this at somewhat sustainable prices. Also, another thing, if you want to look into uh drug prices, you might think that what today is called the orphan drug, the orphan pathway for like situations like relapsed refractory AML, where the patient would have to be palliated with only best supportive care, where you can where it is allowed by FDA and EMA to uh to get on the market after a phase two. If you can if you can prove substantial uh substantial added value in these orphan situations. And I think we should have an honest societal discussion about making this not the orphan pathway, but the standard pathway. Because uh already with the orphan pathway, we are at probably trigger in most cases triple digit million tickets for like the whole party to approve a new medicine, and uh the phase three alone adds another triple digit million, and what it delivers is data on how long does the treatment work and what are rare side effects, and that takes years. So I think we might want to balance more between um added value to a patient because after phase two, we at least know it works, yes, and then we might have it approved, allow developers to earn some money and not have to exorbitantly inflate prices to break even after spending another triple-digit million. Yeah, makes sense, and uh at the same time give the decision to to the patients where they need, and this is where where the physicians come in. We have to make an informed decision, we call it the informed consent to choose a novel therapy approach, or or to stick with the standard of care, and being on the market after phase phase two, yeah, I think can bring down the costs in our healthcare systems by quite a lot because this is the validation cost, not even the development and design itself, but the validation safety, and then the clinical trials, that are the main cost drivers for novel and paid inotherapies.

SPEAKER_03 54:32

Makes sense, makes sense, yeah. So it's almost like running a live trial after phase two, where you're continuing the journey with a patient.

SPEAKER_00 54:41

Yeah, that's basically yeah, basically the same in the orphan in the in the orphan in the orphan approval pathway. This does not mean you you scrap the phase three and do not do not do reports and forget about potential side effects. No, you still do all that research, but you do it while on the market, and that allows you for much larger groups, so much more patients will report data. That's actually the we call that phase four. That's like market surveillance. Once we are on the market, we observe the patients long term and add that to the database on that specific uh specific treatment has to go on for 10 years. And in the and you do you still do this with the today orphan approach, so in the end, the data might be even more valuable, and you are able to deliver value to uh to a larger number of patients at an early stage, and in the end, get a new therapy out there at the at lower costs, which in the end should be our the interest of us all.

SPEAKER_03 55:55

Well, I mean, if if anything, um the speed, the efficiency has a lot of benefits that it brings along with it. Um which one of the big unlocks is is more data means higher quality, more insights. But yes, it's not necessarily without risks, but the risks could be somewhat mitigated through informed consent. And and so if you have this effective monitoring mechanism, you can you can adjust, you can pivot along the way.

SPEAKER_00 56:29

Yes, yes, indeed.

SPEAKER_03 56:31

Okay, uh Henry, it's been fantastic to have you on. Um, I know it's Easter weekend, so go spend some time with the family.

SPEAKER_00 56:39

Um and uh pleasure to me as well, and wish you and all the audience happy Easter.

SPEAKER_03 56:46

Thank you, thank you. Same to you.

SPEAKER_00 56:48

Okay, okay,