🚨 Bioverge Access Fund 4 is now accepting investors! Leverage Bioverge expertise and back 15 leading healthcare startups through a single investment. Learn more and invest

The Bioverge Podcast: Engineering Intelligence into Cell and Gene Therapies

Tim Lu, co-founder and CEO of Senti Bio, sits down with Neil to discuss how his company is using synthetic biology to engineer cell and gene therapies with programmable gene circuits to make therapies that are safer, more effective, and precise.

Ayk8vtkvt5ccqioayxrx
Ayk8vtkvt5ccqioayxrx

Tim Lu, co-founder and CEO of Senti Bio, sits down with Neil to discuss how his company is using synthetic biology to engineer cell and gene therapies with programmable gene circuits to make therapies that are safer, more effective, and precise.

Available on SoundCloud, here.

Available on iTunes, here.

Full Transcript

Danny Levine (Producer)
Neil. We've got Tim Lou on the show today for listeners not familiar with Tim, who is he?


Neil Littman (Host)
I am thrilled to have Tim on the show today. He is the co-founder and CEO of Senti bio, a company that he co-founded in 2016. Tim was an associate professor at MIT for about a decade in the departments of biological engineering and electrical engineering and computer science. He was on the SAP scientific advisory board of a number of biotech companies, ton of experience in the space. He has his MD from Harvard medical school, a PhD in electrical and biomedical engineering from MIT. Needless to say, he's got a wealth of experience that combines the disciplines of the biological sciences and computer sciences. I'm excited to dive into what they're building it septic. That's sits right at the intersection of all these disciplines.


Neil Littman (Host)
It's not unusual for synthetic biologists to sound like computer engineers, Tim certainly fits that model.


Danny Levine (Producer)
How do you think that shapes the drug discovery and development approach?


Danny Levine (Producer)
Does it somehow make it more deliberate?


Neil Littman (Host)
I would think so. In, in many ways I think the language that synthetic biologists use are, are really one of a programming language. And, I think, what they talk about is this idea of engineering biology, right. Doing it in a very logical order. Of course it's never quite that easy, right? Biology isn't inherently messy. It's not like you just, you write a program and, a computer script, runs it, there's all these myriad of interactions. I think from a synthetic biology perspective, that's the goal, right. To be able to write some , code and in GNA or program cells to perform in a specific way. I'm excited to talk to Tim cause Senti is developing I guess what they call it, intelligent medicines, we could debate, we know what intelligent actually means, but they're building in these what they call gene circuits. Right. So they're like logic gates.


Neil Littman (Host)
I, I guess it's like a dumbed down fashion, what I can relate to is it's analogous to like writing a formula in Excel, right. It's like, if then, right. If this happens, then do that, right. If you, if the cell encounters, this antigen then kill the cell, if it doesn't, then don't kill this all type of thing. That's a rudimentary understanding. I'm excited to talk to Tim about what these logic circuits, entail and what that means for the development of their therapies. Right. It doesn't make their therapy safer. Does it make them more efficacious, maybe some combination thereof. I'm excited to dive into of some, some of the preclinical Zio detail that they've seen.


Danny Levine (Producer)
What are you hoping to hear from Tim today?


Neil Littman (Host)
I'm hoping to hear how they're using their platform, which is based on, allogeneic cells, specifically natural killer cells that are engineered with each gene circuit. I I'd like to understand the platform technology, why they chose NK cells, what these gene circuits actually do. They're targeting both solid and liquid tumors, but they've really done that actually a masterful job of partnering led by their chief operating officer, Carl Herbert's and have partnerships with spark and blue rock in areas outside of oncology. They really have developed this fundamental platform technology, which could be broadly applicable in the field of cell and gene therapy. I'm excited to hear about that, as a a former BD person myself, I always love to hear about the partnering strategy. I want to talk to Tim about that, but really excited to understand this idea of a programming Dean circuits and what that means for the development of novel therapies.


Danny Levine (Producer)
Well, if you're all set,


Neil Littman (Host)
Let's do it, Tim. I'd like to welcome you to the show today and say a big, thank you for joining us.


Tim Lou (Guest)
Yeah, thanks for having me. I appreciate it.


Neil Littman (Host)
My pleasure. Today we are going to talk about Senti bio, which is a synthetic biology company based on a platform technology that you're developing a, which you described as gene circuits, which I'm really excited to dive into as listeners of this show know, I love talking about technologies that are bringing science fiction to life. It certainly sounds like what you're developing at Senti was in the not too distant past, probably thought to be science fiction, but today it is very much science facts. Really excited to dive into some of the nuances there. Before we jump into some of those details, I'd love to start with of your background. You were an associate professor at MIT for over a decade. You work where your work straddle, biological engineering, electrical engineering, computer science, I'd venture to guess 10 years ago. That was a strange combination of discipline support together.


Neil Littman (Host)
Can you talk about your interest in those areas and how they all came together?


Tim Lou (Guest)
Yeah, thanks to you. My originally interest was computer programming. I was very interested in trying to take a, physical machine and figure out how to do it, do your bidding through to designing, computer programs there. What really peaked my interest in biology was first time I heard about the human genome project as well as the like emerging field of synthetic biology. This is in the early two thousands. What that allowed me to really start thinking about that press biology could be programmed one day as well. At the time I think, it was still relatively challenging to think about that being possible. Over the last 20 years, the cost of DNA sequencing, the cost of DNA synthesis has continued to drop and our ability to read and write DNA has really increased at a tremendous run of scale. As a result, it's actually given us the toolkit now to figure out how to design, do DNA codes, how to stick them into different cells and then see how they function.


Tim Lou (Guest)
I think over the last 10, 15 years, you've seen, I think a really large growth of interest in people trying to figure out how do I start programming biological systems? How do I try to figure out, how natural biological systems are wired up on their own? Can I basically create new programs that carry out some function of interest? I think today, my background wouldn't be so unique or, or special, but back in the day, it was certainly exciting to think about how do we take some of the engineering mindset and approaches that we've applied to the computer systems, clinical systems, et cetera, and really start applying that to biological systems that we've come to really focus on.


Neil Littman (Host)
Tim, and in many ways, Senti bio is full of the language of electrical engineering and computer science as a synthetic biologist. I mean, how do you think about the concept of engineering biology and how does that change the way you will, your approach to developing novel therapeutics?


Tim Lou (Guest)
Yeah, and I think it's important to point out that, the language that's being used here is being used primarily as a way of describing and also in some cases, abstracting away the way we do design. What I mean by that is we use these languages to help us communicate the types of behaviors and circuits that we're building. It doesn't change the fact that at the end of day, we're still manipulating DNA, we're doing genetic engineering, et cetera. The reason why we find this language useful is the same reason why computer engineers or computer programmers use this language because it allows you to go from very low level things. The electrical analogy, it's, how are these electrons moving from one place to another? There's a lot of physics behind them that you need to describe. There's a next level up of them. Like how do I actually build this thing, this physical machine.


Tim Lou (Guest)
There's the higher level of somebody typing on the computer and writing some piece of code. For all of those three different layers to work together, there needs to be some shared language of how the system works. I think that's a concept that's really important in biology and especially because biology is so complex, natural biological systems, aren't really human. They're obviously not human designed. They're guided by evolution over time and evolution is messy. So, the way one gene interacts with another gene in ourselves, there's no clear wiring diagram that exists there. If you want to try to figure out what's there, number one, you need to be able to look at a lot of data at once and process that. And then on the flip side, which is what we're doing here at Senti, if you want to design something, you could either try to just copy the way biology does it.


Tim Lou (Guest)
At some point it probably seeds are human intuition on, how these things actually function. Or you could try to purposely try to build in, build the modules in such a way that you think they're going to actually be more engineerable and stackable later on. That's why we try to use that language here at Santee, because it helps us, remind ourselves that, ultimately our goal is to build, perhaps more complex programs, more optimized programs. If we're going to need to do that, then we need human based ways of describing those to each other and to the outside world.


Neil Littman (Host)
So, so Tim, let's, let's drill down into some of that using that language of programming. In many ways, what you talk about is this concept of programming gene circuits into living cells. We can, we AR can you first start off and talk about what you mean by gene circuit?


Tim Lou (Guest)
Yeah. Gene circuit is again, a form of a description, but basically what we mean by a gene circuit. Typically it's a piece of DNA that we insert into a cell that DNA is encoded with multiple instructions that tell us what to do. Those instructions are in the form of typically multiple genes, right? So, and the reason for that is it's not really that interesting to just put in a construct that just a DNA construct that just makes one protein at a very high level that's fairly straightforward to do. We've known how to do that for quite a long time through the tools of genetic engineering. If you start wanting to build a cell that can sense what's around it, a cell, they can make decisions, a cell that actually hits multiple targets at the same time, but then you actually need to be able to control how much of a gene is being made when that when those genes are expressed.


Tim Lou (Guest)
That dynamic behavior really comes from interactions between genes or genetic components. Simply speaking, I think a genetic circuit is a piece of DNA that has multiple genes on it, and it's been designed so that those genes interact with each other in such a way that it gives rise to, desire, function, the analogy I typically like to use. It's very, again, very similar to, like an electrical circuit that people may have played with in high school. You have your resistor, that's like one component, but if you hook that resistor now up to a battery and to a light bulb, it actually has a different behavior. It's really that full circuit that we're putting together that we're inserting to the cell.


Neil Littman (Host)
And, and so those circuits consist of different, I guess what I would call gate functions. Right? Maybe you could talk about those types of gates that you've built in. If I understand correctly, there's a not gate or an or gate or an if then gate. If there's some biological activity, it triggers one of these gates, which then allows the cell to act or not act in a specific way. Could you, could you talk about how that works?


Tim Lou (Guest)
Of course. Yeah, no, that makes a lot of sense. I would just, the way we think about gene circuits is a general term. The gene circuit can actually be designed to do several different functions. Maybe I'll just give a higher level of review first, before I go into logic gates. For example, we can design a gene circuit to detect or sense things, right? We want sensors just like, the computer I'm talking to you now has a microphone. We want to engineer the cell to be able to detect what's going on. There are certain elements of that gene circuit that basically their function is to detect the environment or detect something special in the body. So those are sensors. There's a second part, which is like you said, logic gates, right? We want to take all that information into the cell. We want to decide what to do with that.


Tim Lou (Guest)
And, and that process of decision-making can be described as logic, and I'll go into that . Once the cell has made a decision, for example, let's say you have a cell that you put into the body, you want it to kill the cancer cell. The cell actually needs to decide, okay, I need to kill this cell coming in contact with, or I need to spare this other healthy cell, but I'm coming in contact with. There's the output side of the world, right? There's many biological outputs one can have. Again, you can encode multiple genes of these gene circuits that hit target a target B target C. So those are different outputs. Those are the types of things gene circuits can do. Like you said, a core component of what gene circuits can do is that idea of logic. I'll give you an example of a logic gate that we are designing here at Santi.


Tim Lou (Guest)
It's what we call the knock gate. We call it a knockout gate and OT gate, because what it does is it protects healthy cells from being killed. Basically what we're telling R and K cells are that we're putting into the body is, do not kill these healthy cells. So that's sort of not Kate does. The way it essentially works is we put it in case our natural killer cell, into the body. It's constantly sensing what antigens, the cell surface that what, what antigens are on every target cell it's going after. If the target cell has a cancer energy and it kills it, but if it has a healthy tissue energy, it doesn't kill it. That's the type of logical behavior that we can put into these products by designing these logic gates. The reason why this is powerful, if you compare it to, for example, chemotherapy, which is probably the most, un-targeted one of the most targeted we treat cancer chemotherapy goes in and it's a carpet bomb.


Tim Lou (Guest)
It kills off many cells healthy and cancer cells here. What we're trying to do with this knock gate is make the targeting much more precise so that we can spare the healthy cells while still kill the cancer cells effectively.


Neil Littman (Host)
In many ways, this is a very precision based medicine approach. T T Tim, you mentioned NK or natural killer cells just to take a step back for our listeners. Can you, can you describe what a NK or natural killer cell is?


Tim Lou (Guest)
Yeah, so a natural killer cell or NK cell is a certain type of immune cell in the body. Naturally, those cells are floating around and they're responsible for getting rid of six cells. Those cells could be sick for a variety of reasons. They could be cancer cells. It could be cells that are affected by a virus, et cetera. Basically their job is to, recognize if a S if a cell is stressed out or, kind of messed up and kill it. Now, it's not the only immune cell in the body. There are obviously other immune cells, people have probably heard of T-cells as well, that are important in the immune system as well, but we like NK cells or natural killer cells, quite a lot because of several reasons. One is, as a name implies, they are natural born killers. It's not that difficult to turn that killing activity in cancer against cancer.


Tim Lou (Guest)
Two is there've been a lot of clinical studies on natural killer cells in cancer that have shown that it has the potential to be very safe in patients compared to other cell therapies that have been attempted. Thirdly, these cells can be used in an off the shelf and what we call allergenic fashion. That term essentially means that you don't have to take the patient's own natural killer cells, and then give it back to them. You can take natural killer cells from a healthy donor, do the engineering that you want, and then put it into the actual patients. The reason that this is potentially very helpful is that it simplifies the manufacturing process potentially makes it much more scalable and accessible. Those are some of the key reasons why we like natural killer cells for our gene circuits, even though our gene circuits, like I mentioned earlier, are these general programs.


Tim Lou (Guest)
We can put them into any other cell type that we care about, but essentially we're focused on these metric killer cells for our internal programs.


Neil Littman (Host)
Tim, I want to spend a few minutes and talk about the allogeneic approach here. Was that a strategic decision that you made at Senti was that based on the biology that led you in that direction and just for our listeners, the allogeneic, as you said, it's f the shelf versus autologous, which are cells from, from the patient. Yeah, I'd love to understand your thinking behind that.


Tim Lou (Guest)
Yeah. It was primarily a strategic thinking that led to come up with an allogeneic product. As I mentioned, when we started Senti, it was really about building this engineering platform for all cell and gene therapies. We've shown at safety that we can actually build gene circuits for T cells for natural killer cells for IPSC derived saw, et cetera. There's no technical reason why we can't work in other cell types. However, in terms of thinking about our own programs and pipeline and the future of cell and gene therapies, we wanted to go with a cell type that had, good safety track record already, and we'll just be much more accessible to people, the patient population that's out there, both in terms of, time to delivery the potential costs associated with making these products, the burden on the patient as well. And, there's a lot of things that are potentially beneficial if you can make it an allogeneic product, because it essentially really reduces the supply chain and manufacturing issues associated with, like you mentioned, the autologous therapies, which are much more labor intensive to produce.


Neil Littman (Host)
Yeah. And, and Tim let's, let's talk about the production of these cells. It more complex to manufacture your cell therapies relative to existing car T's or other types of cell therapies?


Tim Lou (Guest)
Well, I think if you speak in general terms, autologous cell therapy certainly are quite complex to manufacture because you have to obtain the cells from the actual patient. You have to ship them to a facility typically and get it engineered in a very short period of time, and then do all the QC checks before shipping it back to the patient in time. There's a, a time-based complexity associated with any autologous therapy, allogeneic therapies, if you can achieve them, potentially get rid of that issue. Cause you can stop pile the truck and use it as needed. However, with allogeneic therapies, you have to think about how do you expand the cells? How do you make, many batches of the cell, so that's not trivial. How do you freeze the cells? How do you ensure the health and quality of those cells after their thought before delivering to patients?


Tim Lou (Guest)
There is process development and optimization that you need to do, but I think we've made a lot of progress in the field as well, has made a lot of progress in ensuring that is true in terms of, if you compare it to Santis allergenic therapies versus, other folks who are developing algebraic therapies, I wouldn't say that ours are any substantially more complex at the end of the day, what we are delivering is our set of genes into the cells. That's similar to how, previous products have been made and attempted. There's a lot of learnings and portability of those previous experiences. Now for us, we do oftentimes want to build special assays and ways of monitoring that the product is what it is. We certainly do customize how we do manufacturing, but I don't think it's substantially more complex or than other approaches.


Neil Littman (Host)
Tim, do you do the manufacturing in-house or is that something that you work with a contract manufacturer on?


Tim Lou (Guest)
Yeah, so we internally essentially have actually built a, our own internal team for what we call process development and technical operations, so that we can make these cells in house and QC, then make sure that they're good. There are certain elements of the process that, there's just, if there's a contract manufacturer, they can do it more efficiently than us. We, we will consider that, but in general, set, he has control over the overall manufacturing process and the know how that required.


Neil Littman (Host)
Great. And, and what do about how the cells perform based on some of the preclinical studies that you've completed to date?


Tim Lou (Guest)
Yeah, that's a great question. Let's go back to the example of the natural killer cell that has the knock gate. One of the key areas that we want to use that in is in acute myeloid leukemia, which we call AML. One of the key challenges in AML is that, you have patients who unfortunately have, basically, blood cancer and many of the existing drugs that target those blood cancer cells also kill off the healthy blood cells, right? It's it, you always straddling this concern that if I treat the tumor or the cancer really aggressively, I'm also going to hurt the bone marrow or hurt the ability of the patient to produce proper blood or proper hematopoietic cells or immune cells. Where the knock gate is being applied in that process is we've essentially engineered natural killer cells that can affect it. We recognize and kill cancer cells that express a specific set of tumor antigens or tumor targets.


Tim Lou (Guest)
The knock gate is designed to protect the healthy bone marrow stem cell, also known as the hematopoietic stem cell. It does that by recognizing a specific antigen that we call safety antigen. It basically, it's a donate me signal for those cells. So that's how the Nakia functions there. We've now tested this, these natural killer cells in a variety of models. We, we most recently published data at the American society for hematology Ash conference back in December, where we basically showed number one, that this design is able to kill AML cancer cells effectively, both in a test in the lab, as well as in multiple different animal models. So that's on the killing side. You want to do a kill, obviously kill those cancer cells, but it's also able to protect those healthy cells. What we did was to take healthy human donors, were able to isolate those healthy blood stem cells.


Tim Lou (Guest)
We showed that the knock gate was able to protect those stem cells from being killed in a variety of axes. We've, we're pretty excited about that data. We think it's, opening up the door for, like you said, precision targeting of cancer. There's a lot of applications beyond AML that we're looking at now, and hopefully we can move those forward into the clinic for those other indications as well.


Neil Littman (Host)
Yeah, that's very cool. You mentioned that this concept of the don't eat me signal. I remember during my days at the California Institute for general medicine, we funded a similar program. It came out of Irv Weissman lab at Stanford was targeting CD 47. We basically called it was the don't eat me signal. It was really interesting that technology was spun out to 47, Inc. His company was acquired by Gilead, really nice story, but yeah, brings back some, some memories of a program I was close to. So, so Tim then if I think about then how your, therapies or potential therapies are different than what's being done today, right? There's a lot of therapies that enlist the immune system to fight against cancer and in a variety of different ways. The advantages, if I'm understanding correctly of having the type of, I guess you call it intelligence or gated logic built into these cells is, the idea is that they make the therapies potentially safer and more effective is, am I thinking about that?


Neil Littman (Host)
Correct.


Tim Lou (Guest)
Yeah. By the way, going back to what you just described, the CD 47, that's like an actual example of it. Don't you need signal, which is really exciting that the bio body works like that already. So in our case, yeah, you're right. Not that we're designing here is basically an artificial version of that. We're taking what biology does already and basically, figuring out how to apply it ourselves. I think that's a really good, I could use a good example that you just brought up, but yeah, to answer your specific question here, I think the safety and efficacy in drugs is really intimately linked with each other, especially in oncology. I think for almost all the cancer drugs we have, we're always threading the needle between, I want to treat this cancer more aggressively, however, I'm running into some toxicity that's limiting it. The vision here for this knock gate is basically how do we decouple the safety and efficacy issue, right?


Tim Lou (Guest)
If you're re if you have a drug that, hits the healthy cells, 30% of the time, it hits the cancer cell, 70% of the time, there's going to be a limit on how aggressively you can treat that patient. Unfortunately, cause you have to protect the health. You have to limit the collateral damage on the healthy cells. If you can make a product that says, that's basically 0% or 5% on the killing of the healthy cells and 94%, 95% killing of the cancer cells, you can treat those patients much more aggressively. You can dose more frequently. You can dose at higher levels. Hopefully that will translate into a stronger efficacy signal. That's how we view the world, that safety without safety, you can't get efficacy in this system. I certainly, when we're doing our product designs, we're trying to make the maximally effective product, knowing that the safety elements with the precision elements that we're building, it allow us to actually go after certain targets more aggressively or build in more potent product profiles.


Neil Littman (Host)
Let's talk about the development timelines for your lead candidates. You've publicly stated you expect IMD filings for your lead product candidates. 3 0 1 in 2023. Could you give us the highlights of, of each of those programs?


Tim Lou (Guest)
Yeah. Thank you for asking about that. So, as I mentioned earlier, since you two is an allogeneic car and K program that's to address acute myeloid leukemia, it contains the knock gate that we mentioned earlier, which whose goal is to prevent the killing of healthy cells. It also actually contains an additional element, which we didn't really talk about in detail, which is another type of logic gate called the or gate and or gate kills a tumor. If it expresses tumor antigen a or tumor antigen B, in this case, we've identified CD 33 or flip three as the tumor targets. The goal of the Oregon is a bit different than knocking. Whereas the gate is meant to protect healthy cells. The organ is meant to maximize the killing of the cancer cells. The reason why went after CD 33 or flipped three, is that these are both targets that are well-known in AML.


Tim Lou (Guest)
If you can kill any tumor cell that carries either CD 33 or for three or both, then you're naturally going to potentially be much more effective at clearing opportunities. That's essentially the core of what Santi 2 0 2 is. And, and we aim to bring that into clinic, for AML patients, 73 0 1 is a different program it's targeted towards liver cancer. The goal there is to number one, kill liver cancer cells, but to also transform the tumor micro environment that is found in liver cancer. I say tumor micro environment, it's basically, in the tumor and surrounding the tumor finds a way of shielding itself from the body's own immune system. Oftentimes it creates a suppressive environment so that any, any T-cell and K cell B cell that's going to that environment basically get shut off and ineffective it the force field that's being created.


Tim Lou (Guest)
What we're trying to do with the second 3 0 1 program is to penetrate that force field. Number one, we have our allergenic and K cells. We've engineered them with one of these car receptors, kinda primary antigen receptors going after a target called GPC three. It recognizes GPC three, it is able to target those cancer cells and kill them. In addition to that, it actually contains the ability to actually generate two different cytokines. The cytokines are these proteins that stimulate the immune system. One of the cytokines is IO 15, which is important for stimulating in Cate cells, as well as other immune cells. Aisle 12 is another one that is well known to be very stimulatory of the immune system, including for T cells, B cells, dendritic cells, et cetera, all of the cells that are important in triggering a strong immune response. Our goal with 53 0 1 is to be able to not only kill liver cancer cells, but to produce these cytokines inside of the tumor, and really try to knock that force field down from multiple angles.


Neil Littman (Host)
Tim, I'm always curious, how did you go about selecting the indications of AML and liver cancer?


Tim Lou (Guest)
Yeah, that's a great question. I think what we wanted to try to do is match areas of high unmet medical need so that, we want to obviously solve a problem that no one else was currently able to solve. So that was one. We spent a lot of time talking to, key opinion leaders, physicians, no other drug companies in the space to really understand what the gaps were. We segregated, the world essentially to two major buckets. One part of the oncology space are cancers that don't have like a queen antigen to go after a clean target, to go after where the logically concept can really make a lot of hay because, the vast majority of cancers, you can't just find a single target, this a silver bullet target to go after. It's not that simple, but once you have a logic gate that can go after multiple targets, it simplifies the product and potentially makes it more efficacious and safe if you can achieve it.


Tim Lou (Guest)
That's where, AML popped out as one of the indications. Again, there's no perfect antigen there. We thought that logic gates could really make an impact there. We liked the fact that AML patients, sorry, AML is a liquid tumor. It's simpler of a study to go into and, the ability to track responses in patients, by, taking blood out, et cetera, has some potential benefits as well. I think AML was a good first use case for our logic technology. We do have other programs looking into solid tumors, like colorectal cancer that we're working on with similar logic getting programs. The second category is, solid tumors like liver cancer, where there's a target, that's known like GPC three, but there's been, insufficient responses even after going after those targets because of that force field or that suppressive the tumor micro environment. We thought that the gene circuits could really make an impact in that area.


Tim Lou (Guest)
Again, that was essentially looking at the intersection between unmet need versus what we thought was feasible for our first studies.


Neil Littman (Host)
Yeah. Through partnerships, you're actually applying your technology to a broader array of non-oncology applications. You've, you've had some great partnerships that have been announced recently. Can you, can you give some sense of the deals you've made and in particular being a former BD person, myself, that the strategy behind these deals and partnering out, non-oncology, assets or indications. Yeah.


Tim Lou (Guest)
It's funny. One of our investors in the series B was Intel capital. One of the taglines we use internally, although I don't think it's ever been officially vetted by Intel is we want to be the Intel inside of, selling gene therapies of the future. I mean, the types of programs that we're writing now for our natural killer cells, really just one sliver of what's possible and really were directed against the cancer because we think it makes a lot of sense for a company of our size and scale to do that. I think that's, that's all we did. It would be missing the power of the technology. Our approach so far to partnerships has been, outside of oncology, so that we're not creating, direct competition with ourselves. Especially in other cell types or other gene therapy types, we want to find the best partners out there who will be responsible for downstream manufacturing and clinical development, because they have that expertise and infrastructure that we can work together with.


Tim Lou (Guest)
In these collaborations, really what we're doing is we're bringing our know-how and our platform and our IP to the table where we can design genetic circuits that overcome, some of the key issues in the field today. The two partnerships that we've publicly announced, one is with spark, who's obviously a leader in the AAV gene therapy space, basically using adeno associated viruses to deliver genes into the body. They're a pioneer in that area. However, one of the challenges in AAV gene therapy that has been, I think becoming clear over the last multiple years is how do you get these AAV gene therapies to be highly specific for a cell type of interest? Certain diseases may only take place in a certain cell type. You may want, you may not want to hit all the other cell types in the body. And so what Senti is doing there is designing gene circuits that have sensors in them, and that can detect what cell type am I in?


Tim Lou (Guest)
Should I be on, or should I be off? That's where we're applying that gene circuit know-how and design platform with our second partnership. This is what blue rock slash Bayer, they're taking a really, leading position in IPSE regenerate medicine type applications. Similarly there we're designing genetic circuits that are helpful for outfitting, those stem cell based products for function in the body.


Neil Littman (Host)
It's very cool. So, I mean, this is very much what you're building at Senti is this idea of a, a platform, biotech company and in many ways, or I guess, even, maybe it'd be more correct a tech bio company. I, I do, I always love asking this question, assuming that you do consider yourself in this group of tech bio, how do you think about that? I mean, what, what does, what does that term mean to you? What do you think that means in terms of, building a company, not just terms of the technology which we've talked about, but also the culture.


Tim Lou (Guest)
Yeah. Yeah. That's a great question. I think we like to think of ourselves in that vein of what you just described because a lot of the underlying workflow that we're doing at Santi is engineering-based, there's a ton of computational work machine learning, automation, et cetera, that is being built into our design processes. I think number one, that's the mindset that we want to instill in people here is that, every time we design a product or design a gene circuit, it's not like we're going to be one and done, like not only do we want to make that a great product that we can test and patients put two is we actually want to learn from that design experience. We go through all these designs, a lot of them don't work. A lot of them do work to varying degrees. That's all super valuable information that if you analyze the data correctly, if you capture the data in a quantitative way, you can learn about what the design rules are going back to what we talked on the beginning, like biological design rules are complex.


Tim Lou (Guest)
They're not simple. We need that data so that we can crunch the numbers and really understand. Now the next time I do it, can I be 50% better than I did last time? It's really about instilling that the one mindset and ethos into the company, but also building out the infrastructure so that you can capture that data and analyze that data in a quantitative way. That's super important to us. I think that's hopefully how we think about it. And, and the reason for that is ultimately we want to be that platform that could be more and more efficient over time. Hopefully one day, I started off as an experimentalists in this field, pipetting stuff. I hopefully less and less pipetting happens in the future. More and more computer design happens because it'll just really change the economics, the speed by which, and the efficiency by which we can design new drugs, which I think we all want to do to try to tackle all the diseases that are out there.


Neil Littman (Host)
Bring back some memories of when I used to pipette stuff seems like forever ago, and that's actually kind of what drove me out of the lab. I think among other things,


Tim Lou (Guest)
One day, hopefully we will move more and more. I won't say we will get, be able to get rid of it a hundred percent, but I think, we should be trying to minimize the amount of just trial and error that's being done in the field.


Neil Littman (Host)
Yeah, no, I think you're right. Know, one other question I wanted to drill into, we have a lot of, young entrepreneurs who are looking to build companies who are listeners to this show, as you think about the composition of the team, do you have, the uterus all like biologists and chemists, and then do you have hardware and software engineers? Is it a merging of those two? Are you more or less weighted to one discipline versus the other? I'm just always really curious how these teams come together.


Tim Lou (Guest)
Yeah, that's a good question. Our team composition has morphed over time. I think in the early days were, in the process of transitioning these technologies out of academia, figuring out how to really, w we refer to this as robust defying them, right? What's required for publication. In nature of science is very different than what needs to go into human. You need to make sure these technologies work well. I think in the early days, it was a lot of synthetic biology, molecular biologists folks that we brought on board, as a company, got its footing and figure out the platform. We did start bringing in a lot of what we say, more infrastructure, building people, folks who are building that software layer, as well as the computational and, and automation expertise within the company to, so that, at least from our perspective, start capturing the data and generating data and analyzing data in a way that we felt would be useful.


Tim Lou (Guest)
And that's unique to what we're doing here at Senti may not be applicable to all drug companies. Certainly as we've matured further, and as we started to bring programs forward, bringing in biologists who knew how to do the relevant assays to test for like, it's like you asked earlier, efficacy and safety and all those other features, as well as then the people who know how to advance these forward in the manufacturing team, in the cell and gene therapy space, it's not trivial to do that. We've had to bring in a lot of that know-how and expertise. I do anticipate as we get closer to the clinic, we're going to continue to expand, the folks who are actually going to execute the clinical study. It's always a transition process that you have to build. I think we're always hiring and adopting the team. We've been really proud of safety that we've, I think built a great culture here centered around this idea of, gene circuits, be able to potentially transform the way we use therapeutics.


Tim Lou (Guest)
Everyone here is quite passionate about that, and I hope, other budding entrepreneurs can also, bring their knowledge technologies into the field. The key thing is to find great folks that you can actually work with. It's, it's a difficult process to do this. You kind of find people who really actually like working with, and we'll stick with you long through good times, as well as bad times.


Neil Littman (Host)
And Tim along those lines. I guess on a slightly more personal note, I mean, what's enabled you or what motivated you to make the jump from academia to industry and to founding and building your own company?


Tim Lou (Guest)
Yeah, that's a great question. I, you can probably tell, like a lot of my thinking is, is looking at comparable trends or analogies that have happened in the past. If you think about like the semiconductor world and how that transformed our lives. In the last 50 years, there was a time point at which what would really drove. That was something called Moore's law. It was named after Gordon Moore, one of the founders of Intel. Basically he, he drew on a graph that, he could predict every 18 months or every two years, the number of transistors on a chip would basically double. That basically meant that were on an exponential rise in terms of our computing power, right? That's obviously what drove this information revolution around us. And, that was a once in a lifetime thing, the people who figured that was coming, we're able to make tremendous impacts and build long lasting companies.


Tim Lou (Guest)
That was super exciting. I think similarly biology, when we started seeing that, the, the trends in DNA synthesis and sequencing were advancing at the rates that they are, to me that just represented an opportunity to have to be involved in. So, I started off my career in academia at MIT and had a great experience there with the community there, but I just felt that there had to be a company that was going to be in charge of, or not in charge of, but, have a chance at being one of the leaders in this translation of this technology to the real world. I want it to be, involved in that. That's really what led to the founding of Senti together with, like great co-founders and really pulled me away from the academic world into doing this.


Neil Littman (Host)
Yeah. And, and to my, I, I wholeheartedly agree and that's, one of the things I love about my job is this notion of the , this wave that we're riding into the biological sciences and the next evolution of how drugs are developed and, tech and intensity is really at the forefront of that. And, I love being an investor in this space and it's just, it's so cool. I'm just so privileged to have a chance to have conversations with folks like yourself. Tim, with that, I know we could probably talk for the next, four days straight about some of these topics, but I do want to be cognizant of your time and say a big thank you for joining me on the show today.


Tim Lou (Guest)
Yeah, no, thanks so much for the great questions and really appreciate the opportunity. Happy to reconnect with you or any of your listeners in the future, and thanks a lot.


Danny Levine (Producer)
Well, now, what did you think?


Neil Littman (Host)
I, it was a great conversation. I mean, it was, I thought really fascinating to talk to Tim about these logic gates. I haven't heard of any, really anyone else doing this type of gated logic and programming them into cells, but this concept of a not gate or an, or gate or an if then get, you heard Tim describe all of that stuff. It's really, I think really interesting, the impact that could have one making these NK cells much more targeted to destroy cancer cells specifically, and basically leaving healthy cells alone. You heard us talk about this, but that, the, the concept would be that the cells could be not only safer, but also more efficacious. So I think there's, it's really promising. It sounds like they have some compelling, early data. That'll be really, I think, interesting to see what happens as they move into the clinic.


Danny Levine (Producer)
Senti is focusing on developing allogeneic cell therapies. Do you think the whole field is going to move in this direction?


Neil Littman (Host)
Oh, that's a really good question, Danny. I, I'm not sure that it will necessarily move in this direction. You heard Tim talk about the benefits of the allogeneic based cell therapies versus autologous. A lot of it comes down to scalability, how they're manufactured, certainly the cost of goods in particular, right. Well, allogeneic approaches could be much cheaper to manufacture and produce then autologous. I do. However, think that it's going to be indication specific. In other words, I think we will see that the autologous approach maybe is actually a more effective way to go for certain indications, specifically, indications that have a smaller patient population, for example, whereas an allogeneic based approach, you can really benefit from the scalability from the reduced cost. That's going to be probably the only way to go from which a larger patient population. There's a lot of debate whether, which approach is going to win.


Neil Littman (Host)
And I don't view it that way. I think, I think each of them has benefits in different indications.


Danny Levine (Producer)
I think the example Tim offered of the company's AML targeted therapy was interesting because it's a reminder about the importance of not just making therapies more effective, but safer preventing it from hurting healthy cells. I, what does this say to you about the potential for applying this technique?


Neil Littman (Host)
Yeah, I mean, that's critical obviously. I mean, you not only want them safe, what do you need them effective that, there's a lot of other approaches out there bi-specific antibodies, for example, which are targeting to two antigens on a, a tumor cell, for example. There are different approaches to immunotherapies and to biologics that are trying to be much more targeted than, what has existed in the past. And, you heard Tim talk about chemotherapy is like the blunt instrument, right? As that is still very much the standard of care and a lot of, cancer indications, but a lot of these novels immunotherapy cell and gene therapies, right? This is all in the field of precision medicine. A lot of it has to do with, again, you heard him talk about this concept of the tumor micro environment, the ability of tumors to grow resistant, right. How do some of these novel approaches overcome some of those challenges?


Neil Littman (Host)
So, these, these are still major challenges that need to be overcome, but I think there's really a lot of novel approaches to being much more targeted with therapies and being very thoughtful about how to try to, design therapies to get around some of these, tumor, micro environment issues and not just go at it with a blunt force trauma, if you're willing to, and to be really thoughtful about how's the cells are engineered, okay.


Danny Levine (Producer)
Issues like the tumor microenvironment make this a particularly compelling approach for treating cancers. I'm wondering though, do you see this type of approach having potential to treat other types of diseases more broadly?


Neil Littman (Host)
I would. I mean, I would think so. I mean, you've heard Tim talk about some of the partnerships they have that are outside of the oncology indications, right. There was a blue rock 10 talked about for a partnership around induced pluripotent stem cells, which is what blue rock. I guess Bayer are working on you talk, he talked about his partnership with spark therapeutics, which obviously is in the eye disease space. They have an approved gene therapy for, I believe it's a rare version of retinitis pigmentosa if I'm not mistaken. Yeah, I mean, I think what's really cool to me is the broad applicability of what Senti is doing in terms of a platform technology that can be applied across different therapeutic areas and indications within those cell and gene therapy field. It's still early days, but I think it's really fascinating, the different avenues that sentience is taking and how they're going about developing partnerships for some of their non-core therapeutic areas, which is, a tried and true strategy for, building value in a biotech company,


Danny Levine (Producer)
Given this type of capability to build intelligence into therapies. What do you think it says about where we're heading with precision medicine?


Neil Littman (Host)
Yeah, I mean, I, I think the jury is still out until we see clinical data in many ways, but, as you heard Tim say towards the end of the show, right? I mean, he, he talked about his move from academia to industry some of the rationale behind that, because he was so excited about, a lot of these novel events that were taking place in this wave that the industry is riding, so to speak. So, yeah, I mean, I, I, I think we're no question we're moving towards more of a precision or personalized based approach with an oncology field and other areas, we're not there yet to a large degree, but, we may very well look back and, 50 or a hundred years and say, this concept of treating folks with chemotherapy was outrageous, cause it was such a blunt instrument and it wipes out all your healthy cells along with the disease cells, but obviously the best we've had for a long time.


Neil Littman (Host)
Yeah, I think what companies like center you're doing, it's, it's really cool, very cutting edge and holds a tremendous amount of promise.


Danny Levine (Producer)
Well, until next time.


Neil Littman (Host)
Thank you, Danny.


Danny Levine (Producer)
Thanks for listening. The bioburden podcast is a product of buyer where Jake Bessman platform funds visionary entrepreneurs with the aim of transforming healthcare. Bioburden provides access enables everyone to invest in highly vetted healthcare startups on the cutting edge and innovation from family offices, registered investment advisors and non-accredited individuals to learn more, go to bio verge.com. This podcast is produced by over. Use it for this podcast is provided courtesy. Joan will be in collect opinions expressed in this podcast by participants are solely their opinions, not reflecting leveraging or its affiliates. The participants opinions are based upon information. They considerable neither bio verge or its affiliates warranted or accuracy, and it should not be relied on. So nothing contained in the company.