90. Flipping the Light Switch on Cells: Deniz Kent of Prolific Machines

[00:00:00] Erum: Denise Kent of Prolific Machines. We are so happy to have you on the Grow Everything podcast.

[00:00:06] Deniz: Thanks for having me.

[00:00:07] Erum: All right. All right. Well, let's get into it. I'm sure we gave a little teaser in our intro, but your company controls cells with light. I mean, this is insane. Can you explain a little bit more about what's going on there?

[00:00:22] Deniz: Yeah, yeah. So, we should probably start by taking a step back and exploring just how we have controlled cells in the past. because I think it's worth grounding people in that before we talk about controlling cells with light. So for the last few decades, we have been controlling cells with molecules and these molecules can come in many different shapes and sizes.

[00:00:42] Deniz: They tend to be in one or two categories, either proteins or chemicals, and we mix them up kind of like cocktails. And then we add them to the cells and different cocktails do different things and this has worked reasonably well it has led to the modern biotech industry which is doing quite a bit but i think it's fair to say that biotech hasn't reached its full potential we there's a lot that cells could that we are currently not using them for.

[00:01:09] Deniz: my opinion is that we should have a better toolkit to control cells that moves away from molecules to non molecular inputs. And if we had a better toolkit, I think biology could do a lot more than it is currently doing. And the things that it is currently doing, it could do better. so that was really the motivation with Prolific and building a new toolkit to control cells using light.

[00:01:31] Deniz: the reason why we're doing this with light is that light systematically solves all of the issues that are with molecules and now those issues range from pretty well and well understood problems like those molecules being expensive to less well understood problems like those molecules being very hard to control in the time axis, very hard to control in the space axis. And these leads to yield and, yield issues and, limits on structural products that can be made. There's issues with sterility, there's issues with reproducibility, and these systems tend to be hard to optimize. Light can solve all these problems because light is the cheapest possible input into biology.

[00:02:10] Deniz: And so Prolific is the floor, bow, jeep, by biology process can be. , but it's also extremely controllable. So you can very precisely control where you shine it and when you shine it. And the time axis gives you yield advantages and the space axis allows you to pattern things. it's also extremely reproducible.

[00:02:29] Deniz: It's sterile. and it's easy to optimize because you can build machines that can administer light and machines can't just make molecules out of nothing. They're all supply chains to make those molecules that then get fed into the machines. And so the big picture vision with prolific is. We're building the world's first machines that will be able to truly control subcellular biology selectively.

[00:02:50] Deniz: I think that's exciting. I think it will lead to a lot of interesting new things becoming available. and it's worth understanding that like the machines that can control biology today. They do exist, they just don't control biology very well. So they control biology very superficially.

[00:03:06] Deniz: they can move cells from A to B, they can move liquids from A to B, more sophisticated ones can, image cells. what I'm talking about is very different. What I'm talking about is a machine being able to control an intracellular process. Specifically. So for example, we have tools that can, activate a receptor on the sepsis cells.

[00:03:24] Deniz: We have tools that can activate an enzyme in the cytoplasm of cells. We have tools that can do precision gene editing. We have tools that can, dynamically toggle transcription. We have tools that can turn one type of cell into another type of cell. All of this can be done with light. Basically any cellular process can be controlled with light at this point, ProGo is building Best tools to do that. We want to make it very easy for people to do this. So nobody needs to have any, particularly sophisticated symbiote experience in order to use this. So we just make it super simple. The constructs come, ready made, ready optimized. We have cell lines that people can use if they don't have cell lines.

[00:04:01] Deniz: The hardware is plug and play with existing infrastructure and the software is also just comes with the hardware. So we're trying to make it super easy for people to have this new and improved toolkit.

[00:04:12] Karl: That's amazing. , I have so many questions about this and I know we'll get into it, but give us some background in terms of you, Dennis, what's your background? You've got a PhD in stem cell biology. how did you find yourself starting this company? What, were you doing before you did that?

[00:04:28] Deniz: Yeah, I've been working in science my entire career. I started working with CD8 T cells in the context of cancer and trying to see if we could use T cells to clear tumors. out that tumors are really good at suppressing the T cell response, so I was trying to understand why that is and whether any of those mechanisms were druggable.

[00:04:48] Deniz: I then moved into the pharmaceutical industry. I was developing a single dose cure for asthma. it's a very interesting project. We're trying to basically reprogram the immune system to respond with tolerance instead of inflammation to whatever you were electrocuting. And then I moved into stem cell biology and I was very interested in salamanders and axlotl and how you could cut off their arms and legs and they would regrow their arms and legs and this is just The craziest thing that I've ever seen.

[00:05:15] Deniz: And I was like, that's amazing. if we could do that, that would be so awesome.

[00:05:19] Erum: regenerating body parts.

[00:05:23] Deniz: and so I started studying the human liver because that's the closest that humans get to being able to be like axolotl and, the liver, obviously you can cut off off your liver and it will regrow. Some people know that, the liver community has been trying to figure out what the mechanism for that is for a very long still not totally clear.

[00:05:42] Deniz: I was investigating that for a while. So I was very fortunate. I was in, one of the best lymphstem cell labs in the world. And we did a lot of single cell RNA sequencing on the human fetal liver and the human adult liver and mapped it out and identified some new cell types and characterized some of those new cell types.

[00:05:57] Deniz: That was very fascinating. So I've got quite a lot of experience with, dealing with cells, which made me acutely aware of the problems with the tools that we have to control cells, which kind of set the stage for building better tools.

[00:06:11] Erum: hmm. Mm hmm. Have you always been very interested in biology? Is there like a moment in time in your youth that sparked you're like, you know what biology? I'm going into it. I'm going into it.

[00:06:23] Deniz: Yeah. I mean, was actually not a super great student in school. My teachers didn't really like me too much. I was a mischievous student. remember moment that really things for me was when I first got into the lab. I was good at science but I wasn't that excited by science until I got into the it's just something about textbooks that just find a way to make science very dry and dull. It was also so psychotic, there was like something about the philosophy of how it was being taught that rubbed me the wrong way, where it was kind of like Here is our knowledge, and you will now take this knowledge as if it was the ground truth.

[00:07:00] Deniz: But the thing that's really exciting to me, and I only really realized once I started going into the lab and doing experiments, is that we don't really know the truth. the whole scientific method is a way for us to slowly uncover the truth. And, that's the part that's exciting. So science is not this thing that you're reading in textbooks.

[00:07:21] Deniz: Science is this thing that we are all co creating. and I think that is not how it's taught, but that is how it should be taught in my opinion. Because if you were to teach science to kids, as it's this thing that we're all co creating and we don't really know what it is, but we can do these experiments to get glimpses into reality.

[00:07:40] Deniz: That is far more exciting than just being like, okay, here's a textbook. This is what it is. learn it and then we'll quiz you on it in six months. that's not very exciting. It wasn't very exciting to me, but getting into the lab and doing experiments. and I specifically remember this one moment where it was, early on in my first project and I, generated some data I remember it was late at night and I remember being alone in the lab and I was like, I'm the only person in the world that knows this little, tiny slice of reality.

[00:08:08] Deniz: I'm the only person that knows it. Right now. tomorrow I'm gonna tell some people, but today I'm the only person that knows it. And that's a really beautiful, exciting thing. if you've never done any science, this is what you live for. and I think the people who end up staying in science are the people that get excited by that, because I also saw other people that were generating data and they were like, Oh yeah, they don't feel it's an emotional thing. if you get excited by that, then I think you'll end up staying in science because it is exciting for me.

[00:08:38] Erum: I think a lot of science for me is being able to ask the right questions and being curious how does like control cells and what a crazy question. and then going down that rabbit hole, which you have done so beautifully with company and everything.

[00:08:52] Erum: But I mean, I love it. I love the way that you explained it.

[00:08:56] Deniz: how light control cells. It very much depends on, , the context. So light can do a lot of different things to cells, So there is the most well understood mechanism for light to control cells is photosynthesis, which is not what we do. , so photosynthesis is light, creating energy.

[00:09:14] Deniz: Mainly studied in the context of plants and algae and cyanobacteria. this is very commonly confused with what prolific does, which is not to use light as a source of energy. What prolific does is to use light as the signal, we use glucose as the source of energy, light as a signal.

[00:09:31] Deniz: light can also do other things, there is a whole field called phototherapy, which is very interesting, where people have been using light to treat diseases. that seems to be based on response of the mitochondria that gets hit by red light and infrared light that induces ATP generation and, reduces, oxidative stress and et cetera, et cetera.

[00:09:50] Deniz: That is again, not what we do. But does that work?

[00:09:53] Deniz: yeah, works.

[00:09:54] Erum: Okay. Okay. All right.

[00:09:55] Erum: Yes. Cause I just bought a red light panel and I'm just like,

[00:09:58] Erum: am I okay?

[00:09:59] Deniz: too.

[00:10:00] Erum: Nice. Yes.

[00:10:01] Deniz: phototherapy works. There's actually over a hundred years of data on phototherapy, so going back to 1903, someone won the Nobel Prize for using red light to treat lupus. we know that light is safe.

[00:10:13] Deniz: We know that light has a bunch of, therapeutic properties on cells and on us. but that is not what prolific does. What prolific does is a different form of light control. So what we do is we take light sensitive proteins from, plants and algae and cyanobacteria that are already eaten. And we attach them to various different things inside the cell.

[00:10:35] Deniz: And at the simplest level, all that allows us to do is to bring things together and to separate them using light. Because these proteins, they have one shape in the dark and a different shape in when you hit them with the right wavelength. And when you hit them with the right wavelength, they bind to each other with extremely high affinity.

[00:10:52] Deniz: And then if you stop hitting them, they dissociate. so that's really it. At the core of Prolific we just bring things together and then separate them using light inside of cells. But it turns out that it's such a simple thing, but it turns out that simple thing can control pretty much everything inside of the cell.

[00:11:10] Deniz: that's the crazy part. Just bringing things together and separating them can control everything. at a high level, that's what we do.

[00:11:17] Karl: so what are the advantages of using light that way? I mean, you say it's, high level bringing things together and pulling them apart. compared to conventional methods for controlling cells, you still have to feed them. what does it enable to be able to do that?

[00:11:30] Deniz: good question. the signaling molecules that I started this podcast by talking about, the signaling molecules are by far the most expensive thing in media. Which is what scientists refer to as the soup that the cells grow in. So there's generally four components to media. There's water, which is very cheap.

[00:11:51] Deniz: There's sugar, which is very cheap. There's amino acids, which is comparatively to the first two more expensive, but still pretty cheap. And then the fourth component is the signaling molecules. And it's the signaling molecules that are extremely expensive in many cases, they're more expensive than gold gram for gram.

[00:12:09] Deniz: And so it is the signaling molecules that prolific eliminates the need for, and replaces with light. That has a number of advantages. It has a, immediate cost reduction advantage, but like I alluded to, earlier in the podcast, it has large advantages and control, the temporal control that you have with light because you can switch it off and switch it on instantaneously, which you can't do with molecules.

[00:12:32] Deniz: you add the molecules into a reactor, coffee here. So you imagine I drop drop of cream into this cup of coffee and then we watch the cream dissolve. This is basically my scale down model of a bioreactor. the cream moves around randomly, So you can't control where the cream goes.

[00:12:49] Deniz: You also can't control when the cream goes where it goes. And this is what we're doing in bioreactors right now. We're adding in molecules and we're hoping for the best. The problem is, having that control ends up being quite important, because the control on the timing axis leads to, your yield. So the tighter the control you have, the higher the yields you can get to.

[00:13:10] Deniz: and on the space axis, control gives you the ability to do patterning. And if you can do patterning, then you can make structured products. And if you can make structured products, you can solve a whole bunch of problems like, structured meat products for planetary health or tissues and organs for human health.

[00:13:27] Deniz: the low hanging fruit there is with higher fidelity representations of disease models. Which is something we're working on.

[00:13:33] Deniz: other advantages, like light is sterile, light is reproducible, machines can understand light. There's a whole host of reasons why you would want to switch from molecules to light.

[00:13:45] Erum: Can you, help us envision how this light is being used? So you're saying it's in a bioreactor. What type of light is it? is it infrared light? I'm just wanting to know, like practically what's going on, in the lab. Okay. Or in the, manufacturing plant, if you want to level up.

[00:14:01] Deniz: these light sensitive proteins, exist a whole, spectrum of, wavelengths. You can activate them in blue, activate them in red, green, far red, even UV. this is a consequence of just natural evolution, because these proteins were initially invented by cyanobacteria.

[00:14:18] Deniz: And then the cyanobacteria evolved into algae and the algae evolved into plants. And obviously this happened over the course of billions of years. evolutionary events happened in different contexts, and because they happened in different contexts, these light sensitive proteins have evolved to be activated by different wavelengths.

[00:14:36] Deniz: So, for example, an organism in the ocean would have a different light sensitive protein to an organism in a rainforest that may also have a different light sensitive protein to an organism in a desert, for example. the reason why these proteins evolved in the first place, like with everything is because they were useful.

[00:14:54] Deniz: And the reason why they were useful is because these organisms, if you imagine you're a algae and you're floating around in the water, , You don't have any of our sensory mechanisms, but you do have a need. And one of those needs is, , knowing where you are. And if you don't have any of our sensory mechanisms, you don't have eyes or um, how does the algae know where it is?

[00:15:17] Deniz: How does the plot know which way to go? and you notice you have house plants, they start angling towards the windows. How do they know where the window is? And the reason why they know is because they've evolved these light sensitive proteins and these proteins change shape when they get hit by light and this shape change triggers, biological responses that allow them to understand where they are.

[00:15:37] Deniz: So with an algae, you can regulate your buoyancy. With a plant, you can grow towards the sun. prolific is absolutely not the inventors of this technology. The inventor of this technology is the cyanobacteria a long time before humans existed and we are just using the cyanobacteria's invention in new ways, that are hopefully useful for human health and planetary health.

[00:16:00] Erum: Yeah, that's so interesting. just have one follow up question. So, you're producing these photosynthetic proteins

[00:16:08] Deniz: photoactivatable.

[00:16:09] Karl: we attach them to various different things inside the cell, and then that allows us to bring different things together or dissociate them inside of the cell, and that allows us to control pretty much everything inside of the cell.

[00:16:21] Deniz: So we have tools to activate receptors on the surface of cells with light, we have tools to activate enzymes in the cells with light, we have, we can do precision gene editing events with light, we can total transcription, we can change metabolism. And very much everything that you would want to do, we can do with light in mammalian cells, which are not normally light sensitive, with the exception of your retina, that obviously has light sensitive cells.

[00:16:43] Deniz: Otherwise you wouldn't be able to see me right now. but other than your retina, mammalian cells don't have any light sensitive proteins. So that's the beauty of it, So only the things that you tag with these light sensitive proteins respond to the light. this is key because with the existing inputs that we have to control biology.

[00:17:02] Deniz: So, for example, a lot of people use temperature to control biology, or they use pH to control biology, or they'll use a molecule that will do a whole bunch of different things. pH and temperature also do a whole bunch of different things. So, for example, you shift the pH or you shift the temperature, you may be impacting the thing that you want to impact in a positive way, but the problem is you're also impacting a thousand other things.

[00:17:24] Deniz: And the nice thing by doing these perturbations with light is The only thing that you are triggering is the thing that you've tagged with the light sensitive protein because mammalian cells are not naturally light sensitive. This is different if you're doing it in plants or algae or cyanobacteria that obviously have natural light sensitivity and so why toolkit has really been built for mammalian cells.

[00:17:49] Deniz: so I think about it like if you have a kid and that kid has a fever and you would like to reduce the fever of your kid. You have several options available to you. One option is you just blast the AC and you get the kid's fever down by blast, but blew the whole house down, but which results in the kid being cooler, which is great.

[00:18:10] Deniz: But now you have other problems. Now your husband is upset. Now your dog is upset. Now your other kid is upset because it's too cold. You've perturbed the entire system instead of just the thing that you wanted to perturb. you can think about our technology as not needing to turn on the A. C.

[00:18:27] Deniz: and instead just getting a cold towel and putting it on the forehead of the kid that has the fever because now you just go straight to the thing that you want to control. You don't control the whole system. this is what makes prolific unique is that we built a toolkit that can control subcellular biology selectively for the first time ever and do that very cheaply and precisely.

[00:18:49] Karl: amazing. I was hoping that you might be able to run us through a use case, for example, like how would this work in a way that benefits the pharmaceutical industry? Could you give us an example?

[00:19:01] Deniz: so there are many different examples how this could be useful for the pharmaceutical industry. one which I already gave is making higher fidelity representations of disease models. So obviously most drugs. end up failing in the clinic. A large part of the reason is because we don't have excellent disease models.

[00:19:20] Deniz: So we either use mice, which can lead to a lot of false positives and false negatives, or we use, in vitro models, which tend to be monolayers of cells, which are obviously not representative, which can be human cells, but are not representative of the full complexity of humans. One way that we can help is by using light to not only grow the cells, but then pattern them into, disease models that much higher fidelity representation of the disease that you're trying to model.

[00:19:50] Deniz: let's say I used to do work in, fatty liver disease modeling. I used to just have, a hepatocyte layer, but instead of just having a single monolayer of hepatocytes, what if you could use, blue light to make the liver cells and then green lights to make the cholangiocytes and red lights to make the endothelial cells and far red lights to make fibroblasts and all of these are arranged, in a structure that highly mimics, the structure in which they are found in this disease state.

[00:20:19] Deniz: And let's say you do this with cells that have a certain mutation in them that drives this disease state, and then you screen all of your drugs on that, you're going to get a much better selection of drugs to take into the clinic that have a much higher probability of working. So that's one example. Another example would be in the production of biopharmaceuticals. So, for example, with antibody production. So, we have been producing antibodies for a long time. and they are great if you live in, developed nation and you have lots of money because they tend to be extremely expensive. If you live in Africa, you actually don't have access to antibodies right now.

[00:20:55] Deniz: Or if you live in Latin America or any, developing country has. Basically, either zero or extremely limited access to, many of the most advanced biopharmaceuticals. that is a function of cost. And the cost is a function of the toolkit that you have to grow the cells and control them. by using light to produce antibodies, to produce cell and gene therapies, we can dramatically bring down the cost of production.

[00:21:23] Deniz: And if you bring down the cost of production, A lot more people can use these things. It doesn't have to be limited to rich people. We can actually give these life saving drugs to everyone, which would be wonderful. So there's a whole bunch of work that we could do and we are doing that.

[00:21:36] Deniz: for the developed countries, obviously companies want to make more money and so we can help them make more money. but There's also new drugs that people want to be able to produce, but for one reason or another, they become very difficult to express. we're actually working on a new project that can take these difficult to express targets that nobody can sell right now, even though they believe that There's a market for because you can't produce them and that can be varied at various different reasons for why you can't produce them.

[00:22:02] Deniz: Some of them have a very short half life. Some of them are cytotoxic to the host, but we actually have a program that prolific, which focuses on these difficult to express proteins and turns them from, difficult or impossible to express to expressible. And there is a large amount of, value to be created there for companies and also just for public health generally.

[00:22:22] Erum: Incredible. Yeah, I love applications and pharma. I love that. It's making it more accessible to people in areas where they can't access this type of health care. so that's amazing.

[00:22:33] Deniz: there are applications beyond farmer as well. So I'm very personally interested in the planetary health applications, which is an area, if you think about biotech, broadly speaking, biotech has been so human health focused. human health is a good thing.

[00:22:47] Deniz: we should have healthy humans. If we can have more healthy humans, I'm very supportive of that. But I do think that biotech generally has neglected planetary health. There are so many interesting planetary health applications of biotech that get basically no attention. At least relative to the human health applications.

[00:23:04] Deniz: We look at the total amount of money going into human health versus the total amount of money going to planetary health. Huge delta there. don't think that should be, I think that the amount of resources that we're putting into planetary health and human health should be roughly equal because their importance is roughly equal, if we are, really healthy, but the world has been entirely destroyed, that doesn't help us. And if the world is really healthy, but we are extremely unhealthy, that also doesn't help us. So we need both. applications of growing meat using light, making dairy products using light. these are things that I'm very interested in.

[00:23:36] Erum: Yeah, absolutely. I mean, we're friends like you, me, Carl, same because this is how we operate a messaging lab. we say a third of our clients are biopharma, a third and bioindustrials, which hits on the climate, the sustainable sustainability side of things, and then, tools and other types of companies that support the biotech.

[00:23:56] Erum: Industry writ large, not just biopharma. So I love it. And this leads into my next question, which is, can you give us more examples of how prolific machines reduces the cost of by manufacturing? Because that is the biggest. Elephant in the room. It's not an elephant. It is like everyone's talking about it, we had the founder of Cauldron on. One of the ways that they're doing, they're reducing the cost is having continuous continuous precision fermentation. thinking about that as I'm thinking of prolific machines. Curious even if you want to do a thought exercise on that.

[00:24:30] Erum: But I think, it's, exactly what we want to talk to you about too, because again, the podcast called grow everything, the idea of shifting from dependence on petrochemicals. I don't want to say eliminate because, there's room at the table for everybody, but

[00:24:42] Deniz: Mm hmm. Mm hmm.

[00:24:42] Erum: we want to be able to make more bio based products.

[00:24:45] Erum: So love your thoughts on this, the costs. Let's talk more about that because you did talk about The signaling molecules and media. I think that was a great, great ad,

[00:24:53] Deniz: if you think about the total cost stack environment factor and you have, inputs, which is a very large chunk, prolific can address the largest part of that, which is the cycling molecules, as we've already discussed Solve the signaling molecule problem. remaining three components are, water, glucose and amino acids.

[00:25:11] Deniz: water and glucose are basically a non issue. Both are cheap as chips. The amino acids are Relatively more expensive, and there's various different ways that you can get around that problem. you can hydrolyze plants and get your amino acids like that, and so you can actually take, for example, plant waste from a farm.

[00:25:29] Deniz: Let's say you have a corn plant, and you know you've harvested the corn, or you've harvested the wheat on your wheat plant, and then you have The rest of the plot, which nobody wants to buy right now, we could actually take that hydrolyze it and then you can get your amino acids like that, which is a cheaper way of getting them.

[00:25:46] Deniz: And then there's a various, interesting new technologies that are coming to the amino acid space. For example, you can thermochemically produce amino acids, basically use chemistry to make the amino acids. Glycine is an example of an amino acid that you already have this, so you can buy glycine for 1, 600 per metric ton, which is extremely cheap.

[00:26:06] Deniz: No other amino acid is that cheap. I do think that we'll see more thermochemical production of amino acids in the future. I'm also very interested in, transamination which is basically like process where you can turn one type of amino acid into another type of amino acid inside the cell.

[00:26:20] Deniz: So you could imagine if you could only need glycine instead of all of the amino acids then you just convert glycine into all of the other amino acids that you need inside the cell. That would be transformative. Okay, so but then moving past that. So these are all like the input problems. I think that the input cost problem will be solved by a combination of prolific and amino acid innovations that we're not doing, but other people are then the next bucket of cost is the capex and there's lots of different ways to think about the capex cost.

[00:26:49] Deniz: one is, you could reduce it by getting more yield, which is what prolific helps with, Because if you can get more yield per unit time per cubic meter, your effective capex cost goes down because your capex cost is a function of how much you can produce per unit time. So if you can produce more per unit time, then you will be able to.

[00:27:11] Deniz: have a lower effective capex cost. so that is something that Pilotic will be able to help with. I think moving to continuous culture rather than that makes a ton of sense and that will happen as well. All of these things will reduce the effective capex cost. And then there's a way to actually reduce the capex cost itself by redesigning the bioreactors.

[00:27:32] Deniz: And I think that will happen as well. we have large stainless steel tanks that were invented by the pharmaceutical industry and they work pretty well, but they were not designed for biotech at large. They were designed for high value pharmaceuticals. I suspect that over the next decade, we are going to see a lot of new bioreactor designs come out, and many of those bioreactor designs will look nothing like what you expect them to look like.

[00:27:58] Deniz: They will not be made from stainless steel. They will probably be made from plastic. They probably will not require clean rooms. They will probably be stackable. So there's a whole bunch of really interesting stuff that is happening. And I think that There will always be stainless steel tanks and there'll be like the sort of typical pharma capex will continue for pharma.

[00:28:20] Deniz: But for the other applications, I am expecting to see a lot of new innovation coming that will completely transform the cost stack.

[00:28:27] Erum: yeah.

[00:28:28] Erum: and I would just say, too, on the cost stack, that seems like you can certainly help with, is a strain engineering part of it, Being able to optimize different strains, maybe even engineer them, To model unique non model organisms. a whole area over there. I was just actually listening to a webinar hosted by Sydenham.

[00:28:47] Erum: and they had a few, people in the industry talking about how strain engineering can be a good lever in this whole. Biomanufacturing stack that you mentioned, because they were all street engineering companies. So that's probably what they were talking about, but, we'll have some thoughts over there on the strain engineering front.

[00:29:03] Deniz: Yeah, I mean, so much of what Prolific does is strain engineering, ? So there's, three parts of what we do. There's the genetic tools, which is, strain engineering, by a different name. there's hardware, and then there's software. another part that we haven't really touched on in that cost stack is after you've solved the input problem and you have solved the CapEx problem, you still have more costs.

[00:29:24] Deniz: And one of the biggest costs ends up being labor, depending on where you are. one of the things that prolific is doing and what I think makes a lot of sense is teaching machines how to control cells and grow cells. Because if you can teach machines how to control and grow cells, then in the future they will be able to do that autonomously to a degree that will be far superior to what any humans can do.

[00:29:47] Deniz: none of these are, I think, silver bullets on their own, but I think when combined and you solve the input problem and you innovate on the CapEx and get higher yields, and then you build autonomy into how you run these bioreactors, I think the combination of those things will take biotech from being something that is used in, niche applications that doesn't really touch that many people's lives to biotech being used Everywhere and touches everything.

[00:30:12] Karl: Yeah, you're speaking, to the converted, I imagined that, you engineer these cells so that they are light sensitive. And then, I'm going to imagine that, we've ordered them from you to produce a valuable molecule.

[00:30:26] Karl: Is it just that you would use one form of light and you're just shooting that light constantly or like, how does the different, applications of light work? would you just put red light on the cells? would there be like, at the beginning of the cell growth cycle, you would maybe use red light and then add blue light later on?

[00:30:41] Karl: Paint the picture what that looks like.

[00:30:43] Deniz: Excellent question. So it all depends on what tools you want to use. So, for example, we currently have four different tools that we offer customers. We have the OptoReceptor tool, which activates receptors. We have OptoMeta tool, which tunes metabolism. We have the OptoPro tool, which tunes transcription. We have the, OptoGest tool that turns one type of cell into another type of cell.

[00:31:05] Deniz: Depending on which of those tools you want, there will be a different engineering scheme, and there'll be a different light patterning scheme. So, for example, if you just wanted one of those tools, then it could be as simple as a single color, being applied to the cells. But what we found is that it is not the case where you just want to leave the light on.

[00:31:25] Deniz: All the time. It is the case where you want to pulse the light and different pulsing patterns do different things. And this will be this Coca Cola secret source of prolific. It's not that we use light. It will be in the specific light patterns that you're using for your specific application. And those light patterns can change over time.

[00:31:43] Deniz: So the light pattern that you're using at the beginning of may not be the light pattern that you want to use in the middle of your run and may not be the light pattern that you want to use at the end of your run. And because that may be different, the cells may have different needs at each of those times. And hence the power of light, because you can actually tune the signaling to the cells evolving needs at different time points, rather than just having molecules, which you just add in and hope for the best, and if the cells need something else, it's like, well, we already added in, I'm going to remove all of this molecule from a 10, 000 liter tank, and you can't.

[00:32:14] Deniz: And so it's like, dump it in and hope for the best is how I would summarize the state of the art molecular biomanufacturing today. I think we should be better than that.

[00:32:24] Karl: you guys engineered the strain for producing this biomolecule, how long does it take you to optimize it based on, the different life patterns that you're going to use for it?

[00:32:33] Deniz: with so many questions, it depends. It depends on, it depends on, it depends. Well, it depends on who is asking this, how much money they're willing to spend, uh, how many other customers, how many other, customers we have at that time, how many different tools they want engineered and optimized, what format they want that engineering and optimizing to happen.

[00:32:53] Deniz: And but let me just. Reduce all of that complexity down into a simple answer, which is, normally for us to take on a new project, it will take us probably about 3 to 6 months to go from someone telling us that they want us to do something new to us having the proof of concept data done that shows that it's possible.

[00:33:14] Erum: yeah, we get it. That makes a lot of sense. Spoken like a true entrepreneur, a true CEO. and I wanted to shift gears, talk about a bit about your, the business development. You recently raised 55 million, which congratulations, sounds like a nice chunk of money to get you moving.

[00:33:29] Erum: for having me. but I'd love to learn a little bit more about how do you prepare? How are you preparing to commercialize your platform? what industry are you going to? You mentioned pharma, you mentioned your four tools. Can you picture your go to market a little bit?

[00:33:41] Deniz: Yeah. So there's, three industries that we are really interested in. One is, meat and dairy. I combine them together because we can address them together using cow cells. and these cow cells can be grown and they can be, producing a whole bunch of high value nutritional proteins, but then you can also harvest those cow cells and sell them as meat.

[00:34:01] Deniz: Or as a flavor ingredient. So there's a number of different things that we can do with them.

[00:34:06] Deniz: and then the, other part of what we're currently focusing on is a cho cell based biomanufacturing platform that uses light to grow and control the cho cells, which is the sort of workforce of the biopharma industry.

[00:34:17] Deniz: And that is tailored towards biopharmaceutical production. So the customers there would be big pharma companies or the CDMOs companies use. to do that manufacturing. outside of there's future work that we're interested in doing and disease modeling and organoids and phalangein therapy and et cetera, et cetera.

[00:34:36] Deniz: The list goes on. but all of the big prizes are really in mammalian cells, which is why we're focusing in mammalian cells in the longer term. I think we will also do non mammalian cell applications because there are some really interesting applications to go after in microbes and we will eventually do it, but there is just so much work to be done in mammalian cells.

[00:34:58] Erum: Yep. we've noticed a lot of companies, in the biotech space, they want to go into, bio industrials or cultivated meat, they raise a bunch of money and then they soon quickly realize, Oh, I'm going to I think we should just go give it to the farm industry because that's where the money is right now.

[00:35:12] Erum: Right? So that is a trend that we see. so dairy and meat, of course, that's, the industrial side that we can unpack a bit more are those. The traditional, livestock, industry, or you're looking to work with cultivated meat, which I know is still very early,

[00:35:29] Deniz: Yeah,

[00:35:29] Deniz: yeah, so on the meat side, consider that being two different customer bases for us. One is the cultured meat companies who are very excited about what we're doing, but generally don't have that much money. And it's unclear how many of them will survive. And then there is the big meat players that do have a lot of money, but move very slowly and, have a low willingness to try new things until, they have to.

[00:35:57] Deniz: so what I see happening is that we'll have some early adoption with the cultured meat companies, but then eventually the big prize. for me is getting the major meat players to build cultured meat facilities using this technology. And I think that they will do it eventually, but I don't think that they will be fast movers because they don't need to be, you know, they're already making a ton of money from slaughtering animals.

[00:36:18] Deniz: They don't need to be a fast mover and disrupting themselves. So see is that, startups be the first movers. and then once the first major meat company builds a cultured meat, facility, all of them will be forced to, because our whole hypothesis around meat is that growing meat with light is by far the most profitable way to make meat.

[00:36:36] Deniz: And all of these companies have a fiduciary responsibility to maximize profit. think that they will switch over to cultured meat in the long term purely because they will want to make more money and this will be the way for them to make the most money, but I don't think that they will do it until of their competitors is doing it, in which case you'll see a series of dominoes fall around the world where all of these major meat players I think are going to start building cultured meat facilities within our lifetime.

[00:37:00] Karl: Yeah. We have seen them all making investments, in this space, even though the space has been, a little hurting the last year and a half or so. Tyson, was a huge investor, in culture bait. and do you have any specific strategies in terms of like how you're approaching each of these markets?

[00:37:17] Deniz: well, we have a lot of data and relationships in meat. so that one we're engaging with, I've actually been very receptive. front the dairy front, Fonterra, one of the largest dairy companies, let our series be.

[00:37:31] Deniz: and so obviously, obviously we're engaged with them and have now started talking to, many other big dairy companies on the farmer and CDMO side. We have initiated conversations with many of the largest pharma companies and the CDMOs, and it's been extremely positive, the feedback that we're getting, which has felt quite good because, you for the last four and a half years, we've just been doing R& D, just trying to prove that this stuff works.

[00:37:55] Deniz: And it's been really refreshing for me going to speak to these customers who have consistently told me that a real problem here that we're solving. And they're really excited and happy that we're offering them this toolkit because they want to use it. that's been really energizing and exciting, especially coming out of fundraising where like dealing with is, uh, the unpleasant and,

[00:38:16] Erum: Yeah.

[00:38:17] Deniz: and, with customers.

[00:38:19] Deniz: , some investors are great. so it's definitely not, but I would say that at least for me, dealing with customers is so much more enjoyable than dealing with investors.

[00:38:27] Erum: yeah, yeah. You're getting that feedback, and you have a range because you're talking to the owners of these, cultivated meat companies or the farmers, I mean, or like the big meat, they're not really farmers, technically, but then pharma side. So you have these, biopharma scientists they're speaking your language.

[00:38:45] Erum: Like you guys are scientists. Of course, it's fun. You guys can just, talk

[00:38:48] Deniz: Yeah. and, it's also, it's a different vibe, Because with investors, they don't have a burning problem that you're solving. You know, they have capital that they need to allocate, but they could allocate it to you. They could allocate it to, a hundred other startups. None of them have this burning problem.

[00:39:02] Deniz: Whereas with customers, Customers actually do have a burning problem. It's like they need to get their costs down or they're going to die or they need to find a way to express this protein or they're going to die. And it's like, they have a burning problem and we are solving that burning problem and that is a very different dynamic and a far more enjoyable interaction.

[00:39:20] Erum: Yeah, absolutely. Absolutely. I did another question because I was looking at your LinkedIn and I noticed that you're a part of the Founders Pledge. Can you tell our listeners what that is and how does prolific machines participate in it.

[00:39:36] Deniz: Yeah. Yeah. Founders Pledge is a really interesting nonprofit, prolific machines. doesn't participate in it. I participate in it personally. what it is is a way for founders to legally commit a certain percentage of their earnings to nonprofits and founders pledge does a really good job charity scene is a bit of a mess.

[00:39:58] Deniz: a lot of different charities out there. A lot of them are doing good work. But a lot of them are not doing good work, and it can be really hard to pass out those things. what founders pledge does is they put a lot of resources into, doing rigorous analyses of all of the nonprofits that exist and trying to figure out, are the ones that are being actually impactful and who are the ones that are not, and then they make available to everyone so that you can direct your charitable givings to the avenues that are actually making the most impact rather than these nonprofits that say they're doing something they actually aren't or the money is flowing elsewhere or etc, etc, etc.

[00:40:35] Deniz: So I've committed a certain percentage of my earnings from profit. Two founders pledge, because I think it's a good course.

[00:40:42] Erum: That's amazing. Cool. I love that. That there's that that exists. amazing.

[00:40:46] Karl: as we, close up and want to be mindful of your time, Dennis, you've had this journey from academic research and become a CEO. Are there any key lessons or challenges you've learned from, that you'd give to aspiring biotech, entrepreneurs?

[00:41:00] Deniz: there's lots. One is, be cautious who you listen to, because a lot of people will give you advice that is wrong, and a lot of people will give you advice that is based on their experiences that are not relevant to what you are trying to do, and so if you overly index on the wrong advice, then you may go down the wrong path, listening to what people have to say, but really not getting swayed too much by people who have never done what you were trying to do before.

[00:41:30] Deniz: especially not close family, close family love you, but will frequently give you bad advice. so, be wary of, you getting advice from parents or siblings on, business stuff because they don't know and they may lead you down the wrong path. Getting advice from people who have done it before is a good idea, but also make sure that they've actually done something that is very similar to what you're trying to do because someone who has started a software company getting advice to someone who is trying to do a biomanufacturing company, that may not work or they they may guide you down the wrong path.

[00:42:05] Deniz: just being very, very cautious and critical about who you're listening to.

[00:42:09] Erum: think that's great advice. I think that's something I don't think a lot of people talk about, but I'm glad that you're being candid and like, look, just, grain of salt, yes, being an entrepreneur is scary. There's a lot going on. It's a complex world out there.

[00:42:21] Erum: There's people that have done things, but let's just, evaluate everything before you make a decision.

[00:42:27] Deniz: and actually one of the best pieces of advice that I was given was, when I was thinking about starting this company, it's around risk and how we view risk. And a lot of people don't do startups because they see it as a very high risk thing to do. that can be true, but it's very dependent on how you define risk.

[00:42:48] Deniz: So if you define risk as probability of creating a extremely valuable company that makes you a billionaire, yes, the risk is high. The probability is very low. That's just, we know this, less than 10 percent of companies will do that. however, I don't think that that's the right way to view risk.

[00:43:05] Deniz: I think the right way to view risk is getting to the end of your life and realizing that you never pursued any of the things that you really were passionate about. That's the real risk. It's not doing something that you're passionate about and failing. I don't think most people view risk like that, but I think that is how people should view risk.

[00:43:24] Deniz: There is nothing wrong with going after something that you're passionate about and failing, but it's very sad to get to the end of your life and realize that you never, pursued any of the things that you wanted to pursue. That's a much bigger

[00:43:36] Erum: Yeah, yeah, wow, that's profound. I don't know how old you are, you seem young, and that's a very powerful thing to think, at your age. Age.

[00:43:46] Karl: Yeah.

[00:43:50] Erum: Gotta use that red light therapy.

[00:43:54] Deniz: and final, thing for me before I sign off is that if anyone wants to work with Prolific, we want to make these tools available to everyone. So get in touch, our BD email is partners at prolific machines. com. My personal email is Dennis at prolific machines. com. If you want to work with us, feel free to reach out to me or feel free to reach out to our BD team.

[00:44:16] Deniz: We would love to work with you.

[00:44:17] Erum: Amazing. Amazing. Thank you so much, Dennis, for coming on the pod. I've learned so much. I still have a million questions, but your time is valuable. All our time is valuable. we need you to go do your thing that you wanted to do. So before you die, so do it. But thank you so much.

[00:44:35] Deniz: for having me guys.

[00:44:36] Karl: yeah, thank you so much.