Deniz Kent PhD of Prolific Machines (August 2024)

[00:00:00] Thanks for joining us on the cultured meat and future food show. We are here in Emeryville, California with Deniz Kent. Deniz, welcome to the show. Thanks for having me back. So the last time we were actually recording a podcast the episode was released in September of 2022 almost two years ago, maybe a couple months shy.

But that was just the recording. We actually, or that was just the publishing, we actually officially recorded that episode maybe, I would say, at least three or four months prior to that. Yeah, it was a long time ago. It was a change. It was a long time ago. I would say well over two years since we actually had that recording.

Yeah, we were in the basement of the Tenderloin. Yeah, IndieBio, famously known, yes, as probably famously known as the basement of the Tenderloin. And even back then, the team wasn’t as big as it is now, and we’ll get into that, but even back then there was quite a bit of a team [00:01:00] working outside of the co founders.

Loosely, how many people do you think you guys were back then? I think probably like 10 to 15. Okay. Now we’re 45. Now you’re 45. Okay. And and and that was San Francisco. Now we’re in Emeryville very close to Berkeley. And I think there’s actually a Berkeley bowl very close to here. And this is an amazing space.

I don’t know. Maybe we’ll do some shots afterward and Cut them into this segment, but we’re in a really cool space. And I’m not just talking about the conference room or you just gave me a tour and this tour was, it was a little bit mind blowing, right? Because not only do you see the different departments, everything that’s happening, the technology, which we’ll get into But everything was state of the art, right?

Very fresh off, how do I say it, like fresh out of the box or whatever you mean, whatever I mean by that. Everything just looked like it was the highest end [00:02:00] technology. And that’s very impressive. And but before I, I get further into that. You guys moved into this space, you said 18 months ago?

Roughly. Okay. And you had mentioned making references to this space. So it’s summer 2024 now. When did you guys know you were going to move into this facility? We were actually in Indy Bayou looking around lab space in the Bay Area. Inspiring because most of the lab space in the Bay Area is just like boring concrete block after boring concrete block.

And then we came to this place, which, for the people who are just listening, we’re in the old jelly bean candy company’s manufacturing and distribution center from the 1950s, which we basically tore out and then retrofitted into, state of the art labs, including, molecular biology lab, a cell biology lab, a hardware workshop, a pilot facility.

And it’s beautiful, you got high ceilings, you got beautiful artwork. It’s a inspiring place to live. Yeah, no, and it’s also a cool area. Of course, there’s Pixar not too [00:03:00] far. But even, I just actually came from University Avenue, Berkeley, Fourth Street. They’ve completely revitalized that.

It was a very short drive. It’s actually very cool to see everything. being, and the term is gentrified, but it’s pretty nice around here. Okay. So that’s the facility. And you said that the facility that we’re in right now is about 40, 000 square feet in total. There’s getting built in phases.

And you’ve your team has completely essentially gutted this building and put a new everything. Yes. What was that process like? Very painful, long and tedious. But, okay. So a lot of times companies, or at least different firms, especially for biotech, they hire like an outside firm construction engineering.

Did you guys do that? Yeah. The, so we had internal team members did the design, but obviously we had outside firms that actually did the construction and hi decks and Okay. Construction crew and all this stuff for interior design and that kind of [00:04:00] thing. So most of the design work was led internally, but the actual Oh, really?

Execution of it was Oh, of course. Yeah. And I wanted to say that it’s actually it not only a cool space from, the walls and everything but also the cubes and the chairs and interior design. It makes you feel like. Holy shit, I’m in a tech startup, right?

Like a next gen tech startup. So that was really cool. Okay, so another big kind of You know thing about that previous episode was that you guys were still in stealth. Yes And so now we have a lot more information. I think there was a couple big outlets that covered what you guys do And I want to get into that and then I want to circle into your background, which might be a little bit redundant if you heard the last episode, but okay, so give us that, the explain it like I’m five of the technology of prolific machines.

Sure. So at a high level, what we’re doing [00:05:00] is building a new toolkit to control cells. So traditionally, the toolkit that has been used to control cells uses molecules. Those molecules can come in different shapes and sizes. They tend to be either chemicals or proteins, and these molecules have a number of problems associated with them.

They can be very expensive. In many cases, they can be more expensive than gold, gram for gram. Meat and what we are always talking about, media. Yeah, these are the molecules that you put into the media in order to control the cells. So there’s just a to take a step back, the media tends to have, four components, broadly speaking.

You have the water, you have the sugars, you have the amino acids, and then you have the signaling molecules. Okay. It’s those signaling molecules that are the most expensive parts of it. I see. They’re cocktails of chemicals. And the fact that they’re expensive is pretty well known. But there’s several problems with them that are more nuanced.

One of them is around control. So these molecules, as soon as you add them into a [00:06:00] bioreactor, you lose control. You lose control over where they go, and you also lose control over when they go, where they go. It’s like dropping a drop of cream into a cup of coffee and then watching the cream dissolve.

Yeah, without spinning it. Or with spinning it. Either way, you can’t control it. The molecules move stochastically. It’s a random movement. And this is a problem, because let’s say you want a certain pattern of timing of the signaling in order to get maximum yields. That’s a very hard thing to do with molecules.

Or let’s say you want a certain pattern to be created in the cells. That’s very hard to do with molecules because they are moving around randomly. And so this lack of control over both the space axis and the time axis is a problem that not you see the effects with various industries that are struggling to use these molecules.

Another problem associated with them is reproducibility. So many [00:07:00] of these molecules, especially the proteins have a lot of batch to batch variability. And this is because they’re derived from biological sources and, back when I was a PhD student, I would do the same experiment with the same recombinant proteins, bought from the same supplier, and you wouldn’t always get the same result.

And you’d call up the supplier and they’d be like, yeah, that’s batch to batch variability, I’m sorry. And that’s even without the user error, which is reproducibility. This is just the input reproducibility. There’s also sterility issues that can be introduced by these molecules. That can be overcome by using viral filters, but those viral filters are expensive.

And generally it’s hard to optimize these systems because these molecules are not something that machines can really understand. And because machines don’t really understand them, it’s really hard for us to create these systems which are easy for machines to optimize. And this all led us to founding Prolophic, me and my two co founders.

And what we wanted to do was to build a new toolkit that would move away [00:08:00] from molecular inputs to non molecular inputs. And the non molecular input that we think is best is light. And so we have been building various different tools to control cells with light. And there’s three parts to that. There are genetic tools, and we can talk a little bit about what those are.

There is hardware to both illuminate and sense the cells. Literally illuminate. Literally illuminate. And and then there are software that can understand what’s happening and then optimize the light patterns to give you the ideal result and different light patterns can be applied at different times to optimize for whatever direction you want to optimize.

Yeah. And I guess when you’re talking about software, you can use software to control a bioreactor settings, right? But it’s very hard to use software to control the cells directly. Yeah. Or even those molecules that are, aiding and assisting and changing the cells, right? But to use software to change light is like literally one to one yes, we can.

Yes. [00:09:00] And what we’re talking about here is really a paradigm shift in our ability to control biology because we’re talking about building machines that can control subcellular biology specifically for the first time ever. We haven’t had machines that can do this. We’ve had machines that can control the entire system.

We’ve had machines, they can move cells from A to B or you move liquids from A to B or image the cells, but we haven’t had machines that can interact specifically with a certain pathway inside of a cell and perturb that pathway without the other pathways being perturbed. Because if a lot of people use things like, changing the temperature or changing the pH, if you do that, it impacts everything, right?

It’s your child has a fever and in order to address that fever, you blast the AC. And yeah, like the child’s getting colder, but now your husband’s upset. All of the other parts of the system have also been perturbed. So if you’re using, if you’re using light, you can. Just address [00:10:00] the thing that you want to address without perturbing everything else.

It’s like putting a cold towel on the kid’s forehead instead of blasting the AC. And the way that this works is by utilizing light sensitive proteins. These light sensitive proteins evolved in nature, so originally invented by Cyanobacteria, and then the cyanobacteria evolved into algae and then the algae evolved into plants.

So all plants have these proteins, all algae have these proteins, all cyanobacteria have these proteins. There’s light sensitivity. Yes, there’s light sensitivity, so you notice the plants will start moving towards the window in your home. Like, how do they know where the window is? They don’t have any of our sensory mechanisms.

Oh, yeah. They know where the window is because they have these proteins that change shape when they’re hit with light. Ah, okay. And there’s various, lots of them, thousands of them, and activated by different colors of light because these organisms evolved in different situations. And so each protein that evolved in a different environment is activated by a different wavelength.

And there’s many different types [00:11:00] of them, but the ones that we use are are dimerization switches. And I’ll explain what that means, but what these proteins do is they have one shape in the dark. And if you hit them with a particular color of light, they change shape. And when they change shape, they bind to each other with extremely high affinity.

And We take advantage of this by attaching these proteins to various different targets inside the cell. So we can attach them to receptors on the surface of cells and then dimerize those receptors with light. Or we can attach them to enzymes inside of cells and dimerize those enzymes with light. Or we can attach, a promoter to a transcriptional activator to control transcription using light.

So Timing is also very important. Yeah, we can tune metabolism using light. So there’s all of these different processes inside the cell that you can control by attaching these light sensitive proteins to various different targets. And this is neat because for, from a food standpoint, these proteins, we’re [00:12:00] already eating these proteins because all plants have these light sensitive proteins and we know that they are safe because we’re eating them all the time.

That’s a very nice thing because a lot of these molecules that we’re using, be it chemical or protein, have some safety concerns associated with them, especially the stabilized growth factors and the small molecules that mimic their effect. They can transform the cells and so there’s an additional benefit beyond cost and control of switching from molecular inputs to non molecular inputs.

But I, I started the podcast by talking about all the different issues with the molecular inputs. And the reason why we’re building this company is because light systematically solves all of those issues. So it’s the cheapest possible input into biology. So prolific is the floor for how cheap any biomanufacturing process can be.

It’s the most controllable because you can very precisely control where you shine the light and also when you shine the light. The control over the time axis allows you to get yield [00:13:00] advantages. The controller of the space axis allows you to pattern cells and make structured products It’s also inherently 450 nanometer wavelength like today is exactly the same as it will be tomorrow and it’s exactly the same a thousand years from now you don’t have that input reproducibility with molecules It’s also inherently sterile so you don’t need viral filters to sterilize your recombinant proteins anymore And importantly, it’s a digital input, right?

So machines can understand light because it’s just electrons running through a circuit board, going into an led. And that’s important because it’s getting, so one way to think about what we’re doing is getting biology into a format that machines can understand and optimize, because if you can engineer cells to be light sensitive, which we can by tagging these various different targets with light sensitive proteins, Then you can toggle those targets on and off by shining the right wavelengths onto the cells, right?

So you have a way of specifically [00:14:00] interacting with subcellular biology the specific being important because these cells are not naturally light sensitive So the only parts that are Light sensitive are the things that you’ve tagged with these light sensitive proteins So you have the biology being light sensitive.

You can also build machines that can administer the light So you’re bridging the gap between this biological world You And the mechanical world that haven’t had a way to directly interact with each other until now, which is what we’re doing. And so it’s I see prolific as like the first generation of machines that can truly control biology.

Okay. And so a few questions here I’ll go in the order as they were coming in. So first off are you customizing the proteins so they are reactive to light? Excellent question. The first generation of products that we’re building, which is tools and hardware and software, which we’ll make available to everyone.

This is just using naturally occurring light sensitive proteins. Okay. So we don’t edit. Like a plant that goes towards the window. [00:15:00] Exactly. We don’t edit the light sensitive proteins. We use them exactly as they exist in nature. The second generation of our products will have those light sensitive proteins improved in various different ways.

And what you can do is introduce point mutations in the light sensitive proteins that change their properties. So you can change the wavelength at which they are activated. You can change the on off kinetics because all of these proteins, the shape change that I’m referring to is reversible. It tends to, switch on in the order of.

Milliseconds to seconds, and then off on the order of seconds to minutes, but you can change those things. You can introduce mutations that will make that faster or slower. And we’ll continue to innovate on the optogenetic tools, but we want to get out Customers with the tools that already exist, which we have been showing works and can deliver value immediately whilst continuing to innovate on the back end.

Okay. And then alluding to my earlier question about media. So your systems are still running media, just cheaper [00:16:00] media because it doesn’t have that, I guess the cocktail is the whole thing, but it doesn’t have that expect expensive component of that cocktail. We still need media.

Yeah. We still need media, but you don’t need the most expensive part of the media. So our media is much simpler. We just have sugars and amino acids and water, all of which can be sterilized a lot easier and as much cheaper than the signaling and more consistent and more consistent. The signaling molecules are, The bulk of the media cost, 90 plus percent of the media cost comes from the signaling molecules.

And so from a technology standpoint, you described the system, but what we saw, the hardware was very cool. Essentially, this wrapper around the bioreactor vessel that was, with these LEDs and all controlled by the software. And you had mentioned the LEDs themselves are off the shelf.

So cheap. Yeah. Very cheap. Very accessible. Very abundant. LEDs have thankfully become commoditized by the consumer electronics industry, which is why it’s a great [00:17:00] thing to use in cultured meat, because we want cheap. Oh yeah. Of course. Yeah. The whole point of doing this is to make things Consistent.

Cheap. Consistent. Bulk. Exactly. So LEDs are very cheap. The LEDs give you control over the time axis, but they don’t give you control over the space. So if you want to go down the space access, you have to use lasers. Those lasers are more expensive. They make they give you control of the space access, which means that you can, you can use a laser and mirrors to project different colors of light in different places.

Okay. And that allows you to make structured products. And those structured products command a higher premium. So the hardware is more expensive. The price of those products. But yeah, for the bioreactors and just growing up cells, making, make, allowing our customers to make ground products that just uses LEDs.

Okay. Yeah. And I guess that’s in production, right? But these, this and, okay. So we, I, I was introduced to this term through the I think these these articles that [00:18:00] recently came out, but up to genetics. Did I say it right? Tell me about the typical application or research for optogenetics before you guys came into the picture.

What is optogenetics typically used for? Is it used for a similar type of thing or different things? So optogenetics prior to Prolific was a research tool to interrogate biology, right? So you can be like, I am interested in understanding how pathway X is involved in process Y. You can build an optogenetic tool to interrogate that question.

And the vast majority of the research had happened in the context of neuroscience. Oh, okay. And people had been controlling neurons with light and probing things like how does consciousness work? How do we make decisions? Can you, and people have even shown that you can control, you can use light to, to control how a mouse makes a decision, for example.

Okay. Prolific was definitely inspired by the field of [00:19:00] optogenetics. We’ve been building on it quite a bit and so we’ve been taking the tools that exist and making them easier to use and making them accessible to people. Because academics did a really great job at building this technology or like The building blocks of the technology, but didn’t really think about how it could be used to manufacture things at scale.

So nobody was really doing bio manufacturing with optogenetics. So we were the first to do that. Okay, so production with, getting to production with optogenetics. And using light as a manufacturing tool, I think is very interesting. Oh, yeah. And something that nobody was doing. And even more interesting than using it as a research tool, for the reasons that we’ve discussed.

And so now we be we built tools to, activate receptors using light, so eliminate the need for growth factors and get yield advantages. We’ve built tools to differentiate cells we’ve built using light, we’ve been built tools to control transcription using light, we’ve [00:20:00] built tools to control metabolism using light.

And so all of these tools are now available to people in a format that is very easy for them to use. The DNA is ready. The hardware is ready. The software we can give to them will be connected to the hardware and that hasn’t been available to people. People have just had. Molecular tools available to them.

And so now with this expanded toolkit I think that a lot more things are going to be possible in biology and biology in general, not just cultured meat. I think that’s very exciting. Yeah. I think we’re we’re on the cusp of a new era of biology where a lot of things that we thought was just not possible like economically viable cultured meat, I think is about to be possible.

Okay. So one more question, then we’ll do a short break. So when customers can come to you now I can imagine that you are selling a hardware piece that comes with a software piece. Are you also selling protein? We’re selling genetic tools. Okay. The whole, yeah. We’re selling the whole gamut.

So the way that it works is customers would tell us these are the tools that we’re interested in, interested in [00:21:00] OptoReceptor or OptoPro or things like that. Optometer, which is the metabolism tool. And once they tell us the tools that they’re interested in, I’m very happy to talk to people about that.

They can reach out to me directly at Deniz. prolific machines. com or they can reach out to our commercial team of partners at prolific machines. com and we’ll talk to them about the tools that we have, share our data. And once we know the tools that they want, we would design the hardware embodiments that.

works best for those tools, because each tool has a different level of precision requirements. So you imagine you just want to dynamically regulate a growth factor receptor. That’s a different precision requirement to, you just want to do a bulk differentiation of all of the cells into adipocytes or myocytes or whatever it is that you want to do.

So depending on what tools they want, there’ll be a different hardware embodiment that would work well. Great. So There’s two ways to interact with us. One is, you can tell us the tools that you want. We would send the customers the [00:22:00] tools, they can do the engineering, or they can send us their cells and we can engineer their cells with the tools that they want.

Different price points associated with each of those options depending on obviously different costs to us. And then, Once we know the tools that they want, we would send engineers to their facilities to retrofit their existing bioreactors. So you don’t need to buy new bioreactors to do this. We, all of our hardware fits into existing bioreactor infrastructure.

And then the software comes with the hardware. It would be like a, basically like a prolific machines app where you can log in and you see all of the, See all the reactors that you have live. You see how the cells are doing. You can tune the light patterns, whether it’s on site here or you build it for them.

Totally. Yeah. Okay, cool. So we’ll do a quick break and then we’ll come back. This is fascinating stuff.

Okay, we are back and you just gave us a really introduction to the technology and [00:23:00] the process. Really product suite for prolific machines. And we learned about optogenetics. We discussed it on the first show, but now that we have the frame of reference, the context for the technology tell us about your background before prolific machines.

Sure. I’m a scientist by training. So I Spent most of my career on the bench. I started working with CD8 T cells in the context of cancer. Cancers are very interesting because they can evade your T cell response. And that’s one of the reasons why cancer is such a big problem is that they’ve found various different mechanisms to basically evade your immune system, especially the T cells, which are like the effector cells of the main effector cells of the immune system.

As I was studying How does that work? Like how does the cancer evade the T cells? And it turns out that one of the main mechanisms is for a chemical called adenosine. And so I was looking at whether we could block that signaling pathway. So I was co administering the T cell treatment with adenosine blockers to [00:24:00] see if we could increase the ability of the T cells to kill the cancers.

I then moved into the pharmaceutical industry at GSK and I was working on a single dose cure for asthma. We’re basically trying to reprogram the patient’s immune system to respond to an allergen with tolerance instead of inflammation Because obviously asthma is an inflammatory response Based on your immune system thinking that the thing that you’re inhaling is a threat and it’s not a threat but your immune system thinks it’s a threat and then it, you know destroys your lungs by Responding as if it’s a threat when it’s not so we were trying to like an allergy.

That’s what Basically the same thing. They’re both allergic responses. And so we’re trying to reprogram the immune system to not do that, to treat this allergen with tolerance. And so it was a lot of dendritic cell engineering, which is the type of immune cell. And then after that I went back into academia for my master’s and a PhD and.[00:25:00] 

I was really interested in Axel lot and salamanders, these reptiles that you can cut off their limb and they’ll regrow their limb. I dunno if you’ve watched the timelines videos, but I are super fascinated by this. How is this happening? , how they regrew that arm. And I was very interested in trying to understand the mechanism of that and then seeing if we, do we know why that happens or how that happens?

We do. Okay. At least a we know we know we know a little bit about it. We’ve asked a few salmon Exactly. Like with all these things, I think we know enough to know how little we know.

And so I was interested in trying to understand tissue regeneration and see if we could get that. Could we engineer humans that, could regrow arms and legs? That was a very exciting thought for me. And so I was very fortunate. I got accepted into one of the best liver stem cell labs in the world and started doing my PhD in that lab and did a bunch of different projects there.

But it was really exciting. Mainly based on two projects. One was doing a lot of single cell RNA sequencing on the human fetal liver and the human adult liver to try and understand how does the [00:26:00] liver regenerate because the liver has this incredible capacity. You can cut off half of your liver and it will regenerate.

Other organs don’t do that. You cut off half of your lungs. You only have half a lung now and, but your liver will regenerate. And our hypothesis was that if we could better understand how the liver regenerates, Maybe we can better understand how we could engineer other tissues. That’s how you got into this lab from that concept.

Yes And so we after we did a lot of the single cell sequencing we found that there was a lot more complexity in the liver than people thought so what people were calling leather stem cells ends up being seven different populations of cells that nobody had seen because they hadn’t done single cell sequencing and then then I spent several years characterizing one of those subpopulations that Has some properties that we were very interested in because it could make Areas cells and could suffer a new.

So we were like hypothesizing around whether this was the true liver stem cell. And there’s a lot of characterization to be done around that. Like how do you [00:27:00] sort it? How do you grow it? What’s the right media? What’s the right scaffolding? What happens if you put it into mice? All of these questions that were outstanding.

Could this be a cell therapy candidate? And the other part of my PhD was around disease modeling. So again, in the liver. So I was interested in trying to use these stem cell derived liver cells as a way to better understand and treat liver diseases. And there were two diseases that we were doing research on.

One is called half one antitrypsin deficiency and the other is called NAFLD or NASH. And we were creating disease models. And so I spent a lot of time, but creating those disease models, but then also Hitting them with a battery of drugs to see if we could find cures for any of these diseases.

So that’s my background. I spent really just the scientist and prolific now. Initially I was was in the lab in the early days helping do these experiments, but [00:28:00] now I’m not, thankfully for prolific far more talented people are now in the lab and I spend most of my time dealing with.

investors, customers, and, managing the board, managing the leadership team. I saw the reference from Bill Gates. Yeah. That was cool. That was very cool. You mean the part of his mentioning us on his podcast? Yeah. Or some interview or something. Yeah. His his venture capital firm, Broker Energy Ventures are amazing and led our Series A.

So yeah, we’re very grateful for that support. Yeah, and so the most recent announced fundraising status around is 55 million. Series B. Yes. Just B or B something? B1. B1. Okay. Yeah, we’re stuck on that. You gotta add something strange to it, right? Yeah. I’ll be hearing, we’ll probably hear like B sharp in the future.

So yeah. Okay, cool. And In total, yeah, The Series B that was announced was including some convertible notes. In total, we’ve [00:29:00] raised around 90 million from some of the best investors in the world. And really the point of doing the Series B now was to transition the company from being an R& D focused company, which is what we’ve been for the last four and a half years, to being a commercial organization.

So in the last few weeks, we’ve had a huge amount of interest in Prolific, which has been very exciting as we announced the B, and we announced what we were doing, and the reception has been great. Overwhelmingly positive more positive than I thought it would be. And a lot of people have started reaching out.

And so now we’re going to be announcing some partnerships in the next few months. And really the plan is to get these tools into the hands of as many people as possible. Yeah. So if you’re listening to this and you are interested in controlling cells with light, please reach out. You can go on our website and partner with us there, or you can contact us.

That’s what the contact information that I shared previously, we are in the phase where we just want, we want people to use this because we think that we have the best way to control [00:30:00] cells that exists and in order for it to have an impact, we need people to use it. Yeah. And it seems like with the facility you have here, you have a pretty healthy output.

You could create a lot of these, I’ll say these technologies more broadly, And that’s even, before the, all the pilot plan and everything else is continues to grow. So that’s super cool. I want to go back to optogenetics, your co founders, Max and Declan. And I think after that podcast, Maybe you actually couldn’t come to this one, but we had Oren’s Hummus.

I think you might’ve, were you that, were you there? No, but I love Oren’s Hummus. Yeah. What’s that? I love Oren’s Hummus. Oh, it’s so good. So good. And so I think that was after the podcast recording, I met up with them. Who brought the optogenetics model to the picture? I put the founding team together.

So I, I. I met Max at a bar in Worcester. So I I picked him up. That’s in the UK. No. In [00:31:00] Massachusetts. Oh, okay. Okay. So during my PhD I had the idea for prolific and then my PI sent me to Massachusetts to do some experiments. And so I went there and I didn’t know anyone and I got this email and the email was like, so and so is leaving.

We’re having a drinks at this dive bar. Everyone’s welcome. And I was like, Oh, great. Okay. Everyone includes me. Yeah. I went to this dive bar not knowing who the person was who was leaving and then I was sat next to Max and I remember asking him like, what do you do? How do you spend your time?

And he goes, I build super resolution cryogenic microscopes. Wow. And I was like extremely interested because I knew that microscopes were just like machines, right? So if you think about a microscope, you have a. Light emission source a bunch of mirrors goes for a sample and then you have a detector.

And so it’s someone who can build a Super resolution microscope knows how to build hardware to manipulate light. Yeah, and so Max didn’t fully understand why I was so [00:32:00] interested in him at the time. Yeah, and he was like, you know This line doesn’t normally work this Oh yeah! And Custom designed an NDA And Me up with me a couple of days later for me to tell him this idea.

And then after I told him, Max, understood immediately what the potential was here. And then so got him on board. And then afterwards I reached out to Declan, who was my childhood best friend with this like massive email where I was like, he was earning so much money, like leading the machine learning team at Zillow.

And I was like, here are all of those for you. Yeah, he was the software guy and yeah, I managed to convince him to take a pay cut from I don’t know, 300k to zero dollars, which is all we were paying ourselves at the time. And so that’s how it started. And then the three of us went into bio, started doing the experiments and then raised the seed round.

And then that’s where we started getting employees. And then. Raise the series a and [00:33:00] then more employees and then really did the de risking the bulk of the de risking off to the series a and now Technologies in a place where we can give it to other people. Yeah, which is why we just did the series B, right?

From a management standpoint, you know as the CEO How has it been to learn to communicate with team members hire team members. I feel like I just met like the world class scientists in every little department you showed me. It was awesome. Some familiar faces too, which is very cool. Irfan.

But how is that experience? Are there, is there like a book that you’re, business book that is like a bible to you or is it just, how does it work? Yeah, it’s been a very interesting experience and a steep learning curve. We really spend a lot of time thinking about making sure we’re hiring the right people.

And spend a lot of time interviewing and a lot of time thinking about what [00:34:00] we really want when we’re hiring people. We look for people who are both exceptionally brilliant and also extremely kind and have high emotional. One of the things that we’re doing is trying to bring together so many different disciplines.

So it’s not just optogenetics, and AI, and Hardware and material science and cell biology and molecular biology and all of these things need to be harmonized. And in order to do that, you don’t need just technical expertise, you need technical expertise. You also need emotional intelligence to be able to interact with all these people.

So I think one of the things that we’ve done very well and something that I think I am very good at is hiring extraordinarily good people. That’s your talent. That’s, I think, probably the main value that I’ve added to Prolific in the last four and a half years has been in hiring world class people.

One of the nice things about hiring the best of the best is that they know what to [00:35:00] do. I try not to tell people what to do as much as possible. They know what to do. And that’s my real philosophy with hiring is if you hire the right people, they should be telling you To do right now, you telling them what to do, if you’re just going to tell them what to do, then you didn’t need to spend all the time hiring the best of us could have just hired someone mediocre and told them what to do.

So I think giving people the freedom that they need and the resources that they need to do their best work is the most important thing. I am constantly trying to make myself obsolete and I think I’m not totally obsolete yet, but I’m approaching that point, which is great. But yeah, hiring really amazing people and then giving them the space that they need to do their best work.

Yeah. Obviously like giving them the boundary conditions is important. But if you hire really good people, generally they know what to do. You just have to trust them. And trust that this guy at the time in the basement has the vision and [00:36:00] now seeing one of the coolest, electronics labs and also, Bio lab that you know makes the university labs look old like it’s super cool to see this space Thank you. Yes. It’s a it’s a Inspiring place to work. Absolutely. That’s also really important like work should be fun. Oh, yeah people should want to come to work that’s one of the things that we look for is like You’re not just doing this because you want a salary like obviously you should get paid That’s not really the people that we’re looking for.

We’re looking for people who see this as their life’s work and they want to go all in on this because this is how they derive meaning and purpose from their lives. That’s really, those are the people we want to hire. Yeah, very cool. I’m going to ask you one more question and then I’ll step back.

I’m going to ask you two more questions. The last question is if you have any last insights. And, but before I ask that question, What’s the story with the murals? Who created them? When did you guys put them up? Oh, the murals were done by a friend of ours called Mila. He’s a local [00:37:00] tattoo artist.

Hopefully you didn’t trade stock like Mark Zuckerberg, or maybe you did. Yeah, we actually did give him a little bit of it. Okay, that’s partially why these murals are so beautiful.

No, at the time we didn’t, so it was actually a great deal for us and a great deal for him. He basically did this all at cost. But yeah, that’s stunning. Oh yeah, no, and maybe, we’ll cut in another shot of this, maybe if we can get that later. As we wrap up, you mentioned a couple of emails, we’ll put those in the show notes.

Do you have any last insights for our listeners today? Let’s see, I think, something that I’ve been seeing just in the world more generally is that there’s a sort of this deep cynicism about cultured meat and whether it can work. And, I’ve considered myself a cultured meat cynic, but I have been convinced over the last four and a half years that cultured meat can work.

If we transition away from molecular inputs to Non [00:38:00] molecular inputs and I think light is the best non molecular input to use And so i’m actually feeling full of hope right now. I think cultured meat can work We just need to bring everyone to the table and have a more collaborative mindset And i’m here doing this podcast because I want to speak to all of the cultured meat companies And if you’re listening to this and you’re a cultured meat company, we want to work with you We want to give you all of our genetic tools.

We want to give you our hardware We want to your software we want to give you everything that we have for you to be set up with success And so reach out to us if you haven’t already like I said, I’m on Deniz. prolific machines. com or reach out to our commercial team at partners@prolific machines.com.

We’d love to work with you. And if you’re not in the culture meat industry, but you want to control sales with light we do that too. So you can also reach out to us and yeah, I think the future is awesomeDenizis. Thank you so much. Thanks Alex. This is your host Alex, and we look forward to seeing you on our next episode.