Autonomous Labs & the Future of Cell Culture | Jimmy Sastra (Part 3/4)

Intro - 00:00:06: Welcome to the Biotech Startups podcast by Excedr. Join us as we speak with first-time founders, serial entrepreneurs, and experienced investors about the challenges and triumphs of running a biotech startup from pre-seed to IPO with your host, Jon Chee.

Intro & Outro - 00:00:25: In our last episode, Jimmy reflected on grad school grit, his move to Silicon Valley, and lessons from Willow Garage during the rise of ROS. He also shared how building the first biology cloud lab at Transcriptic shaped his bias for speed and focus, guided how he hires for mission, and led to later roles at Built Robotics, Robust AI, and Ginkgo before meeting his Monomer co-founder. If you missed it, check out part two. In part three, Jimmy talks about founding Monomer, starting with consulting to validate the problem, then honing a thesis around autonomous cell culture and industrializing in vitro disease models. He also shares how Monomer integrates instruments with a vertically integrated stack, real-world deployments across tissue types and customers, and why their go-to-market includes software-only landings, pilot runs in Monomer's lab, and full robotic work cells for teams ready to scale.

Jon Chee - 00:01:42: And when you guys came together and then ended up founding Monomer, what were the early days like?

Jimmy Sastra - 00:01:49: I had a background in biotech and robotics. My co-founder, Mark Zhang, had a strong background in software engineering and was very passionate about design. And so the first year or two of Monomer, we were more of a consulting company, which I think is a great way to start a company because you get to know your co-founder, you make some money. We also hired our founding engineer, Carter Allen. So it was three of us and we got to have experience building a business. We even made it to becoming profitable. And then over time, coming up with a thesis by getting hands-on experience helping other biology labs get started.

Jon Chee - 00:02:25: And what was that thesis, and how did you refine it?

Jimmy Sastra - 00:02:28: Yeah. We noticed an alignment of our interests. Like I mentioned, we're really interested in cells, seeing various companies asking us to build automated cell culture work cells. And from there, the thesis got started around building robotics and software for cell development.

Jon Chee - 00:02:46: Very cool. And when you had that thesis, you know, and then you're comparing it to the state of the market and the status quo. What is the status quo, and how does Monomer's secret sauce disrupt the status quo?

Jimmy Sastra - 00:03:00: Yeah. We went in thinking about that application, which I think was very fortunate. We went in thinking, "How can we industrialize cell culture?" and that later evolved to, "How can we industrialize in vitro systems?" So in layman's terms, in drug discovery, a lot of drugs, before they're tested on a human, before testing in mice, are tested in vitro, meaning disease models in a dish. And so we've taken that on as our mission to not replace, but reduce the need for animal model testing. And so we help scale the growing of stem cell-derived disease models in a dish to drive down reliance on animal models. I don't think it'll completely go away. I think it'll always need to be there, but at least we can do earlier testing in a cheaper way on in vitro systems.

Jon Chee - 00:03:52: Very cool.

Jimmy Sastra - 00:03:53: Through working at Strateos, through doing that consulting business in the early days of Monomer, we always saw for the smaller companies, there was always a room in the corner that was for cell culture. It usually had no window. Fluorescent lights. Biosafety cabinets and fans, those are really loud. Things buzzing, and that did not look like fun to me.

Jon Chee - 00:04:17: It is not.

Jimmy Sastra - 00:04:18: Right. And then I'm seeing scientists repeatedly every day going into the lab, taking cells out of the incubator, looking at them through a microscope, looking at the cell morphology to see if they're healthy or unhealthy, and then making some kind of judgment call on that. And then through their experience, looking at cell morphology, deciding what to do next, whether it's passaging cells or changing media, trying to add some other growth factors or other reagents, and then going to the biosafety cabinets, doing the pipetting, and putting it back in the incubator. Often taking half a day every day, Monday through Friday, but also the weekends. And I'm sure this can be done better.

Jon Chee - 00:04:58: That was my job, by the way. What you're describing is, like, I did a lot of...

Jimmy Sastra - 00:05:02: Yeah. It took me back to undergrad. I had to do some of that. That was my job. So, yeah, I learned a bit of cell culture. Yeah. And then tying that to my robotics background, seeing, "Oh, people are looking at cells and then making some kind of decision and then actually doing something in the physical world." Well, that's a very typical robotics loop, and I felt it could be done autonomously.

Jon Chee - 00:05:25: Very cool. Talk about the technology that you guys have developed to do that.

Jimmy Sastra - 00:05:30: Yeah. So now we integrate common lab instruments into automated work cells with our cohesive software suite of workflow automation, data analysis, and decision-making tools. So the robotics automates the tedious cell culture that's done manually today a lot. It increases consistency, reduces biological variability. And then our software provides real-time visibility. It lets you look at all your microscopy images, sample health, morphology, and growth. And then scientists can then remotely manage and collaborate on their cell cultures. And then besides robotics and software, our third pillar is biology. We go really deep into understanding the biology to help our customers with protocol development and quickly onboarding new tissues and also making it easy to optimize new protocols.

Jon Chee - 00:06:23: Very cool.

Jimmy Sastra - 00:06:24: Yeah. So to date, we have deployed half a dozen robotic work cells, grown about a dozen different tissue types, and very complex tissue types from stem cell-derived tissues. The big three in toxicity is usually cardiac, liver, lung, and we've also done brain tissues.

Jon Chee - 00:06:45: Very cool.

Jimmy Sastra - 00:06:45: And all the way from single monolayer cells to 2D to 3D organoids.

Jon Chee - 00:06:52: Badass. And, I mean, I can't imagine this was all done in one go. Kinda walk me through, like, you talked about the three pillars, the evolution and how you got to where Monomer is today, you and your team.

Jimmy Sastra - 00:07:06: Yeah. Like I mentioned, the first one or two years was consulting. We helped labs spec out different instruments, helped their lab build it out. And as we were doing that, we would offer to write different software applications for them. So Mark wrote a lot of different single-purpose applications that glued things between different software. Then over time, we formed this thesis around autonomous cell culture and helped companies automate their cell culture.

Jon Chee - 00:07:33: How hard was it to actually start getting the hardware and the software to play nice?

Jimmy Sastra - 00:07:37: Yeah. I like to say robotics is a game of inches. It's all these little things that have to come together for the fully automated robot to work, and then the biologist has to cooperate as well. So there's a lot of attention to little details and a lot of teamwork, and no person can do it all on their own. I enjoy building multidisciplinary teams, making them talk to each other, and you are forced to collaborate and understand each other.

Jon Chee - 00:08:04: And did you have to work with the manufacturers of the equipment to make it all play nice, or is it just out of the box the stuff can be integrated?

Jimmy Sastra - 00:08:12: Oh, yeah. I think I look at the software as the glue between all these instruments and try to form good partnerships with different instrument vendors, taking inspiration from ASML, building the world's most complex machine, but they look at themselves as systems integrators. Not necessarily making all the parts themselves, but having a good understanding of the application then lets you glue all those different things together as the value add.

Jon Chee - 00:08:39: And what did it take to get the manufacturers of these equipment excited and onboard with your guys' integration efforts?

Jimmy Sastra - 00:08:47: A lot of the lab automation industry has started with different automated instruments, like an automated liquid handler, automated incubator, automated microscope. And then I look at that as a modular layer that we can then glue together with different software. A lot of software tools are very horizontal. So there are companies that are focused on just scheduling and open-loop executing protocols across these different experiments, which I think was fine as the industry was starting with screening. And so, for example, small-molecule compound screening. So trying a million different compounds, searching through a whole library, trying to find the hit, causing some effect in some disease pathway. That can be done open-loop, like, blindly when you run it for several weeks and at the end, you look at all the data. Then there are other tools that can help you manage your data, and they don't necessarily talk to each other. And so with Monomer, what we do differently is really focus on one particular vertical of cell culture. But then vertical integration, à la Clayton Christensen, from those books I read as a teenager, industries change from being horizontally organized to being vertically integrated. And for cell culture, we thought the vertical integration is key because I saw scientists looking at cells after taking them out of the incubator, making some decision, acting on them, putting them back in the incubator. So that loop, I thought, requires a good execution layer and a good data management layer to then enable this decision-making.

Jon Chee - 00:10:26: Absolutely. And I think the vertical integration... I mean, I think about Excedr and we're always looked at... when other leasing companies are compared to us. You're just like, "You guys are weird. You guys only do lab equipment," but exactly what you focus... it's the focus and being able to find that alignment within the vertical. And then, the longer you do it, the deeper those relationships get. And your expertise too. Right? And you just get so deeply familiar with the domain that it unlocks magical things. Whereas, you know, we talk about the horizontal. It's hard to become excellent when you're spanning so many different domains, and it's impossible to be amazing at everything. It's kind of this thing where you're like, "We don't do any leasing for anything outside of the laboratory." But that's a sacrifice that we make in order to become domain experts in this vertical. So it's a similar... you're talking about cell culture. There's making sure that it's just like everything sits flush, versus just, you know, having this horizontal thing where it's just like, "Oh, this is okay, not... it's suboptimal." So I see a parallel in what we do.

Jimmy Sastra - 00:11:33: Yeah. I think industries shift from vertically integrated to horizontally integrated. Mhmm. Different times in the industry, it makes sense. Uh, I often reread Clayton Christensen's Innovator's Dilemma who goes in-depth on disruptive innovation. But, yeah, if you look at the computer industry, vertical integration is needed when you need to create groundbreaking innovations. So, think like the iPhone.

Jon Chee - 00:11:57: Yep. Absolutely. And now that you got your thesis, you've polished it. You've polished it, and you have these three pillars for Monomer. What is your approach to the go-to-market for this? It seems pretty novel, and I'm going to imagine it takes a different kind of go-to-market motion.

Jimmy Sastra - 00:12:15: Yeah. Yeah. So now we have these three pillars of robotics, software, and biology, focusing on cell culture, but still, that's pretty wide. In cell culture, we decided to go after one of the most painful. So we went out, we found the most challenging cell culture protocols and therefore looking at stem cells. Because they're very finicky. They like to spontaneously differentiate. There's a lot of domain knowledge. Scientists will spend a whole PhD focused on a particular stem cell line, and only they have a green thumb for growing that type of cell, all the way to the point where they even have trouble explaining it to other scientists and scaling. So, yeah, impossible to scale because as a company, you're relying on one scientist to stay at your company.

Jon Chee - 00:13:03: Yep. And, like, did you surface that pain via conversations? Did you do market research? Like, how did you come to this insight?

Jimmy Sastra - 00:13:11: Yeah. A lot of it is through our consulting in the beginning and doing custom projects, and I learned ASML kinda started the same way. They did a lot of custom things for people. Yep. And it reminded me, kinda see the pattern. What's difficult and what's easy and what are the pain points?

Jon Chee - 00:13:27: Got it. And so you've targeted the pain, and that's a wise thing to do. It's just like... what if there's another saying just like, "Are you a painkiller or you're a vitamin?"

Jimmy Sastra - 00:13:38: Yep. Right? You wanna be the painkiller.

Jon Chee - 00:13:39: Yep.

Jimmy Sastra - 00:13:39: Or are you a solution looking for a problem? Are you a hammer looking for a nail?

Jon Chee - 00:13:44: Or... Yeah.

Jimmy Sastra - 00:13:45: Exactly. We're obsessing over the problem is one of our values. Certainly, no one, I think, within biology, loves doing cell culture on the weekend. So, yeah.

Jon Chee - 00:13:56: For sure. And so you've now... you've targeted. You've found that pain, which, by the way, a lot of people never actually find the pain, and they just spend... they, you know, they're chasing... they're going down roads that are ultimately dead ends. So you found the pain, which is important. Now you're like, "Okay. We need to actually start getting this into the hands of the users." Are these... were you like, "Okay. These are small companies, big companies, academic, government," or was it just all of the above?

Jimmy Sastra - 00:14:24: Yeah. In the beginning, there were a lot of startups who like to innovate, early adopters. I'll highlight one of our customers, Rosebud Biosciences, who was a three-person startup, and we're able to get them growing 1,900 organoids at a time with our robotic work cell, just one operator.

Jon Chee - 00:14:44: Cool.

Jimmy Sastra - 00:14:44: So that was a really great win. We brought up that work cell in six weeks. And then since, we found other startups and then have worked our way up to bigger companies. We've deployed at as big as a several-hundred-person biotech. It's a gene therapy company. And, yeah, on our website, you can see our various customers, including Prime Medicine, where the co-founder (David R. Liu) was a pioneer in CRISPR prime editing and base editing. So, yeah, it was really cool to work with such amazing scientists. And then now we've deployed also at a core facility and are working with a core facility at a hospital.

Jon Chee - 00:15:24: Cool.

Jimmy Sastra - 00:15:25: So our customers are cell line development teams within biotech or pharma, also known as stem cell biology teams or cell biology teams that create cell or tissue models that then get used downstream for testing. Other organoid startups fit really well and then core facilities.

Jon Chee - 00:15:45: Very cool. How does the strategy on getting a deal done differ with all of them? I mean, my wife is in... she works at Cloudflare, and the sales motions are so different when it comes to small businesses, mid-market, enterprise. She works in the government, so she's selling to the government, which is a completely different beast in itself. Or not to say that they all have to be different. Maybe it is quite like, "We just... here's the pain. You're all experiencing the pain. So easy enough. Like, let me solve the pain for you." Did you have to customize your approach with each of them, or was it different?

Jimmy Sastra - 00:16:20: Yeah. I'd say the hardest thing for us is the timelines. So the startups, really quick. Biotechs, a little faster. Big pharma, long.

Jon Chee - 00:16:29: Yeah.

Jimmy Sastra - 00:16:30: A lot of relationship building. And, yeah, we're also in the process with a Japanese big pharma.

Jon Chee - 00:16:35: Cool.

Jimmy Sastra - 00:16:36: And learning a lot of that is, you know, a lot of relationship building too, which I think is also enjoyable. As a startup, you have to think about, "Cool. Is there a way we can get started faster?"

Jon Chee - 00:16:47: Yep.

Jimmy Sastra - 00:16:48: We don't have the luxury of taking very long. So before, we'd always try to sell fully automated robotic workflows. And then this year, we've had two deployments now of software-only for manual workflows. We're still focused on cell culture, but it's protocols that are done manually. But we collect data from, let's say, a microscope and a single-cell counter and then manage the workflow and the data coming off of instruments, but without a robotic arm.

Jon Chee - 00:17:18: Got it. And I'm gonna imagine a robotic arm... there's room for the robotic arm to play? It's kinda like stepwise, kinda like one step at a time, like crawl, walk, run.

Jimmy Sastra - 00:17:27: We call it a fast land. Yep. And later, we can expand to fully automated robotics work cells once we've started a relationship and removed some pain points.

Jon Chee - 00:17:37: Yep. Prove some value in the very beginning. Cloudflare does the exact same thing that led to the freemium model. Right? You're just like, "Alright. Here you go. Here's the basic free version." The free version is fantastic, but eventually, they're like, "Oh, I need those paid features, a lot. I now realize it." And sometimes they don't even know how painful it is until you get in there and show a little bit of value first and demonstrate it and surface the pain.

Jimmy Sastra - 00:18:06: Yeah. The full robotic work cell was a hard sell because our value add is the software, but the hardware is so expensive. As you know, as a leasing company.

Jon Chee - 00:18:16: Yep. Yep.

Jimmy Sastra - 00:18:17: So your tagline is, "Extend your runway, raise at a higher valuation." We're listening to the podcast.

Jon Chee - 00:18:23: Yeah. There we go.

Jimmy Sastra - 00:18:24: It's working.

Jon Chee - 00:18:25: Yeah. Yes. Working. The subliminal messages. Like, yes. Yes.

Jimmy Sastra - 00:18:28: So before, the work cell sale was very hard to acquire a lot of trust, a lot of upfront costs. Now we have the land-only. So one, it's a lot less upfront costs. And then we're a small team, so we can only do a limited set of design partnerships, but we've started lining those up now, which is really nice. Meaning, it's a free trial for three months, and then it converts to paid once we've shown the value.

Jon Chee - 00:18:52: Very cool. Very cool.

Jimmy Sastra - 00:18:54: I'll mention the third option with which you can engage with Monomer. We've now moved into an office and a lab here in San Francisco where if you're not quite ready yet to buy a whole robotic work cell and have a lot of upfront costs themselves, you can come to our lab and we can run pilot projects. So you bring your cells, you bring your protocols, we'll onboard it, run it in our facility, and you get to try it out.

Jon Chee - 00:19:20: Very cool.

Jimmy Sastra - 00:19:21: So as software-only monitoring your cell cultures, that takes three days to onboard before we can show value. Generating data in our lab with the pilot project, that's maybe four weeks to onboard. And then fully automated cell culture, after the hardware is all there, it can take as fast as six weeks to onboard.

Jon Chee - 00:19:42: Yeah. I'm imagining having these various entry points is important because some people are just like, "Yeah. Give me the whole shebang."

Jimmy Sastra - 00:19:49: That's how it works.

Jon Chee - 00:19:51: That happens. This is... it's kind of the early adopter curve, and then there's the naysayers on the other side. You gotta find different wedges into each of those segments. They're all... various people have varying degrees of conservatism when it comes to adopting new tooling and approaches. So I love that approach.

Jimmy Sastra - 00:20:13: It's meeting where the customer is, but also reacting to, unfortunately, today's pretty tough environment in biotech.

Jon Chee - 00:20:20: Right? Yeah. Absolutely. Yeah. And it's the flexibility. You know, as of right now, flexibility and efficiency is paramount. So, I like the way that you guys have adapted on the fly because I think it makes a meaningful impact for your customers, I'm sure. And so, interesting to go back to the large Japanese company that you're working with, it's like there's also different business culture when it comes to doing it. And it is very different. I mean, you went to Japan, you know, and you lived there, so you kind of have firsthand experience. But, what's your experience like now? Like, is it you're just like, "I kinda know the ropes. I can kinda get this done."

Jimmy Sastra - 00:20:58: Yeah. I'd kinda get back to the beginning of this podcast. My international upbringing, I think, really helped there. One, obviously, I had lived in Japan, so I knew Japanese so I can break the ice a bit. Say a couple sentences in Japanese.

Jon Chee - 00:21:12: Yeah.

Jimmy Sastra - 00:21:13: But I guess, yeah, from an early age, realizing all the different cultures. Right? So, like, Dutch folks, not to stereotype, but they're very direct. Japanese people, very much reading between the lines, very polite, and very much cared about harmony. Then moving to The US, at least in Philadelphia, people are very... not rude, but it's sort of like... if people like you, they relentlessly make fun of you.

Jon Chee - 00:21:40: Yes. I understand that. Yes. My closest friends rib me a lot. So I get it.

Jimmy Sastra - 00:21:46: Yeah. And it's like a skill set in every different culture. Like, being polite is a skill set in Japan. Ruthlessly teasing each other on the East Coast, another skill set. And now being on the West Coast, the teasing doesn't really happen. So I feel I've lost that skill set.

Jon Chee - 00:22:01: Yeah. Yeah. These soft skills are real, super real. And that's why I'm always curious, right, like, working with the government, working with academia, working with companies that are based in different countries. Right? If you're gonna work with them, these soft things are important. Right? It's not just the technical. You've got to appeal to these other aspects that are important to them. One of the partnerships that we were forging, it's with also a large Japanese company. And when we first got started, I was much younger and born in the Bay Area, just American. I was just too forward, too quick. I was like, "Why don't we... this just makes sense. Let's get this done now." That doesn't fly. Yeah. That does not fly. We work together now. I'll give you the spoiler now. Like, we're partnered now, but it took a lot and they were fortunately patient. This was their American outpost that I was interfacing with more, so they kind of understood, like, "Alright, Jon. You're coming in kind of hot right now. We gotta build consensus here, back in Tokyo. Just heads up." And just knowing that, knowing those intricacies... you know? And I can see how your international upbringing can really complement this. You know? You're working with a varied group of folks and stakeholders.

Jimmy Sastra - 00:23:18: Yeah. I think the international upbringing always makes me listen first, trying to gauge, "Alright, what are the norms? What is the human style?" And I kinda adapt both in terms of talking to, let's say, a Japanese big pharma versus a Dutch startup. But also within engineering, since we do robotics, which is both hardware, software, and biology, listening across disciplines.

Jon Chee - 00:23:45: Yeah.

Jimmy Sastra - 00:23:45: You know, like, understanding each other. Because every problem, since we're vertically focused on specific applications, we can control... do we solve this in software? Do we solve this in biology? Yeah. Do we use a different reagent that lets the cells come off the well a little faster? Or do we take the plate to a shaker and kinda help the cells come off mechanically? And you kinda make all those trade-offs, which I think is super fun.

Jon Chee - 00:24:13: Super fun and I think not done enough because sometimes people are like, you brought up, "You're a hammer looking for a nail." And oftentimes, everyone's domain or specialty is the only way to do it. You're just like, "No. We got to do it, insert whatever specialty it is, this way."

Jimmy Sastra - 00:24:32: Yeah. "This is the best practice."

Jon Chee - 00:24:34: I absolutely agree. You need to cross the line. So I'm a wet lab guy. And when I was still in the lab, comp bio was starting to get a lot of momentum. But, for us, it was just wet lab only. Like, the computer stuff, not real. It was just... and so there was a battle. It's kind of like when we did X-ray crystallography for structural bio. Like, "We got to do the lattice to confirm the structure." And the comp bio people are just like, "No. We don't. No. We don't."

Jimmy Sastra - 00:25:07: Yeah. It's not hard to talk across boundaries, but every one is an opportunity. Yeah. I think that's how we differ from a lot of companies in our space. A lot of companies, like I mentioned, like Clayton Christensen, traditionally in our space have been focused as horizontal tools, so a scheduler that can do any protocol or a data ingestor that can ingest any type of data. We slice across those layers and focus on cell culture, specifically the most difficult cell cultures like iPSC-derived tissues, and then make trade-offs between all those layers.

Jon Chee - 00:25:42: Absolutely. And that's where magic happens, obviously. It's like when you can be cross-disciplinary and collaborative on that front. And it is so funny. It goes back to when I was thinking about when I mentioned that my dad was like, "Why can't you do the math and physics?" And my dad was always thinking about everything in the math, physics, engineering lens. "So do it this way." It's like, "I don't think like that. I just don't think like that." We ultimately come to a similar place, but just from different angles. It just... there's a bunch of ways you can problem-solve. It doesn't have to be a very specific way. And it's like I was thinking orthogonally, which is, I think, again, another skill set. It's like understanding soft skills, having those soft skills, and using it at the right time and just knowing who's on the other side, but also being able to think orthogonally. And it helps when your co-founders are from different backgrounds, and it sounds like you've managed, again, just like strength, weakness, strength, weakness. Like we talked about, finding your limit. I think you said, "Look, I'm decent at software, but I'm not amazing at software," but your co-founder...

Jimmy Sastra - 00:26:48: Yeah. I'm a complete hacker, but I know enough to make things work and speak the language.

Jon Chee - 00:26:54: Yeah. Exactly. And it's kind of that... it's like that too. Right? It's kind of being able to work together across lines and covering one's weaknesses with someone else's strengths is an excellent way to do it.

Outro - 00:27:06: That's all for this episode of the Biotech Startups podcast featuring Jimmy Sastra. Join us next time for part four where Jimmy shares why he treats fundraising as just one tool, how Monomer added a services arm and its own SF lab to accelerate learning, and the go-to-market wedges (software-only, in-house pilots, and full work cells) that meet teams where they are. He'll also talk about decisive calls with incomplete information, managing risk in a tough biotech climate, and the vision behind Monomer's AI scientist cell culture hackathon, plus personal shout-outs and advice to his 21-year-old self. If you're enjoying the podcast, subscribe, leave a review, and share it with a friend. Thanks for listening. The Biotech Startups podcast is produced by Excedr. Subscribe. Excedr provides research labs with equipment leases on founder-friendly terms to support paths to exceptional outcomes. To learn more, visit our website, www.excedr.com. On behalf of the team here at Excedr, thanks for listening. The Biotech Startups podcast provides general insights into the life science sector through the experiences of its guests. The use of information on this podcast or materials linked from the podcast is at the user's own risk. The views expressed by the participants are their own and are not the views of Excedr or sponsors. No reference to any product, service, or company in the podcast is an endorsement by Excedr or its guests.