Ben Kaplan 0:00
Hey, this is top CEO. The show about CEOs making tough decisions featuring CEOs from startups, scale ups and fortune 500 enterprises. Top CEO is a business school case study, telling the story behind the story, and what you can learn from it from those who have faced the fire and come out the other side. Welcome to the top CEO podcast.
The Detective 0:31
Imagine you're the CEO of smart labs, a company that creates dynamic customizable lab spaces designed to adapt and evolve alongside scientific research. The business model revolves around providing lab Infrastructure as a Service, clients pay a fee to access the lab spaces, which are tailored to their specific research needs, without having to invest in building leasing or maintaining their own facilities.
In the beginning, you believe that providing a wide variety of laboratories could cater to the ever changing needs of the scientific community. You even built labs like Legos, easily assembling and disassembling them in order to offer endless possibilities. But as time went on, you faced mounting challenges.
Amrit Chaudhuri 1:22
My co founders and I built the business in 2015. We found out about 18 months later that the assumptions and premise service model didn't make sense.
The Detective 1:34
How could you anticipate the specific needs of various research projects in advance? How could you ensure that your labs were always ready and equipped for the rapidly evolving world of scientific research? Furthermore, how could you convince a risk averse industry to trust in your innovative solutions,
Amrit Chaudhuri 1:53
our business wouldn't get to a break even point of revenue. And we would never be able to fill our capacity past that breakeven point. So we're like, Okay, this this isn't working. But why is it not working?
The Detective 2:06
These were exactly the challenges faced by Amrit Chaudhuri
CEO of SmartLab. This is the lab.
Ben Kaplan 2:22
What was the initial premise that you built this business on? You raised money against you have people saying you're gonna disrupt this industry? And then what was the obstacle that suddenly you realized that would prevent that from working? Yeah,
Amrit Chaudhuri 2:35
so maybe, to help with that, let me give you a backdrop of where the industry was when we started the business. So you know, my co founders and I came from the biopharma industry, working in industry, on everything from drug development, to tools development to bioinformatics platforms. And so there's a history of drug development primarily, has been a singularly focused industry for about 100 years, we used to make drugs the same way from aspirin through chemotherapy through everything else. And what my co founders and I originally launched our business around was, we thought that there was a window of opportunity that the entire world drug development is about to change. We were going from a one to two technology industry, from the 80s to 2000 10s, in the 2000 10s, and you're about to start this accelerated transition from going from me to technology industry to a 20 technology industry. And at scale, biopharma wasn't ready for it. So he said, Okay, if everybody is going to change the infrastructure, and the resourcing strategies and strategies of what types of drugs and how they're going to pursue those, which technology perspective, I mean, like, the technology is as different as if you're used to trains and boats, here's an aeroplane, how does that disrupt transportation for the world? That type of foundational change? Imagine 20 types of change happening rocket ships and airplanes and cars and everything else in between happening at once?
Ben Kaplan 4:08
What's driving that? Usually in transportation, for instance, you don't have rocket ships and airplanes and segways and levitating devices and all at the same time. But why in pharma? Was that coming?
Amrit Chaudhuri 4:17
Yeah. So if you don't about how we think of drugs, drugs used to be small molecules, and they were systemically applied. You take aspirin, you take Tylenol, it applies everywhere in your brain, every cell gets this dosage and either your nerves or your brain or somewhere else, is there an effect happening? And in the 80s, we transitioned to a new type of technology basis, we call biologics, monoclonal antibodies, fusion proteins, enzymes, and all of a sudden, instead of like painting a room, all of a sudden we could do pointed repairs. We could start inhibiting biological activities we could start having more than one order of magnitude effect. On and more complexity and targeting with drugs, and that unlocked a huge, huge, entirely new industry humera the auto immune drug that's one of the largest selling drugs in the world is based off of these new technologies. So the PDL ones and PD ones that are in the market that are the forefront of cancer drugs right now are all based off of these two theologies. Well, what are the patenting was that technology brewed, the second technology or industry uses biologics, large scale biologics took 30 years for pharma to adopt for literally the invention of the biotech industry was the adoption of these new technologies for the 80s to today. We now are facing things like autologous and allogeneic cell therapies mRNA, gene editing, where where that is two orders of magnitude of complexity, completely different foundational, resourcing and molecule and material development, different manufacturing, different discovery, different development. And it turns out that we science is progressing so quickly, that we're discovering 10s of these new world changing technologies in a decade, whereas it took four decades to move from one to two technologies. And so it's just the pace of the change of the world that we're seeing.
Ben Kaplan 6:31
So all that was happening was the backdrop, you're you have a background in the industry, you're seeing opportunity, because basically there's a lot of complexity in a short amount of time, people don't know how to deal with it, I see a business opportunity here. So take us through what was that opportunity that you originally launched on and raise money on.
Amrit Chaudhuri 6:49
So as you look at the fact that all of the process of developing drugs, but a change from the ideation through how you get a phase three drug approved, and the workflows, the equipment, the people, the types of facilities, the types of operations, the types of regulations are all being invented simultaneously, we realized that the industry was about to go through another cycle of reconfiguring how it works. And at the time, we thought, Hey, would it be great if we took a trend that happened period for each and every other a global industry that had yet to happen in biopharma have this concept of fractional access? How do you do the AWS data center model? For pharmaceutical research, if you think about it, fractional access to infrastructure and operations happens in every other industry. You don't We don't buy planes and fly them, we go onto an airline and we go use Uber to get around, we go to AWS sort of manage data center environment to go and serve, instead of having to build server farms anymore,
Ben Kaplan 7:53
it's more efficient for you to be a biopharma company. And why build all the infrastructure that you would have to do in the same way that ideally, it'd be like a utility in the same way that Amazon Web Services, which you alluded to, you could just turn it on, turn it off, you need someone else handles the complexities, who thought let's just make this infrastructure exist to make it simple,
Amrit Chaudhuri 8:11
like literally billions of dollars, the dollars per drug is what you're spending, yeah, to go in and do that. So we're spending like hundreds and hundreds of billions of dollars on equipping, not with high utilization or high efficacy, just because it's been done this way, the resources and infrastructure for the industry. And so we said, Great, let's go figure out a way of building the Amazon Web Services for product development. And that was the initial idea behind the business.
Ben Kaplan 8:41
What is the first step build a world class example of what this infrastructure lab looks like? We've got to put one together so people know what this is.
Amrit Chaudhuri 8:48
So when we bought built the business, we had a very unique opportunity space. And for the record, we thought, eventually larger companies would do this, but it would have to be de risked by the startups and midsize companies at scale over time for larger organizations to even consider doing it this way. So the idea was to is to enter the market
Ben Kaplan 9:06
because of fear, uncertainty and doubt that they're risk averse. This works for us we want to do it, we don't want to risk going into a startup that might not be able to do it and pull it off, go under something else. Let's let a bunch of people that aren't so risk averse. Do it first and then maybe you can kind of classic Good to Great model, right? Can I then move up the chain and get higher parts of the chain? Yep,
Amrit Chaudhuri 9:26
that's exactly it. And so we then to launch, the company did three things we partnered with at the time at the number one biopharma outsourcing will be called contract research organization in the world, called Charles River labs, and we developed a program and project and decided to go and jointly open a program that they were going to run in the same area, a program that we were going to partner with that wrapped around their program for scientific programs, and be able to utilize that relationship At a give us some instant credibility and some some really deep partnership with the organization that everybody already used. Let me give you some context 60% of clinical trials to get into a clinical trial we call ind enabling applications go through this organization. So whether you're Pfizer or you're the startup 60% of all clinical trials in the US, it sounds
Ben Kaplan 10:24
like this is based in Cambridge, Massachusetts, because I went to Harvard. the Charles River is there it says Charles River labs, is that where it is?
Amrit Chaudhuri 10:31
It's a Boston area based company, but it's global. And they're they're a $20 billion market cap, global biopharma. They're the largest outsourcing organization in biopharma. But they were, you know, 80 years ago by these 1960s 50s.
Ben Kaplan 10:43
So you're like, Okay, we're small, we need to partner with someone that's established, because we get a halo to us to add credibility. So you do that number one.
Amrit Chaudhuri 10:51
And number two, we ended up partnering with us, there's an opportunistic moment in time with vertex pharmaceuticals. So vertex is a Boston area, pharmaceutical company, they were built in Boston, there today, I don't know 4050 $60 billion market cap. They're one of the largest Boston built pharma companies that still independent. And they were in a unique moment of time, where they were moving from Kendall Square, Cambridge, where the heart of biotech is where they adjust in the last five or six years launched their new global headquarters of research, to their new global headquarters of research in the Boston seaport. That was, you know, 10x, the size, they were getting into a 1.2 million square foot, new centralized headquarters of research. And they were taking, I think, five or six different sites they had in Cambridge. So they're
Ben Kaplan 11:42
having physical infrastructure of great scale coming online, you're like, hey, maybe we partner with them and use a portion of airspace or something like that. So we use the space that we're exiting, oh, you said, Okay, you can have the fancy space, we'll take your other space, that's just fine for us. We'll leave
Amrit Chaudhuri 11:56
it there. I'll give you space, the regs and it was quite fancy.
Ben Kaplan 11:59
Okay, we'll take your fancy space. Okay, good.
Amrit Chaudhuri 12:03
Exactly. The environment we were inheriting was in the like, top 5% of like spend in pharmaceutical environments. I mean, really, really heavy infrastructure, like five years old, like, you know, on a 20 year useful life,
Ben Kaplan 12:15
there's the one you made the partnership to, you found the space because a bigger player was exiting something they had and what was three,
Amrit Chaudhuri 12:21
and then it's capitalizing the business. So we needed a certain amount of capital, we did just shy of $9 million capitalization initially, which to just give you some context, if we didn't walk into a relationship with Charles River. And if we had hadn't walked into a fully built out environment, to test this business model out would have cost us close to $100 million, not 10. Stevie some context of how lucky we were and opportunistic we were, and being able to go and perform this and the labs, were talking about doing, what 125,000 square feet of labs that cost $2,000, a square foot to build. And what we found is that our business would get to a break even point of revenue. And we would never be able to fill our capacity past that breakeven point. And we were scratching our heads, we were like, what's going on? Why are we losing business? Like we can get to this point, we're stable, but we're not ever going to be willing to make profit. And we tried 2030 different things to figure out how to maybe it's awareness can be its marketing, maybe it's our sales process, that we went through so many different issues, we're trying to figure out what the root cause of it was, was that the revenue challenge, right, it's, you know, we were doing just well enough that we were alive, but we weren't making any money. So that wasn't investable. It wasn't global, you can scale that business model. But we weren't dead as a company, like, you know, we could have just fallen flat in our face, lost all of our money and not made any revenue. We were, we were lucky and unfortunate enough to be like, you know, the zombie company, you're just doing well enough to survive. So we're like, Okay, this, this isn't working. But why is it not working? Because there's no way we can go and grow this and the building we went into vertex only had another three and a half years of lease on. And so after that lease was done, we weren't there's no job. There's no way that this proof of concept project basically was going to yield in the capital, we need to go and build our own massive scaled, you know, billion dollars of infrastructure.
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Amrit Chaudhuri 15:00
When we this is where the pivot really happened, you know, we were trying to capitalize on an industry pivot, to open a window of time to make the industry behave differently. And in that first 18 months, we realized that we had some mechanistic problem here that we weren't accounting for. And we decided to actually look into it, like, take a step back, stop worrying about sales, marketing, whatnot, and to say, what's actually happening to us, right? We're not dumb. We're very big. We were amazing people, we have really, really smart strategies. Everyone is all of our clients are speaking so while about us, and even the people who were not coming into our program, were like, That's a great idea just doesn't work for me. So why doesn't it work for you was the question we asked what what's going on there. And what we learned, and like the epiphany was, Oh, my God, I actually missed the problem. The problem space completely. So if you think about fractional access to complex infrastructure, as a model that's used everywhere else. Airlines, you know, Uber, co working space, like we work data centers, they're all the same basic business model, right? In terms of you invest in infrastructure, you put an operational overlay, you sell fractional access or subscription access to that, so that people don't have to build the thing and run the thing themselves, which is heavily expensive, and liabilities and static nature of our industry and biopharma actually had one order of magnitude more complexity, and like physical limitations that these other industries didn't have. The easiest way that I could probably put that is let's use data centers. As an analogy to our business model, we're trying to build the pharmaceutical data center. At the end of the day, regardless of whether you want to put an IBM blade server, Dell, EMC server running Windows and virtualized, a different type of server based on a different hardware system, running Linux or Unix, the infrastructure and the operations that you're developing and investing into, are completely fungible across all of those, you swap out the servers, but you don't have to break down and rebuild the datacenter. Like the server rack is a server rack as a server rack. Once your server fits in a server rack, and you have the power and the cooling the internet connectivity into that building, you can change consistently upgrade the technology. And you're not having to reinvest 90% of the capital, in between the different use cases and the different evolutions of technology that happened inside of that space, an office space, if I'm a tech company, and I'm using an office space, and I decided without my landlord can go and sell it to an accounting for more marketing firm.
Ben Kaplan 17:53
So the infrastructure is flexible. And it's scalable by its nature,
Amrit Chaudhuri 17:57
okay? Yeah, by its nature, it's interchangeable across multiple use cases. Turns up a lab is not allowed. It's not a lab. If you build a heavy chemistry lab to make mRNA. That is a different type of chemistry lab than analytics. A tissue culture lab at virology research is completely different. An animal research lab to do rodent environmental holding environment, so they live for their entire life cycles is completely different. manufacturing space is completely different. So we're talking about your every technology you're based off of requires a different and every stage of science and every type of workflow. And then every capacity that you're talking about, okay, let's set up to do small molecule synthesis. Am I going to synthesize that with five people with five keywords? Or am I going to be a scaled organization doing that with 30 people and 20 fume hoods, those are different things. And to get one or the other, is a is a static investment you're making. So either I build the 20 fume hood environment. Well now if I only need five fume hoods, it's not like I can go and repurpose the other 15 for something else, I've now over invested into infrastructure that is just going to sit there underutilized. Or if I built five, and now I need 15 More, it's gonna take me three years to build 15 More fume hoods, because I have to change like every part of the building, I have to increase the power in the building, I have to increase the exhaust through the building, including shops and distribution, I just shut down the labs to go in to add the HVAC ductwork to go and do this. And so the challenge space in our industry is that it turns out this is what we realized was like oh my god, this is impossible. When I when somebody comes to me and says I need to do a research program and I need exactly these kinds of systems for at power this on generator, this type of 150 psi nitrogen gas law It is reverse reverse osmosis purified water, this kind of environmental protection, positive pressure, negative pressure in my room, this level of HEPA filtering, like the we're talking about completely controlled, like hazard environments that are specific to the exact workflow science you're developing?
Ben Kaplan 20:20
And let me ask the obvious question, which is, why didn't you know that earlier? Now you say it's obvious, but is it harder to figure that out? Because like you said, You're a smart person, you got smart people,
Amrit Chaudhuri 20:29
no one in the world thinks about this, that I mean, you have, you basically say, you build a lab based on the science you're planning on doing. And then you just have that resource. And if you need a different type of science to be done, your lab no longer is utilized. utilizable. And that's just such a foundational, like, assumption that everybody has that and that no one seems to have a problem with, because that's just the way it works, that it's just not like nowhere in the world do you really go and say, Huh, labs are broken, like, labs are built the right way. People to say, oh, that's just how it has to be that through lab is if Pfizer goes and spends $400 million, and I'm not saying that they do, I'm gonna use their mezza as an example here. But if a pharma company goes and spends $4 million on infrastructure, and it turns out, they don't need that anymore, in five years, the research program that they're going to be they're putting as a research work through was like $2 billion a year of research going through that space, if you have to go out and demo and rebuild a new resource for another $300 million. It's a rounding error to the volume of r&d Spend you're making, because it's so expensive to do scientific research. So if I'm in 10 years, going to be spending $20 billion. If I spent 500 million and then had to re spend 400 million, that's a cost of doing business for $20 billion of research that we're going to be doing, right. So that's the challenge space, where if it was prohibitive, from an economic perspective, and remember, the problem the industry was, there wasn't much change happening. Initially, you're working with one technology set, most of your labs are mostly utilized and applicable, that you started working with two technology sets, and now you had underutilization happening, but still an acceptable range, when you get to 20. All of a sudden, you have to have 20 sets of infrastructure. At any given time, he's going to be having variable levels of utilization. So the problem space is only actually also coming up in like the last decade and a half. And so, so there wasn't this wasn't a problem in the 1940s. This is a problem that he doesn't 10s of, hey, this is getting worse, as our sciences diversifying at an exponential rate. We've now diversify hundreds of billions of dollars of infrastructure in a way that we're not we've never had to do before. In the World History
Ben Kaplan 22:56
response, as you went to investors to people get it right away, you have a pretty good analogy there to sort of say, hey, it's in these other industries that people get it was difficult was a challenging, it might be more complex than other infrastructures you have to build,
Amrit Chaudhuri 23:07
we have to simplify this in a very different way. We have to present the opportunity from the lens of hey, look, this isn't about if I go and tell you that I'm gonna go and take Pfizer's 9 million square feet of laboratories. And suddenly they're going to use my platform instead of their own internal platforms, and be laughed out of the room. And so you couldn't use that was the opportunity space, our opportunity space, the way we presented, it was, hey, look, Pfizer is about to start investing more and more heavily in other companies that they eventually want to partner with or acquire, to develop drugs, because the number of drugs that need to be developed and explored is so varied hundreds and hundreds of them, that Pfizer with a $10 billion budget isn't going to be able to explore all those areas, they have their own internal projects they're working on that are already in mid flight. They're gonna start making external investments in startups and midsize companies as partnerships and out licensing for those. Now, for those companies that aren't historic, don't have 10 million square feet of infrastructure. They're having to make a buy versus build decision to constantly around the infrastructure and tools to develop these next generation of therapies. Well, let's now give them a third option that's do buy, build or subscribe to that infrastructure. And because they don't have the historic infrastructure in place, that's not I'm not trying to make somebody change behavior from something they've already invested into. They're going to have to invest one way or the other into new infrastructure. The question is, is that new model more cost time or functionally effective compared to them going building a building or leasing some shelf space and building out labs and running labs and, and all of the complexity to do that?
Ben Kaplan 24:55
So paraphrase, you weren't trying to some of these really big pharma companies with really deep pockets and really elaborate infrastructures. You weren't trying to say use us instead of that, because that would be a difficult site, you're trying to say, use us for these other projects that you're partnering with other people that aren't using your core infrastructure, we can be more efficient in deploying that. And it's changing because there's more startup companies, there's more innovations. There's more early stage things where Pfizer doesn't have to develop everything from scratch, they might let someone develop it, get it far along, and then partner or buy them and you're gonna target that is a multi billion dollar acquisitions
Amrit Chaudhuri 25:31
happening every year right.
The Detective 25:36
Smart Labs had to tackle inventory mismatch and complexity. They had difficulty convincing large pharma companies to switch to their platform, and struggled to scale due to the diverse lab infrastructure needs. Amrit had to reflect on their entire business model as it grew stagnant. How did he overcome the old way of thinking and set SMART labs up for the future?
Ben Kaplan 26:07
I'm read take me through the pivot and where you find your new business model. And then what results from that? Oh, so
Amrit Chaudhuri 26:12
when my co founders and I built the business in 2015, we found out about 18 months later that the assumptions and premise service model didn't make sense. So we had to think on our feet and then do what scientists engineers do, which is analyze and understand what was the root cause of the problem. And why why our business wasn't going to be able to work and what the actual problem was for the industry. And that actually ended up restructuring and relaunching our business in a completely different direction. So I think the easiest way of giving an analogy is we thought we were going to build a business model like Uber, right for Pharma. There was this idea of fractional access. And when we realized that the, the prohibitive nature of that was the actual infrastructure, and the diversity of inventory challenge, the inventory mismatch challenge. The first question we asked is, is this only happening to us, it's only happening to us, it's really not worth investing in trying to figure out how to fix this, that it turns out that we found that this is actually a problem that gets worse, the larger the organization you get. So a large pharma company, with 5 million square feet of labs is actually juggling an inventory of 5000 different types of labs in different regions and geographies, all on a micro level, that in order to make a change, they have to predict the kind of science you're trying to do in five years. You don't have to happens in five years to your science, everything changes. Science is literally experimentation, what will work and what won't work, things that work, you double down on things that don't work you kill. So how do you know in five years be exact projects at the exact scales in the exact regions in the exact kind of laboratory infrastructures and operational infrastructures you need that you have to commit to today, but that if you don't commit to today won't be in place in five years. So this is a macro macro, like this is like a trillion dollar problem space. Like truly, I'm not like over emphasizing this, this in the next 10 years. It's a trillion dollars worth of infrastructure. And so when we were like, wow, this isn't actually about us. This is the fact that our industry is about to break from an infrastructure perspective. So that's where it's super valuable to go and spend our time. So going back to the Uber example, Uber gets things from one place to another. Another business model gets things from one place to another, but has a lot higher complexity, SpaceX, SpaceX will get your thing into space. That's it. That's all they do. But in order to make that business model work, they had to reinvent the rocket. Right, SpaceX invented the first reusable rocket because they said, if every time we have to get to space, if you have to go and spend a billion dollars on a brand new rocket, space exploration and getting being able to launch things into space is going to be so held back that unless the most highest and critical nature, things happen, the barrier to entry is too high. So it's up spending a billion dollars per rocket launch. What if we spent $2 billion on a rocket we can use across 10 lodges. And now we've just reduced the cost by 18%, of getting something to space.
Ben Kaplan 29:18
So you need to think about how do you make a reusable lab instead of a reusable rocket? How can you create a framework that allows you to reuse components make it more modular to upgrade one thing and not have to upgrade the
Amrit Chaudhuri 29:32
whole thing? Exactly. So we built the world's first dynamic and universal lab. We took that 1000 skews of inventory of laboratories and over since 2016, to today, they were in version eight right now. We've compressed it to two and so we are the most advanced infrastructure engineering design, construction and operations company in laboratories in science in the world today. And we today have invented the first universal and completely reconfigurable reusable lab, we build labs like Legos. And so we can actually in a massive building, take, you know, 10,000 square feet. And if you needed 20, tissue culture hoods, and 30 different rooms, great, we can build that, if you needed to write all of that work and erase it and rebuild it. It's just a massive chemistry facility, we can do that. And we can do that in two to four weeks for $20 a square foot, instead of the industry average of two years, and $500 a square foot
Ben Kaplan 30:34
when you have the idea. And you sort of had to pivot what float on the business side from that, like there's a technological advancement you have to do. But you also have to, you know, we don't want to eat just ramen, we want to eat salads and desserts. So what do you do,
Amrit Chaudhuri 30:46
we did a pilot program in our existing building, we ripped out 10% of our footprint. And that would be really unique part of I guess the founders, including myself is that I'm a bioengineer, and a synthetic protein chemist and that they work in product development. But like I had a second life in systems engineering, robotics and automation. And so I look back and I was like, Oh, this is really interesting. The process in which our industry develops a lab is not like the process that the automotive industry develops a car, or the computer industry developed the motherboard, there is no systemization or framework being developed to be reused or the ability to swap out components on the on the fly, right? Today, I can go into my computer, pop up the processor upgrade, the processor changes the RAM around and in, you know, a day the computers still functional. Well, the way that our industry works today is that you can rebuild a computer every time you want to go and make a change.
Ben Kaplan 31:41
And what are the challenges going forward now to realize your full vision what what's the obstacle,
Amrit Chaudhuri 31:46
so there is a billion square feet of labs in North America. And our current trajectory is to get to two or 3 million square feet, it's a scratching of the surface. So in order to change you can just do behavior we have to 10x 250 x the the footprint and a scale we're moving towards to create true industry adoption and shift.
The Detective 32:08
Smart labs revolutionising the way life sciences companies access and utilize lab spaces. Their unique business model, offering flexible lab infrastructure as a service to clients and their ingenious Lego like approach to assembling labs. An inventory mismatch. Industry skepticism, and a scaling issue nearly halted the growth of a disruptive and innovative company
by creating a lab infrastructure that is completely reconfigurable and reusable. Smart labs revolutionized the industry. Operating in stealth mode for several years they built trust and a track record of success. By continuous piloting and refining their business model. They overcame obstacles much like a catalyst accelerating a chemical reaction, propelling them forward to reshape the scientific landscape.
And with that, it's CASE CLOSED
New episodes will always updated regularly
