We literally have a Concerto sticker that says it takes a village of microbes, because we also believe that it takes more than one microbe to do anything useful in biology. Yeah, we love our communities of microbes that are working together to keep us healthy.
The microbial world within each of us has been incredibly difficult to see, until now. From the depths of our intestines to the surface of our skin, our bodies our hosts to trillions of microbial cells, spinning thousands of species. While critical to helping us to fend off illnesses and digest complex foods, we know very little about the complicated interactions among these microbes. For this episode, our special guest is Dr. Cheri Ackerman, CEO, cofounder of Concerto Biosciences. Her team has put in place a key step in advancing the understanding of ourselves, a system called the kChip that enables measurement of the interactions that occur among a multitude of microbial species. Let's dive in.
Welcome to Tough Tech Today with Meyen and Miller. This is the premier show featuring trailblazers, who are building technologies today to solve tomorrow's toughest challenges.
Hi, everyone, it's my honor to welcome Cheri Ackerman on Tough Tech Today. Cheri is the CEO of Concerto Biosciences, which is reinventing humanity's relationship with microbes. We're really excited to dive deep into the actual company, the technology and a little bit of Cheri's background today. So let's get to it.
Awesome. So Cheri, we have heard that you are working on something called kChip devices. Can you give us the lay of the land? What this is—I presume is not something edible—and kind of go into the so-what behind this?
Sure. Yeah, maybe it's good to start with how this type of device is actually applied? What do you actually do with it? So we invented this technology at MIT. And the motivation for creating kChip was we understood that the microbiome, which are all of the microbes that live in, on, and around us, is a very complex ecosystem, where the way that any one individual microbe works depends on the other microbes that are around it, or the environment that that microbe lives in. And the problem, if you want to study that, experimentally, is that it just becomes literally millions, billions of experiments that you would have to run because if you have one microbe and you want to know, okay, well, what if I put in the presence of this other microbe? What about a different microbe? What about this one experimental condition or some other condition? It's a combinatorial problem, and you end up with billions of things that you have to be able to test. So then the question is, how do you actually physically set up all of those experiments? The way that you might think to do it is, let's try to use a robot. So we'll just program a robot into, well number one of 96-well plate, we're gonna put microbe one and microbe two, well number two, we're gonna put microbe one and microbe three, etc, and array out all these microbes. Theoretically, this works okay, except microbes are growing the whole time that you're trying to set up your experiment. So you suddenly end up with these massive batch effects. Plus, if you do the math of combinatorial problems, it just is literally too many things to test. So as an example, if you have a microbiome that has 1000 microbes in it, and you want to measure all of the possible pairs, so make every possible set of two, and then measure how each of those work. That's half a million measurements that you would have to make. And if you make those more complex, say out to sets of four, you're now talking about billions of different possible combinations. And you need to make and measure each one of those combinations to understand how all these microbes are working together. So this issue of combinatorial experiments, how do you physically set up combinatorial experiments? That's what kChip was designed to solve. And how we're using it today is that we basically have these libraries of microbes or different conditions that microbes can grow in and then we make all of the different possible combinations, measure them all, and feed that into a computer algorithm that allows us to then say, well, like if you have this thing, this thing, and this other thing that we didn't test, can we predict how that combination would behave? And can we pull out the best combinations to put into specific products that will do useful things for people. And those can be things like, let's make a combination of microbes that we can use to treat eczema, which is one of our early applications, or let's make a combination of microbes that you could use to treat recurrent vaginal yeast infection. So kind of a long answer. But that's the overview of why the technology matters. And I can tell you more about how it works as well, if that's of interest.
Yeah, that would be great. I think just even taking a step back: could you help us understand what the range of microbes you can test in the system? I mean, there's, of course, lots of bacteria, many types of species, what are that class that you are focusing on, or what are the limitations here and just want to learn more about that side?
Yeah. So kChip was originally designed to work in oxygen, it was designed to work on the soil microbiome. So the original papers, we isolated, we—my cofounder, who was a graduate student at MIT at the time, isolated microbes, literally from Killian Court at MIT, and put these into kChip. They grow just fine. So all of the same growth kinetics that you would see on a 96-well plate is exactly what you see in kChip. From the microbes' perspective, the volume issues are not a problem at all.
Just so want to understand Cheri, define like microbes in that space for us, and what are some of the types of microbes that the kChip can test? What are the limitations of that space? How many combinations can it test? Just trying to understand the boundaries of the technology?
From the question of what counts as a microbe: bacteria, fungi, viruses, phages. Things that we've actually put onto kChip: bacteria, fungi, plenty of genetic material as well, just straight up DNA. We haven't actually played much with viruses or phages, although there's no reason to believe that it wouldn't work. And then in terms of which types of bacteria, which types of fungi, they can come from anywhere. Originally, the chip was designed to work in oxygen, we designed it using soil microbes. But then we've also been adapting it to anaerobic conditions. So now you can we can grow things like gut-derived microbes on the chip, and it works just fine. And then in terms of the limitations of size, so the way that the chip works, it is a MicroWell array. Um, so you can think of it like a 96-well plate. In fact, it's the size of a 96-well plate, except it has 100,000 wells on it. And each well holds somewhere between one and sevenish nanoliters. So it's very, very small volumes in order to make that geometry fit.
I want to know before we get too far away from it, did your cofounder find anything interesting in Killian Court, I imagine the microbiome of a court where you see a lot of student traffic could be a little interesting.
That probably is true, we definitely weren't looking for anything. We're looking at microbial ecology, right? So we're looking at how do these microbes metabolize different sugar sources in order to be able to grow together? I can tell you things like he found a whole bunch of facilitation, a whole bunch of competition, like all of the different possible relationships, you would imagine. You can find them out in nature, which is very cool. I can't make any conclusions about the undergrads at MIT.
I imagined like the boba tea, you know, could be a sugar source.
Yeah, exactly. Exactly.
I'm thinking through this... You mentioned kChip and is this a physical... or I know it's a physical aspect but um, could you describe that? Could you be the eyes for our viewers and our listeners?
Yeah. It is a plastic, a flexible plastic chip that is the size of a smartphone. If you know what a 96-well plate is: it is literally the size of a 96-well plate. It is about this thick, and the way that we make it is through a mold process. So the plastic that it's made out of starts as a liquid, and you pour it into a mold, and then it hardens and you peel it off. And then when you peel it off there all of these little tiny wells that are in the surface of that chip, and those wells are big enough that you can see that the surface of the chip is fuzzy, but small enough that you can't really see each one individually.
So then is this something that.... this may go into the some of the sort of revenue generating aspects of Concerto... Is it that we could sell the sort of physical hardware and maybe some of the analytical capabilities on top of it to a pharma company, for example, as an option one. Option two: perhaps being able to operate, keep the kChip sort of physically in house but having other folks contributing their fungal or bacterial strains for analysis or something there and then Concerto can share those results, the data, and then the third being all in house like a vertical, integrated approach to make Concerto's own kind of ointments or drugs or something. Can you walk us through those three or more pathways that you have ahead of you?
Yeah, we actually decided pretty early on that we're not going to do the version of the company that would be build the box and sell the box. So we don't make kChips that other people could buy and bring in house. A big part of that is that the technology itself is still... like you need a very specific kind of microscope, you need to be able to make the nanoliter droplets that go into the chip, and all of this specialized hardware plus understanding how do you actually design a kChip discovery campaign in a way that will get you statistically meaningful results, because as soon as you start testing, you know, many, many, many chips, you're getting millions of data points. And this is a type of experimental design that most scientists don't play in very much. So we've actually chosen: we like to have it in house and be the partner for another company that can generate this type of data at a volume and a price point that isn't really available anywhere else. So we do have our own internal discovery projects: those eventually will be out-licensed, we don't anticipate that we're going to be the company that's selling to a farmer or to a doctor or something like that. We work with other companies, whether we're out-licensing the more developed assets, or we're starting from the very beginning with a partner who has an idea—oh, we'd like to develop this thing from microbes, can we work with you, and now we have a data set that we wouldn't have had access to before. And then from Concerto's perspective, we get the expertise from that partner on what do their customers really want and maybe they have expertise in running clinical trials or things like that. And that is super helpful for us.
Yeah so Cheri, what you described very much is like, yeah, that early part of R&D you want the sort of R&D I guess you want to be focused on and then really finding the partners to bring it to market, which makes a lot of sense. If we come back to the kChip, the actual physical device, you mentioned, you're gonna you'll have maybe like millions of these chips running and figuring out all sorts of combinations of these microbes. What are some challenges with like manufacturing the chip? Is this like a sort of a standard microfluidics thing that we have a lot of manufacturing capabilities for? What are some of the constraints around making like millions of these?
Yeah, so we fortunately do not need to make millions of the chips. That would be a huge undertaking. What we can do is make tens to hundreds of chips, where each one has 100,000 experiments on it. So then, multiply that out, and you end up with millions of data points that are coming off of tens to hundreds of chips. In terms of the manufacturing side, we make them in house, and it's a very standard soft lithography. If you happen to know what that is... process. They're made out of PDMS.
What's, I guess,
Building on Malvika's question, what is the toughest technical challenge you've had to solve to bring your dream to reality.
So the invention of the chip was actually done before me. I am one of the inventors of the later development of the chip, but the original invention was made by Jared Kehe and Tony Kulesa, Paul Blainey at MIT. I think in terms of getting it out into Concerto, one of the tougher technical challenges has been adapting it to an anaerobic environment. And that's not just getting the chip into an anaerobic chamber, which you can definitely do totally fine. It's also figuring out how do you read out the biology on the chip, because if you know anything about green fluorescent protein, GFP, which is what everyone uses to study microbes, GFP requires oxygen to mature, GFP does not fluoresce in an anaerobic environment. So this workhorse of a genetic tool that every microbiologist works with is suddenly not available as soon as you want to measure what microbes are doing in an anaerobic environment using microscopy, which is exactly what we're trying to do. So it's been a lot of working around, basically developing new strategies for assays that will work under those conditions, which we have done, and it works, which is great.
And what does that open up in terms of additional markets? Just paint that picture for now being able to have this capability? What can you do? Is it other types of... like gut... new environments? Yeah, just curious how that changes the game now?
Yeah, it was super important. So things that were accessible before were things like skin microbiome, plants, a subset of the vaginal microbiome. It's like microaerophilic. Lots of things that happen in water as well. Things that were not accessible: oral microbiome, all of the things that cause plaque and gingivitis are either anaerobes or the environment where they grow in your mouth is pretty anaerobic. Most of the vaginal microbiome actually grows anaerobically. So if we want to look at things like, you know, preterm birth and STI transmission, bacterial vaginosis, those are all... you need the anaerobic conditions to make that happen. And then, oh, my goodness, so much gut microbiome that's now accessible. So these are things that you probably have already heard about in the news like C. Diff. infection that Ferring and Rebiotix have been working on, as well as Finch, Vedanta, you know, for a long time and have now seen success, right, which is super cool for the field. Two things that are really hard to address, we know that there are associations between, for example, the microbiome and autism, Alzheimer's, Parkinson's disease, how do we actually begin to understand that biology? I think even the ability to work in the gut microbiome, like we'll see if those are things that Concerto can ever take on that complexity of biology. But it's everything that has a tie into the gut, which can be immune things, gut-brain axis, all kinds of... gut and cancer actually is another area that people are really interested in with the microbiome. Yeah, metabolic diseases, diabetes, all kinds of stuff.
And I just want to jump on one more question, but then I'll let others talk. But you mentioned the complexity of these microbiomes. And if we think about the skin, right... with what your lead product is trying to address with eczema. Like just paint the picture... like how many types of microbes are on our skin, and now you're growing it in these little MicroWells, like how well is that really approximating... I don't know, maybe the thousands of types of microbes and growing on a larger surface, like how are you like.... that sort of standard, like in vitro, in vivo correlation? How are you really addressing that?
Yeah, it's a huge problem in the field. Because when we look at animal models too for microbiome, how do we begin to approximate what these microbes are actually experiencing? On the surface of the skin, in the gut, etc, in our experimental models. So I would say that the way that we get around this is actually by testing just hundreds of thousands of millions of different conditions. So when we find a group of microbes that looks like it's going to perform this desirable function. So as an example, we've been working on eczema. The underlying biology of eczema involves the bacterium Staphylococcus aureus, Staph aureus, and Staph aureus will grow on the surface of skin, it will secrete toxins and proteases that break apart the skin and aggravate an immune response. So what we were looking for were three microbes that when Staph is grown in the presence of those microbes, the Staph aureus doesn't produce those toxins, those proteases. So even if Staph is present on the skin, you can put these microbes on the skin and now Staph is pacified, it's under control. When we found the different groups of microbes that could possibly perform this function, right, under one set of conditions, we observed them performing this function, we then took that same set of microbes, and exposed it to hundreds of thousands of potential conditions that it might encounter on the surface of skin. So we threw it into our biobank of all the different microbes that we isolated from human skin and asked in the presence of all of these different microbes, does this group continue to function? So was any one of those conditions a good proxy for skin? Everywhere? No. But by testing it against all of these different conditions, we have a pretty good idea of which microbes found on the surface of skin will contribute to what we're trying to get this ensemble of this collection to do, and which ones might get in the way of what this group of microbes is trying to do. And then we can also do the same thing with nutrients. So if we expect that on the surface of skin these microbes are going to encounter certain sugars, amino acids, different compounds that are found in you know, lotions, that people use, etc, we can use kChip to make all of the different combinations of the different nutrients that might be found on skin and ask how well does this group of microbes inhibit Staph aureus in all these different possible conditions? So it's not really a question of is any one particular well on kChip a good proxy for skin? It's more like if we can throw all of these different possible conditions that it might encounter at this ensemble and then ask if it keeps working? That's a pretty good proxy for it's gonna keep working, even if we put it on skin later.
That's super helpful. Makes sense. Yeah.
Is that then that a lot of the value creation of Concerto is in amassing this library from the profile of Killian Court to vaginal swabs to skin conditions, and then.... so like a pile of data that hasn't previously been been acquirable, or at least not at scale, and then getting into a better sort of almost predictive capability so that drugmakers or treatment people would be able to say, okay, we can down select from thousands of thousands possible ways of treating eczema to maybe the ten most likely to work kind of approaches, is it that kind of a sort of sense of value creation and capture?
Yeah, exactly. So when we started our eczema discovery campaign, we started with a library of microbes that was around, I think, 1700 or so. If you look at all of the possible combinations that we would have had to test to downselect to our top, now-lead candidate for this therapeutic, it comes out to something like 800 million things that we would have had to test. And we can use kChip to explore a subset of those, kind of learn a little bit about the landscape, downselect a little bit more, learn a little bit more, downselect little bit more. And so it allows you to sift through what otherwise would be a completely intractable number of combinations, down to actually finding what is the best combination of microbes that you want to put into a cream that will help someone with their eczema.
And so when you generate all of this data is this is owned by your partner customer, or does this go into a library of data that's owned by your company?
Basically, everything that we do internally, when we take on the discovery ourselves, we own all the data. When we partner with another company, that's part of the negotiation actually. And we think that it's very important for us to be able to at least to be able to take the data and put it into our database. There are plenty of companies that obviously don't want their data to be specifically accessible to a potential competitor or something like that. And we can protect against things like that, too. But it's interesting, actually ownership and terms like that are just always part of negotiating. Almost anything can be purchased.
Your CEO wouuld probably have to do a lot of that work.
For sure. Yeah, yeah. And it's really important. I mean, our partners are incredibly important to us. So we want them to get what they need out of a partnership. And for some partners, access to the raw data is super important. And then for other partners, they don't care that much about the data that drove to that discovery, or that recommendation of these are, you know, the top fifty combinations: what they care about is, well, which ones are the top fifty combinations. And it's just about understanding what the partner is really looking for, how and where they would drive value.
You mentioned earlier, right? There's sort of the field of the microbiome, and a lot of it focused on therapeutics, understanding also there's sort of the agriculture application as well that I think your company is also exploring. Could you talk a little bit about that angle too, so not just the sort of biotherapeutics side, but also the AgTech application?
Yeah, there are two major areas where people tend to apply microbes in agriculture. One is bio control. So replacing pesticides and herbicides, things like that, with microbes, and bacterial pests, fungal pests are the ones that are a huge problem that are readily addressable by... we can just put the right microbes on the leaf of a plant or in the soil, such that molds or whatever can't grow in that location. The other major category is bio fertilizer. So if you want to fix nitrogen and carbon, make more nutrients available to the soil. That's another area where microbes are very good at doing that naturally. And so then how do we take those natural processes and either amplify them or, you know, make sure that the right microbes that perform those processes are present, that's a major subset of how microbes are used in agriculture.
And in terms of the maturity in this space of using these ensembles of microbes as either therapeutics or as like biofertilizers. Like what is the precedent right now, you mentioned Seres Therapeutics and the recent approval there, but... and how is that maybe helped or de-risk some of the clinical aspects of what you're trying to do or in the AgTech field, is there anything approved as like the microbe product there and yeah, just want to understand that precedence for these kinds of therapeutics or agriculture applications.
Right. On the therapeutic side, there are exactly two and they are Rebiotix's product, and Seres Therapeutics' products. Those are derived from fecal matter as opposed to.... I think there's another strategy, which is let's build these ensembles or consortia from the ground up. So we're going to take this microbe plus this other one plus this other one. That strategy.... people are working on it, tons of companies are working on it, but nothing has made it all the way through to approval yet. Single strain strategies are also pretty common, although the success or efficacy of those on the therapeutic side has been maybe a little bit more limited. So it'll be interesting to see the companies that are pursuing that strategy, how far any of those companies get. I think, on the agriculture side, single strain has been the majority of products, there are some that take single strains and then combine them. But the idea of making these combinations of microbes is somewhat less common. And often people see it as a cost of goods issue, where if you're gonna... if you have to make one product where now you're manufacturing these different strains and you then you have to combine them together, all of a sudden your product just got three times or four times more expensive. So there are also companies that are working on how do we do co-fermentation so that we can get these defined ratios of microbes out of a single fermentation process. And I think there's a lot of value to be added there, not just in... I think we feel it most acutely in agriculture, because the margins in Ag are so small compared to therapeutics, but it will also drive down the cost and make it a lot easier to produce on the therapeutic side, too.
Is this something then that... that there's some overlap in the Venn diagram within synthetic biology, where fermentation challenges are considerable to be able to grow or cultivate at scale these these engineered microbes, and where Concerto's technology would be able to potentially help increase the lifespan or growth span or whatever so that we can have—not just for therapeutics, but also for non-medical purposes of biologics —that could start to, in some way, start to replace parts of the chemical industry with the complement complex molecules that biology inherently likes to burp up?
Yeah, yeah, absolutely. I think figuring out how to optimize synthetic biology outputs has been a major challenge in the field. And you see, companies like Gingko, which have made their entire business on optimizing the genetic circuits that pump out these very special molecules, and very useful molecules. Then the question is, can you also optimize a microbe that has been engineered to produce something that it wouldn't normally produce? Can you optimize that microbe using its environment? So which different kinds of sugars are you going to feed to this microbe and cannot change the yield of your engineered microbe? Or is there another microbe you can add to the fermentation process that, for whatever reason, is helping... maybe it's removing a waste product that this microbe would make? Or maybe it's providing some cofactor that like, we don't even know that this microbe needs right? But you can find these things experimentally, just by taking this genetically engineered microbe and coculturing it with all of these other natural microbes and asking how does the yield of your desirable product change in the presence of these communities. In the case of then having to do the co-culture for the fermentation itself, I can tell you, there are probably fermentation engineers that will be listening to this just cringing, thinking about trying to keep a co-culture in a defined fermenter running the way that they want it to and not having this ecology go sideways. But I think there is space there, right? If if it turned out that we could get a major yield boost, then maybe it is worth it to do co-culture fermentation. I think we're really early days on that. I think optimizing the growth conditions and the nutrients, micronutrients, metals, sugars, things to optimize a synthetic circuit: that's something that's much more tractable, right now.
So I'm kind of curious on the delivery mechanism for some of these products. So for example, like the eczema product, is it like a cream, like a yogurt-type thing, that you put on your skin? Or can you describe that?
We do use the analogy of yogurt to help people understand just how safe it is. So you would never be concerned about rubbing yogurt on your skin. IT contains billions of microbes: totally fine. We are actually still working on the formulation for this. So the possible formulations could be as wide as, for example, a spray. There's a company called AOBiome that has a spray of a Nitrosomonas that you just literally spray in your face, spray on your arm. There are other companies that have done things like creams, oils... the main thing is for the microbes that we're working on, we need them to not be exposed to water. So they need to be somehow dehydrated, in order to be shelf stable. And because otherwise you run into cold chain issues of... oh, we have to keep them frozen or refrigerated... nobody wants to keep their lotion in the freezer. That's not really a thing. So formulation is a huge issue in this field, and we're working on it right now. We'll see where we ended up.
This past fall Concerto raised, I understand, over $20 million as part of the Series A, and in that a predominant focus is on on setting the foundation for the eczema play, as well as I imagine the the overall sort of platform which in biotech land is as well as in other fields, startup communities, or like build the platform, not the product kind of thing. How, as CEO, how are you thinking about the ways of being able to almost handle two very different levels of zoom, so to say. Zooming in very close to make a tactical product that that would need to perform well in the market, to selling to the average Joe consumer, and also, at the 10,000 foot view, so to say, of you know what, now we can we've successfully demonstrated one play one area, now we're going to do it, times two, times three, times four in other markets. Walk us through that.
Yeah. The unifying principle is that Concerto operates through out-licensing. So everything that we do, we're not going to be the people that bring it to the end customer. In the case of the eczema product, we're doing enough on that product to make it something that another dermatology company would look at, and say, that's really valuable, I wish that I had that in my portfolio. There are other areas where companies are more willing to jump in from the very, very beginning. So, for example, in agriculture, we've seen a lot of early traction, where a company will come with more of a concept. Like I wish that I had a set of microbes that could deal with this particular fungal issue or this biofertilizer issue. And we work from the very, very beginning. But again, it's an out-licensing model in the sense that we're not going to take this product all the way to the farmer: the other company will take it forward after we work together to figure out what the product is going to be. And then from that, it just becomes a portfolio optimization problem, where you know, how much money are you going to have to sink into any one asset in order to get it to a point where you can start getting revenue back in, which in our case is going to come from a license? And what is the final value of that product, versus the risk of that product not panning out at all, and the time it's going to take to get there, right? So it becomes this multivariable portfolio optimization problem. And I don't think there's any... there are certainly books and books and books that are written on the math of how to do this. But from just a sort of armchair philosophy standpoint, you meet people all the time, who have lots of different ways of thinking about these types of problems, and whether it's better to just focus on that one asset, get that one asset, the proof of concept really, really solid, out-license it and then you know, make a billion dollars, or if it's better, to be more diversified. And in our case, I think we're choosing a slightly more balanced approach where we do have second, third, fourth projects that are running. But that can't come at the expense of the first area. Because that first area is what's going to validate that our discovery approach was good in the first place. So that's why it's so valuable to push that first asset all the way to actually getting data. In our case, in people—in Ag, it would be in the field or whatever.
When might we be able to have the eczema yogurt on our skin?
On your skin, ha. So we are going the FDA route. So that means phase one, phase two, phase three clinical trials; typical timelines for that are something around ten years. In dermatology, it's a little bit shorter. So I would say you're gonna have to hang on until probably the late 2020s.
That's great. And Cheri, one question that jumped up when JMill was asking about the platform, and you know, thinking about investments into that. My understanding is you reached this... there were republished papers from the MIT work with the kChip, and you then built the anaerobic capability. What are some of these other big technical milestones that you want to demonstrate with the platform? Is it focused on adding more assays, trying to figure out what you can measure from this chip, like adding sequencing or or adding even more other, like you said—you mentioned like phages viruses, like adding a lot more complexity in the diversity of microbes. Walk us through a little bit of those technical milestones; like what are some of those upcoming ones you see, as priorities?
Yeah, we tend to prioritize technical development based on the products we're going after. So we develop new assays, as needed, based on the type of biology we're trying to address on the person in the field, etc. So we talked about the anaerobic development earlier: that was really important for unlocking this entire type of microbiome, right? Now we can access the gut microbiome, which wasn't a thing before. There's another sort of... I would say, okay, actually, no. So we were accessing the anaerobic microbiome: this is a whole new area that we couldn't get to before. So now, we can access aerobic and anaerobic microbes, which are basically the two types of microbes, then there's another type of development that we're working on, and that is just throughput. So this isn't trying to make kChip be able to do something that couldn't do before: it's literally just making kChip faster. The way that kChip was originally designed was to be used by a person. So you use a different microfluidic device, not the chip itself, a different device to make all of these nanoliter droplets that end up in the chip, and then you pull them all together manually, and then physically pipette them into a flow space that goes underneath the chip. And then physically, you just like rock the chip around, so that all these droplets will flow over the chip. And you can think of them like marbles that are like falling into cups. That process is super manual requires a human. Humans need to sleep and eat and robots don't. So we think a lot about how do we take this very manual process and make it more automated. So imagine if you could have a person sitting at home, designs an experiment, there are literally robots that go to a freezer or pull out the microbes that we want to test, they get made into droplets automatically, they get loaded into a kChip, the kChip goes on the microscope, all the pictures get taken automatically get beamed up to the cloud, like what would it take for us to get to that version of running kChip? And what's the sort of scale we can expect, if we can do that? That I think is a very cool problem. But it's very different from new capabilities like new assays or things like that. And the automation thing is something we're actively working on right now.
There's a considerable amount of responsibility that you have as CEO of this growing company. What are some of the experiences that you've had prior that you've been able to lean on to help you be able to sail this ship? Because it's working on new technologies, complex fields; there's a lot of uncertainty there. How do you manage that?
Obviously, my technical training is a huge piece of this. And I don't just mean that from the perspective of I have a pretty good intuition of what will probably work, what will probably not work on the kChip. That's a very useful thing to know when talking to potential partners. But I also mean that from the perspective of having technical training, just helps you be good at solving problems. And my experience of being a CEO is just having to learn to do my job faster than whatever the company needs me to be able to do. So if you had asked me to lead the company now, but with the experience that I had two years ago, I would fall flat on my face because I, over the last two years have grown to be the person with the experiences that can actually lead the company where we are now. And I think for me, I'm always trying to figure out who do I need to become six months from now? And how do I invest in those experiences that I need in order to be that person by the time six months from now arrives. And a lot of trying to find the answer to that question is actually talking with advisors. I'm in like a CEO roundtable group, making sure that I am doing the "meta" work of not just doing my job, but figuring out what my job is going to be six months from now, and that I'm going to have the skillset that I need to do that job then, and that I honestly think like comes a lot out of my PhD training of seeing the bigger picture of problems and not just how am I going to solve this thing? But how does this thing fit into the larger story of the bigger picture problem I'm trying to solve? All of that willingness to experiment and take data on... the experiments that I'm running with my team, for example, the way that we run our company, is that working? Is that not working? Should we be trying a new organizational structure? Should we be trying new communication methods? All of that comes because the cofounders of Concerto are scientists. So when we think about even our organizational problems, we're thinking about them from a scientific method perspective.
Can you talk to us a little bit about the the origin story about the company? I don't know if we've had a chance to dive super deep into that.
We spun the company out from the Broad Institute, which is at MIT and Harvard, for people who are not in the Boston-Cambridge area. The technology was originally invented in Paul Blainey's lab at Broad and MIT. And the way that we got started in the company was Jared Kehe, who's one of the inventors basically asked me, hey, do you want to see if we can commercialize this thing that we're working on in lab. And I had come into my postdoc, very open with Paul about the fact that maybe I want to start an academic lab, maybe I want to actually start a company. And he was totally cool with that. And so we started doing a whole bunch of different accelerators and incubators. We did the... MIT had a biotech startup thing that ran for just January that we did that Tony Kulesa started. And then we did the Harvard Nucleate Activator program, like twelve weeks of, let's learn what a competitive landscape is, and how does IP work, and for us, it was really just figuring out what vocabulary exists in the industry, and then connecting with a whole bunch of mentors and expanding our network. That was the spring of 2019. We spent a lot of the summer and fall of 2019, trying to figure out where we could possibly get money, and what our actual market was and who our customers could be. And then going into 2020, we got our first money, two weeks after Boston shutdown for the pandemic. And that money was going to become available on June 1 of 2020. And we took it and decided to leave Broad, and became Concerto on June 1 of 2020.
Wow. Was it scary taking that final leap? And kind of leaving the nest, starting the company full time?
You know, people ask me this all the time? And the answer is no, I was super excited about it. We had a cofounding team of four amazing people. And we all trust each other really deeply. And we were completely complimentary to each other, like none of our backgrounds were remotely the same. And yeah, I was like, well, we have the money to do it. Let's try. And I was very excited about it. Yeah.
So you got you started as this team of technical, I guess nerds who built the technology. How have you as a CEO, right with that deep technical background, and now this whole founder-scientist movement, like how have you picked up sort of the other side of the job that entails that business aspect, that acumen that a lot of people get just from experience? Like who are some mentors or—you don't have to name them, but just what have you...? What are those experiences that you were mentioning that you've tried to have? Or how have you prepared yourself for that sort of business side?
Yeah, listening to people, asking a lot of questions. And that started as early as the Nucleate Activator program. We were paired up with three mentors, who one of them is an observer on our board today, the other two I consider to be friends and, you know, nominate us for awards and do all kinds of things to get us plugged into the larger—even still today now, four years later, right?—this network is incredibly tight and supportive in the biotech community, and being able to ask them questions about what's normal, what's not normal. The thing that I'm learning right now is much more the practical side of business development. So we recently hired a senior director of business development: he is phenomenal. We have a fractional Chief Business Officer, also fantastic. And it's been really amazing to watch these two people, not just come in and lead business development at Concerto, which they're definitely doing, but also help me and help the other cofounders see: this is what's normal in business development. And these are the things that you can expect in this type of a conversation. Here's where we are in the story arc of how business development happens. And I think putting people around us who are willing not just to be really good at their jobs, but also to teach us this part of biotech that, how would I know? They're not looking down on us and in any way, right? They're perfectly happy to explain this is what's going on in this situation and share what they see. And then we get to share what we see and understand from a technical perspective, or from a team-building perspective, or all the things that we've learned along the way too.
Cheri, would you like to share—as we come to the end of our conversation together—what you are looking out for to help Concerto. How can our listeners and viewers help? Are there particular positions that you're looking to fill? This is this is your time to let us know.
Yeah, thank you, I would say what we're looking for right now are people who are interested in building microbial products. So people who work as scientists or in business development at other companies who see the potential for microbial technologies. Maybe you don't have a microbiome program at your company, but there's interest there. And trying to find these people and form collaborations with Concerto, make Concerto's technology available to you, make your expertise in your field available to us, so we can make something together that we wouldn't have been able to make individually.
Let's admit it. The the overused but always effective proverb of it takes a village to raise a child, we're a startup. And so the collaborative approach is certainly looks like the way to go.
We literally have a Concerto sticker that says it takes a village of microbes because we also believe that it takes more than one microbe to do anything useful in biology. Yeah, we love our communities of microbes that are working together to keep us healthy.
And the name of the company Concerto certainly works well for the these ensembles of microbes.
It's a great name.
Thank you so much for tuning in. For this episode, we have a request. But first, we have in the works several episodes that are focused on emerging opportunities in space. And these are some things that we are really excited about. So join the mailing list, and get notified when we have the next episode dropping soon. Anyhow, back to our request. We have been delighted so much to see you writing five-star reviews and sharing Tough Tech Today with your friends. If you've been enjoying this show, we do kindly ask you to consider supporting the show by joining our new membership plan. As many of you know, Forrest and I have been supporting the show out of pocket today since the show's conception. We strive to provide you, our Tough Tech Today champions, a way to pay what you can to support the show's production. We have a link included in the show notes so you can take a look. We will continue to share the show for free so if you can't afford to support right now, that's totally okay. But for those of you with some extra funds, consider supporting Tough Tech Today's continued production so that we can continue expanding the quality of content we produce while maintaining that high-quality production across video, audio, and written media. You know from recording equipped, transcription costs, production time, and all the little details that we are proud that goes into making each episode, the effort is substantial. And so, we appreciate so much how many of you have noticed the consistent quality we have delivered. Until next time, stay tough
