119: Bio-Reactor or Bio-Rocket? Scaling Up with Arsenale Bio's Massimo Portincaso

[00:00:02] Karl: All right. Portincasso. We are so happy to have you on the grow everything podcast.

[00:00:08] Massimo: My pleasure. Looking forward to it

[00:00:10] Karl: So you and I've known each other for a while and you recently, probably about a year ago, you started a company called Arsenale BioYards and you guys are focused on bridging this supply chain gap. Between bio manufactured products and non bio manufactured products, and it's something like a 200 billion market, which is staggering, but outside of biopharmaceuticals by manufacturing has had a hard time.

[00:00:36] Karl: It's not seen as something that's economically viable. How is it that you guys are turning that, practicality into lucrative business?

[00:00:44] Massimo: because we're trying to emancipate ourselves from biofarm. I think this is on the one side, a blessing because these are the bands, the industry dramatically. insulin produced this way, GLP 1 produced this way. But the curse of that, comes with huge baggage. It comes with huge baggage, which is called regulatory on the one side.

[00:01:04] Massimo: which can be overcome, but the other point is that one thing is to produce something that costs 5, 000 or 10, 000 per gram. And one thing is to produce something that should cost per kilogram. And the big problem is that we've been trying to use the cost structure and the infrastructure of one to do the other.

[00:01:23] Massimo: you don't need to be rocket scientist to understand that this is probably not going to work from a cost point of view. And this is the point. So the way we're addressing this is we're trying. And we're working to emancipate ourself. Concretely, what does it mean? It means that we are completely shifting 180, the approach that we're taking to it.

[00:01:42] Massimo: you need to go deep because you need to understand that in pharma, all of the value is created in the lab. If you manage to get a molecule in the lab, You have won the lottery, basically, because then producing it becomes almost a nuisance. You need to do it, but the value is created the molecule.

[00:01:58] Massimo: GLP 1 is a perfect example of that. therefore, everything that comes after, I wouldn't say is seen as an afterthought, because people and pharma companies are putting a lot of emphasis in getting the manufacturing right. But as I said, something costs 5, 000 per gram and you manage to bring it down 500, you still haven't solved the problem that we're addressing here.

[00:02:18] Massimo: And why is this so important? This is important because if you're focused on the lab, you can neglect one of the main characteristics of biology, which is context dependency. Meaning that biology really is context dependent and if you have something that works in the lab doesn't tell you anything about how this is going to behave in industrial conditions, which is okay if you're creating the value in the lab.

[00:02:42] Massimo: But it's a big problem if your value is created at the industrial scale, because this is where you produce the quantities that are needed and the price that you generate is what is going to determine your success. what we're doing with Arsenale is basically we are inverting this. We are acknowledging the context dependency of biology and instead of trying to bring the lab condition to industrial scale, which is what is happening today, we're inverting this 180 and we're bringing the industrial condition in the lab and not the other way around.

[00:03:14] Massimo: By doing so, the idea is to let people design directly at scale, which is not Scale down. It's something different because you have a much broader option space and you can really let the scientists, the biologists work in industrial condition with the guarantee that what you're doing is going to work a scale and searching in a much better search space because Very often it is so, almost it's the rule, that the best strain in the lab is not the best strain at the industrial scale. Usually, when you expose the strain to the industrial condition, you have completely different performances by the strains. this is the way we plan to do it. This is on the one side, on the side.

[00:03:51] Massimo: On the other side, the other point is that biology doesn't scale linearly. the bigger you get, the higher the level of complexity, we're talking about really complex adaptive system. So you increase dramatically the complexity of it. what we're saying is we shouldn't go up the same way.

[00:04:08] Massimo: We didn't bring down the cost of photovoltaic and solar by doing bigger and bigger panel. We brought it down by doing the same panel again and again. We're saying actually for biomanufacturing is the same. We shouldn't go bigger and bigger vessels to bring down the cost and leverage economies of scale, which are very, very much driven by the petrochemical world.

[00:04:31] Massimo: You know, if you build a refinery, the bigger the refinery, the better your cost structure, but biology doesn't work this way. And we think that the right way to scale is to scale out and not scale up. by doing so, you can basically utilize standardization, modularization and all of those things that allow you to bring down the cost on the capex and opex side of things dramatically down.

[00:04:53] Massimo: So we improve the performance on the biological side by bringing the industrial condition in the lab, and we massively improve the industrial condition and the cost structure. By scaling out instead of scaling up and the combination of these two, we believe is going to allow us to bring down the cost by one order of magnitude.

[00:05:12] Massimo: that is what is needed by this industry to become economically viable ultimately. So this is in a long nutshell, the only thing that I will add, and it's an important addition. is that the two things are really deeply correlated and intertwined. Why? Because if you don't bring the industrial condition to the lab, then every time that you scale something, you're going to build a bespoke plant, as it is the case today.

[00:05:40] Massimo: So we literally build plants around a specific molecule, a specific process. This means that every plant is bespoke, you have zero standardization, you have huge engineering costs. The time to build the stuff is really, really, really long. But because we're bringing industrial conditions to the lab, instead of us building the plant around the strain and the organism, we design the organism and the strain around the plant.

[00:06:05] Massimo: And this allows us to really and truly standardize because otherwise if you don't do this, everybody's talking about standardization but if you don't do this, becomes very, very different. You can Standardized, but I wouldn't say at the superficial level, but there is a limited amount of standardization you can do because you bespoke by the way you're bringing things to technological scale.

[00:06:26] Erum: Yeah. Wow. That's incredible. Spoken like a true consultant too, which

[00:06:31] Karl: Bye

[00:06:31] Erum: like you really looked at all the economics and the business structuring.

[00:06:37] Massimo: I'm

[00:06:37] Massimo: a recovering management

[00:06:39] Erum: Yeah. Yeah. Yeah. I want to kind of dig into that. And I definitely want to go into, more use cases and, the next steps for Arsenale, but you spent a significant part of your career at BCG before coming into this world of by manufacturing with Arsenale.

[00:06:53] Erum: So what motivated this transition from consulting to founding a hardware software by manufacturing platform?

[00:07:00] Massimo: the founder of BCG, which is, the company where I spent a big chunk of my life, more than 20 years, the founder, Bruce Anderson founded BCG with 48. And, I always had this idea that, before 48, I really wanted to decide what I want to do as a grown up. having been exposed and working on the reports, for instance, like the one I worked with Carl on nature co design, I realized the potential about what is happening.

[00:07:25] Massimo: I decided I wanted that future to make it happen. To be sincere, when I left BCG, I naively thought that, the industry was there, it was just a matter of happening, and I could ride the wave. after leaving, I co founded a company, Officina Bio, that Carl knows well.

[00:07:43] Massimo: with Officina, we realized that actually the industry is in a completely different place that it projects to be. On the industrial side of things, on the pharma side of things, things much more advanced for the reason that we have just discussed, and there is a huge potential there. But on the industrial side, we realize that idea of scaling is really the big, big And to be sincere, this bottleneck is becoming, by the day, bigger because the more generative AI we have, the more protein design we can do, the bigger the bottleneck is going to become on translating these. into production and industrializing all of that, which is the bottleneck that we're trying to overcome.

[00:08:18] Massimo: So I left BCG. I had this idea about nature co design. I thought this is the next wave. I want to contribute to really drive this shift from an exploitative to a generative paradigm, use nature, as an industrial platform. So biomanufacturing the industry of nature is beautiful vision. And then I really encountered the reality after a while and decided that. There is a huge opportunity 200 billion, possibly more 200 billion is only the bio manufacturers. Can we reshape our economy? Can we reshape the economic and industrial fabric of modern civilization, but it's not going anywhere. And then I decided, okay, there is a huge opportunity. There is also the possibility to create a new market and contribute to reshape.

[00:09:00] Massimo: that fabric. that's what drove me to found Arsenale.

[00:09:05] Karl: Yeah, I mean, it's been interesting to know each other and see the way you think. I was very fortunate to meet you and work together on the nature of co design, paper and then worked together. With you and, Davide on Aficina, but, when it came to nature co design, the idea was we're leveraging nature's design principles at an atomic level.

[00:09:24] Karl: And to me, that means that, we're making this transition from this world of scarcity to a world of abundance, which I think people still have a very hard time comprehending. I think we're going to have a Tough transition. And we're seeing it. I mean, you just mentioned this ability to use generative AI is going to drive an increase in a need for biomanufacturing.

[00:09:44] Karl: But where do you think we stand today when it comes to, working with nature, co designing with nature? And how has that vision shaped what you're doing at Arsenale?

[00:09:54] Massimo: It it massively. And I'm really putting in action all the stuff that we wrote about back in that report. All the principles are there. I deeply believe that for this industry to be successful, we need to move away from this idea of drop in and replacement. Because we're never going to win that war.

[00:10:16] Massimo: I mean, we need to get there from a cost point of view, but the real moment in time where the real pivot for the industry is going to be when we start talking about bio better molecule with added value that can do things that. Today, you cannot do. This is going to be really the tipping point for the industry and this whole idea of nature could design is really deeply rooted in the way we're looking at things that are synodic, particularly on the biological side of things.

[00:10:44] Massimo: The industrial side of things have a report coming out soon that we have co authored together with L'Oreal, McKinsey, Evonik, Cradle, and a few other companies. And one of the core tenets in that, report is that we need to basically have bio manufacturing precision fermentation move from being a high technology development to a low tech deployment.

[00:11:07] Massimo: This is really important. This is what I always love to say. This we need to move from being a scientific endeavor to become an industrial endeavor. So, of course, we need to crack and start thinking in terms of industrial terms, but when it comes to the biology, the core idea that we're trying to do and, at the end of the day.

[00:11:24] Massimo: We're not developing any specific for biology. What we're trying to do is to give biologists a much better platform to do what they're good at doing. And specifically to your point about nature co design, one of the first objective of Arsenale with our lab part of the equipment, because we're building an end to end platform, the only way to do this, and this is what I think is very unique of Arsenale, is that we're addressing both the lab side.

[00:11:48] Massimo: And the industrial side and by connecting the two, this is how you can really invert the process and bring the industrial condition into that. But in the lab, one of the important things that we're doing bringing the industrial condition is that we want to allow biologists to work on the strain development.

[00:12:07] Massimo: and the process condition at the same time. And why is this important? This is particularly important because it's purely a numerical piece, and this is something that I learned from David at Officina. If you have, I don't know, 400 possible strain designs, Which is what usually happens and you pick one and then you go into process development and you have 300 possible process, conditions and you pick one.

[00:12:28] Massimo: Normally you think, Oh, out of 700, I've picked the two best. I've done a good job. The problem is that. Your option space is not 700. Your option space is 12, It's 400 times 300. It's not 400 plus 300. And what happens today is that people basically look in this smaller subset, which is usually suboptimal, look in the 700.

[00:12:51] Massimo: don't find the right solution, struggle to bring it to, industrial scale, go back, redevelop, look in another 700. And it's a very, very painful process that we all know. But what if, and this is what we're doing by building our batteries of automated reactor. What if you can, at the same time, look at the strain and the process condition, then you can navigate these 12, 000 option space.

[00:13:13] Massimo: And those are completely random numbers. Those are not the real numbers. But what if we can do that? Then we can navigate these 12, 000. And Nature co design part is about navigating proficiently these option space because within those 12, 000 possible solutions, Nature has found a couple that are way superior to anything else that we can Develop so it's about finding the solution and really co designing with nature.

[00:13:37] Massimo: So this is not about adaptive evolution. This is about navigating the space, which is already there and finding this space and find the solution that nature has already found make it available and then industrially the essence. Ultimately of what nature co design is, and what our scenario is trying to do.

[00:13:55] Massimo: So giving the biologists the possibility to do this, and imagine you can navigate this 12, 000, option space instead of 700, and you have the guarantee that what you find is going to scale industrially. This is a big, big, big change compared to how things happen today.

[00:14:11] Karl: that was very well said. Very poetic. I love the part where you're saying giving nature biology, a better platform to do its thing, rather than shoehorning, like a E coli and really forcing it to produce, which Is a problem, You're not necessarily getting the yields that may be another bug or another process will allow you to do. so you pinpointed some bottlenecks in by manufacturing. and we want to know, what are the challenges facing companies looking to manufacture with biology? very specific things.

[00:14:40] Erum: And I know you mentioned a few of them, but on the flip side, what are the opportunities?

[00:14:45] Massimo: I mean, I will split it into upstream and downstream upstream is what we've been discussing is, the design of the strain what today people call the tech transfer, basically the going from the small scale to the B scale, these industrial scaling, this is really the pain process, which is painful.

[00:15:02] Massimo: it's super costly. Time intensive is really a recipe for pain. so that part we have covered. But I think forgotten half of biomanufacturing is the old ESP side of things that usually comes down and is super intertwined with what happens on the upstream side because you can improve dramatically tighter.

[00:15:23] Massimo: But if, what you get is not clean. And then your recovery rate goes down. Then all the increase that you got in the tire that go down. And this is where, 30 40 percent for certain product is 60 70 80 percent of the cost is generated on the DSP side of things, and it's almost forgotten.

[00:15:40] Massimo: and it's determined Upstream, but it's incurred downstream then building that bridge is another very important point. And this is why there's an alley. We're really trying to embed the DSP side of things in the early phases so that we design develop processes that then are also working from a DSP sign.

[00:16:00] Massimo: it's really something that I learned from our CSO. Bordana shares. 25 years of experience in the space, she, she was, leading R and D for a perfect day. And she keeps hammering and say, DSP is important. We need to think about it early on. We need to think people don't think about it because you consider all of these, a scientific endeavor, DSP is almost a nuisance say, okay, it's an industrial thing that we need to do to extract this molecule.

[00:16:26] Massimo: But I'm generalizing, of course, there are scientists that are. Considering this, but mindset is very much this, but this is what is going to really make you profitable or not. better consider it from the get go.

[00:16:39] Karl: Yeah, I mean, just as a reminder for our listeners who don't know DSP means downstream processing, and it's everything that happens after you grow your bug, and it's producing your product, and you have to purify your product out. I find it fascinating that you're saying that downstream actually is 60 to 80 percent of cost.

[00:16:58] Massimo: certain instances, usually it's more in the 30 to 40, but a significant amount of costs. And also thinking in terms of OPEX, what are the operating costs all of these is really, really something that is particularly important when it comes all of these.

[00:17:13] Erum: Yeah,

[00:17:14] Karl: I wanted, just bring this back. one of the things that really stood out to me in the nature co design report that I always took with me is this idea that CAPEX and OPEX end up shifting when we're talking about biology and CAPEX ends up being strain design whereas OPEX ends up being everything else.

[00:17:33] Karl: Is that still the case or has your thinking on that shifted?

[00:17:37] Massimo: No, no, is not shifted at all. And actually, I'm building a company around that. we said in the report, in biology, you have two topics. You have the topics steel and you have the topics your organism, your chassis. those are the two key determinants of your cost, that you need to master, but you need to master both.

[00:17:54] Massimo: it's really a complex, equation that you need to optimize for. you have yield, titer, rate on the one side, and on the other side, you have CAPEX, OPEX, and time. Time is a very important piece, because let's not forget, even if we look at One of the most successful example, that we have in this space and I'm lucky to have the person who built the factory, to do that in the team, which is the video example of Genomatica of Jano, that is produced It's one of the few instances where we are producing something with synthetic biology that costs three to four euro per kilogram and making money with it.

[00:18:32] Massimo: they took seven years, I think six years to go something in the twenties, thirties to 140, 150 gram per liter. But it took them seven years to get there. You can imagine, how the IRR, the internal rate of return of such an endeavor is. you cannot take seven years to develop a molecule, which is standard.

[00:18:51] Massimo: It's okay if the reward after that are billions because you have pharma, you have the clinical trials, and you can take the time to do that. But in an industrial world, this is not conceivable at all. really not, conceivable.

[00:19:03] Erum: Yeah, makes a lot of sense. And I was going to also make a comment on this. it's really interesting when you laid out that you're not just focusing on the lab scale, trying to bring the industrial conditions and the Engineering of these organisms or the process of the upstream.

[00:19:18] Erum: there's an upstream, there's a downstream, but then there's the here stream, the now stream. when you said that, we should not be building on a linear level. I'm like, yeah, okay. Well, we do live in linear time. I'm getting deep, but to be able to think how do we Bring the two processes together and be able to, make the process more efficient because they're doing it simultaneously in a way.

[00:19:38] Massimo: I love that you're bringing this up maybe for the audience, a couple of words about what our scenario does. So we're building an integrated, software and hardware platform that goes end to end from the lab. to the industrial scale and allows companies to design, their organism to produce the molecule of interest, and then allow them also to produce it at industrial scale using this platform.

[00:20:02] Massimo: If you want, we're building something like the TCMC. of biology. TCMC where people, design the chip. Apple is designing their chip themselves, but then TCMC is the one that is allows them to produce those chips, for the piece. And this is what we're trying to do with Arsenal. Now, how do you connect those two wars, the lab with industrial scale?

[00:20:22] Massimo: Because those two wars are separated. the way we're doing this is through data. data is what allows us to connect those two words. And data is what allows us also to bring the industrial condition in the lab. The problem is, and this is something that I learned the hard way with Oficina, is that The cost and the frequency of data in the lab is relatively high, and the price, it's okay, it's still high, very high, because the moment you go with certain, with the standard, milliliter fermentation can cost you up to 3, 000 euro.

[00:20:54] Massimo: 250 milliliter fermentation. So of course, people are not exploring the option space. It's way too expensive, you don't have the data because you don't have the possibility to recreate industrial condition in the lab through that. this is we're doing. So we're basically taking the data and we're building data generating machine at the lab level at the industrial level.

[00:21:15] Massimo: , because 50, 000 liter run, it's going to cost you more than 100, You don't want to run 000 liter runs to generate data. It's way too expensive, the data point. So we really need to change this. We need to think of all of these biological And they were all of these industrial endeavor as a data play in the very first place, and we need to dramatically increase the data availability, both at the lab scale at the industrial scale to be able to turn these into a data play.

[00:21:47] Massimo: This is the only way to bring down the cost and to seeing the two world. Otherwise, those two words are going to be always separated. We can do this. And everybody's talking about AI. We're using a lot of AI to design the proteins because we have a lot of data. You can do eye throughput screening. You can do all of those things and you can generate those data.

[00:22:06] Massimo: As of today, you cannot do eye throughput fermentation. That's what we're trying to build. We're trying to build the machines to allow people to do eye throughput fermentation. We're building the big bioreactor with sensing capability that are unprecedented. order of magnitudes higher than what is available today and really understand what is happening in these processes and use the power of AI that is now available to overcome those bridges and connect those two worlds and being able to predict.

[00:22:32] Massimo: It's very important to predict because we are not simulating biology. We are still too far away from doing that, but we can predict. we can replicate, not simulate. We can replicate the condition in the lab, see how the organism reacts. And this is part of the nature of the design. So it's nature telling us what is going on.

[00:22:49] Massimo: And then we use AI to recombine those things and predict how this is going to happen at industrial scale. this is basically. Turning all of this industrial biomanufacturing to data play ultimately

[00:23:01] Karl: I love that you're saying that because this is something that Iram and I talk about and we have these conversations with people where, we see the impact that AI is having on, protein design. and when we talk about pharma, we see that the places that are not being talked about where AI can have the biggest impact are things like bioprocessing.

[00:23:20] Karl: Clinical trial design patient identification, and there's people working on that, but it's not top of mind but when it comes to industrial biotech Knowing that you guys are focused on that really makes me happy because I do think that there's a humongous opportunity For optimizing which very clear that that's what arsenal is doing

[00:23:37] Massimo: totally jokingly say that basically what we're not building bioreactor, we're trying to build highly efficient data generating machines and actually my dream is one day to have bio data centers, where we have batteries, hundreds of our microbiome directors, 50 milliliter running 24 7 no consumables, which is a nice way to really milk your client.

[00:23:59] Massimo: No expensive consumables, automated, features so that we can run 24 7 and then generating data continuously 24 7. by doing so, then we're going to really map these options space very well and then develop the algorithms. to understand what is happening and project these, to industrial scale and, turn all of these.

[00:24:19] Massimo: And I think this is a characteristic of Arsenale because we are really inverting the paradigm here as well. you can tell, I love to go first principle and really try to go to the root causes of, things. But also in this case, what was driving us from the get go was a software first approach.

[00:24:35] Massimo: Normally what happens is that people develop the hardware and then overlay these with the software layer. But the moment you do that you are limited by the capability of the hardware that you have developed and you cannot fully leverage the power of the software. So we decided to see this as a data play from the get go and see this as a software play enabled by our word that we develop and design, because this integration of software with hardware is super essential, for this kind of approaches.

[00:25:03] Massimo: we have determined from the software point of view, those are the data that we need. And then we built the micro bioreactor and the macro bioreactors to generate those data, to be able to have the algorithm work across the two scales and develop those things. And this is a to shift if you want is comparable to the one that happened with internal combustion cars and electric vehicles, on the internal combustion cars, you are basically talking about.

[00:25:27] Massimo: Mechanics and thermodynamic on the electric vehicle, you're basically talking about electricity and software. both get you from A to B, but the paradigm underlying them are completely different. Completely different. And this is a little bit of what we're trying to do. So we are in the camp of the software building the underlying infrastructure to be able to connect it.

[00:25:48] Erum: Yeah, this all sounds really great, and I think for myself and for my audience, maybe for Carl, maybe for you too, , to be able to ground this in a very specific example, perhaps a production of something, maybe something you either, researched or maybe, client that you're working with talk about what part of the process was optimized?

[00:26:05] Erum: Was there several processes? Did you decide on something different because you had this methodology of upstream downstream together at once being able to collect the data and make a decision that, Hey, look, if we do this, we're going to reduce the cost by 50, 60%.

[00:26:20] Massimo: So the example we're working on right now is myoglobin, and I cannot talk to the details of it, but there is a lot that can be done around it. also to put things in perspective, the company, basically, we started in January 2024. We already have two 500 liter bioreactors up and running and fermenting.

[00:26:39] Massimo: We had two batteries, of eight. So. 16 microbiome reactor functioning, and we're gonna get to the first battery 48 very soon. so we are now entering the phase where we can really do all of this because the past year was about building the infrastructure. As, as you probably know, building an all functioning 1000 liter facility less than 12 months.

[00:27:03] Massimo: it's rushed, is fast. so now we're gonna go. As fast in working with clients, we already start with two of them, and we have a lot of interest. But right now we're really limited by our capacity. to be sincere, because we cannot serve more than two for the time being. hopefully soon much more.

[00:27:21] Massimo: But I think for me is also really important. You know, unfortunately, this is an industry that has for long overpromised and under delivered. and, I really want to make sure that we can deliver before I can promise the world, because it's relatively easy to do, but that's not what this industry needs, again.

[00:27:40] Erum: Yeah. And just really quick, just to help me envision. So get the two 500 liter, bioreactors, but then your, micro bioreactors do the high throughput. how big is the micro bioreactors?

[00:27:49] Massimo: 50

[00:27:50] Massimo: milliliter.

[00:27:51] Erum: wow. Okay. Perfect. Tiny.

[00:27:53] Massimo: Yeah, 50 milliliter and it's steered. with sparging. So it's a complete replica of course, we're not trying to squeeze a 50, 000 liter because this is going to be the size of our big bioreactor in a 50 milliliter because it's physically possible.

[00:28:07] Massimo: But those are designed in a way that we can recreate those condition and we can replicate the gradients over time of pressure, temperature, pH, DO that you have over time in the big bioreactor. And we're going to use, that's why having many of them allows us to replicate their different condition and then use the AI to reconnect them and predict how this is going to operate in the broader sense.

[00:28:30] Karl: that's great. I want to make one comment. I mean, when you were talking about, this idea of bio data centers and the way that you guys are generating data and taking that first principles, approach, it reinforces for me this idea that, both A. I. And, computer chip design is really going to change based on biology because biology is just a different beast than data.

[00:28:49] Karl: so I love hearing you say that because the algorithms that we use right now for processing data just aren't efficient enough for what is coming with the tidal wave of biological data that we're generating. So being able to make it more efficient and taking that software. approach, I think is really very smart.

[00:29:08] Karl: I'm curious, okay, so you guys are moving up, you've got a thousand liter capacity right now, but let's think 10 years ahead. What does that look like? what are the biggest hurdles you see between now and 2035? You and I have talked about potentially containerizing the Arsenal model and, having these bioyards all over the world.

[00:29:26] Karl: How are you getting ready for that? What does it look like?

[00:29:29] Massimo: was split the challenges in two different camps, but the idea is indeed to have a distributed production model with the buyer yards. The buyer is the unit of six container ultimately because we are indeed containerizing all of the production and then you have batteries of six. And you can multiply and then have, 300, 600, 1, 000, 200, liter of capacity and then distributed close to the production.

[00:29:57] Massimo: The idea is we to build the infrastructure for the incumbents, particularly because I know for sure that all of the incumbents, given the possibility to switch to bio based ingredients, they would embrace it immediately, given that they have. Parity of costs and ideally superior performance, which is what we're trying to deliver.

[00:30:17] Massimo: So I could envision our biowares placed close to the facilities of these incumbents. and if you ask me, the biggest challenges is, of course, continuing to develop, these software dimension and these, what we call designer scale software, expanding it from one organism, because we're going to start with yeast, because What we're trying to do is very complex and we need to put some constraints to make the complexity manageable.

[00:30:41] Massimo: this is why also having fixed sizes is important. And we're going to start with yeast and then we can expand to E. coli, Bacillus, one day also to filamentous fungi. this is going to be the challenge that we have on that front. think on the other side, challenge of industrializing it. I'm pretty confident we hopefully we will be able to announce soon an important partnership that we're working on to help us on the industrialization side of things.

[00:31:07] Massimo: So I'm pretty confident that we can manage that. What keeps me not awake at night right now, but what could become hurdle for that is really finding the right capital stock model something that Edward has been talking about, and I think he's totally right. I think we need to manage to transform these into a true asset class.

[00:31:27] Massimo: I think getting this right so that you can make all of this facility. As, bankable assets, that can be used to do project financing, this is going to be really important in these. I really completely share the vision that Edward has brought, with synonym, and I hope is successful in doing so.

[00:31:46] Massimo: And we are successful in leveraging these from our side. I think we have a big advantage in what we're doing because the way we're approaching this by bringing the industrial condition in the lab. We can truly standardize and then it makes much, much easier, to make those assets bankable, but developing the capital stock to deploy because our goal is to have 2025 facilities is going to be around about 25 million.

[00:32:08] Massimo: liter capacity by then we're talking about two, 5, three, let's say many, many billions, of capex that needs to be deployed. And believe me, I'm not looking forward to raising that money and I don't want to raise that money and it will be a stupid use of money to finance, that part. So that part needs to be really correct.

[00:32:26] Massimo: But if we don't do the part before. Then this becomes irrelevant. It's all about now really bringing down the cost one order of magnitude. it has been used in multiple places, but I love to use it as well. We really need to force the so called Bessemer moment for biology. in 1856, Steel was a known product as it is industrial biotech today, but it was not used because it was way too expensive. As it is with industrial biotech today, and then Bessemer came and he didn't change the product. He changed the process and brought down the cost from 40 per tonne to 6 per tonne just by changing the process.

[00:33:06] Massimo: And all of a sudden steel was the product of the Industrial Revolution. It is what led to the Torrefell, to the railways, to Pittsburgh and all of those things. we need something like this. We need to go from the hundreds in the tens. Per kilogram, to become available and then a new market is gonna happen.

[00:33:24] Massimo: And if you look at the numbers that McKinsey's put together for this report that we're going to just be publishing, it's more than 1 trillion. I don't want to say it's 1 trillion point 2 is 800 billion. It's irrelevant. It's a huge, huge, huge market that is going to completely change and reshape the nature.

[00:33:40] Massimo: of our economic and industrial fabric. deeply believe that. And this is what Arsenal is working to make possible.

[00:33:47] Erum: Amazing. Yeah. hear you. We are on the same page. This is what we want you to succeed. So we all succeed. That's incredible. But you're talking about a company that's very complex, its biology's industrial process machine learning. It sounds like software hardware. What type of people are you surrounded by now?

[00:34:04] Erum: Who are you looking for? a huge endeavor. So we'd love to hear how you're starting off.

[00:34:08] Massimo: Yeah. first of all, I'm looking for crazy people I'm serious when I say that, my personal motto is that normal is dangerous. I really like people with the spike, but I like people that have a so called T shape so that people that can operate horizontally in deep vertical expertise, but can connect the dot horizontally.

[00:34:28] Massimo: This is really important. and also the way we are structuring the company is quite different. because if you default to the classical way with the classical or charts and then the different verticals, you're never going to be able to bridge this. So. At this point in time and for the foreseeable future, as long as I'm around, you will never see an org chart of Arsenale.

[00:34:49] Massimo: We don't have one. There is not an org chart. and basically our org chart are four, circles It's a Venn diagram overlapping in the middle. And then everybody has their Cantabile. And those four dimensions are biology. Engineering data, sensing and actuation. And those are the four domains that we need to bring together.

[00:35:08] Massimo: And then depending on what we're doing, you need to pull together all the different project capabilities to be able to succeed in what you're doing. And this is should be the mindset. It's always what is needed. Those are the four domains that we have. How can we combine them together to achieve what we're trying to do?

[00:35:23] Massimo: And then they're going to be different people driving these with different expertise. But you know that you can tap into these and your realm is not a you are in this vertical and you can work with these people, your space is all of those four domains and you can pick the people to be able to do that.

[00:35:39] Massimo: the kind of people that I'm looking at really people that are willing to challenge the status quo, that are open to look at things in a different way. one way of also bringing down the cost is doing the same things, but coming from a different angle. So what if instead of looking at biopharma as something coming from, the pharma world, I start looking at it.

[00:35:58] Massimo: with the food angle and apply the technologies that are coming from that space where you have a completely different cost structure and you have a completely different, kind of approach. It's not very different from what Elon Musk did when he worked on SpaceX. He was not looking at the aerospace industry as his reference point to bring down the cost.

[00:36:19] Massimo: He was constantly looking at the automotive space to bring down the cost. And if you look, his rockets are partially done out of. Plain steel is the cheapest way of doing this in different consideration into that, but this is the way that we need to look at it radically. Okay, this is not because this is done this way that we need to continue doing this.

[00:36:38] Massimo: And you need a certain kind of people because, going back to the person that built the plant for Novamont that is working now with us that I managed to bring back from retirement. and would be amazed to see which level of energy and openness is approaching all of these and seeing these as a challenge, not coming in saying, that's the way I've been, doing these.

[00:36:57] Massimo: And that's why we need to do it rather than that's how we did it. But how could we do it differently? Leveraging that expertise and doing it in a different way. really, I think the art here is understanding what is good, um, of the old thing that you should keep and what should you change and innovate about, but you need very different kind of people to do that.

[00:37:18] Massimo: It's just that I love to say if people look at normal environment at Arsenale, they're the wrong place. We're all a little bit crazy. and if they're not crazy, they're not going to join us. So that's part of it. like spiky people. I think one of the most, A successful fund hummingbird.

[00:37:33] Massimo: I think one of their requirement to invest in a company is that, the founder needs to have a very spiky profile. think there is some, truth into that.

[00:37:41] Erum: Oh, yeah. I like spiky people too. several people that come to mind, when, when I think of spiky people. and they're very interesting. some amazing rabbit holes that we have gone down for sure.

[00:37:52] Karl: Yeah. Massimo, as we close this out, you mentioned Hummingbird as a fund. I know you left BCG, initially started a fund, helped build, uh, Fuchina and you continue to advise, funds. I mean, what kind of advice do you have for anybody who's thinking about biomanufacturing?

[00:38:11] Massimo: see it as an industrial endeavor, not the scientific. Mostly people doing it are PhDs in biology or postdoc in biology. Don't think this is an extension of your academic career. This is an industrial endeavor. And it's damn hard. It's damn hard. start with the end in mind. to give you an idea of how I literally mean it, is instead of starting in a fancy lab somewhere in a nice city, we have now literally built two labs, an analytical lab and microbiology lab, in the middle of a factory.

[00:38:43] Massimo: There was an empty space where usually The forklift was moving around and so on. And we took over the space and we built two labs in the middle of the factory. This is the kind of attitude that you need to have if you want to be successful. I think, look at Sologen, the way they approached it, the way they started, it was really, really hands on and really pragmatic, industrial, view of things.

[00:39:05] Massimo: And I think this is the way to be successful. Having a great strain that. Does great stuff in the lab is not going to bring you anywhere. And there are so many companies that have been built on that. start with the end in mind don't forget DSP by the way. that's another one that quite important.

[00:39:23] Erum: DSP, baby. Yeah, absolutely. that's really cool. Where's your, manufacturing plant? Where's that located?

[00:39:29] Massimo: Important owner is, 45 minutes North of Venice. it's between, Benito and Friuli. it's a very nice era and I was surprised, but we've been able to attract great talent there.

[00:39:39] Erum: mean, I'll go. That sounds great. It's

[00:39:43] Erum: Italy.

[00:39:44] Erum: Sounds

[00:39:44] Erum: great.

[00:39:44] Massimo: even have. People moving from San Francisco to Port Benone.

[00:39:48] Erum: It's probably more affordable.

[00:39:50] Massimo: definitely

[00:39:51] Karl: Yeah, amazing. Well, Massimo, it's always a pleasure to chat with you. This has been such an enlightening conversation. We'd love to have you back in a couple months or next year to just hear about your progress. we'll make sure that we put contact information in the show notes.

[00:40:07] Karl: thank you again so much for taking the time. We really appreciate it.

[00:40:10] Massimo: Always a pleasure to chat with you.

[00:40:12] Erum: Thanks so much.