good morning welcome to Flagship Studios at JPM I'm avak kahen I'm a general partner at Flagship and a pioneering business unit leader uh developing new bioplatform companies at Flagship uh today we have a really interesting conversation lined up for all of you today um we have some really important uh partners of of mine colleagues who work with us on origination uh we often get asked question asked questions about how we do what we do uh who does it uh what our bioplatforms and we're going to try to dispel all of these questions and answer all of them for you today um and we have the protagonists here uh who can who can tell you straight uh what what they've been doing and what they're up to and what the future holds for some of our new uh Innovations um sometimes people ask me outside the industry what is a bioplatform or what is a platform uh I often point to what they're holding in their hand uh or one of these devices a piece of hardware and a software ecosystem that is essentially generic something that everyone can use and that others can develop multiple applications on really a universal device a universal utility and in our world closer to home uh the quintessential platform is madna a universal capability to make nucleic acids a Foundry for creating l&p encapsulated RNA that can be programmed for virtually any disease Crea creating vaccines cancer vaccines rare disease medicines and so on so that's what we essentially do we create multi-product bioplatforms and we want to give you a sneak peek into how we do it uh why we do it who does it uh and uh like I said the colleagues here we we'll give you direct and specific examples of some of the things that they're working on and what's coming so uh why don't we start with you Molly why don't you introduce yourself in one of the biop platforms you're working on awesome hi Molly Gibson I'm an origination partner at Flagship and a leader of one of our uh pioneering business units um I spent a lot of time thinking about how AI is going to transform the future of Science and a lot of my companies have that theme within them so an example of one is generate biom medicines uh we founded this company in 2018 really with the premise that AI was going to transform the field of protein Therapeutics and that AI itself could actually generate spe specific and precise proteins uh for any therapeutic function and any therapeutic modality um and so that company has been now building for the past six or seven years on that and actually translating these findings into the clinic um with some really profound results um so this an example of a type of company where we're infusing AI into the science to build a novel biop platform K great hi I'm Kyle Chang uh regation partner here I've been with Flagship for about four years now um I work closely uh in Osio Martinez's group where we create uh biop platforms to serve both human health as well as uh agriculture Health as well as sustainability we call this planetary Health um and so before that I've been working in the startup world for about 15 years creating uh human health companies outside of the flagship ecosystem uh so I have a bit of a perspective on what it's like creating platforms you know here in Flagship and how that's unique maybe one of the companies I'd like to highlight that that we've been working on is called Monti Therapeutics relevant to um nuar's note earlier this week about poly intelligence um monai is really a great example of a company that uh wants to learn from nature um we're focused on a a subset of natural product chemistry we call anthr molecules that have co-evolved with humans for Millennia and this has been a rich source of drugs but to to identify the ones that are useful for therapeutic use that's really relied on Serendipity and Decades of academic work so by using m tools and and accelerating discovery of of leads from this chemical space we're able to to pull from nature and and refine that and insert that into our drug develop development process to identify new small molecule candidates to to treat um inflammatory diseases great Jake awesome to be here um a privilege to speak about building platforms which is the core of what we do at Flagship um I've been doing that now for close to a decade uh on our team came to Flagship from MIT and have uh had the Good Fortune of helping breathe life into three of our platform companies uh first company called SAA biotechnology that's developing cell and Gene therapies uh to cure diseases focused on regenerative medicine immuno oncology Immunology after that started a company called tessora Therapeutics uh where we've developed technology that allows us to write new genes into the Genome of cells by delivering just RNA into those cells and more recently I've spent a lot of time uh leading a company called quo Therapeutics and I'm super excited about the platform that we're building at quo um it is really a great uh example of what it means to be a platform what we are doing is sequencing the DNA of individual cells in our bodies based upon the recognition that each of us actually has a distinct sequence of DNA a distinct genome in all 30 trillion of the cells in our body and what we've shown at quotient is by sequencing this DNA we can discover new drug Target tets which are the most important source of data for decisions that we make in the drug Discovery pipelines of every company in our industry and the reason that this is a core platform is we have a consistent team a consistent set of methods and Technologies and we can broadly go across diseases change the input keep consistent the machine and find a new output for each of those distinct applications and happy to describe that in more detail later yeah so I I really want to get into that with each of you to describe why you believe your platforms are really Universal or at least applicable to multiple things and how you navigate that so let's talk a little bit about that Kyle why don't you go deeper into it you know when we start these companies um in in what we call our protoco phase a lot is really trying to push the envelope of seeing what's possible with the the tools and this platform that we're building um and that's what really gives us this confidence about uh universality of of of of the platform but really it comes from from a therapeutic point of view in the candidates you trying to start to fill out a pipeline starts to bring tangibility and and reality to the platform uh and so at Monti you know we've gone through these evolutions and we've decided that we want to focus on II because this space is really highly networked and likewise when you're building a team it's hard to build expertise across all therapeutic areas so to be able to focus and concentrate your internal resources into placees really all allows you to accelerate the platform and the proof of that platform by demonstrating progress against multiple candidates and I think you can do it once you can do it twice that could still be luck but when you start populating a pipeline with three or four or five interesting candidates uh that starts to show uh the the the strength of your platform uh as well as the repeatability just to build on that thought you hear people talk about trying to have a pipeline in a pill and these are targets or these are drugs like k truda a drug that can work across many indications but you keep the drug consistent it is I'd argue impossible to predict which of these drugs are become pipelines in a pill until you bring them into people that's expensive and it takes a long time and this is what farma is incredible at what we build are pipelines in a platform just like Kyle's describing every company we start has the potential to create a pipeline and because of that I would argue that they're in fact the lowest risk Investments you can make because of the opportunity to create a broad set of therapeutic opportunities by investing in that core technology like what monai has built what generates built tesser has built quotients building that can be deployed over and over again across different indications yeah Molly why don't we kind of delve into platform product Market fit and how we explore that with one of your platforms for example yeah for sure um and and before I get into that I wanted to expand a little bit of what is is is saying and around thinking about like the economies of scale of our platforms one of the things that um we think a lot about is is how do you get that economy a scale how do you get that generalizability from our platforms one thing that I've been also thinking a lot about recently is how is that going to change in the age of AI um so just as we think about the economies of scale of getting a a a whole pipeline from a single platform I think the future is going to also look about look different with AI how are you going to get the intelligence of scale so not only how do you think about a platform creating multiple products just from its generalized ability but how does a platform get smarter over time when you inject in Ai and and that's a whole new realm of platforms that we have the opportunity to build in this age of AI um but equally challenging is the ability to then use that platform to create value um you know what we do here is not just to create platforms that do interesting science but that science has to be connected to something that people care about something that's going to make impact I think all of us here the reason that we're at Flagship is because we want to create value for the world we want to create impact in the world um and the only way that you can do that is to really create this you know platform Market fit um product Market fit we think about this a lot for our platforms um around at generate for example a lot of what we thought about is what are the types of things that we weren't able to do before with existing technology that now using AI to generate novel proteins for specific functions that we can do so uh types of proteins where uh people have wanted to optimize directly for function but we had no mechanism to do that before um and so trying to identify those you know perfect fits or uh there are mechanisms where if you could make this protein you know binded a 100 times tighter that would open up entirely new therapeutic windows but you just can't do that with existing Technologies honestly you can't even measure that tight um in high through put to be able to do any kind of screening so if you can use Ai and understand the specifics of the mechanism and the specifics of The Binding you then can actually reach those um you know reach those new heights of Therapeutics that weren't possible before so it's all about connecting the technology specifically what do the technology uniquely enable you to do and then how do you match that to an an unmet need in the world um that's going to create value for patients and and uh investors but then also just create impact in the world Absol absolutely like this is I think just as important for our companies as what is the platform it's what do you do with the platform how do you go from having a platform actually creating a pipeline um at uh at Tess we thought about um how we could build a technology that allows us to write genes into the genome and then where are the places where we can do something no one's ever been able to do before and what we realized is there are applications in in uh genetic diseases in imuno oncology where the ability to deliver RNA into a cell and edit the gene that causes Alpha an tiripon deficiency the mutation that causes CLE cell disease being able to write a chimeric antigen receptor into cells in the body would create a set of opportunities which were previously impossible for people to even imagine and now only once we've imagined this platform brought it to life and are deploying it can you conceive of how you go from platform to a broad pipeline of differentiation yeah it's these insights that are so important to actually creating the value what's the win state of the platform um that we often talk about you know if you're just doing something slightly better slightly faster yeah you start to lose the power of why are we building this company in the first place this platform in the first place um we really want to make sure that we're placing these Platforms in places that previous technology really just couldn't touch so we talked a little bit about you have a platform where do you apply it but let's talk about the hard part we do in the beginning yeah right the investing in the platform to get it to a certain point before we can apply it talk to me a little bit about that challenge maybe Kyle you want to start I know you all have gone through this I've gone through it and how do we decide how much to invest in one versus the other and yeah it's a dynamic and uh iterative process and you know when we launch our companies we we we work together to Define goals of what can be achieved in in the constraints of our protocal period which is you know uh a modest investment you know over a year or two right and so um we may have visions of great platforms that can that can change the world but we have to take that first step uh and we we need to be able to demonstrate that uh with some limited resources so that's really where we start um but as as we all talked about you know then you need to start to focus your investment of of your people your knowledge and start demonstrating achievements of your platform against known benchmarks and this is where I think you have to manage risk um if you're coming in with new modalities maybe you don't want to go after brand new targets if you have a new Gene editor maybe you want to go after some genetic disease disas have been very well described and you know what are the changes I need to make to make an impact on a patient what are the levels of this protein I need to achieve to make a clinically positive outcome uh and so managing that risk as the platform evolves and you understand where it it excels and where you still need to to to grow uh the effort uh allows you to get some wins along the way and that generates confidence for us to invest more in the project for for potential Partners as well as outside investors coming in do either of you have EX examples of the platform was able to do X in the beginning and we did it but then we worked on it to make it do y and we had a progression in terms of the capabilities of the platform over time I have an example of that from generate um you know one of the things that our our vision for Generate was always that you could create a denovo binder to any point on any protein specifically um and when we started out thinking about this this was you know pre-alpha fold this was was you know before really anybody had been thinking about app using AI to apply um to generate novel proteins and so that was a vision that we had we actually didn't know and the field didn't know if that was even possible um and so we started out looking at well where are the valuable things that you could use could do if you understood the the connection between the protein sequence and the function um that is on the way to creating the noo proteins and so we really focused on multi-parameter optimization so AI allows you to optimize not just for The Binding but for all of the developability properties that that you need to develop a drug along with it and so by creating that technology we're able to move the platform along and along the way be developing all of our denovo technology and now we're able to repeatedly and routinely create denovo proteins with the platform and so that opens up in entirely new value pools that weren't available to us from the beginning but are only available to us from those investments from the early the early pipeline yeah I think of a similar example from quoti Therapeutics where we're sequencing the DNA of individual cells in the body when we started the company our academic co-founders had shown that it was possible to sequence the DNA of individual cells uh and to find Targets from that information but they'd only done it in one disease a disease called mash um and that that affects one organ system the liver we saw that if what was true in the liver was true across the whole body then we would have the opportunity to to have a better approach to find Targets for every disease every aspect of human health so we started with this one disease but now we've shown that we can apply this to other cardom metabolic diseases to infectious diseases to autoimmune diseases to immune oncology to genetic diseases and we have real exciting early data that we're just generating now in neur degeneration respiratory the list goes on and on and on so we start from this single insight and what we are so uniquely good at at flagship in my opinion is daring to dream daring to dream about how we could go from that initial insight to a huge broad opportunity enabled by these platform technologies that we create maybe one example from the monai point of view of what we couldn't do early on that we can do now um you know when you train ml models you have to give an example of what good looks like so it can find more of that and when we're uh starting our platform we had a more limited chemical space that we were working on um we've since grown it to over 200 million uh molecules in our virtual library um that limited chemical space allowed us to find things uh new chemistry but really we're looking at Targets like transcription factors gpcrs inhibiting enzymes things that we know small molecules can already do right but since we've expanded this chemical space we've been able to identify um molecules that disrupt protein protein interactions at the level of cyto and cyto receptors and we could only do that when we got those little winds along the way had the commitment to expand that chemical space grow our library and find those hits that we're able to train against and so that's you know I think that's a nice example of making sure you can collect some winds along the way before you you you swing for the fences with the the ultimate goal that you want yeah so you guys are describing very nonlinear paths you're describing a lot of thinking trying um tell me a little bit about the culture you have to build the teams you have to build to do this we're starting from scratch so it's often one or two of us in a room and then we have to build team teams and companies so describe some of those Journeys yeah I'd love to start because culture is just so important right to all of these entities and I think that's where Flagship really provides that culture of innovation down to all of our protoc Co you know when when people look for jobs and they see these stealth mode companies with only a handful of employees you know they're taking a risk and and and and leaping and and and joining a company and and usually it's incredibly uh exciting science and Cutting Edge science that draws them there that's exactly what we have here we have that culture of innovation but I think they also have the understanding that Flagship is willing to take these bigger leaps and wanting to go for um these really Innovative platforms and people are excited to to to come to these companies and learn Hands-On how we do things and um I think what's really important at these early stages of of companies is having really clear communication so I mentioned how Dynamic it is as you get data react to data where the platform is working better or not you want to collect those wins and the plans that you have on day one might not be exactly the ones you execute for protocol right you're trying to show where these platforms work and the teams need to be able to move dynamically with you and I think small teams are actually best suited for that right people with that right mindset of understanding what we're trying to achieve and understanding what the data coming in tells us about our platform and to be able to react quickly beautiful couldn't agree more you know we we talk a lot about Explorations as part of our process said Flagship I like to zoom out and think about and think that every time we set up to do something we're going on an expedition mhm and the exploration is part of figuring out where you want to go what we try to identify in our companies are these enduring Peaks these opportunities where if we can reach the summit everyone us and the rest of the world will undoubtedly look at that as a first achievement of planting the flag at the top of something an a human achievement over over the life Arc of all of us and to do that effectively you need to have grit and resilience and Agility and the willingness to push through challenges um one of the teams I'm the most proud about that we've built that Flagship is uh in a company that's still in stealth mode where we've been trying to Summit one of these enduring Peaks over the last couple years um and it has not been the easiest Journey not at all compared to other companies where we started with a platform that was already somewhat operational we've had to push through challenges and I'm more proud of what that team has accomplished because of that than some of the other efforts that we've already announced publicly which are objectively just absolutely crushing it I think to add to that um I totally agree resiliency in these early teams is essential um the other component is as we're talking about we're constantly moving you know between different states of stability um constantly dealing with different types of tensions within the organization of you mentioned how much do we invest in the platform how quickly do we go towards pipeline how do you hold both of those things in tension um the teams that I've seen really excel at building these platforms that are you know really going out into unknown territory can deal with those uncertainties deal with those tensions deal with those kind of things that seem to be at odds with each other but are actually synergistic and actually necessary to hold both at the same time um to hold both the the probability that you can reach that Summit and the probability that that summit's actually over there and you actually want to Summit this other this other Peak um that might end up being actually where where the the most value is um and teams that can navigate that and just like quickly say oh yeah we're going to go this way react to data you know go the opposite way and then you know be able to hold all of that together in one picture at the same time um is really essential to be to be able to be successful in these uh really unknown unknown territories yeah one thing you guys left unsaid though is that yes small teams are agile but these teams are not always small yeah and they're actually not always um of the same ilk they're not coming from the same background so we have to touch on that I know it's thrown around a lot interdisciplinary research interdisciplinary work but I think in our case we're re architecting some of these we're architecting these platforms from scratch so we have to rearchitecturing talk about that we we know AI is impinging upon everything we do and so on and so forth yeah maybe there's two points there one the team may be small but the ecosystem is large right and the support provided by the ecosystem is unlike any other VC or Venture creation organization out there and to be able to have you know the the the support on the machine learning side from the expertise we're building with pioneering intelligence but also the experience that the I don't know we're probably over hundreds of years of R&D development experience you know in our in ecosystem to to be able to support um each one of these early stage companies it's it's a really unique unfair Advantage but to to your point about harmonizing communication across functions that come from very different places namely computation and biology it's something that you have to do intentionally and um at Monti we spent a lot of time you know going through a lot of the jargon that these teams use and get them aligned so we know exactly what we're working towards and what we're trying to deliver um because just that little misunderstanding about what someone thought they wanted can waste a tremendous amount of time and we don't have time right we we're trying to innovate here and we need to move with speed we need to move with efficiency and so uh it may seem mundane but just getting people to use the same words in the same language so there's an understanding across all levels right not just at you know C levels and VP levels but with engineers and and research assistants that that are that are in the weeds with what they're working on to know exactly what they're pushing towards and and what they're maybe rowing towards you know so everyone's on that same page yeah I think this is a core part of the culture of all of our companies um we spent a lot of time also at generate and and some of the new companies we're working on on on figuring out how do you create a culture where everybody's voice is at the table um and that's from you know top to bottom of the organization and and across across the organization every function um I don't think this is the case as much today but when we started generate there was a strong sense that computation was a service to biologists and we had to fight that every single day to make computation and biology equal we had to we had to think about how how do we not make you know our computation team you know elevated above our biologists this really is that these teams are are you know working as equals towards the same Mission um this happens today in different domains so you know I spent a lot of time in in the AI world now um and we think about this a lot with Scientists and Engineers so Engineers that are building the infrastructure to train models at scale are absolutely essential to the success of these companies oftentimes you know they've been seen in the same light as a support system towards the AI scientists but really how do we El create that you know tension so that we can make them as equals and make everybody that is is working in these companies um essential to the mission that we're on and creating that kind of culture where everybody knows their place understands how their work is contributing to where we're going and that that their work is essential to to where we're headed is an incredibly important part of the culture that we build in these companies yeah I just add to that um science is a team sport building companies is like a team sport on steroids right um because it's not just the science it's all of the other people who support the scientists that are doing the work and I think part of the secret sauce that we have at FL which doesn't get a lot of attention is we have Decades of expertise not just in science but in building companies so that is of course the entrepreneurship but to do entrepreneurship effectively we need experience in legal um Capital formation financial planning accounting procurement Communications this beautiful event yeah all of these incredible people who support these companies and enable them to be successful and I think the success from is actually comes down to the people the culture and then to the exponential of 25 years now of experience all of that compounds over time to maximize the probability of success for everything that we build yeah great I'm going to surprise you guys with a question oh boy personal one many of you have developed your careers at Flagship right we've um you've left school looked for some kind of endeavor that is scientific yet entrepreneurial and you've essentially done it at Flagship you've practiced it at Flagship what have you learned about yourselves during the time you've been there well I don't really count I back doored into this you know I I don't think I don't think the fellowship would accept me you know coming out of college so I I've definitely had to learn on the Fly um you know I coming in here with the experience I have on creating companies and building programs and and getting to be in the room with Associates that came through the fellow fellows program and have gone through this this training we provide over the summer it's the analogy I use it's it's almost like improv I can't say no right at this stage it's about yes and and trying to shape our Explorations into a place where we can develop a protocol and a protocol plan that is tangible and does make sense but really keeps that sort of that Peak you know in view um and so this is some of that tension that you talk about and this is you know Newar has these phrases that are you know oxymoronic right and so you really need to to embody this on a day-to-day basis in the activities that that uh that you're partaking in so that that's my personal learning I think the the thing that I have learned the most about myself and and really about building companies um is well one I love building like the process of building not just building uh a science but building teams is so essential um and I have really learned to appreciate and we've talked a lot about it here how important important the people are to what we do um you know I think often people will talk about you know an idea is only the beginning and then it's how you execute um to me that's that's so true but it's also about how do you bring the right people around the table to do something that feels absolutely impossible um and Inspire them get them motivated and do that on a daily basis when things get really hard because things do get really hard um um people feel down people you know have to come back from setbacks and it's about how you build those teams to be able to deal with those moments because those moments will come um that really kind of results in in the best outcomes um and making the most amount of impact in the world and um I've learned that that's something that I really love to do I love to bring the right people around the table um to solve really impossible challenges um and the problem Sol solving in the Str that goes into that is just a really fun puzzle on a daily basis um something I didn't I didn't appreciate as much early in my career that I've learned to to really really value yeah I agree with both of you guys I'd say when I started Flagship I I thought that the most important skill was certainty and confidence about where we should be going how we're doing it and I've come to learn that actually the most important skill is agility it's being able to learn and change directions do experiments that inform and Define our mental model of what we should be doing and how we're going to do it and so I value more than ever working with people who are highly agile and have a learning mindset to everything that they're doing I've heard recently um people talk about like know it all cultures and learn it all cultures and how valuable the learn all culture is this is something that has absolutely resonated with me and something that I think is just like ingrained in the flagship ecosystem the more that we really embrace the fact that you know every we're learning and it's not that we know you know we don't have all the answers but we're willing to go out there and find the answers and put ourselves on the line to find those answers um it's essential and so important it's it's inspiring to be a part of and how have you guys shared your lessons uh amongst yourselves we're all very much focused on our own Endeavors and they become all-encompassing yeah it's you know we're also as an organization evolving a lot and so what we do is is evolving the resources we have are evolving so you know we meet what was it bi-weekly you know together with the origin Nation Partners um just to keep a breast of what's going on in our teams but also what's coming you know for for Flagship and how we can adjust how we originate uh to to meet sort of the the new version of Flagship as we hit our 25th anniversary yeah I think another thing that's important in that is that we don't only share those lessons with each other but the new origination uh teams that are being built um we Jake and I have shared for example all of our lessons learned from building generate building tessora um with the junior members of our teams and I've repeatedly heard from them those are the most impactful experience that they experiences they've had because those are the lessons they need to be learning um they want to hear like real life you know battle stories on the field War Stories um and uh so it's it's about sharing those lessons across the teams but also you know we're training the next generation of regeneration leaders and we have to make sure that they're learning not just from their present day but from you know all of the history of lessons we've all learned and the successes and the successes just the fail yeah I mean I joined Flagship as an intern 10 years ago and I'm a partner now and it's crazy to me when people come and they're like you've made it to the top and like it doesn't I went to your PhD defense fun fact I defended my PhD in the tux um do you remember that no I don't I would have teed you about it I remember um and um where was I going with this all right so but what what I've come to appreciate really is um it's I benefit Molly's benefited from it Kyle joined a little bit later from avoc and Jeff and Newar building a organization that trains the next generation of leaders of people who aspire to be great biotech entrepreneurs and I think some of our most important responsibilities is paying that forward which effectively enables us to then scale our influence as an organization and do more and take bigger leaps as Flagship yeah well all these talks of years is making me feel old so I think it's time to wrap up the conversation so thank you all for your cander uh and and actually improvising with me here uh I appreciate it um and thank you all for joining us uh and getting a sneak peek into what Flagship does how we do it and who's doing it thank you thank you
2025-01-21 10:53