# VC10X - Dawn of Programmable Humans - Loretta TIOIELA, Founder, Next Sequence Ventures

An episode of [VC10X - Investing, Venture Capital, Asset Management, Family Office, Wealth Management](https://invisiblenetwork.ai/podcast/1632806986), 15 Jul 2025, 50 min.

Audio: https://anchor.fm/s/a453ddd4/podcast/play/105485154/https%3A%2F%2Fd3ctxlq1ktw2nl.cloudfront.net%2Fstaging%2F2025-6-14%2F403893418-44100-2-c15e54716fa6a.mp3

Loretta Tioiela is the founder of Next Sequence, a venture capital firm at the forefront of one of the most exciting fields in science and technology: the convergence of artificial intelligence and synthetic biology. With a rich background in deep tech, holding strategic leadership positions at global giants like Huawei and Samsung, and working as Chief Product Officer at cloud innovator Scaleway, Loretta possesses a unique and powerful perspective. ⭐ Sponsored by Podcast10x - Podcasting agency for VCs - https://podcast10x.com Next Sequence website - https://www.thenextsequence.vc/ Loretta Tioiela on LinkedIn - https://www.linkedin.com/in/lorettatioiela/ 🎙️ Hosted by Prashant Choubey Follow Prashant on X - https://x.com/ChoubeySahab Follow Prashant on LinkedIn - https://www.linkedin.com/in/choubeysahab In this episode, we talk about: - The Dawn of "TechBio" and Programmable Life - The Convergence of AI and Biotech - Redefining Health, Aging, and Disease - Rewiring the Brain and a New Look at Psychedelics - The Future of Computing and Data - The Importance of Open Collaboration In BioTechnology & lots more Timestamps: (00:00) Introduction (02:40) Defining tech bio and its significance (03:42) Next Sequence Ventures' investment thesis (06:11) Convergence of AI, quantum computing, and biotechnology (09:23) Programmable humans and potential applications (13:16) Current stage of longevity research and potential for extending human lifespan (16:07) Exploration of psychedelics and their potential applications (22:19) OpenSynthBio and the importance of open-source collaboration in biotechnology (28:18) Portfolio companies and investment strategy (36:18) Challenges and perspectives as a woman in tech and venture capital (43:26) Potential breakthroughs in synthetic biology and tech bio for the next few decades (45:49) Rapid-fire round of questions about investing and the accelerator program For sponsorship or guest appearance requests, write to prashantchoubey3@gmail.com Subscribe to VC10X on Youtube, Spotify, Apple Podcasts.

## Transcript

[0:00] The bio economy is going to be impacting everything that human
[0:03] being consume or produce. A view of biotech where life
[0:08] become programmable. And I really think that this
[0:11] notion of programmable life is really Center for what our
[0:15] industry is aiming for. Now when we're talking about
[0:18] tech bio, a lot of us now more and more on the longevity space
[0:23] are thinking about aging as it is.
[0:27] A DNA has the ability actually to store huge amount of
[0:30] information on a form factor, which is actually ridiculously
[0:34] small. I'm talking about being able to
[0:37] store the equivalent of the national archive for a country
[0:40] on something that is as big as appeal.
[0:45] Hey everyone. This is Prashant and I'll be
[0:46] host of the VC10X podcast. And today we have Loretta TOELA
[0:50] with us. Loretta is the founder of Next
[0:52] Sequence of a capital firm at the forefront of one of the most
[0:55] exciting fields in science and technology, the convergence of
[0:59] artificial intelligence and synthetic biology.
[1:02] With a rich background in deep tech, holding strategic
[1:05] positions at global giants like Huawei and Samsung, and working
[1:09] as Chief Product Officer at cloud innovator Scaleway,
[1:12] Loretta possesses a unique and powerful perspective.
[1:15] In this episode, we talk about the dawn of tech, bio and
[1:19] programmable life, the convergence of AI and biotech,
[1:23] redefining health, aging and disease, rewiring the brain and
[1:27] a new look at psychedelics. The future of computing and
[1:31] data. The importance of open
[1:33] collaboration in biotechnology. Lots more.
[1:35] So without wasting any time, let's dive straight in.
[1:38] This episode is. Sponsored by my own podcasting
[1:40] agency called Podcast 10X, where I help venture capitalists,
[1:44] asset managers, allocators and family offices in starting their
[1:48] own podcast and building a strong brand.
[1:50] Podcast 10X is designed in a way to work well with the busy
[1:54] schedule of investors, where we handle every aspect of podcast
[1:58] production so you can focus on investing.
[2:01] If you're looking to build a strong investor brand, starting
[2:04] a podcast should be right up your priority list.
[2:07] It's the only form of marketing where you can showcase your
[2:10] strong network. In other words, access to
[2:13] limited partners and founders and grow that network further.
[2:17] And contrary to what most people hear, it's still very early to
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[2:22] newsletters and thousand X more blogs than there are podcasts in
[2:27] this world. You can learn more about our
[2:29] podcasting services at podcast ten-x.com.
[2:32] I'll make sure to add the link in the description below.
[2:36] Enjoy this episode. Hey Larita, so good to have you
[2:38] on the VC10X podcast. How are you doing?
[2:41] Amazing, amazing. Very nice to be able to talk.
[2:45] Likewise, great to talk to you. And to start things off, can we
[2:48] talk about how do you define the term tech bio and why do you
[2:53] believe it represents the next industrial revolution?
[2:57] Of course. So tech bio is really about the
[3:01] notion of computational biology and computing technology applied
[3:07] to biotechnologies. And so tech bio is being a term
[3:12] that has been coined and around more and more in the biotech
[3:18] industry. I think what it actually
[3:21] pertained to is the ability actually to think about
[3:24] biotechnology from a software industry and this idea of
[3:28] compressing the timeline of research and development to the
[3:32] power of algorithm that allow us actually to have a faster and
[3:38] wider way to address very large search spaces.
[3:43] Right, absolutely. And what is your core investment
[3:46] thesis at your next sequence ventures?
[3:49] And how do you identify startups that are truly disruptive in the
[3:53] synthetic biology and tech bio space?
[3:57] Sure. So our firm next sequence is an
[4:02] emerging investment firm focusing on supporting investing
[4:07] and accelerating pre seed, seed stage company specializing into
[4:13] using any kind of computing technology to Fast forward
[4:17] biotechnology. So when we're talking about any
[4:21] kind of biotechnology that mean that originally people tend to
[4:24] think about AI in bio apply to topics such as Drex and
[4:30] turbotics. But over the last past five
[4:33] years, we've built a massive pipeline of more than 5000
[4:37] startups globally. And we've seen the evolution of
[4:41] the industry from a vertical perspective, but also from a
[4:47] volume and value perspective. And what we can see is although
[4:52] a lot of startups are still now aggregate around drugs and
[4:56] diabetics, we have more aged cases that basically are
[5:00] extremely interesting from an investment perspective.
[5:03] So we see a lot of startups working in topics such as bio
[5:06] manufacturing as well as climate tech, Food and Agriculture.
[5:11] And you already start to see the application of these very high
[5:16] principles to consumer goods. And so we see more and more of
[5:21] the, we've seen more and more of the last past two years
[5:24] application to use cases such as fashion, tech and cosmetic
[5:29] products. So it really spanned across a
[5:33] very wide range of industry. And I would say that the best
[5:36] way to think about it is maybe to use one of the sentences used
[5:41] into the Bio economy report produced by McKinsey, which
[5:45] basically say the bio economy is going to be impacting everything
[5:50] that human being consume or produce.
[5:53] And so if you start thinking about it from that perspective,
[5:55] that mean that you can really see why tech bio and every
[6:01] application of computing technology applied to
[6:03] biotechnology is going to be a fundamental of the next wave of
[6:07] innovation because you basically span across any industry.
[6:11] Yeah, that that's an amazing perspective there to think of in
[6:15] that way. And you often speak about the
[6:17] convergence of AI, quantum computing and biotechnology,
[6:21] right? What are some real world
[6:24] examples where these fields have successfully intersected?
[6:27] Yeah. So in the field of AI and
[6:30] biotech, I think the most successful application that we
[6:34] can see right now are within the topic of drugs and diabetics.
[6:38] And so we have now more and more companies that are actually
[6:43] becoming companies that we can consider as mainstream such as
[6:49] Bioscience or even Tempest AI that just went IPO just a while
[6:55] ago. And these are very strong cases
[6:59] of the power of what we can do. We're talking about the ability
[7:04] to basically Fast forward the search space and therefore be
[7:09] able to find in the amount of compound possible.
[7:14] And we're talking about millions of possible molecule
[7:17] confirmation, the right potential confirmation that
[7:22] could be turned into drug assets that will go into becoming
[7:26] blockbuster drugs. And so, you know, to to a
[7:29] certain extent, even though AI was not necessarily actually
[7:33] involving to the design of the COVID-19 vaccine, it's really
[7:37] this I principle of putting at a task which is massive the power
[7:44] of competing technology to really Fast forward that cycle.
[7:47] So applying it to the idea of not having an approach to life
[7:52] science, which is based on the idea of having a very iterative
[7:56] approach where you actually observe only what's going to
[7:59] happen from a biological perspective and then trying to
[8:02] mimic it. But we are shifting away from
[8:04] that I am principle that govern biotech industry for hundreds of
[8:09] years to a view of biotech where life become programmable.
[8:14] And I really think that this notion of programmable life is
[8:17] really Center for what our industry is aiming for.
[8:21] Now when we're talking about tech Bayou, this idea of
[8:24] thinking about their lives basic block as something that we can
[8:29] basically program the same way as we're programming actually
[8:33] software where in software we're dealing with zeros and 1.
[8:37] And whereas in bio we're using the four letters that is
[8:41] actually core of our information is actually stored on the DNA.
[8:47] And so from that perspective everything become a target to be
[8:51] program. And I think that one of the
[8:54] challenges that we're facing right now in our industry is try
[8:57] to really aim of this idea that everything is a function and
[9:01] that function can basically be genetically program.
[9:05] So doesn't mean necessarily that we are get entirely there.
[9:10] Biology is messy and we still have a lot of things that we
[9:14] don't know and that we need to learn.
[9:16] But I think computing tools are actually a very powerful way to
[9:19] basically get us there faster and in more efficient way.
[9:23] Absolutely. Yeah, That's quite interesting
[9:25] to think about that. OK.
[9:27] Humans can be programmable too, right?
[9:29] And when you say that, do you mean that by new life that's
[9:33] being created, that maybe we can program that we remove diseases
[9:36] from newborn babies? That's maybe one possibility.
[9:39] Or do you also mean in the context of adults, that we can
[9:42] also maybe program adults and change a few things about them
[9:45] as well? I think that gene therapy has
[9:48] been around for quite some years now.
[9:50] We're seeing a lot of application I've seen, we've
[9:55] seen very successful application of gene therapies allowing us to
[9:59] correct blindness from people that were actually naturally
[10:05] born with blindness. And so we start to see basically
[10:08] this application not normally in fetuses and newborns or babies,
[10:14] but in broader cases. So again, I think that what we
[10:18] don't want as an industry is actually to oversell it.
[10:20] We don't want to actually promising that our technology
[10:24] are not yet able to accomplish. But I do like the idea of having
[10:28] that strong vision that someday soon enough and rather sooner
[10:34] than later because we are really accelerating at a very amazing
[10:38] pace right now that we're going to be basically able to correct
[10:41] some of the diseases. But we're talking about diseases
[10:45] that are either I would say recurring diseases such as
[10:50] diabetes disease that are actually people for, for people
[10:56] that are born with these genetic diseases.
[10:59] We're talking also about rare diseases.
[11:01] I think about the keys from a pharma industry where up until
[11:05] right now for rare diseases, it's there is basically almost
[11:09] no business model. And, and that's actually a
[11:12] strong issue because there is thousands, if not millions of
[11:16] rare diseases that are basically not tackle but are from a human
[11:20] perspective impacting real life families and, and a lot of
[11:24] people are actually waiting. So I think that tech bio and and
[11:28] the usage of biotech combined with computing technology is
[11:32] actually a way forward to, to address some of these use cases.
[11:36] Because in biotech the CapEx involve the timeline involve
[11:42] have made it up until right now impossible for us actually to
[11:45] care for rare diseases. But now if we have computer
[11:49] technology that basically compress the cost structure,
[11:52] compress the timeline to research and the effort needed,
[11:55] it brings to us as a species the ability to really now start
[12:03] being able from the business model perspective, tackle down
[12:06] these these very corner use cases.
[12:09] So from everywhere you think about it, whether it is diabetes
[12:14] and recurring diseases, whether you're talking about rare
[12:17] diseases and boring blindness or any other topics, or if you're
[12:24] talking about maybe Black Swan events such as pandemics, such
[12:29] as a wonderful live through with COVID-19.
[12:32] We really, we really now at a stage where we could potentially
[12:36] really address them through the power of, of bringing together
[12:40] these new technologies such as biotech and and AI and also talk
[12:45] thinking about aging. Because to a certain extent, if
[12:49] you really think about it, a lot of us know more and more on the
[12:53] longevity space are thinking about aging as it is.
[12:57] And so if you start to think about it from that perspective,
[13:00] that may also that we're able to think and start addressing topic
[13:04] of aging as something that we can actually cure through
[13:08] actually trying to develop new technologies based in between
[13:12] the combination of biotech and and computing technology to
[13:15] address this. Absolutely.
[13:18] That's quite interesting to learn.
[13:19] And you being an insider in this space, how would you rate at
[13:24] what stage we are in that in those developments where we are
[13:29] trying to think about longevity and maybe increasing the average
[13:32] lifespan of humans to maybe go beyond even 100 years if that's
[13:36] possible at some point of time, right.
[13:38] So at what stage of developments are we and do you think the
[13:41] coming in of AI and these new technology is going to
[13:44] potentially accelerate us on that path?
[13:48] That's a tricky question to be able to assess at what stage we
[13:53] are that's suppose that I'm able actually to foresee where is the
[13:57] end stage. So I think that's a that's a
[14:00] wild guess. But I would say for sure that
[14:04] there has been for quite some time a lot of hype around
[14:07] longevity. And then just like for any Ibe
[14:10] cycle that I've kind of wind down and we're back at it again,
[14:16] I think Brian Johnson and many people that are actually pushing
[14:20] for the idea of not dying. I really like trying to put the
[14:24] stage of the topic of longevity on the stage in Central.
[14:30] I still think that there's a a long way to go, but it's not 100
[14:36] years. We're really thinking about
[14:38] decades if not less of research that will take us to maybe a
[14:44] next jump. From a human perspective.
[14:46] I always say that most of the people working in longevity care
[14:50] not really so much about just extended actually the lifespan,
[14:54] but they will care more about expanding LC lifespan.
[15:01] So they are caring more about making sure that we live else
[15:04] your life much longer rather than just purely extending
[15:09] artificially life in itself. Again, it's very difficult to
[15:14] forecast how long that will take.
[15:16] But again, I I do feel that decades are what we're talking
[15:21] about here and not centuries. Got it.
[15:24] Thanks for sharing that. And right even to these
[15:27] developments in biotechnologies, there's like two sides of the
[15:31] coin. One is of course need based.
[15:33] There are really catastrophic or really bad problems out there
[15:37] that diseases that need to be solved and found a cure for,
[15:40] like maybe cancer is one of them.
[15:42] But on the other side, there is also you can say luxurious kind
[15:47] of needs of biotechnology that we're seeing these days where
[15:50] people are taking enhancement enhancements to maybe look more
[15:54] different than what they already do, right?
[15:57] Or maybe feel differently, feel in an enhanced state of mind,
[16:00] right? So all those different sort of
[16:02] things are also happening. So give us an insight into how
[16:05] things are looking on that side of things.
[16:08] Yeah, I think I have a topic that I like a lot, which is
[16:12] psychedelics. And I think the reason why I
[16:15] really love psychedelics is because somehow for me, there is
[16:18] a very strong emotional connection to the reason why I
[16:21] started on this journey to begin with.
[16:24] I've grown up in a very poor background.
[16:29] And of course, when you grow up in such background, you have to
[16:33] deal with a lot of the social issue and also behavioral issues
[16:37] such as alcohol or violence. And so violence has been
[16:41] something that I've been familiar with, that I've known
[16:44] ways I've been kind of a thread across my entire life.
[16:48] And one of the reason why I originally started on this was
[16:52] because I have my personal topic that basically violence is the
[16:56] most widespread form of pandemic that we're not addressing just
[17:00] because there is no biological agent behind it.
[17:03] And my focus was to basically try to work on 1st on the first
[17:09] side coin of violence, which is a trauma that comes with it.
[17:13] And so I was interested at that time into brain computer
[17:16] interfaces because I wanted actually to develop and work on
[17:20] technology that read and write on the brain.
[17:22] And so it's really because I, I, I was trying to pull on this
[17:27] idea of finding the better, the best technology that would be
[17:32] able to be mass spread to address these that actually
[17:37] started to tap into and I discover synthetic no biology.
[17:41] And so for me, I think that when I think about psychedelics, I
[17:50] see how the effort that I've been now renewed and rekindle
[17:55] into psychedelics research is actually a massive we're using
[18:00] AI as a way to search again, the space for application of
[18:04] psychedelics to be able to address mental health.
[18:07] And beyond this idea of using psychedelics for mental health,
[18:11] there's a lot of things that can unfold if you really think about
[18:14] it. You can use it to address some
[18:17] of the societal issues that we're facing.
[18:20] So I'm based in San Francisco and so it's very hard to ignore
[18:24] that in San Francisco you have some part of the of the city
[18:29] that are actually dealing with massive drugs issues.
[18:33] And my perspective on this has always been, I think that the
[18:37] way that we're addressing drugs addiction and addiction in
[18:40] general is actually kind of backward because we're trying to
[18:44] solve something by not actually fixing the original problem, but
[18:48] just a side effect. And therefore we are never going
[18:51] really to fix it. Now, psychedelic research shows
[18:55] a tremendous potential into fixing some of these.
[19:00] And I think that one of the reason why is because somehow
[19:03] for something, for a reason that we are not yet able to explain,
[19:07] psychethics allow for that rewiring of the brain, the one
[19:12] that I was telling you originally I was after.
[19:14] And so although the technology is not the one that was actually
[19:17] aiming for, it's not a brain computer interface, it's not the
[19:20] chipset, it's not synthetic neuro biology, it's still a way
[19:24] to rewire the brain. And so I think that in a way, if
[19:27] you really think about it, psychedelics offer some of the
[19:31] potential actually to fix drugs and addiction problem.
[19:35] But behind it, it's not just about drugs and addiction,
[19:38] because drugs and addiction in make you are just symptomatic of
[19:43] deeper issues. And that deeper issues is
[19:45] actually trauma is actually about well-being, about the
[19:48] notion of a consciousness and, and sentience.
[19:52] How are you, are you, why are you here?
[19:54] What are you aiming for? What is the meaning of your
[19:56] life? And so something that is
[19:58] actually anchor very deeply into every one of us.
[20:00] And so it pushed the boundaries of us understanding a little bit
[20:05] more about the human psyche and, and what we are aiming for as
[20:08] human beings. So if you really start, you
[20:11] know, to go into the rabbit hole that that topic of research can
[20:15] take you a little bit further than than what you would expect.
[20:18] So. There is many research topic
[20:20] that I found extremely exciting, psychedelics being one of them.
[20:24] Obviously brain computer interface is also another side
[20:29] of the coin. We've seen, at least on my
[20:32] perspective, I've seen an uptake into wearable devices.
[20:37] We started with the Uber ring a couple of years ago and it took
[20:42] a very crowd sided approach to URA to, to kick start to, to be
[20:47] where it is right now. Right now URA is actually a
[20:50] massive successful product. But for a long time a lot of
[20:53] people didn't believe in URA. And I think to a certain extent
[20:56] now we're trying to think about other ways to use wearables.
[21:01] And really I can see over the last past year and two years
[21:04] really the number of startup working on wearables, applying
[21:07] it now to other side of the body and definitely the brain is the
[21:12] one that most of us thought about aiming for right now.
[21:15] Right, that's quite interesting to learn and about a
[21:16] psychedelics, I was actually unfamiliar with what
[21:19] psychedelics was before about a few months back or maybe let's
[21:24] say a year back when I actually did an episode with the VC was
[21:28] focused on investing in psychedelics, right?
[21:30] And that in that episode we just talked about what is it?
[21:33] It was basically me asking him very new questions about it,
[21:36] that what is it? How do you do it?
[21:38] Who should do it, who should not do it, right?
[21:40] And how is it different from maybe drugs that lead to
[21:43] addiction and things of that sort, right.
[21:46] Personally, I'm I haven't tried it.
[21:49] I'm kind of a little bit scared that maybe I get addicted to
[21:52] psychedelics itself. But yeah, I think there is
[21:56] research out there and people can do their own research before
[22:00] seeing if that's something that works for them.
[22:03] Right. Interesting.
[22:05] Great. So to the next question.
[22:06] You Co founded Open Sync Bio, the first open computing
[22:11] foundation for synthetic biology.
[22:14] What role does open source collaboration play in advancing
[22:18] this field? I think Open syn Value was
[22:22] actually the first foray into building my investment thesis.
[22:27] I was a young executive at that time working on cloud computing,
[22:32] and I needed a way to kind of bridge in between where I was in
[22:36] computing and 15 years of experience in computing and
[22:39] biotech. So Open Symbio was a way for me
[22:43] to kind of assess the appetite of the industry, kind of mapped
[22:48] out also the industry being able to know how strong my gut
[22:53] feeling was, how many startup were basically working actively
[22:57] on AI and value out there. What were they doing?
[23:00] What was some of the problem that they were doing?
[23:02] But it was also my foray into trying to apply some of the high
[23:07] level principle that was very dear to me and that I knew in my
[23:11] gut was actually going to be very defining for the industry.
[23:15] Because when I started to think about it and, and, and jump from
[23:19] where I was to go and, and, and be crazy enough to say I'm going
[23:23] to build an investment firm and I'm going to invest into AI and
[23:26] bio companies. The rationale was actually very
[23:29] clear. What I needed is, as I was
[23:32] explaining, was I could feel the frustration of where I was
[23:36] because I couldn't, I didn't feel like I could move my
[23:39] research on on on the brain to the stage that I wanted because
[23:45] the industry was locked down. And the industry was locked down
[23:48] because basically in bio right now, and it has ever been,
[23:53] everything is built around a strong IP strategy.
[23:57] And this IP pattern strategy makes it very secretive, a very
[24:02] close source, very payrolled when it comes to every kind of
[24:08] information and specifically when it comes to data.
[24:10] Now keep in mind that the way that I was approaching this was
[24:13] from a computer scientist perspective.
[24:15] And So what I was after was basically the data, the data
[24:19] set. I needed that specifically
[24:21] because I needed to be able to tap into that dark matter, and
[24:26] you cannot tap into it if it's not exposed and very quickly
[24:30] because I've been in the industry for 15 years.
[24:34] The parallel that I drew was basically that very
[24:38] interestingly, it looked a lot like what I felt and experienced
[24:42] when I started 15 years ago, 15 years ago when I started in
[24:46] software. Every project basically that I
[24:49] was working on, we're always centered around three things,
[24:53] build me authentication layer, build me a billing services and
[24:59] then build me the core product, which is what we're trying to
[25:03] sell our core expertise. But on either side of the
[25:07] equation, authentication services and billing services,
[25:10] it was pretty much the same thing that I was building from
[25:12] one company to another. Now along the way, the software
[25:15] industry actually exchange it went from being entirely private
[25:19] and until equal source to a huge community of people that were
[25:25] kind of, you know, Ackers believers, noobs, all wishing
[25:29] for a better world and being crazy and and naive enough to
[25:33] think that we could do it through open source.
[25:35] And that open source movement changed everything.
[25:38] If you really think about it, Google wouldn't be Google if it
[25:41] was not for open source. Google would have never made it
[25:45] to becoming a strong competitor to iOS.
[25:48] It was not for Android and Android was basically build on
[25:52] the sheer will of a mass receive open community of people that
[25:58] openly contributed without never being compensated financially
[26:03] for it just because we believed in Android from an open source
[26:06] perspective. So for me, this idea of having
[26:11] open collaboration, having open tools that we actually build
[26:16] together as an industry, and also this idea of stopping to
[26:19] integrate vertically where every one of us build again and again
[26:24] the same stack. But whereas we're right now, if
[26:27] you think about it, when everyone wants to have building
[26:30] and authentication, well, we use Ashicock, we use Stripe, we
[26:34] don't build it ourselves. So this high principle of having
[26:38] not vertically integrated product, but where everyone of
[26:41] US actually build on each other by consuming some of the
[26:45] resources that we need out of people that are specialized for
[26:48] it. This notion of open
[26:50] collaboration, open framework that allows everyone to actually
[26:54] build work. One of the strong, some of the
[26:57] strong core principles that I wanted to import, what I could
[27:00] feel was basically we needed that same moment that happened
[27:05] in software, we needed the same happening in biotech.
[27:08] And so Open Symbio was actually built on these premises.
[27:11] And so it has been pushed right now because we are reshaping it
[27:16] into now what it's meant to be and an entire broad industry,
[27:20] broad initiative that encompass not just me, but some of the
[27:26] strongest player in the ecosystem.
[27:29] But it's served its purpose for me at least as a new emerging
[27:32] manager because it's really allow me very quickly to build a
[27:37] weight test my thesis, to build data on what that investment
[27:42] thesis meant. Meaning in term of volume and
[27:44] value, how many company were basically raising every year,
[27:49] year over year, How much were they raising?
[27:52] How was the distribution between precede seed and series A+ and
[27:56] what that meant. And for an emerging manager,
[27:58] these are essential numbers that you need to be able to convey
[28:01] because it it proves that you goes beyond basically a gut
[28:06] feeling of what you can invest in.
[28:08] But you come into your LP's with strong data about what's
[28:11] happening in the ecosystem and where they actually should place
[28:14] their bets. And so, yeah, yeah, it was
[28:17] extremely interesting for sure. Absolutely.
[28:19] Yeah, that's very good work that you're doing there and needed
[28:22] work not just for your companies but in the portfolio, but also
[28:28] for the entire ecosystem in general.
[28:30] You know, if things become more open, more people and can
[28:33] contribute to it and more people as a result will benefit from
[28:37] it. It's going to compound over
[28:38] time. And like you said, it's happened
[28:40] with software and it should happen with synthetic biology or
[28:44] other spaces as well. So it's very part of work and
[28:47] people should take note of that, right?
[28:50] Great. So can you share some of the
[28:51] interesting portfolio companies that you've bagged and they're
[28:55] doing and solving exciting problems?
[28:58] Yeah. So as an emerging manager, I
[29:00] think trying to build a firm in the most difficult time of the
[29:06] VC industry. I think I took a strong position
[29:11] from early on and my position was to say I will back on the
[29:15] founders first because this is my asset, this is my value, This
[29:19] is really matters and I will go after my investor after.
[29:24] I will go for closing after. So contrary to many emerging
[29:28] fund manager, I didn't go straight and try to raise a fund
[29:31] straight away. I was more concerned about
[29:34] building my pipeline and being able actually to show that I
[29:37] have ability to detect some of the most amazing founders out
[29:41] there. That I have the trust and and
[29:44] that they believe that I have a special view of network and
[29:47] access that can be valuable to them outside of money to show
[29:51] that I can get access and get access to these deals.
[29:54] And so this is basically what I've done.
[29:56] So over the last two years now what I've done is build an
[30:00] accelerator program as a form of the Launchpad where we've worked
[30:05] with a set of founders, originally six of them, and now
[30:09] we extend it to more than 40 of them to basically kind of
[30:14] support them in their fundraising.
[30:15] And last year for the first time, we made one first, a
[30:19] strong investment. That strong investment actually
[30:23] is a very interesting one because I think in a way it's a
[30:26] perfect first investment I could have done because I'm coming
[30:29] from software and AI. I've been in AI for more than 10
[30:33] years. I found some how all the best
[30:36] way to illustrate my career, but also my switch to bio because I
[30:41] decided to invest into DNA storage.
[30:44] Now, why is DNA storage extremely interesting from an
[30:48] investment perspective? It's simply because we're
[30:52] talking here about the future of computing and most specifically
[30:55] the future of AI infrastructure. And so for someone let me, we
[31:00] worked on AI infrastructure and they're probably the first
[31:03] generation of AI infrastructure at Skull Way, a massive classes
[31:10] provider in Europe. I think it's, it was a perfect
[31:13] way to kind of make the connection in between where it's
[31:17] coming from and where I'm going. More than five years ago, when I
[31:21] was interviewed, I was talking about the fact that from an
[31:23] infrastructure perspective, the challenge of AI was not really
[31:27] so much on the use case, but more on the industrialization.
[31:31] And I commanded on the fact that energy and power was going to be
[31:35] one of the most difficult constraint to address.
[31:39] And the reason why I was able to actually to make that assessment
[31:42] is because of course, I was deploying NVIDIA GPUs at that
[31:46] time and I knew and I was dealing with these energy
[31:50] issues. But I guess the really anchor
[31:53] for me was the fact that I'm a physicist by training.
[31:56] I studied fundamental physics. And so physics is always the
[32:00] lens through which I'm actually looking at the world.
[32:03] And so energy for physicists is something that is something that
[32:09] we all learn that we cannot generate it out of nowhere.
[32:12] And energy is something that transfer, but you don't create
[32:15] it out of nothing. And so these physics are low,
[32:19] are not something that you can break.
[32:21] And unless you actually abide by them, it's very difficult
[32:24] actually to build. And so DNA storage address some
[32:29] of the next stage issues when everyone will be done with
[32:32] energy and everyone will will be over addressing the energy
[32:36] issue. My prediction is to say that
[32:39] very clearly on and very quickly on people are going to start to
[32:43] realize that we don't have the right form factor to be able
[32:48] actually to store the huge amount of data that AI enable
[32:52] use cases is going to generate for us.
[32:55] Our industry and the digital station of a world has already
[32:59] put a lot of pressure on data centers and service providers to
[33:02] actually store the huge amount of data that is basically
[33:06] generated every day. And AI is just going to multiply
[33:11] that. But if I factor 1000 if not more
[33:15] so addressing the weight of we're dealing with storing
[33:19] information is actually very critical specifically more so if
[33:23] we're thinking about putting data centers in space because
[33:25] space is a very high constrained environment.
[33:28] So we will definitely not be able likely to afford the luxury
[33:31] of adding racks of storage devices along long corridors.
[33:37] And so DNA was actually the perfect obvious technology that
[33:42] I needed to go to and forward because DNA has the ability
[33:47] actually to store huge amount of information on a form factor
[33:51] which is actually ridiculously small.
[33:54] I'm talking about being able to store the equivalent of the
[33:56] National archive for a country on something that is as big as
[34:00] appeal. So it's a perfect technology
[34:03] from a form factor perspective in its ability to store huge
[34:06] amount of information. But it's also very important
[34:10] because DNA is actually very resistant to temperature
[34:13] changes, which is not the case for classic HDT drive storage.
[34:18] It's also very long conservation that mean that we are able right
[34:23] now to basically think about maybe bringing back the mammoth.
[34:28] And the reason why we can do that is because we have the DNA
[34:32] of the mammoth from million years ago.
[34:34] And so that information has not been degraded over millions of
[34:38] years. And so DNA also really like that
[34:41] long term storage and capability that is unmatched forever.
[34:46] And I think that in a way it's a perfect metaphor of what all of
[34:50] us in tech Bayou are standing for.
[34:52] What we're saying is basically to say for a long, long time
[34:56] human has tried to mimic and replicate in it.
[34:59] And because we didn't have a strong understanding on
[35:02] mastering of biology, we couldn't actually replicate on
[35:06] this mechanism of biology and be able to to master it.
[35:11] And so we invaded intermediary technologies such as silicon
[35:15] based approach to technology and everything that we built before
[35:19] that. But now is the time where we
[35:23] have reached that inflection point where we have become so,
[35:27] so strong technologically that from either computing
[35:32] perspective and our ability to search through white spaces and
[35:35] strong search spaces. Or whether in terms of computing
[35:38] capabilities in crushing huge amount of data or even on the
[35:43] knowledge that we have and control that we have on biology
[35:46] to technologies such as bioengineering and gene editing
[35:50] and everything that has been developed over the last past 15
[35:53] years. We are really at that inflection
[35:55] point where we can really become masters of our future and and
[36:00] really program life as as we know it.
[36:04] And so that means that we can now basically kind of mimic some
[36:08] of the best mechanism on earth. And really I think biology is
[36:13] the most sophisticated form of engineering.
[36:15] And so we're just going back to to that actually.
[36:19] Right. That's, that's quite interesting
[36:21] and extremely impressive on how you think about things and
[36:25] problems. It's rare to find AVC or
[36:28] investor who thinks, who can think so far ahead and with
[36:32] first principles, right. And that's because you have this
[36:36] knowledge of physics and biology and all these science in
[36:39] subjects that not a lot of people have because it requires
[36:43] time. And you're also in technology,
[36:45] right? You spend time there.
[36:46] So that gives you that unique position to look at the world
[36:50] through a very different lens and a different level of clarity
[36:54] than others can, because they're limited by sort of knowledge
[36:58] that they have. It's accessible to most.
[37:00] The knowledge you have is a lot of it is also academic, right?
[37:04] So very impressive and very respect worthy on how you think
[37:07] about things, right? And it's fair to find because
[37:10] VCs also, I see that a lot of these times they're investing in
[37:13] a sector and they know what are the common trends in one sector
[37:16] and they're going to go and find companies in that trend or
[37:19] what's happening in one space. But do you think from first
[37:22] fundamentals, what's going to be big in the next 5010 or maybe
[37:26] 100 years, right, in backing that technology now?
[37:30] That's quite impressive. So kudos to you for doing that.
[37:33] So as a woman and a mother in tech and venture capital, what
[37:38] changes do you hope to see in the industry to better support
[37:41] diverse founders and leaders? Yeah, I think representation
[37:45] matters. I think for me, one of the
[37:48] challenge even on a day-to-day basis is really be able to find
[37:52] myself a spot to be able to exist, to go after what I
[37:57] believed in. And it's not an easy task.
[37:59] And I think that's what helps is really being able to reconnect
[38:02] the dots and human connection, that one push it to get that one
[38:07] advice, that one nice word that will keep you going when things
[38:12] are going wrong and you feel like it's almost impossible.
[38:17] I think representation matters. So we need more women,
[38:19] definitely. I think you cannot build and
[38:22] think about building a wall, whether it is from an algorithm
[38:25] perspective or whether it is at every other level when we are
[38:29] living one side of the equation out.
[38:32] And so we need more women in tech and in this time in
[38:35] general, I think it starts very early on.
[38:38] And it's really about how we actually break the mental images
[38:44] to actually show to the little girls that tech is amazing.
[38:49] It's not just for boys that they can do it also when and they
[38:53] need the support. I think it's also a little only
[38:56] life because you as a woman in tech, you need to really push to
[39:02] have your your space. And so it, it requires some
[39:05] adjustment at every level after the studies when you're entering
[39:09] your career to make sure that women are not dropping.
[39:13] Unfortunately, we have the numbers.
[39:15] It's a huge amount of women that along the way along the careers
[39:19] will just drop out, out of tech easy way.
[39:23] It's also a societal exchange because for that to cure, we
[39:27] need to address the fact that men and women from a biological
[39:30] perspective are different. Women are the one carrying the
[39:33] children and therefore it's a strain on our ability to be
[39:37] fully present physically and and and mimic some of what we are
[39:42] asked you. So we need that adjustment that
[39:45] allow for women to will become mothers to actually be able to
[39:50] still push through their careers.
[39:52] I I would say that for example, one thing that I think was
[39:55] absolutely not normal for me was as a single mother, it was first
[40:01] and foremost extremely difficult because you have to deal with
[40:04] the fact that even if you were a mother with a partner, it would
[40:08] be complicated. But if you are alone, it's also
[40:12] complicated. So at some point as an executive
[40:16] to be able to take my meetings from 78 AM to. 8:00 PM and maybe
[40:23] later on and basically 3 babysitters to be able to
[40:28] support me and, and help me into making sure that my son will be
[40:32] taken care of and, and I would be still able to back and commit
[40:37] without having to justify myself and say, oh, I can make it
[40:40] because I have a child at home. And I think that's not normal.
[40:43] I, I don't, I, I don't have fond memories of that period of time
[40:48] because in a way, the money that I was making was actually used
[40:52] to, to afford that. But I think that that shouldn't
[40:55] be the standard because what about all of the others?
[40:58] What about the working motors that are not making executive
[41:01] salaries and and therefore cannot afford that luxury?
[41:04] So I think there's still a long way to go for our society as a
[41:07] whole to really address some of these keys issue.
[41:10] But I'm I tend to not be pessimistic about it.
[41:14] I can see that a lot of people are pushing forwards, a lot of
[41:18] changes happening. Our society are changing.
[41:22] Also, boys are being raised by mothers, they can see example of
[41:27] very successful Mosers and, and, and women.
[41:31] And so the mentality are changing also.
[41:33] So I, I want to see the wall in a very optimistic way.
[41:37] And so I want to see the good side of things.
[41:39] But that doesn't mean that we still need to wait for it.
[41:42] There is active position that we need to take to make these
[41:46] changes happen. And so it's very important that
[41:48] we stick to it and we really fight for them because otherwise
[41:52] 100 years from now, we'll still be at the same, at the same,
[41:56] same condition. The numbers are very, are very
[42:01] straightforward. If we keep maintaining the same
[42:05] pace for change, it will take us 100 of years to actually reach
[42:10] parroting between women and women.
[42:12] And that's not acceptable. So all the way, I'm optimistic.
[42:15] I'm also a scientist and numbers doesn't lie.
[42:18] And so in that sense I I do wish to see more changes and rapidly
[42:22] changing changes for sure. Absolutely.
[42:26] Certainly a long, long way to go for us in trying to bring that,
[42:30] bring that property in the workforce and try to be more
[42:34] accommodative and more empathetic for women.
[42:37] And like you said, women are different.
[42:40] I think the responsibility they take care of are also different.
[42:43] And you cannot just have the same rules across the board.
[42:46] That just won't work. And you know, women like you
[42:51] show massive resilience to just to keep their careers alive,
[42:54] just to keep going and just to survive, right?
[42:57] Sometime it's in a city even, right?
[42:59] And workplaces need to start understanding that and be more
[43:04] accommodative with that. And I think that's very crucial.
[43:07] So yes, totally my last question before we write wrap this up
[43:12] right. So looking ahead, what
[43:14] breakthroughs in synthetic biology or tech bio do you think
[43:18] will have the most profound impact on society in the next
[43:21] decade? Or maybe if a decade is not
[43:23] enough, let's say maybe 30-40 years.
[43:27] I think I'm going to be selfish on this one.
[43:30] I think for me the most important one is actually
[43:35] neuroscience and everything related to the brain and the
[43:39] research on the brain. Not to say that any other topics
[43:43] such as survival, survival through food chain and and
[43:47] building better food sources or innovation about agriculture and
[43:52] food tech is not important. It is extremely important, but
[43:57] at the essence, I care about what it is to be human.
[44:01] Anything that in order for that to occur, it's really kind of
[44:05] bouncing back on addressing a lot of the fundamental topic.
[44:10] And for me, it's the notion of violence.
[44:13] I do believe, I want to believe that we can't do a violence.
[44:18] I want to believe that it's deeply routed into brain
[44:23] computer technologies and, and, and this address not only
[44:27] violence, but it's also addressed some of the anxiety
[44:31] that you can see now around AI and the fact that AI might be,
[44:36] you know, kind of a threat to our human species.
[44:42] I think I see things differently.
[44:45] I think more a convergence and where AI can be a very powerful
[44:50] tool to educate us, bring back some of us to empathy because
[44:56] our society has lost a lot in term of empathy and what it is
[45:00] to be a human. And so maybe this will be at the
[45:03] next gem for us. So I see it more as a an
[45:06] evolution rather than a threat to the species.
[45:09] But definitely for me, as someone that I started this
[45:13] entire journey looking for something that would address
[45:17] trauma and violence, I I'm betting on every single lady to
[45:21] know science and and that span from being able to address
[45:27] trauma to being able to read and write on the brain to make us an
[45:31] ends to communicate better with yourself, but also with
[45:34] technology. It's open the doors to so many
[45:37] use cases that are fundamental. But I guess the the thread for
[45:41] me is really about taking us back to what it is to meet human
[45:46] and and really trying to threaten what it is to be human.
[45:50] Absolutely. Now, now to the rapid fire on
[45:53] wherein I'll ask you 6 quick questions about the investing
[45:56] you're doing all the accelerator that you run and you can give 6
[46:00] quick answers, right? So the first one is what are the
[46:03] sectors and regions you invest in?
[46:06] Yeah. So everything related to AI in
[46:09] bio. So we started with AI applied to
[46:12] future of computing with CNS storage.
[46:15] Obviously that means that we can do this for biomolecular
[46:18] computing. And so we're thinking about
[46:21] application of biomedical computing as a way for
[46:24] addressing the silicon constraint, extending it to
[46:28] drugs and diabetics and biomanufacturing.
[46:32] Again, biomanufacturing is very important.
[46:35] It can be used for food and also farmer skull all the way to
[46:41] cosmetic products. That's great.
[46:44] What's the typical stage at which you invest?
[46:47] Presets its stage and the goal is for us to bring our startups
[46:51] to a Series A and make them actually a successful growing
[46:56] passes Series A with connecting them with a massive network of
[46:59] amazing investor that can take them on the next journey
[47:03] afterward. Great.
[47:05] Do you lead rounds? No, never, not right now the
[47:08] fund is not demodalized actually too late.
[47:10] So we believe that other investor from our network we've
[47:15] when we're partners are the best one.
[47:17] For now we're focusing on trying to be the best supporting them
[47:21] into really currying from that precedes it.
[47:24] They choose to be safe. So we are basically securing for
[47:27] our investors is their investment and making sure that
[47:30] we're able actually to have that the highest number of startup
[47:34] crossing that shasm in between Precid C then Series A.
[47:38] That's great. Typical check size maybe from
[47:41] the investments that you're made, what do you plan to have
[47:44] on here go. Ahead, yeah, so the fun one
[47:46] modelize basically to have a small check size of 100K at the
[47:51] minimum all the way to 500 K and more as as a first time fund and
[47:58] we'll follow on later on in additional round all the way to
[48:03] C was. AC got it.
[48:04] Where you can founders get in touch in case there's a direct
[48:06] way. Yeah.
[48:08] The best way is issue a founder and you're interested into our
[48:12] support. Reach out to me directly by
[48:17] going to our website sothenextsequence.com.
[48:21] This is on the website for our launchpad and you will have
[48:25] information of a program. We work with you as founders and
[48:28] we can really support you. We are long term players, so we
[48:33] take companies from the very early days and proceed all the
[48:36] way to bringing them to distribution.
[48:38] So typically with our last investment, this is a founder
[48:43] that we've known and worked with for more than two years in and
[48:45] out before making that commitment.
[48:47] So. Right, that's awesome.
[48:50] Last one, where can our listeners follow you?
[48:54] You can invite me on linking. This is where I'm the most
[48:56] active. I'm very bad at Twitter.
[48:58] Although I'm amazingly good at stalking people and getting a
[49:02] lot of my information on Twitter, I'm actually more
[49:05] active on linking. So feel free to reach out to me
[49:08] on linking and follow me. Awesome.
[49:10] I'll make sure to put those links in the show notes below to
[49:13] our listeners. And good day easily.
[49:14] Thanks so much for making time for this, Loretta.
[49:16] It's been a very insightful conversation.
[49:18] I learned a lot of things about bad technology and where we are
[49:21] headed in that space. And also massive respect to how
[49:25] you think about things and your resilience as well for coming to
[49:29] where you have come. And I know there's a long way to
[49:32] go still, so I wish you all the best.
[49:34] Thank you Prashan, really appreciate it and amazing
[49:37] podcast. I really am looking forward to
[49:39] release and thank you again. Hi, Grace.
[49:43] Thank you.

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