174: How Do We Fix the Bias in Biomedical AI Podcast with Victor CEO and Founder of Omica.Ai

Why are billions of people still invisible in genomic research—and what does that mean for the future of precision medicine?

In this episode, I sit down with Victor Angel Mosti, founder and CEO of Omica.Ai, for one of the most insightful conversations I’ve recorded about data equity and building ethical, community-centered AI.

Victor shares not only his personal cancer story but also the staggering truth: Hispanic and Latino populations make up less than 1% of genomic datasets. This underrepresentation isn’t just a data gap—it’s a clinical risk.

We dive into disparities between healthcare systems, the promise of digital pathology as a low-cost entry point, the dangers of “parachute science,” and how Victor is building a living, ethical, transparent biobank through Omica. AI—built for true precision medicine rooted in community trust.

Highlights with Timestamps

• [00:00–01:40] Personal cancer experiences and diagnostic uncertainty
• [01:40–06:50] Victor’s medical journey across Mexico and the U.S.
• [06:50–11:42] The digitization gap: empathy vs. tech
• [11:42–16:43] The “coffee diversity” metaphor for genomic diversity
• [16:43–19:34] Funding disparities & the biotech cold-start problem
• [19:34–25:44] Digital pathology as a gateway to precision medicine
• [25:44–31:44] Avoiding “parachute science” and building community-first research
• [31:44–36:05] The Nagoya Protocol and benefit-sharing
• [36:05–41:47] Omica.Ai’s work, goals, and clinical-embedded approach
• [41:47–49:36] Creating future-proof, embedded biobanks
• [49:36–53:35] Blockchain for transparency and patient trust
• [53:35–54:39] Victor’s call to action: collaborate, include, and stay human
  
  

Resources from This Episode

• Omica.Ai – Community-driven precision medicine platform
• Nagoya Protocol – Framework for equitable biological use
  
  

Key Insights

• Cancer is personal—even for experts
• <1% representation of Latino genomes threatens clinical accuracy
• Digital pathology + AI can leapfrog infrastructure gaps
• Ethical biobanking requires trust, transparency, and local benefit
• Avoiding “parachute science” is essential
• Genetic diversity drives discovery—but only if we capture it
• Blockchain + dynamic consent = future of patient-centered data
  
  

Transcript

Aleks: I have the same problem. I would say my cancer was I had thyroid cancer and that was like 20 years ago, something like that. So I was already in vet school. I'm a veterinary pathologist and so I consider myself being in the know as well you know I knew what kind of cancer that was. I could read publications and yet still like somewhere deep there's always this oh what if it's like this whatever percentage is that it's not going to go so well there is always this little fear doesn't really matter how much you know and I think this this contact with the doctor that can reassure you and can like look at you and just talk to you is so crucial to basically comforting patients in this difficult situation.

Victor: To your question about the patient journey, I think a lot of people underestimate just how anxiety-inducing a cancer diagnosis can be and the wave of emotions [00:01:00] and thoughts that come with it, right? Like, did I do this to myself? Like did I was I eating the wrong thing or you know, doing the wrong thing? Is it something that was just inherited and naturally was going to happen? But it does force you to to think about your environment and and what you're doing in your life, right? which I think is the silver lining in all of this is that it gives you a chance to reassess your life and and also realizing your mortality, right? And how do you want to choose to continue living? 

Aleks: Welcome my digital pathology trailblazers. Today I'm joined by Victor Angel Mosti, the founder and CEO of Omica.Ai. Welcome Victor. How are you today?

Victor: Hi Alex, I'm doing well. Thank you for having me. 

Aleks: So, Omica is a community driven bio bank based in Mexico City, that's on a mission to bring Hispanic Latino populations to the forefront of precision medicine research. Victor, we always start with you. Let's start with telling the listeners, the digital [00:02:00] pathology trailblazers, a little bit about yourself and basically your background, and how did this led you to founding Omica? 

Victor: Of course. Well, I was born and raised in Mexico City. Uh my father is a cardiologist and my mother is a a bariatric nurse. So I always joke that I grew up in a hospital. I spent way too much time in one as a kid. And then I went to school for biomedical engineering and then design. So I find myself to be sort of at the intersection 

Aleks: How interesting combination. 

Victor: Yeah. I love building things. I think that's the that's the takeaway here. Um, and especially things that have to do with biology and medicine, biomedical engineering and then design and have been in startups for the last 15 years or so and a couple of medical devices and ultimately back into biology through you know personal experiences [00:03:00] around oncology or cancer. 

Aleks: Yeah, I want to I want to dive into your personal experiences around in college because this kind of started you on the path of founding the company, right? And I know this from a personal conversation. So, if you could basically share with us your experience with cancer and how that shaped, basically made you create the company that would be fantastic. 

Victor: Yeah. And I and I think I have to preface this by saying that it wasn't it wasn't an immediate sort of action reaction. It actually took some time for for things to naturally occur. But yeah, in a nutshell, I I had a malignant tumor a few years back, and there was a moment where I was living between New York City and Mexico City. So my tumor was actually analyzed by pathologists originally in Mexico who couldn't figure out what it was and then ultimately the tumor sample traveled [00:04:00] to the United States to a number of hospitals eventually making its way to you know Harvard Medical School where a very specific expert on that very specific type of tumor was finally able to identify it a number of weeks later. So in that or throughout that journey, I not only was able to live through or see firsthand the disparities between even one of the top hospitals in Latin America versus, you know, the average hospital in the United States in terms of their workflows and the way that they process data and the questions they ask around sequencing, etc. but more more so the emotional side of of this sort of journey that patients have to go through. I was very lucky in in the sense that my experience wasn't uh so dire and and fortunately everything is okay but you know I got a glimpse into what that experience can be for a lot of people and their families [00:05:00] and it's something that definitely informs and drives uh everything that we do at Omica today. 

Aleks: So, I want you to like tell me what the disparities were, like what is the most and and you being a person who like knows both worlds, right? It's not that? …and like you said, you grew up in the hospital, so you know the health care system, you studied biomedical engineering, so like you're kind of in the know and you still experience this journey. So here I want to hear what the disparities are and I also  if you're fine with it because I know it's a like a sensitive question like how did you feel as a patient and I'm going to tell you a little bit about my cancer experience that was like almost 20 years ago but yeah tell me what you felt and and obviously like you said it was not action reaction but what from these experiences made you later [00:06:00] think okay yeah I want to do something different in my company. 

Victor: Okay. Well, yeah, a lot to unpack, but I think at first glance, the disparities, there is a very basic digitization gap in the way that information is collected and the way that information flows between clinicians. Whereas in Latin America a lot of the there's a lot of inherent silos from the lack of digitization  that calls for slides and blocks to be shipped all over the place at risk of you know sometimes damaging or losing that that sample. None of the information was none of the clinical data was actually digitized. So it becomes a lot of uh there's a lot of gaps in the process that made the the entire experience very, very slow. Everything from permits as to how to export these bio samples properly etc were things that were not really delineated [00:07:00] in any sort of uh coherent process. it was something that we had to figure out and and with the help of you know people at the hospital etc we were able to do so but once you get to the United States side we saw that everything was much more streamlined and and and you know digital pathology was not as big back then it's it's still nent in many places in the United States but at least there is a culture around… 

Aleks: But people know what that is at least right? 

Victor: Yeah and you know at least the information is flowing doctors are connected. Everything is living on a digital platform. But then on the other side, when you go to an oncologist in the United States, something that I realized was that this person wouldn't even look at me cuz he was on epic, right? So he was asking questions, just sort of like typing away sort of like in a very robotic sort of un unempathetic way or empathic way. Not to blame him. I mean, that's how they need to practice and that's what's required of them and that was a very different experience from doctors in Mexico where culturally uh medicine [00:08:00] is still very much focused on bedside manner and focused on the human side of of medicine which is something that does guide our vision as to if we develop digital tools for clinicians. How do you do them in a way that enables them to be more human and less of a you know a data entry data entry role which is essentially what Epic requires these days. 

Aleks: Very much and I I it's so funny it's just you know across the border right you have Mexico and you have uh what you just told me is okay you did have a contact you did have like real contact with your doctor you had a relationship with them which is like what the all US medicine is I don't want to say complaining about but noticing that this has been missing on the other hand on the other side you have like uh digitization you have the tools so I assume you you had everything written with pen on paper and you had to scan it right or however 

Victo: Pretty much [00:09:00]

Aleks: What about so you have like the two ends that optimally would meet to provide the best possible care did you So, was there any option to digitize your slides or did you have to ship everything? 

Victor: We had to ship everything and I've actually been on a quest to find that slide. So, I'm not sure where those slides and those blocks are. I think they're they're lost in some bio repository in one of the hospitals where it jumped around. Um, so yeah, that's it's it's funny. It's ironic that that I collect blocks on a daily basis, but I don't know where mine is.

Aleks: I know. For a living, right? And I have the same problem. I would say my cancer was I had thyroid cancer and that was like 20 years ago, something like that. So I was already in vet school. I'm a veterinary pathologist. And so I consider myself being in the know as well. You know I knew how like what [00:10:00] kind of cancer that was. I could read publications and yet still like somewhere deep there's always this oh what if it's like this whatever percentage is that it's not going to go so well there is always this little fear doesn't really matter how much you know and I think this this contact with the doctor that can reassure you and can like look at you and just talk to you is so crucial to basically comforting patients in this difficult situation and I'm also on the quest to find my blog. I don't know where it is. 

Victor: We should we should join forces. Back to your question about the the patient journey. I think a lot of people underestimate just how anxietyinducing a cancer diagnosis can be. And the the wave of emotions and thoughts that come with it, right? like did I do this [00:11:00] to myself, right? Did I was I eating the wrong thing or, you know, doing the wrong thing? Is it something that was just inherited and naturally was going to happen? But it does force you to think about your environment and what you're doing in your life, right? Which I think is the silver lining in all of this is that it gives you a chance to reassess your life and and also realizing your mortality, right? and and how you want to how you want to choose to continue living.

Aleks: I love it. It it's like yeah the the the quest for meaning is there and especially if something hits you like that. When I was doing research for this interview, Victor, I did listen to a few of your presentations and one analogy that you gave was that in one of your conference talk, you started with a photo you took at a coffee shop and that had beans from all over the world. It was Mexico, Guatemala, Peru and you made this connection [00:12:00] between coffee diversity and biomedical data. Can you walk the digital pathology trailblazers through this analogy because I loved it. It was like spoton. 

Victor: Thank you. Yeah, I think it was a few years back and it was in London and I was supposed to give a talk on yeah diversity for genomic data sets and I was walking around London the day before the conference sort of like thinking about what I was going to talk about etc. And I walk into this coffee shop, and it just has a wall, right, full of beans like there would be like maybe 30, 30 something different types. And I start reading the descriptions and they're like, "Oh, this one comes from a cloud forest in Guatemala above whatever altitude." And these incredibly remote places from all over the world somehow managing to get their beans into a London coffee shop. And I just found it to be so ironic that, you know, coffee shops have this amazing diversity, yet our genomic data sets are still grossly [00:13:00] predominantly white European. So I just I just found it to be a little bit a little bit absurd, you know, that that that we have supply chains to get beans from so far away almost on a daily basis, yet we cannot seem to have enough biomedical samples to to drive equitable research. 

Aleks: So before we dive into like what the reality is and what the disparities are, if you would  to tell us like the mission of Omica and what you do at Omica in like a sentence, what would that be? Because I want to frame everything in the context of why are you doing what you're doing and how you're doing it at Omica? 

Victor: The way we say it is we are unlocking the path towards precision medicine in Latin America and we do so by bringing Hispanic Latino populations and Latin American populations to the forefront of biomedical research and development. And for us everything starts with the data, [00:14:00] right? You need to have data from the different populations around the world in order to inform all the new diagnostics, therapeutics, AI models that are being developed in order for these solutions to be able to be deployed back into the back into the world in an equitable way. 

Aleks: So if we wanted to put some numbers to this problem, when we talk about representation in genomic studies, what does that actually look like for Hispanic and Latino populations? How are they represented or not represented? 

Victor: Last I checked and this is based on you know you like major biobank data. The Hispanic Latino representation in genomewide association studies which are a good proxy for genomic studies is less than 1%. Some people peg it closer to .25%. So a quarter of a percent. Um, yeah, which if you really do the math in terms of how many humans have had their genetic [00:15:00] data analyzed or their genome sequenced, it's a very very tiny percentage of the human population. So, Latinos are even like a even smaller percentage. So when you start to think about you know targeted therapies or any sort of personalized intervention there is you realize that there's a very very stark gap between what is available today and what could be available if we really analyze these unique populations. 

Aleks: So, Hispanic Latino also does not mean like everybody from Latin America, right? But we're talking at the country level or even at the like indigenous uh people's level, right? 

Victor: Yeah. I mean, that's where it gets really interesting. And you know, I'm not a geneticist, but yeah, I've had some very enlightening conversations with with uh people who who have spent their lives mapping out genetic diversity even with this very [00:16:00] tiny sliver of data that is available. And the genetic diversity that you find all over the world is incredible, right? And even within specific regions, even within Mexico from you know one state to the other there's enough there's uh the same I would say the same volume of genetic diversity or between you know China and the Americas, exists between states within Mexic,o right just from ethnic groups that have been separated for generations and generations and generations. Um, which if you look at it through a lens of somebody who's doing target discovery, you realize that these are pools of unique genetic information that have never been seen and that could be the source of novel, you know, drug targets and uh, biomarkers, for things that may, you know, cure different types of cancer or different types of diseases. 

Aleks: Mhm. And this is not the first conversation that I'm having on the podcast about the diversity of data [00:17:00] necessary for actual personalized medicine. I'm going to link to this podcast in the in the show notes. I talked to Matt Levit who is the founder of the digital diagnostics foundation and they have a similar mission um to do it in the US and he's um referring to indigenous populations and different places that are very underrepresented but I think you are operating even at a like totally different level. What do I mean here? I I'm I'm referring to the funding disparity because you mentioned that in one of your talks that Mexico's National Genomics Institute has a yearly budget of 12 million compared to 800 million for its US counterpart. How do you even begin to tackle such a massive resource gap?

Victor: I mean, it's a bit of a cold start problem, right? because you like a chicken and egg in the sense that you don't have data. So you don't have [00:18:00] products based on that data like diagnostics or targeted therapeutics which means you don't have more data coming in. So you're sort of stuck in this in between where you know there's no infrastructure, there's no funding, there's no private industry around it. And I think the way forward is really is really through what I'd like to call like citizen science now, which is people who are passionate uh starting to work at a local level to interface the local efforts with the global global uh industries honestly. So yeah, private public citizen science 

Aleks: And you said that okay uh there is not really anything deployed in terms of digitization in the, in Latin America um in contrast to the US where the doctors are looking into the computer to type. How can this be leveraged to build something that's better what [00:19:00] is causing trouble in the US? 

Victor: The way we see it is we see the opportunity for a leapfrog, right? And and this is something that's been seen in in different industries and different countries, you know, the way that mobile payments leapfrogged over credit cards in Africa. And there's a lot of examples like that around the world. I think precision medicine is one of these leapfrogs or AI enabled precision medicine is one of these leapfrogs that we could see in Latin America by virtue of there not being any legacy infrastructure. So we are in a in a way we are in a wonderful position to really build the infrastructure from the ground up with the vision of what we want medicine to be right. So learning I think what's important is we need to learn from the shortcomings of you know the last 15 years of medical infrastructure that were built in the US learn from those shortcomings and design something uh that's better from the get-go. Uh for us that looks like [00:20:00] integrated data right data that in involves from bio sample to longitudinal clinical data

with you know patient participation sort of like baked in from the from the start. 

Aleks: So, how would it use like give me a very concrete example? Like if you were a patient again and you had this thing that you're trying to build on and and you're working on, what would it be like? Would you have it on your phone? Would it be I don't know what what would it be?

Victor: I think it's a I think it's a platform that connects both a patient portal which can guide patients through the experience that they're living through while also providing them the ability to participate in various research studies. I think people should have the liberty to research on their own and and participate in science on their own valition. Simultaneously this patient portal needs to be connected to some form of clinical decision support tool uh for for clinicians that allows them to parse [00:21:00] through the right type of data to make decisions on their own. I don't think we're at the place where you know AI models can or substitute the judgment calls that an oncologist needs to make on a daily basis. But we can definitely ease their burden by sifting through the troves of data that are that are coming online uh to make sure that they're making the right decision for the right patient at the same time. And then simultaneously these you know patient and physician portals need to be linked into a population scale, population scale data assets that can be leveraged for real-world evidence that can provide you know all sorts of label expansion and and the discovery of of treatments uh that may be either unique treatments for the pharma industry or things like drug repurposing which could provide you know cheaper access to very effective therapies for places that are resource. is constrained.

Aleks: So do you have already [00:22:00] anything in place? How does it look logistically 

Victor: In terms of this infrastructure? Yeah. So we we ironically started from from top down where we started with aggregating a lot of the data that's already out there. So that means crunching a lot of analog data, a lot of paper, a lot of Excel spreadsheets, word documents. We basically run them through our pipelines to harmonize the data, ontologize it, and create these population scale data assets that have longitudinal data linked to bio samples. And now from there, we're able to choose from different strategies of what type of uh OMIX data we want to obtain, right? Is it just the pathology image from the H&E which are becoming more powerful than ever and very low cost which is attractive to regions like LATAM um or do we want to go into you know genomics RNA uh transcrytomics spatial genomics etc [00:23:00] etc.  And I think that's where it gets really exciting.

Aleks: Do you have a direction like what is more doable in Latin America? 

Victor: I think for us it's balancing the excitement of these new technologies and and the what could be you know with all this data and really grounding it in what could be accessible to the place that we're operating out of. And that that is why we are particularly excited about digital pathology because it has a lot of leverage right you can the the input is very low for the amount of impact that you can have, especially now with all the wonderful you know AI models that are coming in from all over the world. It's something where for very for a fractional cost of a genome you can now improve the odds of a patient having a successful outcome or you know spending five more years with their family simply by implementing these very very [00:24:00] simple solutions. 

Aleks: And what we're referring to here is the molecular predictions from H&E images. Right? This is like let's call the one application of AI because I know you leverage AI for workflows and now with the large language models ,I don't know how you guys were thinking about digitizing all this written data without the text recognition and large language models. Oh my goodness. 

Victor: Took us a long time 

Aleks: …and now miracle happens like a miracle happens that you can now leverage paper at scale right but also this like other application of AI that you're saying okay we have these images we can scan them it has a cost associated with it but it's the the cost is a fraction of the cost that would be associated with actually doing these molecular analysis which often is prohibitive meaning they don't happen Um and here okay do we want a prediction [00:25:00] that can guide us in a certain direction or do we want nothing uh I would want to have a prediction from whatever uh is available right in a situation where I don't have an alternative because the discussion here in the US and and in like um wellresourced countries is okay but if it's not like 100% accurate if it's not if it's just like this prediction that guides you in a certain direction instead of like a specific indication of what mutation that is. Right? And here you can use it how I see it. Okay, you could use it for as a triage tool. Use and later do the molecular tests on samples that have been already indicated by AI. Yes, here you should test for this and that mutation. And there have been a few publications about that. But in a place where this is not an option then the second best thing for providing care [00:26:00] would be just use the information from the prediction right. What is your? what are your thoughts on that because I mean resources and okay there is no money for this to do it in Latin America it cannot be the only justification if it's not the right thing to do.

Victor: Yeah, and and you know I think as they say innovation happens between a rock and a hard place. You know in the sense that sometimes resource constraints are really what drive really transformational innovations. And that's an ethos that we've tried to embody in Omica which is we're in Latin America. It's a it's a drastically different health ecosystem. You know comparing ourselves to the US ecosystem and what companies are doing in the US is a mistake simply because it's not our reality. Right. And I think that uh there there's many different you know there's a design also a design saying or or framework um that's most advanced yet acceptable right the Maya principle and it's what is the most [00:27:00] advanced thing you can do that it will still be adopted and implemented in the real world um and that's a check that we constantly have to remind ourselves before getting too excited about new technologies is how do you deploy them and how do you deploy them at scale in a way that makes sense to clinicians at the end of the day and yeah I mean I think digital pathology has a huge huge opportunity in in research constraint settings particularly. 

Aleks: I want to ask about something slightly different because and you have this unique experience of like having lived in both places and I have lived in Poland and I'm living now in the US and historically ,in plenty of places you would have people coming from one place going to another place trying to deploy things that are not deployable. I know it's a sensitive topic because it has like it has all this colonialistic heritage [00:28:00] that people feel very strongly about. But we still kind of I don't know I don't know if we do it. I hope we don't do it. How do you avoid doing it? like coming with something that's not going to be deployable somewhere else even though it may be such a great technology and it's more like a conceptual discussion like what are your feelings and thoughts about that? Do you catch yourself sometimes like do you have to catch yourself like not going in a in a way that you would you would do you would go if you had all the resources or just whatever you feel about that because it's I don't know it's like happening there there are disparities in the world and people from the places that have resources want to help the places that don't have resources but without ever having experienced the reality where they are trying to help and sometimes it causes harm. I don't know. [00:29:00] I hope I'm I'm clear enough this one. 

Victor: Yeah, I think harm harm and and lost resources and and you see that too in in the you know startup VC ecosystem. There's so much waste, waste of resources flying under the flag of innovation when in reality it's a bunch of crap being created that never sees the light of day simply because we don't I think we don't listen enough, you know, as creators, as innovators, as designers, as engineers. Like the fundamental path to creating anything is starts by listening, you know, listening to your user, listening to your customer, listening to what people actually need. And sure maybe people don't know what they need because they're not familiar with the new technologies that are, you know, the new possibilities, but that's that I think the role of a good designer engineer is to translate what's technically possible with what's humanly realistically necessary. [00:30:00] Um, and that's that's where every good design process begins, right? sitting down with your with your end user and then really asking yourself, how do I make this life this person's lives better? 

Aleks: I love it. I know it from from the software side a little bit. Uh where yeah, if you just don't sit together, I mean, you're you're making something for the end user, right? If you don't listen to them, then what's the point of creating this thing? Um I want to switch well, I don't know if we're switching gears. I want to transition into the um the community aspect of this process. You mentioned it this at the beginning that okay you would need to have like local enthusiasts people who believe it believe in whatever the innovation is right in in this case this biomedical innovation at the local level to be able to disseminate it and to gain trust for this that kind of contrast with uh something [00:31:00] you mentioned as well in uh one of your talks the parachute science I was not familiar with this with this term but basically this is researchers coming in extracting data leaving communities with nothing. So um can you paint a picture of what this looks like in practice and why it's so problematic? 

Victor: Sure. I'm gonna try not to get in trouble, but… 

Aleks: You can be be on the edge because be as on the edge can be. No, let's, you know, but let's describe what harm it causes because it kind of ties into what we just said. Okay, somebody comes, wants to do good and then leaves. in this particular context of parachute science, what does that mean for the people that are being researched, let's call it like that? 

Victor: Yeah. And I think that's the issue, right? [00:32:00] It's it's people being researched, rather than being co-articipants in research. And you see that in when people speak of biases, right? And they speak like, oh, that the data is biased. And not only is the data biased, but the questions are biased because the researchers are often not representative of all the populations, right? If all your researchers are from, you know, are English people from Oxford University, the questions that you're going to ask are may or may not be representative of the Mexico City population, so to speak, right? Simply because our needs and our interests, so to speak, or our priorities are different. And I think that parachute science is not, I don't think it comes from malice. I think it comes from simply the lack of a model, lack of examples of how to how to do community-based participatory research properly. And it goes back to my my previous answer which is it starts by listening. [00:33:00] It starts by showing up and and meeting communities and figuring out what the priorities are, rather than seeing them as test subjects or or you know a source for something that you want to extract and this has happened before in in throughout Latin America where you know it's happened with bio acids you know with with natural resources of you know plants that have specific compounds or enable you know people to create certain materials etc. uh that used to be taken and exported and uh exploited internationally without ever giving anything back. Right? So that's where the term biopiracy comes comes through. And I think now as biomedical data becomes more of a centerpiece to research, we need to be very weary of not committing these same acts of biopiracy. And one of the ways to avoid that is precisely by you know involving the community. And the community is not only the patients, it's also the clinician, [00:34:00] the local researchers um people who have an incentive and an interest in actually solving a problem for that community rather than just extracting information um for external use so to speak. Yeah. 

Aleks: So how do you do it? Like let's say you would want to start a project in a new place. Who would you go to? Who would go? Would that be you? Would that be like how how does something like that start even? 

Victor: So, we base a lot of our work on the Nagoya protocol. The Nagoya protocol is was created for biopiracy of natural resources. Um, and it's a wonderful framework that the I don't know if it's the UN or somebody the FAO, but it's a way for scientists to interact with communities around the world uh to do research projects. But there's a key piece in those research projects which is the [00:35;00] agree a fair and equitable benefit sharing agreement.

Which means if I exploit your natural resources or find something in your natural resources, I am uh committing X percentage back to you or something like that. Um and this is a pretty cool framework uh that hasn't been really applied for applied in human research. I know there's a company called Variant Bio that that has pioneered a lot of this work. Um, and they're doing great and and I think it's it's it's one example of something that could really become prevalent in the sense that you now incentivize the physicians and the clinicians, and I mean the patients to participate in research, but they need to get something back, right? Uh for us that's the deployment of AI models back into the system, right? So when we use that data to train a digital pathology model that uh hospital center or network of hospitals receives the AI model back in a [00:36:00] you know free of use type type of agreement. 

Aleks: So basically it's it's a kind of contract right that has to be a kind of a win-win situation. we come in with something and if there is a benefit we can obtain then you will get a counter benefit because you we we're using your resources. Interesting. So I love the I love the example you gave. Okay, we train on your data but then you can actually use it to help your patients. Do you have any examples that you can share like specific models that are already published or anything um like specific that you guys are working on right now? 

Victor: So not yet we can't share it publicly yet but we are working on distributing uh two models. They're they have to do with cancer recurrence. So they predict the you know the possibility of a a patient experiencing recurrence which informs uh the use of adjuvant chemotherapy. So we believe that these will have a tremendous impact in Mexican health systems. Not only [00:37:00] in terms of improving the patient journey and outcomes but also in terms of cost uh that health systems can save in you know unnecessary chemotherapies basically. 

Aleks: Amazing. Most people compartmentalize work and personal values, but when your company is literally addressing medical inequalities, how does that show up in your daily life? Like, do you have to keep yourself in check, or can you like switch it off? Do you act differently there and here? I know I do when I go to Poland um because there I'm in my Polish reality and people don't necessarily know everything how things work here and when I'm here I'm in the US reality so you know it's not not at the business level but basically personal and I think that's I don't know if you can call it lifestyle but that's some kind of skill that [00:38:00] immigrants who did not commit to just one country develop because that's something we have in common. You you work there and you work here and by there I mean Mexico and here US and I also like go to Poland on a regular basis and maintain my relationships there. How do you function in such a situation personally and business-wise and uh what are the things to to keep in mind or how do you feel about it? Or maybe it doesn't matter? 

VictorL It does matter. It's what I'm trying and I I don't know if I've achieved this, but what I'm trying is to make the best of both worlds. And some days it's the worst of both worlds and and you really feel that pressure and you feel like you don't fit in anywhere and you sort of feel misunderstood in either place. And I think there's other days where things click and you're able to really really see the [00:39:00] the value and the connection between both worlds and acting as a translator between spaces. A lot of times this becomes especially with work, it becomes sort of glimpses of each place, right? like what is each in health systems in particular, what is right about this health system and what is right about this one and what is wrong and trying to a mental exercise is trying to to figure out how to borrow from each to create a a whole new reality, right? And and I think this is very very valuable. Um, but back to your original question, I think that being in Mexico and and walking through the hallways of a lot of these health systems is super necessary to remember why, you know, why we're doing this, why we put up with, you know, bureaucracy and why, you know, we we wake up every day to keep chiseling away. Uh because the need is there and it's a very human need. And to me that's that's like pure [00:40:00] creative oxygen so to speak. 

Aleks: I think a big differentiator of these type of initiatives that actually have a potential to change something is the understanding of both realities. You know you have always there are these like discussions going on. Oh, this country is better because of something. The other country is better because of something. US is the sixth country I've lived in. And uh very quickly, I think after the third one, I realized that there's no perfect country. There are things working in one place that are not working in the other place. And also, it's not that you can like swap the non-working things from one place for the working things in another place. So every time there is like an a discussion, oh we should introduce this because another country has this and they live so nicely and an example of that is going to be okay maternity leave right [00:41:00] and in Poland you will get a year in Canada you can get a year here you cannot get a year and like I don't know a mother that would not like to have a year with their kids and yet like just implanting that this in the would not work. Uh and the same same for healthcare, the same for you know all the other things that seem so obvious to be wrong somewhere else but then the magnitude of implementing and all the interconnectedness of this little thing that you would want to swap um can only be understood if you actually live there, if you use this healthcare system, if you somehow uh understand it. Um, so yeah, kudos for wanting to work on it because it's freaking difficult. 

Victor: It's very difficult. It's very difficult. Yeah. And and back to listening. I think sitting down [00:42:00] with a patient, sitting down with a clinician, I think I think something that I've learned is not think about the whole system. I think change happens at an individual level and if it's if it's a good change, it'll spread, right? So it's counterintuitive, right? People always tell you to think bigger and think bigger and how is this huge? And at the end of the day, you just have to make tiny little a tiny little change that's actually a change. 

Aleks: Let me tell you why I love it. Because so I was to do my PhD, I had a scholarship. It was a scholarship for people from different countries to go and study and do something in Germany. And the deal was you we give you the scholarship if you go back to your country and like implement the stuff you don't have to pay it back. If you don't go back to your country you do have to pay it back. So obviously I'm not where I [00:43:00] started right so I had to pay my scholarship back. But um I remember people uh who were our mentors in this scholarship and um I talked to one of them and and I asked why did you like why did you choose to do it because and he said well in the worst case I am giving one person a fantastic experience for three years and fantastic learning experience in a different country. In the best case they will actually go back and implement it. So either way I am helping someone and this is what I'm hearing in what you're saying. Yeah. Like you help one person is like the smallest scale that you can operate on but there is the potential to grow it organically from that one person. I love it. 

Victor: But it's hard. It's hard. 

Aleks: I know…

Victor: For me at least. For me at least. Yeah. 

Aleks: Yeah. And especially you know you're a designer. [00:44:00] You are an engineer like thinking in terms of leverage and now also like in the terms of AI thinking in terms of leverage of impacting more than just one person at a time is how we want to do these things. So then if you only like do one little thing, you get discouraged. But don't get discouraged. I cheer for you. 

But I want to ask you yeah, speaking of technology, um you guys are using blockchain for data transparency. We didn't talk about data transparency. We kind of touched on on the sensitive topics, like indigenous population like the parachute science but um you started talking about this being a consensual process that uh somebody is giving their data and you are using blockchain for that for somebody who's not familiar with this type of blockchain use. Can you explain why this matters and how it changes [00:45:00] the way this consent is obtained? 

Victor: Yeah, so we have used blockchain in the past. Right now we we don't need to use it. I think it's a, I think it's a very good application for blockchain. Why? Because blockchain is immutable, traceable. Uh and you have a contract that is transparent. uh which is one of the the missing pieces in a lot of uh biomedical research studies. Um and back to parachute science, you know, there's been instances where, you know, big pharmaceutical companies come into a country and they somehow get their hands on, you know, a ton of bio samples and those bio samples lead to a drug target and nobody knew where those bi samples came from or if the patients had consented, you know, to participate in research or anything like that. You know and some people argue that you know that it's a net positive and that that research should be done. I think the future is a place where people participate in research right and, and I think as patients [00:46:00] if we know where our information is and how our information is being used I think it's I think it's a powerful it's a powerful narrative and it's a powerful action for people to come together to accelerate research. Um, we saw that too with 23 and me, right? When they went bankrupt, people didn't know where the data was going to go, who was going to buy it.Um, so I think the the world is changing in that regard. And right now there is an opportunity for the creation of these participatory science platforms. And even some that can redistribute profits back to the participants, right? Or benefits. 

Aleks: So basically traceability and like the transparency would be the biggest advantage of blockchain in this and then you know where it comes from and where it should go to in case um not only like in case of benefits but also like okay if you need follow-up, if you need like any additional [00:47:00] data that you would want to have, you can basically… 

Victor: Yeah, exactly… 

Aleks: …go and ask for it and chances are if somebody already gave was invested in this being done, they will want to give the follow-up information. So not only like on the on the side that oh nobody really knows, but here you know exactly and you can ask them and why should they say no if they already said yes. 

Victor: Yeah. And it's it's I think it's a big gap in in bio banking infrastructure. You have a lot of bio banks that were not designed for today's type of research, right? That were designed for a different era where bio samples were basically perishable and you used them once and then you incinerated them. Nowadays, you need to future-proof your bio sample collections, right? You need to make sure that consents are dynamic because you don't know what technology is going to come out tomorrow and you know if your consent didn't have you know spatial transcrytoics 10 years ago. [00:48:00] 

Aleks: Exactly. 

Victor: You need to be able to reconsent patients and I think the only way to do that is to do that through participatory research of keeping patients involved in the future of of science. 

Aleks: So how does your bio bank look like? What is what are you going to be working on this week? And basically what's your what's your daily or weekly routine in Omica as a business? And how is it run differently than than the bio bank just monthly or whatever, right? Uh how is it run differently than the bio banks that you just uh described that may not be future proof? 

Victor: So I think our our routine and the way we operate is starts by being embedded within existing hospital systems. So we don't see ourselves as a you know as a bio bank that's just picking up things from all over the place, but rather as a partner, as a clinic as a partner to the [00:49:00] to the hospitals, in the way that we are able to digitize all of their information and organize their bio repositories and ultimately sequence their bio repositories. So we partner with hospitals to provide them with a future-proof data asset that they can then leverage for research partnerships. Um, so I think that's the that's the main difference is that we are embedded within their workflow. So we do get access to constant patient flow. We are able to consent and reconsent and even recruit patients. Which is the only way that we found that we would be able to implement these sort of dynamic consents and participatory research and and the like versus other bio banks which operate sort of statically and retrospectively. This is like a living bioank. Yeah. 

Aleks: Because you have the contracts with institutions and you're embedded in them. So, [00:50:00] what's your biggest fear about the future of precision medicine if we don't solve the diversity problem that you're working on?

Victor: I think um sort of like getting to this uncanny valley here, right? Where maybe people perceive that and and a lot of people are saying this and I I don't necessarily agree but you know how people are saying, oh no don't longer you should no longer study medicine because AI is going to take over you know the medical practice and and I think that's the wrong narrative but in a worst case scenario I do see a world where AI models [00:51:00] are sufficiently good to be able to be implemented at scale and deployed at scale but sufficiently bad to not be able to translate worldwide, right? So my biggest fear would be to have a shortage of physicians In, or supported by suboptimal AI models uh which lead to worse options. 

Aleks: Yeah, 

Victor: That's a bad situation. 

Aleks: That's bad. Anything that you believed five years ago that you now think was completely wrong? 

Victor: I think it's back to that scale thing, you know, like always thinking how things can be bigger. And I think right now I'm more focused on how to work smaller and more focused. So think small rather than think big. 

Aleks: Okay. And if you could go back and give advice to yourself when you first started, what would you say other than think small instead of think big? Anything else that you would like advise yourself? 

Victor: Think be patient. I think, I underestimated how difficult health systems would be. I think health systems and how long things take as well. 

Aleks: It takes a long time. [00:52:00] 

Victor: Yeah. 

Aleks: I know, That brings me to another thing like then you know obviously everything in life is hard. pick your heart. But then you need to believe in something enough to pursue because there are so many like easier things to do that you know you could do that are lucrative and can help people as well and you as a designer you know you could have picked something else. For people who are listening to this forthe digital pathology trailblazers whether they're researchers, clinicians or just you know people who care about health equity what can they do to help specifically you and Omica in general like what can they do to help the situation? 

Victor: I think both to help the situation and if they want to help Omica out, I think is if you know of research studies that would benefit from data diversity or diverse participants to [00:53:00] reach out, you know, and reach out to us and reach out to all the other, you know, research groups in the region who who honestly we have a lot of underfunded scientists and they're brilliant minds that are working with very little resources who would in would be delighted to work with international research groups. And that would really really propel forward the the mission of Omica and the mission of Latin America as a as a participant in in scientific research. 

Aleks: So, what kind of participants are you looking for? Like is there… 

Victor: Us, particularly right now? We're very, very much focused in breast and cervical cancer. So, that's that's an area that that we would be ready to collaborate on. But in general, um, oncology as our focus. 

Aleks: Okay. Any specific one thing that you'd like people to remember from our conversation today? 

Victor: To think small. To think small. 

Aleks: And I'm going to take that one. [00:54:00] I'm going to that one. 

Victor: Think small and keep it personal. You know… 

Aleks: Keeping it personal. Yeah. Personal, relatable, and then I guess, you know, I don't know. I think always that okay if it's a good thing it's going to be amplified even if you're gonna do it at the smallest scale possible. Thank you so much for joining me today and… 

Victor: Thank you Alex. 

Aleks: …for doing what you do and actually I hope that maybe one day we can do a vlog story from uh going to one of the hospitals that..

Victor: Mexico City? 

Aleks: …that Omica fun. Yeah, I'd love to go.  I visited Latin America a few times. I was in Mexico like two or three times. I visited Bolivia. I would love to dig deeper and see how things look. 

Victor: Oh yeah, let's do it. Okay, let's plan it. 

Aleks: Okay, thank you so much. Have a wonderful rest of your day.[00:55:00] Take care. Bye-bye.