The following interview is a conversation we had with Ignacio Medrano, Founder & CMO of Savana, on our podcast Category Visionaries. You can view the full episode here: $44M Raised to Transform Healthcare Intelligence Through AI
Brett
Welcome to Category Visionaries, the show dedicated to exploring exciting visions for the future from the founders who are on the front lines building it. In each episode, we’ll speak with a visionary Founder who’s building a new category or reimagining an existing one. We’ll learn about the problem they solve, how their technology works, and unpack their vision for the future. I’m your host, Brett Stapper, CEO of Front Lines Media. Now let’s dive right into today’s episode. Hey, everyone. Welcome back to Category Visionaries. Today we’re speaking with Ignacio Medrano, Founder and chief medical officer of Savannah, a healthcare technology company that’s raised 44 million in funding. Ignacio, how are you?
Ignacio Medrano
Very good. It’s a pleasure to be here with you today.
Brett
Super, super excited to have you here. Let’s go ahead and jump right in and talk about your journey. So I’ve had a few founders who were medical doctors, and then they became founders. But I would say it’s not a common career path. You know, normally you go through all of that education, all of that schooling, you end up a doctor and you stay a doctor. You went a different path. You went into tech, you went into building companies. Talk to us about what it was like when you decided, firmly, I’m making this move, I’m making this transition.
Ignacio Medrano
Yeah, exactly. So it’s not that common. It’s maybe becoming a bit more common lately, but 10 years ago, definitely, and especially in Europe, you don’t see many doctors that have become entrepreneurs. And for me, it was just that I wanted to make some impact. And at the beginning, I thought, why don’t I become a manager? Hospital manager was probably where my career was going. But then I discovered that there was this whole thing of data and AI that was starting, and I thought that maybe there was an opportunity there, and I was lucky enough to have the right partners who were not doctors. And we decided to jump into this new world.
Brett
And what was that new world? What was that idea that you had?
Ignacio Medrano
Well, what happens basically, is that everybody is trying to predict things with data. You know, like the statistics is the past and probability is the future. And the more data you have, the more you can predict. And there are many markets and sectors using that. You can see that in food, in the stock market, in sports and everything. And of course, if you apply that to healthcare, then you can bring a lot of good to patients. And that is quite obvious today in 2024.
Ignacio Medrano
But back in 2014, it wasn’t that obvious, but we thought that Maybe with all that information that gets written in the medical records every day, we could do something if we through that into the proper machine learning models and that we could predict, for example, who was going to respond to a drug or who was going to have a worsening in a certain disease. And with that idea in mind is that we started then. So we created our prototypes, started going to hospitals and it worked. And so 10 years later we’re here.
Brett
You know, now when you talk about AI, everyone’s talking about it. My mother, who’s probably miss her age, but yeah, she’s like, you know, mid-60s, she’s talking about AI, you know, everyone’s talking about AI. What was it like to talk about AI 10 years ago? Like, did you introduce this idea and people just kind of dismissed it as, you know, something you see in movies?
Ignacio Medrano
Yeah, it was interesting. I remember in the cafeteria of my hospital, I am a neurologist by background and I was practicing, I was seeing my patients with Alzheimer’s, stroke, these things. And I remember myself telling my colleagues, look, I discover this thing that is called machine learning, which is so incredible. It means that computers, they don’t learn by rules, but they learn by cases, they learn by examples. It’s a bit like children when they learn their mother tongue. And it’s so much more efficient. But the inventors themselves, they don’t really know why it works. It works because it somehow mimics our neural way of learning, but we don’t really know what’s the reason behind it, but it’s very efficient and so on.
Ignacio Medrano
And I remember telling this story and they were looking at me like, yeah, that’s cool stuff, but it’s never going to work. I mean, we’re in science, we’re in proper statistics, you need proper methods. And maybe a hundred years from now that will happen. And you know that we tend to underestimate what is going to happen in 10 years and we tend to overestimate what is going to happen in two years. I don’t know what’s the name of that. There’s a name for that. And I think that’s what was happening.
Brett
From when you started to have these ideas, have these conversations. How long until you were generating revenue was this? You know, three months? Was it three years, five years? Yeah. How long did it take?
Ignacio Medrano
Well, for us it wasn’t that long to generate revenue. Maybe I would say, less than one year. So not bad to be healthcare. Different story is to get on the exponential curve, which you get in other businesses, but in healthcare it’s so much more difficult. But yeah, we cannot complain about the amount of early adopters and innovators that we found in a sector that is known for being very conservative. But to be honest, also in this sector, even in the public sector of healthcare providers, also pharmaceutical companies, of course, we found people that were willing to try this new thing that were telling them about, changing the way in which we did medical research done through machines instead of through humans, in the sense of collecting data automatically, which was a very new thing.
Ignacio Medrano
And maybe it took us more time to convince the journals, the scientific journals that they could publish what we’re doing. That took us three, four years. But the first, let’s say small money came quite early, to be honest.
Brett
And then what was that early marketing strategy? And then maybe tell us, you know, how it’s evolved, if there were any big chapters along the way into what the marketing strategy looks like today.
Ignacio Medrano
Yeah. So what is interesting is to understand that when we launched this tool that is able to go to medical records, apply a lot of validated and scientific natural language processing, which is not the same as other types of natural language processing, we have to invent the methods to make this reliable from a scientific point of view. The idea that you can transform the free text that doctors write into variables into a database. And when we started doing that, the idea was great, but then who would use it? And we found that it was no one’s job to use this kind of tool. And of course the budget were not big, especially in Europe where we started, so we had to pivot very quickly.
Ignacio Medrano
And what we did was we started selling this to pharmaceutical companies because they really have this interest of knowing what is happening to patients by certain disease. So the same technology, the same NLP extraction of data with the provision of hospitals, and then in a de identified way, we started selling it to pharmas. So we stayed there as a company for five years. We survived. We’re incredibly close to die, as probably every entrepreneur would tell you. And then only when the technology evolved, the mindset evolved, the culture evolved around the idea of data, healthcare data, intelligence, especially, sadly, thanks to the COVID situation. Only at that moment, the hospitals were ready to catch up with budgets and with people waiting to use our tools.
Ignacio Medrano
And that’s how we came back somehow to the original idea, which was selling this to hospitals that could then use their own information, aside from pharmas, for all kinds of use cases. So for us it was like a journey where went somewhere, then we had to go somewhere else. And then we came back.
Brett
Like many entrepreneurs and founders I’ve had on the show, makes perfect sense. What types of customers were you initially focused on then? Like, what was that? Icp, where you, like, you know, this is who we really want to try to hammer.
Ignacio Medrano
Well, for us, the moment you extract all that information from hospitals and you create these huge databases, there would be like two main cases which would be for managers of hospitals, they really need to understand what is happening inside. And even if it’s quite counterintuitive, the reality is that in many cases they don’t know. They simply don’t have the right metrics to understand what precise drugs are being prescribed in this certain type of patient and how they are working, yes or no. So outcomes, what you would call outcomes. And that whole thing is interesting because the moment you understand if a drug works or doesn’t, then you can spend more or less and it’s so much more efficient. So it makes sense to have this better systems in that regard. And aside from managers, we also have the researchers.
Ignacio Medrano
And for researchers, again, if you want to understand what’s happening to your patients, you have to collect data. And you do that on an Excel sheet and you do it for literally three, four years, collecting variables, collecting data, patient by patient, variable by variable, and only when you have that, then you’re ready to analyze. It’s an incredibly slow process for something as important as understanding disease and patients. Now, you can literally do that with a click because it’s a machine that goes into those records and extracts those variables and creates those data sets. So researchers are also extremely important for us as customers and users.
Brett
And if we zoom out and I’ll just share, you know, my perspective as probably an ignorant American, you know how I tend to view Europe is regulation is a bit more strict and tight against innovation sometimes. Like, what’s the regulatory structure look like right now when it comes to how AI is being used in healthcare?
Ignacio Medrano
Yeah, exactly. So it’s a bit different here, basically, to put it very simple. In Europe, it’s, with some exceptions, generally not allowed. And maybe even more important than law is culture, I would say generally vaccine. That company, a private company, buys data from a hospital, even if it’s de identified, creates a database and then does business with it, reselling that information to third parties, to other companies. That is extremely common in the US and there’s a whole market with competitors and everything. In Europe, there’s basically nothing, or very close to nothing, because that’s not accepted. Thankfully, things are changing. And now we have a very specific regulation, the General Data Protection Regulation, which says that if the information is anonymized, is de identified and you’re using it for research purposes, then you can use it without informed consent, without telling the patients.
Ignacio Medrano
It took us as a continent sometime to get to that low, but now it is in place and it’s making things so much easier. And now there’s something else again. After the COVID situation, Europe basically realizes that our level of data intelligence is embarrassing and very low compared to the US but also compared to the Eastern countries. And what comes out is something that is called the European data space, health data space, which is basically a framework of how to share data among hospitals and institutions. But more important than that, it’s a cultural change, a mindset change that says basically that formerly sharing clinical data was a bad thing of being a bad European, while now it changed quite quickly. Sharing clinical data is seen as a good thing, is something that a good European would do.
Ignacio Medrano
And I, as an entrepreneur in this world, in this field for 10 years, I’m amazed about how incredibly quickly this changed. But you know, the crisis was so big that maybe that was the click that we needed.
Brett
And is that the trigger, do you think? Is that why things change so fast?
Ignacio Medrano
Well, yeah, that’s what I think. I didn’t read this anywhere and I don’t have factual proof, but yeah, some colleagues agree that those months, the way in which the European countries, Spain, France, uk, even the Nordics, which normally have better clinical data, were handling the situation badly. And not just because of politics, anti vaccine or this kind of thing, just because we didn’t have information compared to what happened in Korea and Japan, in Singapore, in so many other places where the information was in place, or in Canada, imperfect but in place. And I think that, yeah, that was a big part of change of minds. And we realized that unless we start sharing data properly and we are less scared of this happening during the next crisis, which eventually will come sooner or later, we wouldn’t be prepared do you.
Brett
Plan on staying in the European market for the foreseeable future or do you have plans to eventually expand to the.
Ignacio Medrano
US we’re actually already doing a few interesting things in the US we have partners there, big research companies that are helping us get to the global pharmaceutical companies which are normally headquartered there. So that’s interesting in itself, but we’re also doing very nice projects. So, for example, the copd, the Bronchitis foundation of the United States came to us and said, look, there are 20 million people with this disease in the country and only 10 million half of them are diagnosed, the other half are not diagnosed. So could you build an algorithm for us, an AI algorithm that predicts which patients are more likely to have this disease so that once we have it, we can give that to the hospitals and we can find this 10 million which they call the missing millions. And we did it. And the algorithm works pretty well.
Ignacio Medrano
So, yeah, there’s also a good field for us to work.
Brett
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Ignacio Medrano
I would say that the best thing that we did was to kill our first tool for doctors, so our first tool for doctors. Now I see it so obvious, but at that time we didn’t. It was a disaster. It was basically the idea that because we could deep dive into those health records and extract what was happening in the daily clinical practice, if we gave that information to other doctors, then they would see what their colleagues were doing and they could react to that and they could make decisions based on what the majority is doing. And that was called Savannah Consulta. And we thought that was a good idea. We were thinking about the wisdom of the crowds, the idea that if many people are thinking about that, it means something.
Ignacio Medrano
And were somehow trying to replicate, to mimic what happens when doctors talk to each other during their clinical sessions. And were trying to put that into a piece of software. So the idea made some sense, but it was incredibly rejected by my colleagues. And the reason was very simple. The fact that the majority is doing something doesn’t mean it’s the right thing to do. And that’s quite opposite to what Evidence means. Evidence means this is the right thing, no matter if few people or a lot of people are doing it. In a way, were trying to go against the status quo, which is using the right evidence instead of using the majority, the wisdom of the majority. And we realized before, probably before it was too late, we completely killed the tool.
Ignacio Medrano
And we use the same natural language processing capabilities, we used them for a totally different thing, which was simply creating reports of disease and how patients are behaving and how disease is behaving. And that’s how we started building something more interesting, on top of which we finally could come back to our tools that helped decision making, but in a totally different way.
Brett
Let’s imagine that a healthcare tech entrepreneur comes to you and they signacio, I’m getting ready to go into market. I’m getting ready to build this company. What’s your number one piece of advice for them? What should they have top of mind to succeed in this world?
Ignacio Medrano
Well, I would say that what differentiates healthcare is that a bigger amount of decisions that your customers will make will not be based on the rational laws of the market. And fair enough, we are humans and that happens in every market, that people are emotional and sometimes irrational and egos and all of that. But I’ve seen that, you know, from colleagues that come from other markets and they think that they’re going to get it in one year and they don’t get it. And when you ask, the reason is that the amount of decisions that simply don’t make sense from the financial perspective is huge. So a typical case would be you optimize something with which you need, I don’t know, 10 nurses less. And it doesn’t really matter because politically it’s against everything not to count on 10 nurses.
Ignacio Medrano
It’s something that will appear in the newspapers everyone will fight you for, even when it’s pure efficiency and even when you don’t need it anymore. So you come with an innovation that apparently is useful, but then at the end of the day, you have double expense. You now have the software and you have the people, and that keeps replicating and replicating in the sector. So, yeah, considering that not because something makes sense is going to be accepted by healthcare providers, I think is good advice.
Brett
What about fundraising advice? You know, what have you learned about fundraising throughout this journey?
Ignacio Medrano
Maybe so that I can give something more specific that many other people from other sectors could talk about with regards to fundraising. I can talk about healthcare fundraising. And what I mean by that is that the pace is lower so it’s very regulated. Cultural change needs time. And even if your tool is great, it’s going to need time. It’s what happens with drugs, right? We have incredible new drugs that would save lives. And even when that’s the case and it’s lives of people, what is at stake, it takes 10 years to validate them through the proper workflow circuitry.
Ignacio Medrano
So with that in mind, maybe going to the traditional venture capitalists, this is something that you have to consider because these people, normally they need return in three years, four years, and I mean, they have great intentions, they always want to help, they love healthcare and we got really good help from our VCs. I have nothing against them, nothing to complain about them, but thinking about how they can feel about us, you know, at the end of the day, for us and for any company in healthcare, it’s very difficult to give returns. And in that amount of time you normally, you need longer. So that’s something that you may want to think about before fundraising.
Brett
Final question for you. Let’s zoom out three to five years into the future. What’s the big picture vision look like here?
Ignacio Medrano
So things are really going to change. I would say basically we are going to have access to digital tools, apps or whatever it looks like, where our data or part of it is going to be uploaded, call it ecg, emr, I don’t know any report, anything. And what changes compared to five years ago or even to now, is that you have the possibility of running predictive algorithms on top of that, machine learning algorithms, AI algorithms that will tell you how you’re going to react or how your condition is going to evolve. And the level of precision of that tool is going to be high enough so that people are going to want to go there for advice and for medical care.
Ignacio Medrano
And probably these tools, if the companies behind those things, well, will be connected to physical sites, to physical hospitals, of course, will still be in place. But the gatekeeper, I don’t think it’s going to be the hospital anymore. The gatekeeper is going to be a sequence of personalized algorithms on digital that people are going to use on a normal basis. And the reason for that is that two things are going to collide to converge. The first one, the machine learning AI algorithms that we’ve been creating for five, 10 years, five years from now, will be finally validated with clinical trials and everything. Something that we don’t have today, but we’ll have it in five years. So the science behind the AI algorithm for you will be robust. That’s the first reason.
Ignacio Medrano
The second reason will be generative AI, because generative AI doesn’t really add new knowledge, but it improves access to already existing knowledge. It’s like a new revolution of what was Google. So generative AI will help these customers, these patients, navigate those complex algorithms in an easy way. If you put those things together, I see that AI in the phone for healthcare is a reality that is very close.
Brett
Amazing, man. I love the vision. I really love this conversation. I appreciate you taking this so late in the evening, your time. Before we wrap, if there’s any founders that want to follow along with you, where should we send them?
Ignacio Medrano
Well, I think the easiest is to go to our website, Savana Met. I’ll spell that. Savana. Like medical savanamed.com awesome.
Brett
Thank you so much for taking the time. Really appreciate it.
Ignacio Medrano
Thank you so much.
Brett
This episode of Category Visionaries is brought to you by Front Lines Media, Silicon Valley’s leading podcast production studio. If you’re a B2B Founder looking for help launching and growing your own podcast, visit frontlines.io Podcast and for the latest episode, search for Category Visioners on your podcast platform of choice. Thanks for listening and we’ll catch you on the next episode.
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