Nives Rombini — AI, Drug Discovery & Building a Profitable Start-up

Adam Walker:I am Adam Walker, a biometrics consultant, and this is the Pharma Prescribed Podcast where leaders, innovators, and hidden voices in healthcare open up, no sound bites, no spin, just raw insight, one prescription at a time. In an industry driven by data protocols and pressure, we rarely pause to ask the human questions.

What drives us, what breaks us, and what truths live behind the titles we wear?

Adam Walker:Nives. Ramini is a scientist, data strategist and founder whose career bridges molecular biology, immunology, and advanced analytics. Nives leads Navis Bio, a venture dedicated to harnessing data-driven insights for biomedical innovation.

Her professional journey began with Swisscom, where she honed her skills in data engineering and AI applications before transitioning to the pharmaceutical sector. Fluent in German, \[00:01:00\] Italian English, and French. Ramini embodies a cosmopolitan perspective that enriches her scientific collaborations.

With a foundation in both lab research and computational analysis, she\'s recognized for her ability to connect disciplines, close evidence gaps, and inspire innovation at the intersection of biology and data science. Nive, it\'s a delight to welcome you today, pharma prescribed. For those of our audience who don\'t know you, who are you and what is the mission you\'ve been on?

Nives Rombini:Hi, Adam. Thank you so much for having me today. I\'m super excited about having this conversation.

Nives Rombini:And yeah, I\'m Neve my origin comes from Italy. I grew up in a small town in Italy at the beach front. Spending all my summer swimming and having a lot of fun. And my mom is actually Swiss.

From burn. This is why I grew up with these two cultures, very different cultures, the Swiss one and the Italian one. During growing \[00:02:00\] up I always had this very strong interest in science. And not only like biology, but really the broader science and the. Technology space, reason why I studied biology.

And then as you mentioned, I transitioned into the data science space to really combine these two disciplines, which I\'m always very fascinated by.

Nives Rombini:I worked in pharma as you mentioned, and today I did Nvis bio. We are a startup. We work on developing. AI tools and quantitative methods to combine these two disciplines of AI data science for the pharma space specifically, which is the industry we most care about.

Adam Walker:I agree. It\'s the industry I definitely most care about.

Adam Walker:Thank you for explaining that and presumably your multicultural, multi linguistic background has really enabled you to. See patterns and connect the dots around many other things that many of us don\'t see that are not by try multilingual.\[00:03:00\]

Nives Rombini:Yes I\'m convinced that actually the biggest power I think of growing up in these multicultural environments is much more the ability like to connect to people from different backgrounds and actually learning a lot from them. I often am like in front of people that have incredible stories to tell and a lot to explain me and teach me.

And I think this ability actually to connect to people and learn from them is immensely valuable. I think it\'s really mostly these interpersonal connections, which are super important. I think on the science side I probably don\'t see like a direct link of the intercultural and then moving this into science, but I think really on a personal level, like being able to learn and understand different backgrounds and be able to have the openness to learn from other people.

Adam Walker:Yeah I completely agree with you on that particular point.

Adam Walker:I\'m wondering what is it that got you into science in the first place?

Adam Walker:Going back to the earliest days of your childhood, was there something in you \[00:04:00\] that drove you towards that scientific specialty?

Nives Rombini:Yeah, I think I have a super strong memories of our Saturday nights in my house where my mom was always making homemade pizza.

And then we were watching this TV show is actually one of the most famous scientists for explaining like, science to the people. His name is Piero Angela, and then his son also took over the TV show. I think they had amazing impact on the Italian people for teaching and educating science.

So these are like the earliest moments of my love for science, like being in the family, eating pizza, watching these shows it was not only science, it was also like history, like Italian history, how. Cities were built and all of that. I think that is really where my fascination for science and broader knowledge, to be honest was born.

Adam Walker:That\'s a wonderful insight that you share there.

Adam Walker:Beyond your education, you\'ve obviously had a background from a number of different organizations. \[00:05:00\]

Adam Walker:I\'m sensing that something drove you to set up your own organization, Navis Bio, and I\'d love to know more about that if you would elaborate.

Nives Rombini:Yes. Yeah, I think I\'ve seen several organizations and I always loved working in all of them.

Learning from the people in the space and and really in both like at Swisscom, at BMS really being at the forefront of the innovation, developing new methods and all of that, which was great. I think I was also in a very privileged position at BMS to work with several scale up companies that were providing data to us.

And it was always like fascinating to see how they were moving, how fast they were. And it was like inspiring to see their work and I thought, okay, it would be nice to be on the other side of the table at some point. So that was a big motivation. And then the other really seeing the. Rise of ai, like the newest capabilities and thinking that the impact of this technology in pharma can be huge.

And I think it\'s in all organizations are working towards that technology, but I \[00:06:00\] think is at different speed. If you actually have a, like a small company, a small organization to drive the impact in the.

Adam Walker:It\'s a huge risk though, isn\'t it? You leave the confines of corporate world where you\'ve got a regular income and you have all the corporate entrapments that come alongside that, nice offices, holidays paid for, and you\'ve made an enormous jump into starting up your own company.

And like many people that I\'ve interviewed on the podcast. You appear to be the next generation of brilliant scientists coming into this industry who are pushing the boundaries of what\'s possible. I\'m wondering how you see that and what is the intention for Navis Bio in this space?

Nives Rombini:Yeah. Yeah. I think when we started, I saw much more the opportunity than the risk.

Like I have I think an intrinsic confidence that no matter what happens, I will get a job somehow. So I don\'t think I like over index on the risk side \[00:07:00\] of things. And something that I actually think some people underestimate is that there is also risk in staying in a position because sometimes maybe you get.

Too comfortable. And I always remind my manager actually at BMS she at some point, like it was a meeting and she told us that she\'s thinking about upgrading her mattress, but she\'s not a hundred percent sure if she should do it because otherwise she might get too comfortable and have.

Lower appetite for traveling at things like this. So I think I\'ve also been like embedded in a bit in an American team that has I think more like of a risk culture. So I think I didn\'t really see hugely the risk.

Nives Rombini:It was much more the opportunity and the chance to drive impact and this is what we want to do actually at Navis bio really being at the forefront of.

Using the technology like applied the ai, it\'s not really the basic research we do, but really the thinking about bridging AI and bringing it to pharma and I think there we are in a unique position to have \[00:08:00\] pharma experience to be actually able to make the bridge. I see brilliant people on the pharma side, brilliant people on the AI side, but I think there\'s still a lot to happen in bridging these two words and actually bringing them together.

And I think we were in a position to. Do that and be able to drive the change. So I think it, felt like a calling for us. We should do this.

Adam Walker:I think that\'s a compelling observation that you\'ve made there with regards to the risk and opportunity. Some people can see that comfortable chair as exactly that other people don\'t want the comfortable chair.

It\'s an interesting. Perspective as well as an independent consultant myself, I have to go out there and I have to find the work, and that\'s where this podcast was born from. Putting yourself out there, getting outside of the comfortable chair sometimes getting outside of your own way.

Yes. And putting your ego somewhere else, and then letting other people. Drive those opportunities, whatever that might be, so

Nives Rombini:yeah. Yeah, \[00:09:00\] absolutely. You are

Adam Walker:sharing, you\'re sharing an insight into a worthy and willing risk taker, but I\'m sensing that might well be within fairly strict confines with regards to, the kind of risks that you are willing to take in a business sense.

Nives Rombini:Yes. Yeah, absolutely. There are different type of risks you can take in life. And I think there are people that maybe on the sports side like do crazy mountaineering type of thing. I think there is some risk but it\'s still very limited if you look at the broader like life perspective.

I think it\'s actually, for me the biggest challenge was not so much on the risk side, but a bit on the comfort zone side. Not from a work perspective, but really, as you say, putting yourself out there. And being willing to be criticized or being willing to fail, to be honest.

Like we didn\'t know, starting out how this would look. Maybe we would be like one year with zero client or zero revenue or things that is, and being willing to say, okay, but at least I tried. So I think it, it was like mostly \[00:10:00\] that almost, yeah, that part, like the comfort zone about knowing that, I\'m doing a job that providing value and things like this.

And at some point being in a space where, no, you actually have to think hard. How can you bring value to other people? How yeah how can you really have a impact and go outside of your comfort zone in that sense.

Adam Walker:I think that was how I came to be aware of your work in Navis bio was recently I saw some clips and information you\'d put out on LinkedIn, and I\'m immediately peaked when I see people who appear to be doing something different.

I like to connect with people who are doing something different, who are swimming against the tide and not necessarily always staying in their lane. I\'d love to hear a little bit more about. Now this bio, how it started financially, what footing you are on. Because as we talked about risk, I\'m assuming this is something that you are \[00:11:00\] supporting yourself.

Do you have venture capital background?

Nives Rombini:How are

Adam Walker:you managing this?

Nives Rombini:Yeah, so we started the company with one target in mind. So we set ourself one year to see whether we could build something meaningful and then continue growing that. So we knew that we should be able to finance one year ourself to actually test out, I think sometimes.

It\'s more than just a couple of months. You really have to develop products to test them with clients. So that was the mark that we had, and that was like the financial risk that we could personally take to start the company. And it turned out that we were able to generate revenue early on.

With the products that we were developing. This is why now we are a profitable company. Thinking about the strategy for next year. We are still a small company, so see it\'s still the two founders. We have a lot of external support on accounting, on design, on all these other type of tasks.

So we are still very lean. But we were able to generate revenue with biotech and pharma clients early on which was great for us both to validate. The \[00:12:00\] market to validate the product, but then also to have, knowing that we were able actually to grow a meaningful business in that sense.

Nives Rombini:To share a little bit of the work that we do at nvis bio. The observation that we had from the industry. Was really that often there are important decisions that are taken in the r and d space. Questions like, which target you should go after if you have a specific platform technology platform to create drugs or biologics or yeah, any type of therapeutic.

So these are the big decisions. Other type of big decisions are once you have an asset in the preclinical space, thinking about the translation. Which are the indications you want to select and all those questions. And there is a huge cost of capital in pharma, which means. It\'s super expensive to develop these drugs, which means that if you can reduce any amount of time in taking these decisions, this is very valuable.

And people already have the pressure of taking the decisions in a short amount of time, but this means \[00:13:00\] that often they don\'t have the full like scientific and market context to actually take the best decision. So this is was the observation that we saw and then we had in the beginning of the company talking to a lot of people trying to figure out

where we can meaningfully have an impact in the space. So what we really do is to use ai. We develop AI and quantitative methods to process all this information that is out there in scientific literature, in conferences, in clinical trial registries, in patents. We structure it and then we apply quantitative methods to move from all this data to insights which our clients then use to take these strategic r and d decisions.

Adam Walker:Gosh, that sounds very impressive and very detailed, and I\'m wondering how you woke up one morning and thought that\'s the thing that I\'m going to be doing. Because what you\'ve described there are, some very complex ideas and pharma companies and biotechs are by their very nature, as I\'ve mentioned many \[00:14:00\] times before, they\'re conservative.

They don\'t like to take risk. Tell me, do you embed yourself within those organizations or do they just open the hood and just say, look, have a look at what we\'ve got and help yourself and tell us if it\'s gonna work or where we ought to be. Focusing our attention around those key decisions with regards to therapeutic area and those quantitative methods that you talked about.

Nives Rombini:Yes. I think we were of course, very aware of the fact that these companies like pharma is a conservative industry for good reasons. There is a lot at stake. I understand the attitude and we knew. Debt. This is why I think we were very strategic in the beginning, thinking about how to bring value early on from publicly available information.

This is where really where we started. For some companies. We also integrate internal data. For others we don\'t. It\'s purely based on publicly available information. But I think what we observed in our work, like previous work before starting the company, is that there is huge invest. That go into generating new biological insights.

It can be in the preclinical \[00:15:00\] space, but in the end, even the early clinical trials, it\'s still generating new biological insights. But you don\'t work as an organization in isolation, which means you always need to contextualize what you find within the broader scientific like evidence from the scientific community.

And that process was actually still very much manual. I\'ve been in plenty of conversations, people thinking about new targets that they found and then not knowing, has anyone worked on this in the past? Have there been any failures with this competitive landscape? And of course you can hire. MBB companies, like big consulting companies doing the work, but typically it\'s not the budget you have available early on when you take these decisions also for biotechs, it\'s not the same type of budgets they have.

So I think it was really that space, identifying that space, contextualizing the information that you can generate internally within the broader scientific and market context. And this is where we started, and this is where we realized that there is a strong need for the \[00:16:00\] type of work that we do.

Adam Walker:Yeah, I really hadn\'t thought of it that way. And as you\'re describing that I was thinking, I\'d love to understand how you translate those insights. And really, we\'re talking about broad data sets, large language models as well, I think. But correct me if I\'m wrong, how does that translate into a business offering and something tangible?

Because if I\'m a biotech, I\'d love you to. Tell me how you sell that service to me, because as you are speaking, I\'m thinking, I think I need that, but I need to understand why and how I need that and how that will work for me.

Nives Rombini:Yes, absolutely. It really depends on which is the question you have, like if it\'s about assessing targets or even identifying targets that would be a good fit for your platform, I think it\'s helpful to understand what\'s the typical process.

And the typical process is companies going to conferences, reading literature. Going into patent \[00:17:00\] repositories and reading all of these and doing all of these manually to actually find new targets that are maybe a fit for the platform that they have. Let\'s say they want to develop very specific small molecules.

Then you want to maybe go for targets that are already validated or have some sort of clinical validation. Maybe you want to have targets that have been described in the literature. Like there are several things that you do manually to actually find good fits for the platform that you develop, for example,

instead of doing this manually, we can do it with the support of ai. It\'s always with human in the loop because I don\'t think AI is there to really substitute this type of work yet, but we can use it as a tool and the way we do it is that we discuss together with our clients what are the priorities that they have.

If it\'s targets, then we discuss a lot the platform, if it\'s indications they are looking at, then we discuss a lot the asset. And the priorities for that asset. And then we have all these data bases and data sources \[00:18:00\] that are integrated in a data lake that we built and that we own which has all this information.

And we start the search with keywords that we define. And then we do a lot of classifications things like, maybe you care about the glycosylation status of a protein. So you have AI agents that actually goes find this information and then capture that, and then we structure all these data in that way.

So I would say the first part is the search part. The second part is really having. Aggregation and the augmentation. So maybe it\'s information that is not readily available in a document, but we go find other documents that can complement that. And then the last part is really building analytics on top.

So for example, if you have an asset and you\'re thinking about indications, it\'s different. If you have one paper saying this mechanism of action is linked. To Alzheimer\'s disease or if you have 20 evidence. And then there\'s also a difference whether this is a case report or if it\'s a randomized clinical trial.

So we do a lot of analytics to actually then \[00:19:00\] move to this data that we collected and structured to the insights, which is. Quantitative methods to say what is in terms of data the best strategy moving forward. And our users then log into a web application where all the data is being tracked and available with all the traces that we use.

And then they can also have some parameters they play around for the final decision. In the end, the strategy is still on them, but we provide the full landscape of information to guide that strategy.

Adam Walker:Thank you for explaining. That makes clear sense to me now, so I have an understanding that where you are starting from your starting point is the building of the data lake.

Nives Rombini:Yes.

Adam Walker:All the way through to the keywords, the analytics, the structure, and the ultimate insights.

Adam Walker:Can we talk about the human in the loop? Because you referenced the fact that. Human in the loop is so important. Everyone talks about human in the loop in these conversations. We\'re always talking about \[00:20:00\] human in the loop at various conferences.

Recently I\'ve been to, we reassure ourselves that we are the humans in the loop and that we\'ll still have a job tomorrow. But I\'m wondering if those what those human Ute roles are and what specialty and capabilities those individuals have because. Not only do our audience want to understand the now, but they want to know.

Particularly the younger generations want to know what that future facing role might look like as a human in the loop. Can you just elaborate on that particular point, if you wouldn\'t mind?

Nives Rombini:Yes, absolutely. I always make the example, if you go into charge G PT and ask what are the indications I should go after with this asset?

You wouldn\'t get valuable information because that is actually the representation of a probabilistic like distribution and then ai. Sourcing from this distribution and giving the answer. And of course AI in like in tools like T and others also can do a quick web search. This is why sometimes you have \[00:21:00\] still some references to web pages and things like this, but this is very superficial, which means it\'s not really at the point that it can provide value for strategic decisions in biotech and pharma.

So this is the way when you use a tool that is purely based on AI would do, when we talk about human in the loop is sitting down with our clients and then discussing what are the data sources you care about? What are the parameters that you care about? Maybe if it\'s pharma, they already have a distribution network, they have.

Key opinion leaders they work with. There are other elements that come to the strategy that is not simply what is, out there. So it\'s building these other priorities into the overall strategy. And then very practically in terms of human in the loop, it\'s actually me annotating this dataset where we like extract mechanism of action.

For example, I have a notated like almost. Thousand rows. This is something I do even, annotating 30 additional rows or things like this where maybe you have an abstract on an asset. And then in the abstract \[00:22:00\] it\'s described what is the target of that asset. For example, you have a protein degrader.

This is specific for a kras G 12 D molecule, it\'s doing these extraction manually, and then we can always run models to actually verify how well we are at extracting mechanism of action or indications and things like this. So in terms of expertise, I\'m actually not scared at all about ai replacing humans

I think it\'s a tool like any other tools, and I think it\'s important to be able to use it. But there is still plenty of opportunity to provide value as a human based on the experience we have, the knowledge we have. I think we should always stay curious and continuous learning. But I like, I see it as a tool and I honestly also see how often it fails.

Reason why, like we are not able to provide like off the shelf a solution yet because it fails often and we need to be in the loop to actually make sure it goes right. So someone needs to know what is right. So I still see a lot of value in actually having that expertise.

Adam Walker:Thank you for \[00:23:00\] explaining that.

And I think that not only gives me plenty of confidence, but actually when I think about some of the roles and responsibilities I\'ve had in the past that compliment those types of activities, it would be like, I don\'t know, reviewing medical dictionary, coding terms, for example, that huge funnel collecting data in, and also teaching and training those models that then the next time they see them.

They identify them immediately and it becomes a lighter and lighter touch as you take a step back, doesn\'t it? That sounds like what you are, explaining and describing there.

Adam Walker:What is your perspective with regards to the translation of these large language models into everyday pilots now?

Because much the same as a few years ago when we went through the pandemic, everyone became a. Epidemiologist and everyone knew the expert language. I\'m just wondering how you see this one \[00:24:00\] playing out for ai, but particularly and pertinent to the pharmaceutical industry. Biotech companies and the support services, I\'d love to know your perspective on how that might play out.

Nives Rombini:Yes. For me, when we talk about ai, there are always the difference between who is actually developing the. Models around that. Like people at philanthropic, at open ai at universities, developing that that technology. And I think there you would really have a much, much deeper understanding of what is going on.

Of course, and this is not where we play, like we play in the applied ai. Space where you use the models or the technology that someone created and are thinking, how can you apply it? And my co-founder, he has a PhD in machine learning, so of course he also understands the mathematics behind it. But we are still working on a applied AI side.

And I think actually the fact that the technology has been distributed so widely through these like consumer tools is a massive plus for us because people. Have like more experience with that. \[00:25:00\] They know topics around probabilistic distributions, about not like non-determinism, about hallucinations and all of that, which makes our life easier.

But I think that the challenge there is that this is the only experience and large language models can do much more than what we experienced through charge GBTA reason why, like we need to do that. Second part of this this process explaining how you can actually run these models at scale and having much more engineering work to actually make them work in the real life.

And I think everyone uses ity to write email and I think there are just huge productivity gains across the board. But I think to really embed them into. Corporate or even just B2B type of workflows. I think the biggest lift is on the engineering side, so really making sure that we are applying these methods and bringing them to have an valuable output for our clients.

So I think the biggest lift is actually the engineering side there.

Adam Walker:I \[00:26:00\] appreciate you explaining that. I\'m just wondering if anyone\'s listening to this and they\'re hearing you speak about this with such. Enthusiasm and knowledge and understanding. You are brilliant. Your brain is brilliant and clearly your co-founder are brilliant people.

You understand your field intuitively as much as educationally. If someone came to you and said, look, you are that good. Can you clone yourself? I want 10 vees in my company. How? How do you do that? How would you do that? And could you do that if you had to scale? Because you said you\'re a startup, you\'re in the earliest stages.

But if you thought that far ahead, because as you are talking in describing what you\'re doing right now. If I\'m a biotech or a pharma company, like I said, I want your level of engagement with my company, and with my new molecules.

Nives Rombini:Yes. I think the biggest the biggest impact you can have as an organization is \[00:27:00\] actually allowing your people to experiment with these tools.

And I think from the people side to be. Willing to experiment. Like for me, like my training from the university is in biology and immunology, and it was myself like learning how to code in R and if I look at the scripts I wrote seven years ago, I would try because they are very bad. But I think it\'s a start, right?

It\'s a start. And I think it\'s the exact same. Work with ai, I think it\'s trying to understand what\'s behind and maybe trying to build something. I\'m not such a big fan of reading a lot about things because I think in this space you actually need to build the prototypes and you can do it quickly.

But I think that is really where we have the biggest understanding of the technology is more working on that. Like so many people talk about AI agents. And I think like very few people actually built a prototype in that space. So I think building and having the willingness to experiment and on the organization side being willing to have your people \[00:28:00\] experiment, things like having these Friday afternoon projects.

I think there\'s still a responsibility from an organization perspective as well to have some room for people to experiment new things. I think especially in our industry, that is really critical.

Adam Walker:I, I agree. And as you were explaining that, I was thinking about hackathons Friday afternoon hackathons.

The fact that you\'ve done so much programming in our speaks volumes. I think to that particular point, most new programmers and data scientists coming into pharma industry now are very adept to our, historically, we use SAS a lot. But are, and shiny and Python appear to be the programming languages that are driving the future, facing where the industry is going.

Are they not?

Nives Rombini:Yes, totally. I believe even like now with the coding assistance, they actually perform even much better in Python because there is a much more distribution of data. So that is, I think, also something that organizations should think about. Like \[00:29:00\] historically in bio. Stats, as you said, it\'ll sas and then in the research space, very often using R, but now when you use coding assistance, you are so much better using Python because there\'s much more data available.

I think these are like considerations you should take as an organization. This is why like for example, we don\'t do anything in R. Like everything. What we built is in Python because the coding assistance just performs so much better.

Adam Walker:There you go. That was the nugget of excellence I was hoping for, but thank you for explaining that as well.

Adam Walker:I\'m just wondering over the last year or two, what you\'ve learned about yourself throughout this whole journey of discovery. Discovering what the industry is needing alongside the technology as it\'s advancing at such pace and supporting your activities in Navis bio into the future world.

Nives Rombini:You mean on a personal level, right? Yes. Yeah. Yeah. I think the biggest learning for me is that it\'s okay to be intense because I\'m a \[00:30:00\] very intense person. I am very passionate about the work that we do and about the impact we can have. And I think in maybe in other settings, I was maybe too enthusiastic, too intense.

And now I learn, okay, it\'s. Totally fine and people actually feel also energized and these drugs, positive outcomes. So I think that was like a big learning for me, saying, okay, yeah, it\'s okay to be intense. You can be very enthusiastic about what you\'re doing and that\'s totally fine.

Adam Walker:I agree.

And to give you a further compliment to that, I have recently interviewed a couple of other founders of companies in this space, and they have an equal. Level of energy and enthusiasm for their topic. As much as it\'s very evident in the words that you use in the energy around which you describe those things, that this is your passion and this is your world.

And I think that translates really well when people are listening back to this as well. There is a drive and a determination that comes through in \[00:31:00\] everything that you\'re describing. As I say, I\'m trying to simplify the complex for a very broad audience because of course, we don\'t all come at this with PhDs in mathematical modeling and machine learning.

Yeah. I\'m a humble pharmaceutical scientists and I\'ve learned along the way, but I\'m certainly in a very different sphere of understanding than yourself. Except to say I\'m trying to learn as quickly as I possibly can. And I think many of us are trying to learn and acquire this knowledge and these skills.

So that we can translate where we are today in pharma and biotech. Into something that is going to support the future of pharma and biotech. Yeah. In the next 10, 15, 20 years, whatever on earth that looks like because things are moving at such a pace or they\'re not.

Nives Rombini:Yes, absolutely. And I think something that is also super valuable is to be.

Around people that are really the first at trying out new things. And I wish I would be that, I think I\'m the like second or \[00:32:00\] third degree, when new things come up. There\'s typically someone that tells you, ah, have you looked at this? Have a look, and things like this. But I\'m like, with my co-founder and other people in my network.

These are the people that as soon as something is out, they are testing it, they are trying it, and then they can report back to me and say, okay, this is crap, or this is amazing.

Nives Rombini:I\'m always thinking about this MCP like it\'s a new it\'s an integration for large language models to integrate with databases.

So you can ask questions in natural language. This gets then run into. SQL code that is executing on top of databases. And this was released in November last year, so one year ago now. And I remember I received an email from Anthropic, the newsletter saying, oh, we have this MCP out.

And I told my co-founder have you seen it? Have you tried it? And he sent me that day, a repository where we had already integrated MCP with the clinical trial database. By an FDA \[00:33:00\] organization and he had already tried that and used it, and I think this is where you have the value of people testing things super fast.

Adam Walker:So I have to ask you, I don\'t know what MCP stands for. Could you just elaborate on that, if you wouldn\'t mind?

Nives Rombini:Yes. It\'s the model context protocol is this protocol that allows you, again, to integrate large language models with databases. So it\'s a, actually a simple context, but I think it\'s a very powerful.

And again the biggest power is that you can, for example, have all these MCP servers on your anthropic subscription. And then these are connected to databases. So you can ask questions in natural language, and the answer is not based on the distribution of knowledge that the AI model has, but it\'s actually based on real data that is sitting into databases.

Adam Walker:Gosh, that\'s incredibly powerful. Thank you for elaborating that. You\'ve really. My mind thinking and worrying at the moment. There\'s so much that I\'d like to dig into, but actually I \[00:34:00\] want to leave that out there for our audience to give a little bit of thought to what might be coming next.

Adam Walker:So at this point in the conversation, I like to conclude with a quick fire round. That\'s awesome. And I wonder, you may have alluded to it earlier, but what is the one piece of advice you would give to your younger self?

Nives Rombini:Yeah, I think this is linked to the learning probably, and that is about it\'s okay to be intense in the end if you extrapolate it\'s okay to be yourself, and forbid it\'s probably intensity.

So that is the advice I would give my younger self.

Adam Walker:I don\'t think there\'s a problem with that at all. And I would say the same to any young person. Actually just be true to yourself. I say the same to my now adult kids. If you turn up and show up as your true self, you don\'t have to remind yourself what you pretended to be.

You\'re just true. Your personal professional, they\'re side by side. I think that fits perfectly. What are the top \[00:35:00\] three qualities you value most when building a team?

Nives Rombini:Yeah. I think the top one by far, the top one is scientific, scientific approach to things which might sound a little bit vague, but I can explain a bit more what I think.

I think like in the work that we do, the most important thing is to be truth seeking, which means you should have the behavior of actually looking for the truth and being able also, if you do mistakes, to say this is a mistake, and not to concede it, saying, ah, yeah, that\'s a other point of looking at it.

No, you can do mistakes. This, I think is like the truth seeking behavior are really being scientific about the work that you do, I think is like the most important thing. So that is the first one. The second one is probably still being kind, which I think it\'s like very important to, be truth seeking and to tell this is wrong and be clear about things.

But I, I think it should always come from a. Place of being kind to each other because in the end, you still want to have \[00:36:00\] fun, and to build something. And there\'s no reason why, you should not be kind actually to people. So that is, is the second one. And then the third the third is probably being a little bit risk.

Taking, I think it\'s important in anything that you do, being willing to take some risk because I think we often are too risk averse. I think especially like in the culture I\'m embedded within like also the Swiss culture, I find it quite risk averse. So I think being willing to take some risk because you can have outside return for that.

Adam Walker:I appreciate you sharing that. That\'s very kind of you. What is your favorite thing or activity outside of work?

Nives Rombini:Yeah, so I\'m half Italian again, so it\'s definitely family spending time with my family all. I have three siblings, all of them have kids now. And I just love playing with them and seeing them grow and listening to the questions they have and just spending time with my families.

Absolute top of the list.

Adam Walker:So you are one of four. Your parents must have been very busy. Yes. And you must have \[00:37:00\] had a very busy household, I\'m gathering when you grew up.

Nives Rombini:Yes, exactly. I was the youngest kid. You have to learn to defend your chocolate and your space. And yeah. I remember at some point we had a fight in the family about who could decide which show to watching TV and.

I wanted to like, cover the tv, to, to show power. And it even fell so I even broke a TV to try to, conquer my space in the family. I think that was still amazing. I\'ve had an amazing childhood yeah, that was great.

Adam Walker:I think even now you\'re pushing the boundaries.

Adam Walker:And finally, what is your number one golden rule in life and in business?

Nives.

Nives Rombini:Yeah. It\'s a sentence that my dad always told me. I say it in Italian because it sounds beautiful first. It\'s, which means you should take every situation like heads on. And this was all his advice in every situation. If you are scared, if you made a mistake if you want to do something, like just go heads on and do it.

And this \[00:38:00\] was the version that was coming from my. Father, he was a super charismatic person. And then the version that my grandfather, the Swiss one actually told me always is when we were like preparing apples to do like apple juice. He was always telling me if an apple has like an something, that is rotten or an edge or something like this, you should always cut through that first because this is the way, like you maximize the good part of the apples.

And I always think about, cutting the apple where the problem is because then you can maximize the rest. It\'s like stranger associations, but these are learnings I have in my life,

Adam Walker:wow, that\'s wonderful. I think that gives us a really rich idea of what you learned from your family as much as what you\'ve taken forward in your professional and working life.

Adam Walker:This has been a wonderful conversation, Yves, where you\'ve shared not just your. Background and your understanding and how you came into this industry, but indeed why you are at the forefront of making the change and challenging the status quos that we have in our \[00:39:00\] industry. As we\'ve said, it\'s very conservative, it\'s very risk averse, and people like you drive change through what they\'re doing by making.

Change through taking chances. Ultimately, you\'re taking a chance and I think you deserve enormous plaudits for that as much as sharing your truth and what brings you here today, and it\'s been an absolute delight to welcome you to Pharma Prescribed. I\'ve learned a lot and I hope to continue learning from you and the content that you put out there.

Thank you so much for coming on the podcast today. It\'s been just an absolute pleasure to get to know you.

Nives Rombini:Thanks so much, Adam. It was my pleasure. Really enjoyed all your questions , and this conversation.