Drug Repurposing Next-Gen: Interview with Pablo Perdomo (Technical University of Madrid)
Pablo Perdomo is a PhD researcher at the Technical University of Madrid (UPM). Originally from Gran Canaria, Pablo holds a degree in Biomedical Sciences from the Autonomous University of Barcelona and a master’s in Bioinformatics from Leiden University in The Netherlands. In this interview he talks about building a career as a data scientist, and shares an insight into his current role as a researcher at UPM, where he’s exploring the intersection of graphs, artificial intelligence and bioinformatics within REPO4EU.
From Biomedical Sciences to Bioinformatics
Hi Pablo! To start off, could you tell us what first inspired you to pursue a career in science?
When I started my bachelor’s in biomedical sciences, I was initially drawn to the biology side of things. But near the end of my degree, I took a bioinformatics course and found it fascinating, and I decided to focus on this field from that point on. I took additional courses in informatics and AI, and eventually found a master’s programme at Leiden University that perfectly matched my interests. My master’s thesis in the BioSemantics group introduced me to knowledge graphs and drug repurposing — the two main areas I continue to work on today at UPM.
What was it about artificial intelligence that caught your attention?
My uncle, who’s a university professor, introduced me to some of the early breakthroughs in AI — like AlphaGo and AlphaZero. Seeing how machines could outperform humans in complex games felt almost magical. That was when I realised how powerful and fast-moving this field was, and it really motivated me to pursue AI in a scientific context.
Given your interest in AI and computer science, what made you choose bioinformatics instead of going fully into computer science?
I didn’t want to completely abandon my background in biomedical sciences. Bioinformatics felt like the perfect bridge between the two worlds — technology and biology. My mother is a doctor, so I grew up surrounded by healthcare and with a strong sense of wanting to help people. That connection to medicine is something I wanted to preserve in my research.
Exploring knowledge graphs in drug repurposing
Let’s talk a bit about your current work. What questions are you trying to answer in your research?
At UPM, I’m focusing on AI techniques applied to knowledge graphs — data structures made up of nodes and edges that represent relationships, similar to a social network. In the context of REPO4EU, we use these graphs to connect genes, diseases and symptoms, allowing us to identify new drug candidates for existing diseases.
But I’m especially interested in explainability — not just generating predictions, but also understanding why a model suggests a certain drug. Providing explanations or hypotheses helps increase trust in AI-driven discoveries.
What was your first experience with drug repurposing research?
My first real contact with drug repurposing came during my master’s thesis at Leiden, where I worked on knowledge graphs for drug repurposing in the BioSemantics group. Before that, I didn’t know much about the field. But once I started, I was amazed by its potential to make a real difference in people’s lives. It’s incredibly rewarding to know that your work could eventually help patients.
The power of collaboration in evolving research fields
One of the core ideas behind REPO4EU is interdisciplinary collaboration. How has it been for you to work with experts from different fields like medicine, bioinformatics and computer science?
I really enjoy it. My background is in biomedical sciences, so working closely with people in medicine and biology gives me a sense of connection to where I started. At the same time, I get to apply advanced computer science tools to solve real biological problems. It’s the best of both worlds, and it keeps things exciting and meaningful.
You’re working at the intersection of two rapidly evolving fields: AI and drug repurposing. What excites you most about contributing to both?
It’s incredibly motivating to know that what I’m doing could have a direct impact on improving people’s lives. I feel very lucky to work on something that I love, while also knowing it serves a real purpose. That sense of usefulness keeps me going every day.
And on the flip side — what are some of the challenges you face in your work?
The biggest challenge is definitely keeping up with how fast the field is moving. What’s new today might be outdated in just a few months. You need to constantly read, learn and adapt. It can be exhausting, but it’s also inspiring — every new development sparks new ideas and possibilities.
Advice for young scientists and future researchers
What’s the main inspiration behind your work?
My parents have had a big influence on me. My mother is a doctor, and my father is a technology teacher — so I guess I’m the perfect mix of both! That combination of science and technology is my true passion and it’s what led me to bioinformatics and AI, as I said earlier, and that’s what continues to drive my research, really.
Finally, what advice would you give to young researchers who are just starting their journey in science?
Be curious! Explore different areas until you find something you’re truly passionate about. And make sure to surround yourself with a great research group. I’ve been really lucky in that sense — both the BioSemantics group in Leiden and my current group at UPM are full of amazing people, both professionally and personally. When you feel supported and motivated in your environment, your work improves naturally.
REPO4EU: The Podcast
Our podcast brings listeners closer to the latest innovations, research and developments happening in drug repurposing across the globe. The first season, ‘Drug Repurposing Next-Gen’, spotlights the work of PhD researchers, post-docs and young investigators involved in REPO4EU, exploring their role in the project as well as their career journeys. New episodes will be released monthly. Stay tuned for the next one!
