You’re currently working on an idea that uses Swarm Learning to make personalised medicine actionable right now, rather than decades down the line — could you start by briefly introducing yourself and telling us more about it?

My name is Lucas Secchim Ribeiro, I am an immunologist and data scientist working at the DZNE, in Bonn. Although Science moves forward at a steady pace, I am always looking for opportunities to give back to society a palpable return of their investment and trust. I have been a fundamental researcher for most of my career, but since I joined the Systems Medicine department, I have the chance to turn that wish into a reality.

Built for Some, Not for All

At the heart of your idea is a striking observation — that the same medical result can mean very different things for different people. What is the problem you’re setting out to solve?

If two different people do the same blood test, it is likely that they will have the same reference interval — or if not exactly the same, very close. I don’t want to change how things are measured; I just want to change how they are interpreted. If you measure a blood biomarker (for example, HDL cholesterol) in Germany, Japan, Brazil or South Africa, it should give exactly the same result. But what that result means to you might be different from what it means to me. You might be healthy and I might be sick, and we have the same laboratory value — and currently this heterogeneity between different people is not fully taken into account.

Part of the reason is that when we have these big cohorts and big studies done with subjects from the Global North, and these populations are not necessarily representative of the actual patients who are at the end of that workflow. And there is more to science than this. Many people want to explore human diversity, but when they try to be diverse, they face the impact of data privacy and are prohibited from moving forward. What our technology offers is exactly that: we can draw insights from different sources while keeping everything private and secure. We value the science behind it, we value the patient behind it, we value the privacy that protects it and we value the diversity that information brings — and everybody gets what they deserve.

Data That is Visited, but Never Leaves

You work with Swarm Learning, an approach that lets institutions learn from each other’s data without ever sharing it. What made this way of protecting data privacy so important to you?

Respecting the patients’ rights precedes the advent of data science itself, so guaranteeing that their data will be treated with professionalism is the only secure way to go. The Data Visiting principles of our Swarm Learning platform offer a solution towards more diverse and better-performing statistical models for biomedicine, while still consolidating the integrity of this mutual trust system between researchers, medical institutions and the patients.

Your interest in immunology and clinical biochemistry goes back to your time working inside hospital laboratories in Brazil. How did that early experience shape the direction your career has taken?

Walking the corridors of a university hospital as a laboratory intern created an immediate sense of responsibility and accountability about my work. Regardless of how much of my tasks would actually be used in the patients’ healthcare, it always felt like I was making a difference. That is the scaffold in which I built my career. I do not expect to create a single solution that will solve a major healthcare problem, but I see an immense value in the small pieces that, once put together, have a real impact.

When the World Chose One Target

You mentioned that during COVID, you realised how much data science could change the way you work as a scientist. What was that turning point like for you?

The SARS-CoV-2 pandemic evoked a situation rarely seen in academia: every biomedical scientist, regardless of their field, was trying to understand the disease and help to stop it. In a unique, natural move, the world defined COVID as a central target. With that, an incomparable amount of data was generated about a single disease in the most diverse lines of thought. Back then, I was only curious about data science as a scientific tool, but as I watched its true influence towards such a unified goal, I realized that I would need to incorporate that ability into my skill set to become the scientist I always wanted to be.

The Top-Talents-Track

What motivated you to join the Top-Talents-Track at this point in your journey?

My academic findings of the past years led me to explore a novel research field where I could apply my knowledge in clinical biochemistry and data science into a potential tool of immediate use for the medical community. However, being away from the innovation environment for so long led me to believe I was not ready for this journey. The Top-Talents-Track restored my faith in myself and in my concept.

Looking back at the different elements of the Top-Talents-Track: the training sessions, the peer exchange within your cohort, and the alumni contributions — what has been most valuable to you?

The training architecture was really well built and I feel truly integrated with the other members of my cohorts. I really appreciated the participation of alumni from previous cohorts and the open discussion with role models. Since the program provided a safe, free space for interaction, we could really understand the true and important obstacles ahead of us in the real market. Because all of them were raised in a similar academic environment, they could relate to our current struggles and share their solutions of how to overcome the current and future challenges we will face. No sugar-coating: a masterclass in balancing expectations and actionable solutions.

Impact Within a Lifetime

You spoke about wanting to see the impact of your work within your own lifetime, rather than decades from now — could you expand a bit on that?

Scientific progress is built layer by layer through the collective efforts of researchers around the world. Trustworthy science depends on rigorous, continuous investigation, replication and validation, but that is a process that naturally unfolds over a longer time. While this incremental approach is essential for generating reliable knowledge, opportunities to translate discoveries into innovations that extend beyond the traditional academic pathway are comparatively rare but crucial. They have the potential to accelerate the translation of scientific knowledge into tangible solutions and drive breakthroughs that create meaningful benefits for society within a much shorter timeframe.

Scaling Up the Concept

Where do things currently stand with turning your idea into something real, and what has that process taught you so far?

The product has shown very positive results within a small pilot study, for which the research and medical community already recognized the impact and the need for such a platform. Now it is time to scale up the concept to its true size towards a functional MVP. So far, I learned that trial and error is fundamental to the development of a truly deployable product and that can only be achieved if you have the support and feedback of a multidisciplinary and complementary team.

What advice would you give to other researchers who have an idea and are thinking about starting something of their own?

To thrive in such a world, despite their scientific prowess or rigor, one must always solve a real market problem. A gap or a need that only their knowledge can fulfil. For that, choosing the right team is fundamental, because the complementary skills of multiple people can rarely, if ever, be found in a single individual. Lastly but certainly not least, consider intellectual property protection and regulatory pathways as priorities from day zero: it will save you a lot of headache in the long run.

Is there anything else that feels particularly important to your story or perspective that we haven’t covered yet, but that you’d like to share?

Innovation, much like any academic endeavour, can be made of lots of failures that build your resilience towards a tiny sliver of success. If you believe in your idea, hang on to that spark of hope and do not let the disappointments dim your light.

What happens next?

Check out our event calendar(öffnet in einem neuen Fenster) for upcoming workshops. Stay tuned for more updates, opportunities, and success stories! Connect with Lucas(öffnet in einem neuen Fenster) via LinkedIn.
Find out more about the Top-Talents-Track here(öffnet in einem neuen Fenster).

Interviewer & Editor, Design: Laura Walther