Felix Faber is an award-winning entrepreneur and computer scientist with a track record of founding companies that to date have generated over $350 million in revenue. In 2008, he founded the online games company Bytro Labs, which he took public to Nasdaq Sweden in 2015 as part of Stillfront Group. He also gained first-hand experience of the Silicon Valley ecosystem during his time with the German Accelerator. Earlier in his career, Faber twice became a world champion in robotic soccer as part of the University of Freiburg team, showcasing his passion for pushing the boundaries of AI. His diverse industry background gives Faber a unique edge in healthcare, allowing him to bring fresh perspective and innovation to AI applications in the sector.

What is your background prior to this role and how did it prepare you for the work you do now? From an early stage, I’ve been driven by the possibilities of artificial intelligence (AI). The lessons I have learnt have helped me immensely on my current journey to improve patient care. Technical systems need to work 24/7 as patients rely on them, the AI needs to be world-class, regulatory processes need to be in place without slowing operations down, and scientific evidence needs to be sound. A combination of technical excellence, entrepreneurial grit, and business leadership uniquely prepared me to co-found and lead Mindpeak. At the crossroads of AI, pharma, and precision medicine, I see not just an opportunity, but a responsibility to shape the future of diagnostics and deliver meaningful impact for patients worldwide.

What are some of the biggest ongoing challenges in your work? I see challenges as part of the job - they force you to rethink, adapt, and ultimately get better. That’s true for me personally and for Mindpeak. Every obstacle has pushed us to sharpen our approach and build a stronger foundation for the future. Right now, three areas stand out as the most significant challenges, prevalent across the space. The first is bridging translational research and clinical application. It’s one thing to generate promising biomarker insights in the lab, but quite another to make sure those insights are robust and reproducible for applicable use.

The second is navigating diverse global regulatory frameworks for companion diagnostics and digital pathology. These frameworks have become more robust in recent years, which of course brings complexity.

Finally, there is the challenge of scaling adoption in what is naturally a conservative clinical environment. Building trust in AI takes time, consistency, and real-world evidence. It’s about proving, case by case, that AI can be a reliable partner to pathologists, helping them work more efficiently and with greater accuracy.

What is your personal mission statement? What values keep you centred in your work? I was misdiagnosed with a severe illness nine years ago. It took me years of research and persistence to receive the appropriate treatment and this marked a significant turning point in my life. The idea grew in my mind that AI should be able to support experts when challenging diagnoses arise. Since then, my personal mission has been to deliver accurate and accessible diagnostics to everyone, everywhere. I see this not just as a professional ambition, but as a responsibility; the sooner a patient receives an accurate diagnosis, the sooner they can access life-saving treatment.

What are your biggest short-term goals for this year and next year? One of our proudest milestones this year was the opening of our Boston US office in August. Being at the heart of the US biotech, pharma, and life sciences industry allows us to be closer to our customers and to embed ourselves in the oncology R&D hubs where collaboration and innovation thrive. In the short term, our goals are clear. The expansion of our offering to the US means the building of our presence in North America so that we can strengthen biomarker discovery, refine companion diagnostics, and deliver reliable, high-quality insights that get the right treatment to the right patient faster and more efficiently.

What do you see as the biggest challenges facing the industry right now? The life sciences industry is at a pivotal moment. On the one hand, there has never been more opportunity to transform cancer care through precision medicine. On the other hand, the challenges we face are becoming increasingly complex and require new ways of thinking.

One of the most pressing challenges is the growing complexity of tissue biomarkers; a large number of the currently developed ADCs and IO drugs depend on these. Pharma companies are under pressure to stratify patients more effectively so that the clinical trial succeeds. AI can play a crucial role in detecting relevant features to find the responders and non-responders in a trial, as it has been shown by Günther Schmitt and AstraZeneca with their QCS score.

What excites you most about current industry trends? What excites me most right now, both as CEO of Mindpeak and as someone deeply invested in the future of healthcare, is the way the industry is truly embracing digital pathology and AI as operational, not optional. For a long time, many of us working in this space have been convinced that these technologies represent the future of medicine. To now see this conviction mirrored so clearly across the pharma landscape is incredibly rewarding. It signals not just acceptance of AI, but integration — a recognition that it is becoming a core part of how oncology research and development is delivered at scale.

In your opinion what has changed most about the industry since the start of your career? Digital workflows have moved from being optional to foundational. The widespread adoption of digital pathology and related technologies is not simply about improving efficiency; it is about enabling scale, reproducibility, and international collaboration. This digitisation has created the infrastructure needed to support the globalisation of trials, multi-centre studies, and large-scale AI training that simply would not have been possible a decade ago.

Pharma has also made extraordinary progress in biomarker discovery and targeted therapies, which has fundamentally transformed oncology and precision medicine.

Yet, one of the persistent challenges is that these advances too often remain confined to silos. Pharma R&D, diagnostics, and clinical labs frequently operate in parallel, rather than in concert, slowing the translation of innovation into real-world clinical practice. Overcoming these barriers is critical if the industry is to sustain momentum and deliver innovation at both speed and scale.

What do you think pharma will look like in 15 years? 50 years? Looking ahead 15 years, I believe we will see full integration of AI across the entire continuum, from early-stage drug discovery through to diagnostics and clinical decision-making. AI will no longer be viewed as a separate capability, but as an embedded layer that underpins every stage of R&D and patient care. This will make drug development more efficient, diagnostics more accurate, and treatment pathways more personalised.

Within oncology specifically, I expect companion diagnostics programmes to become the standard. In fact, I believe this shift will come well before the 15-year mark.

And looking further ahead — 50 years into the future — I see a world in which compounds will be simulated and completely developed by AI. Cancer patients will get a very detailed, multi-omics diagnosis from an automated AI system.

How do you think AI will transform pharma/healthcare? AI will transform pharma and healthcare in ways we are only beginning to imagine. In the coming years, it will become the operating system of healthcare, running quietly in the background, but shaping every decision from trial design to bedside, uniting discovery, development, diagnostics, and delivery of care.

Most importantly, AI will not be a replacement for human expertise but an amplification. AI will manage the complexity of data so that HCPs, scientists, and pathologists can focus their judgment where it matters most: patients. This shift will redefine the role of HCPs, freeing them from routine tasks and enabling them to act as interpreters, decision-makers, and compassionate caregivers supported by AI.

What problem are you most passionate about solving? As mentioned in the beginning, I am most passionate about solving the persistent gap in cancer diagnostics. Across healthcare systems worldwide, inconsistencies remain one of the most significant barriers to effective treatment. Too many patients are receiving suboptimal diagnosis, resulting in suboptimal outcomes.

If you could have any job other than the one you have now, what would you choose? At heart, I’ve always been driven by curiosity and fascinated by uncovering hidden connections and solving complex puzzles. I’ve always had that instinct to ask “why” and “how” until I get to the root of the matter. In many ways, I’m a natural investigator, always chasing mysteries and trying to understand how things truly work. If I weren’t leading Mindpeak, I could easily imagine myself as a detective, a secret agent, or even an explorer searching for hidden patterns in places others might overlook.

What is your personal or professional biggest achievement to date? My biggest achievement to date is that over 50,000 patients have already been diagnosed with the help of the Mindpeak AI. These are real people out there that are desperately waiting for their diagnosis – patients who rely on and trust doctors and the health system to find the right diagnosis and the right treatment. We hope to have given those 50,000 patients a better diagnosis with the help of an artificial neural network computer system that we developed.

Connect with Felix Faber on LinkedIn.

This content was originally published on pharmaphorum. Reprinted with permission. Please access the full article here.

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