At the recent Neurons and Neckar event in Heidelberg, our CTO and
Co-Founder Dr. Christian Aichmueller explored one of the most pressing
questions in healthcare innovation:
What does it really take to make AI in oncology work; not just in
theory, but in the clinic?
His keynote challenged the common focus on algorithms in isolation, instead drawing attention to the real-world engine behind meaningful AI: high-quality, harmonized, and representative data that can be translated into usable, clinically integrated solutions.
Making AI Work Where It Matters Most
Christian walked the audience through PaiX, PAICON’s scalable and harmonized datalake built from cancer datasets across 60+ countries. He explained how diverse and well-curated data isn’t an end in itself but it’s the foundation that allows AI to perform reliably in clinical settings.
“AI that remains in the lab doesn’t change lives,” said Christian. “To make a real impact, models must be interpretable, trustworthy, and seamlessly integrated into how clinicians work.”
This principle guided his discussion on bridging the gap between development and deployment, highlighting how PAICON designs AI systems to enhance decision-making in hospitals and pathology labs around the world.
Turning AI Tools into Clinical Partners
One of the highlights of the talk was SatSight Dx, PAICON’s AI model for detecting microsatellite instability (MSI) in colorectal cancer. Rather than focusing solely on accuracy scores, Christian demonstrated how usability, interpretability, and integration are what transform an algorithm into a trusted clinical tool. By centering clinicians in the process, SatSight Dx exemplifies AI that works with healthcare professionals.
The presentation resonated with the audience, underscoring PAICON’s commitment to translating innovation into impact. By bridging the gap between data science and clinical practice, PAICON ensures that AI empowers clinicians, enhances diagnostic precision, and ultimately improves patient care.
