Drylabz Selected to Join QAI Ventures Accelerator: Harnessing Quantum Technologies to Advance AI Diagnostics
We are proud that Drylabz has been selected to join QAI Ventures’ Batch III Accelerator Program—a leading initiative dedicated to supporting startups at the intersection of deep tech and quantum innovation. This marks an exciting new chapter to explore how quantum computing can power the next generation of diagnostic solutions.
Pioneering Healthtech Meets Quantum Innovation
QAI Ventures, based at the uptownBasel innovation campus, brings together a curated group of visionary founders whose startups are redefining the future of quantum computing, sensing, and communication. Drylabz joins this prestigious program alongside other ventures working on next-generation quantum technologies.
As part of Batch III, we will explore how quantum computing can accelerate the research and development of novel diagnostics algorithms—particularly for conditions where complex medical records and unstructured health data may hold untapped value.
“We’re honored to be part of QAI Ventures’ accelerator. For Drylabz, this is an opportunity to push the boundaries of what’s possible when machine learning meets quantum optimization—driving real-world impact in patient care,” said Norbert Farkas, CEO and Co-Founder of Drylabz.
“As a particle physicist who previously worked on the ATLAS experiment at CERN, I’m excited to apply novel computational strategies from the scientific frontier to real-world diagnostics. The QAI program gives us the ideal environment to experiment, iterate, and deliver value where it matters most—at the bedside,” said Martin Murin, Chief Science Officer, Co-Founder of Drylabz.
A Shared Vision for Precision Diagnostics
At Drylabz, our focus remains clear: turning unstructured patient data into precision diagnostics, so every patient gets the answers they need. Our recent collaboration with Basel University Hospital, supported by the Digital Health Nation Innovation Booster, has helped us better understand unmet clinical needs, navigate data integration challenges, and design solutions that are both technically robust and clinically relevant. With the support of QAI Ventures’ expert network, we are now building on this momentum—exploring hybrid quantum-classical models for feature selection, enhancing model explain ability, and accelerating clinical data analysis at scale.
