Your Challenge:
Recoding Medicine
Hello, innovators! We need breakthrough innovations to unlock Europe's fragmented health data for AI and to prove its value through concrete medical applications. We need bold teams that turn untapped datasets into groundbreaking innovations for diagnostics, biomarkers, and therapies. We need you.
European hospitals, biobanks, and research institutions hold health data of exceptional depth — imaging archives, longitudinal cohort studies, multi-omics repositories, clinical registries. The raw material for AI-driven breakthroughs in medicine is already here. It remains largely untapped.
The central obstacles are easy access, curation, and the lack of structured collaboration between data holders and AI talent. Researchers with the right methods do not have the right data; institutions with valuable datasets lack the capacity and the incentive to make them available. Existing initiatives close only part of the gap. What is missing is an instrument that makes the creation and curation of high-quality, low-barrier health datasets, AI tools, and benchmarks its central goal — and demonstrates their economic value. This is where Recoding Medicine comes in.
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The Challenge: Curate a unique, high-value health dataset — and prove its worth through a concrete AI application with real clinical or commercial value.
Recoding Medicine unlocks new health data for AI innovation and proves its value through concrete applications. Each team curates at least one unique health dataset of high clinical or societal relevance, in line with applicable law. Building on it, each team demonstrates translational or commercial value through at least one concrete AI application — from biomarkers to diagnostics and clinical decision support to drug repurposing.
A substantial, documented public contribution is expected from each team; its form, layer, and access model are project-specific.
The responsible handling of sensitive health data and the safeguarding of data protection and data sovereignty are guiding principles for every project.
We support:
Potential breakthrough innovations
The challenge runs over three stages and 24 months. A jury of internationally recognized experts supports SPRIND in the selection. At a Pitch Day in early November 2026, the jury decides which of up to 13 teams start in Stage 1 (12 months); up to 7 continue to Stage 2 and up to 4 to Stage 3 (six months each). SPRIND provides up to €480,000 per team in Stage 1, up to €455,000 in Stage 2, and up to €550,000 in Stage 3 (in each case plus VAT, where applicable). Funding is awarded as pre-commercial procurement (PCP). The Challenge is funded by the Federal Ministry of Health (BMG).
Beyond funding, SPRIND supports teams throughout with technical, regulatory, and commercial coaching, opens access to cooperation partners and experts, and organizes Demo Days and match sessions with investors and industry partners. Where breakthrough-innovation potential is evident, further support after the challenge is possible.
JURY
Dr Claudia Fleischer is the General Manager of Roche Diagnostics GmbH since 2023. A pharmacist with a pharmaceutical chemistry PhD (LMU, 2000) and Cornell postdoc, she joined Roche in 2004, holding management roles across Europe. She serves on Fraunhofer, Stifterverband and Romius Foundation boards.
Dr. Rabab Nasrallah is Partner at Earlybird Venture Capital, with a Background in Developmental Biology and Embryology research. She holds board member seats in strong european scale ups and leads the Health Practice at earlybird.
Nathan Noiry is the Director of Data Science and Forward Deployed Engineering at Owkin, with a background in mathematics (PhD), machine learning research, and entrepreneurship. He leads multidisciplinary teams delivering and customizing AI and agentic AI products, combining deep scientific expertise with hands-on engineering execution.
Bettina Goerner is a Senior Advisor to healthtech and techbio companies, advising on health data, AI and regulatory compliance. She previously held data and AI roles at ETERNO, Centogene and Springer Nature.
Leah Morris is the Executive Director of Pillar VC and leads the Encode AI for Science Fellowship, supported by the UK’s Advanced Research and Invention Agency (ARIA).
PROF. DR. GEORG KAISSIS
Georg Kaissis is a full professor of Human-Centred Transformative AI at the Hasso Plattner Institute (HPI) in Potsdam and a Research Consultant at Google DeepMind.
Dr. Paul von Bünau is the Managing Director of idalab. A mathematician by training, he has spent more than a decade supporting numerous biotech, pharma and medtech companies on AI strategy and technology. Paul serves as a lecturer at the Europa-Universität Viadrina and loves to mentor nascent startups.
PROF. DR. CAROLIN VICTORIA SCHNEIDER
Prof. Dr. Carolin Victoria Schneider, one of Germany’s youngest professors, leads a pioneering research group integrating multi-omic data with population biostatistics and AI to advance precision diagnostics and targeted therapies for gastroenterological and metabolic diseases. She is affiliated with the German Cancer Research Center (DKFZ), the Else Kröner Fresenius Center for Digital Health (EKFZ), University Hospital Dresden (UKDD) and TU Dresden.
Leon Peshkin leads the Recoding Medicine Challenge. He worked as a Principal Research Scientist in Harvard Medical School's Department of Systems Biology for 20 years. Trained in AI (PhD, MIT, 2002), he applies machine learning to embryology, evolution and aging. He helped map embryonic development at single-cell resolution and champions radically open science. He also builds open platforms for aging research.
Kasia Stoltmann is a data and AI leader with over 18 years of experience across global technology, pharmaceutical and innovation organizations. As Head of Data Science & AI Solutions and founder of Women in Big Data Berlin, she combines expertise in data science, AI strategy and organizational transformation. She is passionate about responsible AI and diverse leadership.
Colin Hill is the CEO of Aitia and has 20 years of experience in healthcare technology, precision medicine, and the commercialisation of machine learning technologies in the biopharmaceutical and managed care industries.
Matchmaking Platform
You have access to valuable health data, but no specific AI expertise to work with it? Or you have AI expertise in healthcare, but need access to real-world data? The Foresight Institute is hosting a matchmaking platform bringing health data holders & AI talent together.
The Competition
Detailed information can be found in the call for submission and the participation agreement.
Webinar
Webinar 05.10.2026
FAQ
Do you have any questions about the challenge? Write to us at challenge@sprind.org.
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