National AI Initiative for Precision Oncology
NAIPO brings together hospitals, research and industry to advance AI-enabled precision oncology in Switzerland – from diagnostics and personalized treatment to clinical decision support.
Factsheet
- Schools involved School of Engineering and Computer Science
- Institute(s) Institut für Optimierung und Datenanalyse IODA
- Funding organisation Innosuisse
- Duration (planned) 01.04.2026 - 31.03.2030
- Head of project Prof. Dr. Murat Sariyar
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Project staff
Denis Sumin Moser
Marko Miletic -
Partner
EPFL (Leading House)
ETH Eidgenössische Technische Hochschule Zürich
Universität Basel
Université de Genève
Universität Zürich
FHNW Fachhochschule Nordwestschweiz
Universität Bern
Kantonsspital Baden AG
Insel Gruppe AG
Kantonsspital Aarau AG
Oncobit AG
Roche Diagnostics International Ltd.
Tune Insight SA
Debiopharm SA
LUKS Spitalbetriebe AG
HUG - Hopital Universitaire de Geneve
Navignostics AG
Hedera Dx SA
Hoffmann La Roche AG
Sawera Health Foundation
Swiss Medical Network SA
Sophia Genetics SA
Hirslanden La Colline Grangettes SA
Ente Ospedaliero Cantonale EOC
Kantonsspital Winterthur
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Situation
Cancer affects tens of thousands of people in Switzerland every year and poses major challenges for patients, families, and the healthcare system. Despite substantial progress, cancer diagnosis and treatment remain complex. Ineffective or insufficiently personalized treatments can increase the burden on patients and generate considerable healthcare costs. At the same time, cancer care produces large amounts of heterogeneous clinical, molecular, and imaging data whose potential for personalized decision-making is not yet fully exploited. The National AI Initiative for Precision Oncology (NAIPO) addresses this challenge by bringing together hospitals, research institutions, companies, and start-ups to develop and apply AI across the oncology care pathway. A common data foundation is combined with new AI methods and clinically suitable applications. Research includes AI agents to support clinical decisions, language models for analysing clinical records, foundation models for analysis and prediction, and privacy-preserving methods for handling sensitive health data. The initiative aims to enable more data-driven and personalized cancer care by integrating relevant information and making it more effectively available for diagnostics, treatment decisions, and subsequent care.
Course of action
NAIPO is an Innosuisse-funded Flagship project in which research, clinical, and industry partners jointly develop AI solutions for precision oncology. BFH is particularly involved in SP2 and SP6. In SP2, BFH supports the development of a multilingual clinical Large Language Model, focusing on data protection and de-identification of sensitive clinical data. In SP6, BFH contributes to a multilingual app for cancer patients, focusing on PROMs, secure data transfer, personalized nudging interventions, and the integration of the clinical language model to make medical information more accessible to patients.
