Clinical pilots will be conducted at university and private hospitals, with plans for nationwide implementation within four years, serving as a model for future applications in other diseases.

A critical focus is establishing a secure, ethical infrastructure for handling sensitive health data within Switzerland, ensuring patient privacy through anonymization and local processing.

Professor Gunnar Rätz from ETH Zurich highlights AI's potential to make data analysis more efficient and accurate, building on previous successes like the Tumor Profiler project that demonstrated detailed tumor characterization benefits.

Switzerland has launched NAIPO, a comprehensive national initiative leveraging AI to revolutionize cancer diagnosis and treatment, involving top institutions like ETH Zurich, EPFL, major hospitals, and industry partners.

NAIPO aims to develop a secure, AI-powered infrastructure that enhances precision oncology by integrating diverse data sources, improving diagnostics, personalizing treatments, and supporting clinical decision-making across the country.

A core element of the project is creating a federated, privacy-preserving system that enables collaboration among institutions without compromising patient data security, utilizing modern data governance frameworks.

The initiative seeks to rapidly incorporate the latest research findings into clinical practice by integrating various data types, including pathology images, genetic information, and biomarkers, to improve decision-making.

Patient engagement will be prioritized through the development of patient-centered solutions like a mobile app to enhance communication and active participation in care.

Funded partly by Innosuisse with over CHF 8 million, NAIPO involves a collaboration among Swiss universities, hospitals, data centers, and industry, with a total project cost of CHF 18.9 million, aiming for a nationwide rollout within four years.

The project focuses on interpreting large and diverse datasets to improve cancer therapy decisions, including pathology, genetic data, and biomarkers.

ETH Zurich researchers, led by experts like Julia Vogt and Niko Beerenwinkel, are developing advanced AI models, including language models, to analyze and relate different medical data types effectively.

Long-term goals of NAIPO include reducing healthcare disparities, accelerating biomarker discovery, and fostering sustainable innovation within Swiss healthcare.

AI technologies are expected to improve communication and efficiency in oncology, helping medical professionals manage information overload and make more accurate decisions.