Clalit Joins European AI Pandemic Research Consortium

Clalit Health Services has been selected as a partner in PANDAI (European Pandemics AI Observatory), an international research project funded under Horizon Europe - the European Union's flagship research and innovation programme - with approximately EUR 8 million. The initiative aims to build Europe's first AI-based platform for the early detection, prediction, and management of pandemics, connecting healthcare systems across Europe, according to the Jerusalem Post and The Jewish Chronicle.

Partners include the World Health Organization (WHO), the University of Oxford, and research organisations from the United Kingdom, Spain, Denmark, Luxembourg, and Bangladesh. Clalit, which provides healthcare for over 50% of the Israeli population and operates a network of hospitals and community clinics, was selected for its data resources, electronic medical records infrastructure, and COVID-19 research track record.

Prof. Eytan Wirtheim, CEO of Clalit Health Services, said: "In the post-COVID era, we must be prepared for the possibility of another major global health event. At a time when international collaboration faces increasing challenges, this achievement demonstrates that the knowledge, research, and innovation developed by Clalit and the Israeli healthcare system continue to play an important role in the global effort to shape the future of medicine."

Prof. Doron Netzer, Head of Medicine at Clalit's Community Division, said: "One of the world's leading research frameworks has recognised Clalit's research capabilities, expertise, and experience in operating a healthcare system during periods of uncertainty and global pandemics. The COVID-19 pandemic demonstrated that Israel's community healthcare system, with Clalit at its forefront, serves as a critical first line of defense against emerging health threats."

Projects linking multiple national healthcare systems require solutions for cross-jurisdictional data use - often federated learning, secure multiparty computation, or other privacy-preserving analytics. Meaningful outbreak-detection accuracy depends on timely, heterogeneous data streams (primary-care records, hospital admissions, laboratory tests, syndromic surveillance) and consistent metadata and coding standards across sites.

EU-backed efforts like PANDAI combine multilateral funding and public-health institutions to create shared tooling and datasets, which can increase statistical power for rare-event detection but also amplify regulatory and governance complexity. Israel's inclusion in a Horizon Europe project is noted by the Jerusalem Post as significant given domestic concerns about exclusion from international research frameworks. Clalit's COVID-19 vaccine studies were among the first large-scale real-world analyses published globally and influenced policies at WHO, the CDC, and the US FDA.

• •Whether PANDAI publishes technical specifications for data governance or platform architecture (federated vs. centralised).
• •Publication of datasets, model evaluation benchmarks, or open-source components that practitioners can reuse.
• •How the project addresses privacy-preserving validation and cross-border compliance, including any reference implementations or tooling.