On 6 and 7 June, CERN hosted a first-of-its-kind workshop on big data in medicine. It concluded a two-year pilot investigation into how CERN-developed IT technologies and techniques could be used to address challenges faced in biomedicine. The workshop’s main goal was to establish terms for broader future collaboration with the medical and healthcare research communities.
In 2017, CERN adopted a specific knowledge-transfer strategy for medical applications with the aim of sharing knowledge and ideas of particle accelerators, detectors and computing with the medical and healthcare communities to identify relevant applications. Particle physics has pioneered large-scale, distributed, data-driven research models. Now that other scientific fields are collecting and processing ever more data, CERN technologies could help in facing the challenges with data infrastructures, computing technologies, and software applications.
This workshop brought together leaders from a variety of fields related to the application of big-data technologies and techniques in biomedicine, including the World Health Organization, the European Commission and a number of leading universities. Topics included personalised medicine, digital health ecosystems, blockchain, data handling and more. Discussions also focused on emerging technologies, such as machine learning and artificial intelligence (AI), as well as the ethics of these technologies — particularly when used in a biomedical context.
The discussions will serve as the basis for a white paper to be published later this year, setting out the main societal and economic challenges in medical research and healthcare systems, describing how collaborative platforms and big-data technologies can help addressing such challenges, and providing recommendations on how such multi-disciplinary efforts could be organised.