Parallel session 10.00 - 12.00
Artificial Intelligence in medicine development - without the hot air
Please note: this session has been fully booked, it is no longer possible to register to attend this session.
Developments in Artificial Intelligence (AI) are seen as one of the drivers for a fourth industrial revolution, which will impact all human activities, including medicine development and health care. There are obvious benefits for patients (e.g. more data about the patient that can be assessed, freeing up time for health care professionals for human interaction and including the full body of medical knowledge to identify the optimal treatment for an individual patient). Furthermore, AI creates new opportunities in clinical development, such as defining inclusion/exclusion criteria, the assessment of clinical efficacy of new drugs and evaluation of (new) clinical endpoints using innovative data points. In addition, ‘regulatory intelligence’ might be a future AI application that helps regulatory bodies and healthcare providers to structure data streams and support complex regulatory decision making in the era of real-world data.
In this session we will dig into the true opportunities of AI for medicine development, with machine learning as a specific example of current use in clinical trials. Next, presentations from stakeholders in industry and regulatory bodies will set the scene for a healthy and realistic discussion about how AI can find its way into clinical trials and regulation.
- Prof. dr. Kit Roes, Professor of Biostatistics at Radboud University/Radboudumc, chair of the Methodology work group at the College ter Beoordeling van Geneesmiddelen (Medicines Evaluation Board), and a member of the Biostatistics Working Party at the European Medicines Agency
- Dr. Pawel Widera - Research Associate, Interdisciplinary Computing and Complex BioSystems group at Newcastle University, UK
- Prof. Bram van Ginneken - Professor of Medical Image Analysis at Radboud University Medical Center, the Netherlands; chair of the Diagnostic Image Analysis Group