We are pleased to welcome Prof. Pierpaolo Sorrentino as a keynote speaker at DT4H 2026 in Strasbourg. A Principal Investigator at the Institut de Neurosciences des Systèmes, he brings clinical neurology and whole-brain computational modelling together to advance personalized medicine for neurodegenerative disease.
Prof. Sorrentino will present Towards Digital Twins in Neurodegeneration: From Brain Dynamics to Personalized Medicine.
Computational models are increasingly becoming mechanistic frameworks that link biological processes with clinical observations. In this talk, I will discuss how mechanistic whole-brain computational models can infer latent physiological alterations directly from electrophysiological recordings, providing quantitative biomarkers inaccessible to conventional analyses. Drawing on recent work, I will illustrate how personalized models might capture disease-specific alterations, for example in terms of neural excitability, conduction delays, or the effect of drugs, offering mechanistic explanations for clinical heterogeneity and disease progression. I will give examples for multiple diseases. Finally, I will discuss the emerging concept of the digital twin: individualized computational representations of patients that integrate multimodal data to improve prediction of clinically relevant features and ultimately enable precision neurology.
Pierpaolo Sorrentino, MD, PhD, is a Principal Investigator at the Institut de Neurosciences des Systèmes (Inserm and Aix-Marseille University, France). He is a board-certified neurologist and holds a Ph.D. in Engineering. He subsequently worked as a postdoctoral researcher within the Human Brain Project, where he developed computational approaches to investigate large-scale brain dynamics, with a focus on neurodegenerative diseases.
His research has made extensive use of magnetoencephalography (MEG) to characterize functional brain networks and identify electrophysiological biomarkers, specifically in the context of critical dynamics. More recently, his group has focused on mechanistic whole-brain modeling, integrating electrophysiology, neuroimaging, and network science to infer latent physiological mechanisms underlying neurological diseases.
His work has contributed to personalized computational models of Parkinson's disease, multiple sclerosis, amyotrophic lateral sclerosis, and other brain disorders, with the long-term goal of developing clinically actionable digital twins for diagnosis, prognosis, and treatment optimization. He has authored 200 peer-reviewed scientific publications.