This online seminar is organised within the WideHealth project: https://widehealth.eu.
It will take place on Tuesday, 31.05.2022 at 12:00 CET.
The link to the meeting will be sent after you register for the event.

Title: StudyU: A platform for conducting digital N-of-1 trials that link personalized medicine and population health research

Short Bio: Stefan Konigorski, PhD, is a Senior Researcher in the Digital Health & Machine Learning chair at the Hasso Plattner Institute in Potsdam Germany, where he leads the Health Intervention Analytics lab. He is also Adjunct Assistant Professor in the Genetics and Genomic Sciences Department at the Icahn School of Medicine at Mount Sinai in New York. He develops statistical and machine learning methods to derive causal effects from complex observational and experimental studies, with a specific research focus on investigating personalized health trajectories and digital health interventions by using N-of-1 trials and adaptive trials.

Abstract: Traditionally, effect estimates of health interventions have been obtained from studies of large groups of individuals. However, the derived average effects do not allow meaningful insights on whether an intervention will help a given individual – which is at the center of personalized medicine. We have developed the StudyU platform (arxiv.org/abs/2012.14201) which allows to evaluate the effectiveness of health interventions on an individual level by digitally designing, publishing, and conducting so-called N-of-1 trials. In N-of-1 trials, every participant compares different health interventions of interest over time. The data generated from N-of-1 trials are hence single time series, usually within complex causal graphs, and the goal is to test interpretable effects of the interventions. The power of N-of-1 trials can be further enhanced by including sensor data to measure health outcomes. In this talk, I will introduce N-of-1 trials and the StudyU platform, present some of our work on the statistical methods for the analysis and discuss how the StudyU platform might be helpful in bridging individual-level and population-level studies by aggregating multiple N-of-1 trials.