ISPOR Europe 2019
2-6 November 2019
Copenhagen, Denmark
Speaker
Janick Weberpals, PhD
Instructor In Medicine, Associate Scientist in the Division of Pharmacoepidemiology and Pharmacoeconomics
Brigham and Women's Hospital and Harvard Medical School
Janick Weberpals, RPh, PhD, is an Instructor in Medicine at Harvard Medical School and Associate Scientist in the Division of Pharmacoepidemiology and Pharmacoeconomics at Brigham and Women’s Hospital.
His research interests focus on the comparative effectiveness and safety of cancer therapies and the development and application of novel methods to improve causal inference from highly integrated clinical data dimensions including electronic health records (EHR), images and unstructured notes. His most recent projects centered around missing data approaches in EHR, prognostics scores in oncology and applications of machine learning and deep learning networks (autoencoders) to improve confounding control in comparative effectiveness research. He has further conducted and published multiple studies on drug repurposing in oncology, time-dependent biases and long-term population level cancer survival using national and European cancer registries for which he received several awards including the Stephan-Weiland prize and the Advancement Award in Epidemiology by the German Association for Medical Informatics, Biometry and Epidemiology.
Dr. Weberpals holds a pharmacy degree from Philipps University Marburg, Germany, a board certification as specialized pharmacist in drug information and a Ph.D. in Epidemiology from the University of Heidelberg, Germany.
His research interests focus on the comparative effectiveness and safety of cancer therapies and the development and application of novel methods to improve causal inference from highly integrated clinical data dimensions including electronic health records (EHR), images and unstructured notes. His most recent projects centered around missing data approaches in EHR, prognostics scores in oncology and applications of machine learning and deep learning networks (autoencoders) to improve confounding control in comparative effectiveness research. He has further conducted and published multiple studies on drug repurposing in oncology, time-dependent biases and long-term population level cancer survival using national and European cancer registries for which he received several awards including the Stephan-Weiland prize and the Advancement Award in Epidemiology by the German Association for Medical Informatics, Biometry and Epidemiology.
Dr. Weberpals holds a pharmacy degree from Philipps University Marburg, Germany, a board certification as specialized pharmacist in drug information and a Ph.D. in Epidemiology from the University of Heidelberg, Germany.