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Lovisa Afzelius

Head of Computational Precision Medicine Senior Di
Clinical Sciences
Pfizer
Saudi Arabia

Biography

Lovisa Afzelius, PhD, is Head of Computational Precision Medicine for the Inflammation & Immunology Research Unit. The goal of the Computational Precision Medicine group is to leverage clinical biomarker information to enable data driven decision making related to target validation, patient stratification, indication expansion and combination rationale. In addition, the Inflammation & immunology research unit aims to provide disease relevant baseline data to project teams across our major disease areas which include Rheumatoid Arthritis, Inflammatory Bowel Disease, Nonalcoholic Steatohepatitis (NASH), and Dermatology. “Data” is primarily well annotated patient -omics data generated from observational cohorts and internal clinical trials but ranges from single cell RNASeq data for a couple of patients to real world data such as electronic medical records (EMR) and claims data for millions of patients. Dr. Afzelius received her PhD from Uppsala University, Sweden within the Department of Organic Pharmaceutical Chemistry. She obtained her Executive MBA from MIT Sloan School of Management. Since joining Pfizer in 2013, Dr. Afzelius has held several scientific leadership positions. In her current role, she provides strategic leadership to drive qualitative, translational pharmacology across the Inflammation & Immunology portfolio. Dr. Afzelius and her team are working to generate or acquire relevant datasets, in order to curate them to enable cross-study analysis and then apply advanced analytics such as machine learning to extract insights. This is an exciting, rapidly developing field with great promise and the Inflammation & Immunology research unit is working with excellent collaborators such as Professor Altman at Stanford, Dr. Scott Snapper and Dr. Joshua Korzenik at Boston Children’s Hospital/Brigham Women’s Hospital as well as Professor Lars Klareskog at Karolinska Institute to hone in on the key questions that will generate applicable insights to support drug development.

Research Interest

Clinical data management, Clinical trails, Pharmacovigilance

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