Session Abstract – PMWC 2022 Silicon Valley

Given orphan drugs are intended to treat diseases that are very complex and diverse, development is often seen as a risk for the industry – requiring several years of research efforts in drug discovery with uncertainty for therapeutic outcomes.

By starting out with a complete clinical picture via multi-omic data, consisting of genomics, transcriptomics, proteomics, metabolomics, and phenomics data, we can now gain multilayer insights that help us develop better disease models and thus more precise medicine.

This session will focus on examples and emerging applications that demonstrate how multi-omic data can be leveraged to accelerate and de-risk rare disease drug discovery and development.

 Session Chair Profile

Ph.D., Chief Scientific Officer, CENTOGENE

Patrice is a seasoned executive and scientific pioneer with over 35 years of experience at pharmaceutical and biotechnology companies in Europe and the U.S. – spearheading translational R&D to deliver breakthrough treatments. He served as CSO at 4P-Pharma, where he led the R&D drug repositioning strategy and operations towards potential full clinical demonstration and asset-value transfer to large pharma companies. He has held several leadership positions, including as the General Manager of the Roche Institute for Research and Translational Medicine, as well as other senior roles at Sanofi Aventis and Ipsen. Patrice served as CSO at Genethon, a biotech company dedicated to the development of gene therapy treatments for rare diseases. Patrice taught Biotechnology for 10 years at the University Paris-Descartes and has co-authored over 150 scientific papers and patents.

 Speaker Profile

Ph.D., Associate Professor, Bakar Computational Health Sciences Institute, UCSF

Marina is currently an Associate Professor at the Bakar Computational Health Sciences Institute at UCSF. Prior to that she has worked as a Senior Research Scientist at Pfizer where she focused on developing Precision Medicine strategies in drug discovery. She completed her PhD in Biomedical Informatics at Stanford University. Dr. Sirota’s research interests lie in developing computational integrative methods and applying these approaches in the context of disease diagnostics and therapeutics with a special focus on studying the role of the immune system in disease. The Sirota laboratory is funded by NIA, NLM, NIAMS, Pfizer, March of Dimes and the Burroughs Wellcome Fund. As a young leader in the field, she has been awarded the AMIA Young Investigator Award in 2017. Dr. Sirota also is the director of the AI4ALL program at UCSF, with the goal of introducing high school girls to applications of AI and machine learning in biomedicine.

Computational Drug Discovery in the Era of Precision Medicine
I will discuss leveraging molecular and clinical data to advance precision medicine in the context of drug discovery and repurposing.

 Speaker Profile

Ph.D., Associate Professor, Stanford University

Research focuses on developing novel methods for leveraging heterogeneity present across independent cohorts to better understand human immune system for developing novel diagnostics and therapies for inflammatory diseases