I am an Assistant Professor of Medicine at the University of California, San Francisco and Affiliate Faculty in the UCSF/UC Berkeley Joint Program in Computational Precision Health.
My research is motivated by two key questions I frequently encounter in my clinical practice as an intensive care physician and pulmonologist: 1) Why do patients with same disease have such different responses to the same treatments?; and 2) Why are so many promising preclinical treatments ineffective in large clinical trials?
My research uses computational methods to study the dynamic interplay between disease progression, treatment regimen, and drug and biomarker response across relevant scales (molecule, cell, tissue, organ & whole body) to determine causal links underlying variability in (safety and efficacy) clinical outcomes. By integrating multi-scale, and multi-level clinical data, we aim to determine the right dose, schedule, and treatment duration of various therapies, potentially bringing novel, precise and personalized treatment options to patients with unmet need more quickly.
Dr. Schafer is Professor of Medicine and of Epidemiology & Biostatistics at UCSF and Chief of Endocrinology and Metabolism at the San Francisco VA Health Care System. She is board-certified by the American Board of Internal Medicine in the subspecialty of Endocrinology, Diabetes and Metabolism. Her research focus is osteoporosis and bone metabolism. One of her research emphases is osteoporosis treatment and the assessment of response to osteoporosis therapy.
Marina is currently a Professor and the Acting Director 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 experience in translational bioinformatics spans nearly 20 years during which she has co-authored over 170 scientific publications.
1. Programmatic implementation of population-based colorectal cancer screening and follow-up of abnormal screening results. We embrace big data and technology to design, develop, and deliver economic and effective services for patients and health systems.
2. Use of human gut samples to study HIV, Covid-19, barrier function, systemic inflammation, inflammatory bowel disease, and microbiome. Approaches employed: organoid models, isolation of epithelial cells and lymphocytes, single cell, spatial transcriptomic analysis, microbial profiling, and blood-based profiling.
The Benioff Center for Microbiome Medicine (BCMM) stands committed to dismantling the structural barriers to education, research and employment endemic in our society, to promoting awareness of implicit bias and reinforcing inclusivity.