Michal Juraska

Michal Juraska, PhD, MS is a Senior Staff Scientist in the Gilbert Lab within the Biostatistics, Bioinformatics and Epidemiology Program of the Vaccine and Infectious Disease Division at Fred Hutchinson Cancer Center. As a biostatistician, he engages in statistical and clinical trial methods research focused on vaccine science for HIV, COVID-19, malaria, dengue, and other diseases. He serves as a faculty member of the HIV Vaccine Trials Network (HVTN) and the COVID-19 Prevention Network (CoVPN), where he has served as a lead statistician on numerous vaccine and monoclonal antibody efficacy trials.

His educational background includes:

• University of Washington, 2012, PhD (Biostatistics)
• University of Washington, 2009, MS (Biostatistics)
• Charles University in Prague, 2007, MS (Mathematical Statistics)

Dr. Juraska's research spans multiple critical areas in vaccine science, with particular expertise in sieve analysis of breakthrough pathogen features and statistical evaluation of immune biomarkers as correlates of vaccine protection. His work has significantly advanced clinical immunobridging strategies aimed at securing vaccine licensure based on immunological surrogate endpoints when clinical outcomes are unavailable. He specializes in developing statistical frameworks to analyze how pathogen genetic features influence vaccine efficacy across diverse disease contexts.

Analysis of his recent publications reveals a consistent focus on pathogen sequence-dependent vaccine efficacy across HIV, COVID-19, and malaria. His statistical approaches for evaluating how viral genetic variation impacts protection have become increasingly sophisticated, with recent work integrating machine learning techniques to predict vaccine efficacy based on pathogen sequence features. This methodology has important implications for vaccine design, regulatory approval pathways, and understanding immune escape mechanisms.

Dr. Juraska actively mentors students, interns, and early-career statisticians, and teaches specialized workshops on statistical and computational tools for sieve and immune correlates analyses. His grant-supported work primarily involves leadership roles in major collaborative networks including HVTN and CoVPN, where he serves on data monitoring committees and leads statistical reporting for pivotal efficacy trials.

Within Fred Hutch, he contributes to the Gilbert Lab's mission of developing innovative statistical methods for infectious disease prevention. His collaborative approach connects biostatisticians with laboratory scientists and clinicians to address critical questions in vaccine development, particularly regarding correlates of protection and methods for evaluating vaccine efficacy against genetically diverse pathogens.