Speaker
Description
Chronic hepatitis B virus (HBV) infection is responsible for approximately one million deaths per year, worldwide. While existing therapies effectively block the production of new virus, viral rebound occurs rapidly if treatment is stopped. As a result, no cure for chronic HBV infection is currently available. Patients therefore typically receive treatment indefinitely with corresponding life-long treatment burden. Consequently, there is pressing need for new treatment options that block crucial steps in the viral life cycle. I'll show how multiscale mathematical modelling can illuminate biological mechanisms that would otherwise be inaccessible during typical clinical trials, identify circulating biomarkers of drug effectiveness, and help understand new treatments as possible functional cures for HBV. I’ll show how this multiscale modelling can identify a simple predictive relationship between circulating biomarkers and drug efficacy.
