Chronic hepatitis B virus (HBV) infection is strongly associated with increased risk of liver cancer and cirrhosis and accounts for over one million deaths per year, worldwide. While existing treatments effectively inhibit the HBV life cycle, viral rebound occurs rapidly following treatment interruption. Consequently, patients must therefore receive treatment indefinitely. The resulting life-long treatment leads to increased treatment burden for patients and an increased risk of selection for treatment resistant strains of HBV. Consequently, there has been increased interest in a novel treatment modality, capsid assembly modulators (CAMs), that block a crucial step in the viral life cycle. I'll discuss recent modelling work that shows HBV serum RNA is an informative biomarker of CAM treatment efficacy, evaluates CAMs as a potential functional cure for HBV infection, and illustrates the role of mechanistic modelling in rational trial design using an age structured, multi-scale mathematical model.