Modeling hepatitis D virus kinetics during bulevirtide monotherapy: challenges and solutions.

Area of Science:

• Virology
• Pharmacometrics
• Mathematical Modeling

Background:

• Hepatitis D virus (HDV) infection is the most severe form of viral hepatitis.
• Bulevirtide (BLV), an entry inhibitor, is approved in Europe for chronic HDV infection.
• Existing mathematical models often exclude target cell dynamics, potentially limiting their predictive accuracy.

Purpose of the Study:

• To evaluate a two-equation mathematical model (excluding target cell dynamics) against clinical data from HDV patients treated with BLV monotherapy.
• To assess the model's ability to predict viral kinetics, treatment duration, and outcomes like viral breakthrough and rebound.

Main Methods:

• Non-linear mixed effects modeling (NLME) was used to analyze clinical data from HDV patients treated with BLV.
• A published two-equation model was applied to patient data over 96 weeks.
• Model predictions were compared against observed non-monophasic viral decline patterns.

Main Results:

• The two-equation model failed to reproduce observed non-monophasic HDV decline patterns, including biphasic decline and viral breakthrough.
• The model inaccurately predicted treatment duration needed to reach a theoretical cure boundary.
• The model could not explain viral rebound after BLV treatment cessation.

Conclusions:

• The exclusion of target cell dynamics in mathematical models limits their ability to accurately predict HDV treatment outcomes with BLV.
• Incorporating target cell dynamics is crucial for explaining complex viral kinetics, such as non-monophasic decline and viral rebound.
• Improved models including target cell dynamics are needed for better prediction of HDV treatment efficacy and duration.