A perspective on modelling hepatitis C virus infection

Area of Science:

• Virology
• Mathematical Biology
• Pharmacology

Background:

• Hepatitis C virus (HCV) RNA decay kinetics inform treatment strategies.
• Interferon (IFN)-based therapies and direct-acting antivirals (DAAs) have complex effects on viral load.
• Understanding viral dynamics is crucial for optimizing HCV treatment.

Purpose of the Study:

• To review mathematical modeling developments for HCV viral kinetics.
• To analyze modeling approaches for IFN-based therapies, DAAs, and combined intracellular/extracellular dynamics.
• To discuss optimizing treatment strategies through mathematical modeling.

Main Methods:

• Mathematical modeling of early HCV RNA decay.
• Analysis of viral kinetics patterns (e.g., triphasic decline, rebounds).
• Integration of in vitro and in vivo data for viral lifecycle modeling.

Main Results:

• Estimation of key in vivo viral kinetic parameters (production, clearance, cell loss).
• Modeling explains complex kinetics like triphasic declines and rebounds with pegylated interferon and ribavirin.
• New models address rapid declines and resistance emergence with DAAs.

Conclusions:

• Mathematical modeling is essential for understanding HCV viral kinetics and optimizing treatment.
• Modeling advances are crucial for interpreting complex patterns observed with current and emerging therapies.
• Combining intracellular and extracellular dynamics provides a comprehensive view of HCV lifecycle and treatment response.