Iyaniwura Sarafa A, Cassidy Tyler, Ribeiro Ruy M, Perelson Alan S
Theoretical Biology and Biophysics, Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.
School of Mathematics, University of Leeds, Leeds, United Kingdom.
PLoS Comput Biol. 2025 May 6;21(5):e1012322. doi: 10.1371/journal.pcbi.1012322. eCollection 2025 May.
Chronic hepatitis B virus (HBV) infection is strongly associated with increased risk of liver cancer and cirrhosis. While existing treatments effectively inhibit the HBV life cycle, viral rebound frequently occurs following treatment interruption. Consequently, functional cure rates of chronic HBV infection remain low and there is increased interest in a novel treatment modality, capsid assembly modulators (CAMs). Here, we develop a multiscale mathematical model of CAM treatment in chronic HBV infection. By fitting the model to participant data from a phase I trial of the first-generation CAM vebicorvir, we estimate the drug's dose-dependent effectiveness and identify the physiological mechanisms that drive the observed biphasic decline in HBV DNA and RNA, and mechanistic differences between HBeAg-positive and negative infection. Finally, we demonstrate analytically and numerically that the relative change of HBV RNA more accurately reflects the antiviral effectiveness of a CAM than the relative change in HBV DNA.
慢性乙型肝炎病毒(HBV)感染与肝癌和肝硬化风险增加密切相关。虽然现有治疗方法能有效抑制HBV生命周期,但治疗中断后病毒反弹频繁发生。因此,慢性HBV感染的功能性治愈率仍然很低,人们对一种新型治疗方式——衣壳组装调节剂(CAMs)的兴趣日益增加。在此,我们建立了慢性HBV感染中CAM治疗的多尺度数学模型。通过将该模型与第一代CAM药物韦比克韦的I期试验参与者数据进行拟合,我们估计了该药物的剂量依赖性有效性,并确定了导致观察到的HBV DNA和RNA双相下降的生理机制,以及HBeAg阳性和阴性感染之间的机制差异。最后,我们通过分析和数值模拟证明,与HBV DNA的相对变化相比,HBV RNA的相对变化更准确地反映了CAM的抗病毒效果。