Mathematical Biosciences Institute & Department of Mathematics, The Ohio State University, Columbus, Ohio, United States of America.
National Institute for Mathematical and Biological Synthesis, University of Tennessee, Knoxville, Tennessee, United States of America.
PLoS One. 2018 Apr 10;13(4):e0195037. doi: 10.1371/journal.pone.0195037. eCollection 2018.
Hepatitis B virus (HBV) infection is a liver disorder that can result in cirrhosis, liver failure and hepatocellular carcinoma. HBV infection remains a major global health problem, as it affects more 350 million people chronically and kills roughly 600,000 people annually. Drugs currently used against HBV include IFN-α that decreases viremia, inflammation and the growth of liver fibrosis, and adefovir that decreases the viral load. Each of these drugs can have severe side-effects. In the present paper, we consider the treatment of chronic HBV by a combination of IFN-α and adefovir, and raise the following question: What should be the optimal ratio between IFN-α and adefovir in order to achieve the best 'efficacy' under constraints on the total amount of the drugs; here the efficacy is measured by the reduction of the levels of inflammation and of fibrosis? We develop a mathematical model of HBV pathogenesis by a system of partial differential equations (PDEs) and use the model to simulate a 'synergy map' which addresses the above question.
乙型肝炎病毒（HBV）感染是一种肝脏疾病，可导致肝硬化、肝功能衰竭和肝细胞癌。HBV 感染仍然是一个主要的全球健康问题，因为它影响着超过 3.5 亿人慢性感染，并每年导致约 60 万人死亡。目前用于治疗 HBV 的药物包括干扰素-α，它可以降低病毒血症、炎症和肝纤维化的生长，以及阿德福韦酯，它可以降低病毒载量。这些药物都可能有严重的副作用。在本文中，我们考虑通过联合使用干扰素-α和阿德福韦酯来治疗慢性 HBV，并提出了以下问题：为了在药物总量的限制下达到最佳的“疗效”，即通过降低炎症和纤维化水平来衡量，干扰素-α和阿德福韦酯的最佳比例应该是多少？我们通过偏微分方程（PDE）系统建立了 HBV 发病机制的数学模型，并使用该模型来模拟解决上述问题的“协同图”。
