Los Alamos National Laboratory, Theoretical Biology and Biophysics Group, Los Alamos, New Mexico, USA.
New Mexico Consortium, Los Alamos, New Mexico, USA.
Clin Pharmacol Ther. 2021 Apr;109(4):829-840. doi: 10.1002/cpt.2160. Epub 2021 Mar 8.
Modern viral kinetic modeling and its application to therapeutics is a field that attracted the attention of the medical, pharmaceutical, and modeling communities during the early days of the AIDS epidemic. Its successes led to applications of modeling methods not only to HIV but a plethora of other viruses, such as hepatitis C virus (HCV), hepatitis B virus and cytomegalovirus, which along with HIV cause chronic diseases, and viruses such as influenza, respiratory syncytial virus, West Nile virus, Zika virus, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which generally cause acute infections. Here we first review the historical development of mathematical models to understand HIV and HCV infections and the effects of treatment by fitting the models to clinical data. We then focus on recent efforts and contributions of applying these models towards understanding SARS-CoV-2 infection and highlight outstanding questions where modeling can provide crucial insights and help to optimize nonpharmaceutical and pharmaceutical interventions of the coronavirus disease 2019 (COVID-19) pandemic. The review is written from our personal perspective emphasizing the power of simple target cell limited models that provided important insights and then their evolution into more complex models that captured more of the virology and immunology. To quote Albert Einstein, "Everything should be made as simple as possible, but not simpler," and this idea underlies the modeling we describe below.
现代病毒动力学建模及其在治疗学中的应用是一个在艾滋病早期引起医学、制药和建模界关注的领域。它的成功不仅导致了建模方法在 HIV 中的应用,还应用于其他大量病毒,如丙型肝炎病毒 (HCV)、乙型肝炎病毒和巨细胞病毒,这些病毒与 HIV 一起导致慢性疾病,以及流感、呼吸道合胞病毒、西尼罗河病毒、寨卡病毒和严重急性呼吸综合征冠状病毒 2 (SARS-CoV-2) 等一般导致急性感染的病毒。在这里,我们首先回顾了数学模型来理解 HIV 和 HCV 感染以及通过将模型拟合到临床数据来治疗的历史发展。然后,我们专注于应用这些模型来理解 SARS-CoV-2 感染的最新努力和贡献,并强调了建模可以提供关键见解并有助于优化 2019 年冠状病毒病 (COVID-19) 大流行的非药物和药物干预的突出问题。这篇综述是从我们个人的角度撰写的,强调了简单的靶细胞有限模型的力量,这些模型提供了重要的见解,然后它们演变成更复杂的模型,从而更全面地了解病毒学和免疫学。引用阿尔伯特·爱因斯坦的话说,“一切都应该尽可能简单,但不能更简单”,这个理念是我们下面描述的建模的基础。