Collaborative Integration of HCV Molecular Virology and Mathematical Modeling

丙型肝炎病毒(丙型肝炎病毒)是一种嗜肝病毒，约70%的接触者会发生慢性感染。AS 因此，目前全球有7100多万人受到感染，并增加了发展为肝脏的风险。 疾病和肝细胞癌。而有效的不含干扰素的直接作用抗病毒药物(DAA) 治疗组合是非常有效的，DAA的承诺尚未使我们走上实现世卫组织目标的轨道 到2030年消除的目标。实现这一目标将需要扩大丙型肝炎病毒筛查、与护理的联系以及 降低治疗成本。此外，这将需要了解丙型肝炎病毒的传播，特别是如何防止 病毒抗药性变异在个体内的传播，使得这些抗药性病毒不是 传播到人群中。重要的是，病毒的细胞间传播与抗病毒逃逸有关， 免疫逃逸，以及一般病毒的持久性。因此，通过对丙型肝炎病毒的研究获得的见解 应该为未来的抗病毒战略提供广泛的信息。 治疗期间感染患者血清中丙型肝炎病毒的数学模型推动了我们对 丙型肝炎病毒感染动态，干扰素治疗的效果，并导致丙型肝炎病毒定量评估的方法 治疗效果。自FDA批准丙型肝炎病毒DAA以来，我们率先开发了多尺度模型 在体外和患者体内的DAA治疗反应。这项工作揭示了NS5A的双重作用机制 并证明了病毒动力学模型可能允许缩短DAA的持续时间 治疗在大多数患者中。这些临床见解已经从我们的丙型肝炎病毒感染模型中得到了启发。 在细胞培养中，我们能够直接测量细胞内和细胞外病毒和细胞 参数。应用细胞培养实验和体内患者数据，我们最近获得了 病毒进入/传播在维持稳定状态感染中发挥主要作用的证据广泛 关于病毒传播作为抗病毒药物靶点的含义以及传播如何影响抗病毒治疗 在药物疗效、病毒逃逸和药物协同作用方面的反应。 因为这些新的模型提出了关于丙型肝炎病毒传播和抗病毒药物的重要生物学问题 战略，这一跨学科R01更新的目标是使治疗的改善 通过建立和检验丙型肝炎病毒感染和治疗反应的数学模型 在体内和体外。具体目标是：1)改进和验证时间，以使用体内和体内的预测治愈 电子试验；2)阐明有关丙型肝炎病毒生命周期和肝细胞在丙型肝炎病毒中的作用的定量细节 3)扩展和优化丙型肝炎病毒细胞间传播的数学模型；以及4)确定 作为抗病毒药物靶点的细胞间传播的重要性。

Hepatitis C virus (HCV) is a hepatotropic virus that establishes chronic infection in ~70% of those exposed. As a result, currently more than 71 million people worldwide are infected and at increased risk of developing liver disease and hepatocellular carcinoma. While effective interferon (IFN)-free direct acting antiviral (DAA) therapeutic combinations are highly potent, the promise of DAAs has not yet put us on track to achieve the WHO goal of elimination by 2030. Reaching this goal will require a scaling-up of HCV screening, linkage-to-care, and reduction of treatment cost. Additionally, this will require understanding HCV spread, specifically how to prevent the spread of viral antiviral resistance variants within individuals such that these drug resistance viruses are not transmitted to the population. Importantly, viral cell-to-cell spread has been implicated in antiviral escape, immune escape, and persistence of viruses in general. Thus, the insights gained through the study of HCV should broadly inform future antiviral strategies. Mathematical modeling of HCV in the serum of infected patients during therapy has driven our understanding of HCV infection dynamics, the effect of IFN treatment, and led to methods for the quantitative evaluation of HCV treatment efficacy. Since FDA-approval of HCV DAAs, we have pioneered the development of multiscale models of DAA treatment response in vitro and in patients. This work revealed the dual mechanism of action of NS5A inhibitors and has demonstrated that viral kinetic modeling might allow for a reduction in the duration of DAA therapy in the majority of patients. These clinical insights have been informed by our modeling of HCV infection in cell culture where we are able to directly measure both intracellular and extracellular viral and cellular parameters. Applying both cell culture experimentation and in vivo patient data, we have recently obtained evidence that viral entry/spread plays a major role in the maintenance of steady state infection having broad implications regarding viral spread as an antiviral drug target and how spread impacts antiviral treatment response in terms of drug efficacy, viral escape, and drug synergy. Because these new models have raised important biological questions about HCV spread and antiviral drug strategies, the objective of this cross disciplinary R01 renewal is to enable the improvement of the treatment for HCV and other viruses by formulating and testing mathematical models of HCV infection and treatment response in vivo and in vitro. The specific aims are: 1) Refine and validate time to cure predictions using in vivo and in silico trials; 2) Elucidate quantitative details about the HCV life cycle and the role of hepatocytes in HCV clearance; 3) Expand and optimize mathematical models of HCV cell-to-cell spread; and 4) Determine the importance of cell-to-cell spread as an antiviral drug target.