Rational Design and Adaptive Management of Combination Therapies for Hepatitis C Virus Infection.
Rational Design and Adaptive Management of Combination Therapies for Hepatitis C Virus Infection.
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DOI：
10.1371/journal.pcbi.1004040
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发表时间：
2015-06
影响因子：
4.3
通讯作者：
Lloyd-Smith JO
中科院分区：
文献类型：
--
作者：
Ke R;Loverdo C;Qi H;Sun R;Lloyd-Smith JO
最近发现的针对丙型肝炎病毒(丙型肝炎病毒)的直接作用抗病毒药物，增加了通过联合疗法进行有效治疗的希望。然而，丙型肝炎病毒种群的快速演变和高度多样性，加上治疗依从性不佳的现实，使耐药性成为临床和公共卫生问题。我们开发了一个综合了病毒动力学和药代动力学/药效学的通用模型，以评估次优依从性如何影响耐药性的发展和临床结果。我们得出了设计原则和适应性治疗策略，确定了缺少剂量对从头耐药特别危险的高风险时期，并量化了当缺少剂量时需要补偿的额外剂量的数量。使用来自大规模耐药性分析的数据，我们证明了通过将这些原则应用于达拉他韦和阿昔洛韦的联合治疗，可以显著降低耐药性风险。通过提供将患者特征与耐药性风险联系起来的机制框架，这些发现显示了合理治疗设计的潜力。丙型肝炎病毒(丙型肝炎病毒)影响全球约1.7亿人，慢性感染可导致肝硬变和肝癌。直接作用抗病毒药物的新组合疗法在临床试验中取得了显著的高治愈率。然而，丙型肝炎病毒群体的高变异率和高多样性，再加上治疗依从性不佳的现实，使耐药性成为临床和公共卫生问题。通过构建一个评估耐药风险的机制框架，我们为这些有希望的新疗法的合理设计和适应性管理提供了指导方针。特别是，我们确定了丢失剂量特别危险的高风险时期，并量化了当丢失剂量时需要补充的额外剂量的数量。这一框架是朝着开发一种工具的方向迈出的一步，该工具可供临床医生设计组合疗法和适应性管理治疗方案，以实现良好的临床结果。
Recent discoveries of direct acting antivirals against Hepatitis C virus (HCV) have raised hopes of effective treatment via combination therapies. Yet rapid evolution and high diversity of HCV populations, combined with the reality of suboptimal treatment adherence, make drug resistance a clinical and public health concern. We develop a general model incorporating viral dynamics and pharmacokinetics/ pharmacodynamics to assess how suboptimal adherence affects resistance development and clinical outcomes. We derive design principles and adaptive treatment strategies, identifying a high-risk period when missing doses is particularly risky for de novo resistance, and quantifying the number of additional doses needed to compensate when doses are missed. Using data from large-scale resistance assays, we demonstrate that the risk of resistance can be reduced substantially by applying these principles to a combination therapy of daclatasvir and asunaprevir. By providing a mechanistic framework to link patient characteristics to the risk of resistance, these findings show the potential of rational treatment design. Hepatitis C virus (HCV) affects approximately 170 million people world-wide and chronic infections can lead to cirrhosis and liver cancer. New combination therapies of direct acting antivirals have achieved remarkably high cure rates in clinical trials. However, high mutation rates and high diversity of HCV populations, combined with the reality of suboptimal treatment adherence, make drug resistance a clinical and public health concern. By constructing a mechanistic framework to assess the risk of drug resistance, we provide guidelines for rational design and adaptive management of these promising new therapies. In particular, we identify a high-risk period when missing doses is particularly risky, and quantify the number of extra doses needed to compensate when doses are missed. This framework is a step towards developing a tool for clinicians to design combination therapies and adaptively manage treatment regimens to achieve favorable clinical outcomes.
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