Successful clinical drug development requires rational design of combination treatments based on preclinical data. Anti-hepatitis C virus (HCV) drugs exhibit significant diversity in antiviral effect. Dose-response assessments can be used to determine parameters profiling the diverse antiviral effect during combination treatment. In the current study, a combined experimental and mathematical approaches were used to compare and score different combinations of anti-HCV treatments. A “required concentration index” was generated and used to rank the antiviral profile of possible double- and triple-drug combinations against HCV genotype 1b and 2a. Rankings varied based on target HCV genotype. Interestingly, multidrug (double and triple) treatment not only augmented antiviral activity, but also reduced genotype-specific efficacy, suggesting another advantage of multidrug treatment. The current study provides a quantitative method for profiling drug combinations against viral genotypes, to better inform clinical drug development.

中文翻译：

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所需的浓度指数可量化对抗丙型肝炎病毒感染的有效药物组合

成功的临床药物开发需要根据临床前数据合理设计联合治疗药物。抗丙型肝炎病毒（HCV）药物在抗病毒效果方面表现出显着的多样性。剂量反应评估可用于确定在联合治疗期间描述各种抗病毒作用的参数。在当前的研究中，结合了实验和数学方法来比较和评分抗HCV治疗的不同组合。产生“所需浓度指数”，并用于对可能的双重和三重药物组合针对HCV基因型1b和2a的抗病毒谱进行排名。排名根据目标HCV基因型而异。有趣的是，多药（双重和三重）治疗不仅增强了抗病毒活性，而且降低了基因型特异性功效，提示多药治疗的另一个优势。当前的研究提供了针对病毒基因型的药物组合概况分析的定量方法，以更好地指导临床药物开发。