Hoffmann-La Roche Inc, Nutley, New Jersey, USA.
Antimicrob Agents Chemother. 2012 Jun;56(6):3144-56. doi: 10.1128/AAC.06283-11. Epub 2012 Apr 2.
This analysis was conducted to determine whether the hepatitis C virus (HCV) viral kinetics (VK) model can predict viral load (VL) decreases for nonnucleoside polymerase inhibitors (NNPolIs) and protease inhibitors (PIs) after 3-day monotherapy studies of patients infected with genotype 1 chronic HCV. This analysis includes data for 8 NNPolIs and 14 PIs, including VL decreases from 3-day monotherapy, total plasma trough concentrations on day 3 (C(min)), replicon data (50% effective concentration [EC(50)] and protein-shifted EC(50) [EC(50,PS)]), and for PIs, liver-to-plasma ratios (LPRs) measured in vivo in preclinical species. VK model simulations suggested that achieving additional log(10) VL decreases greater than one required 10-fold increases in the C(min). NNPolI and PI data further supported this result. The VK model was successfully used to predict VL decreases in 3-day monotherapy for NNPolIs based on the EC(50,PS) and the day 3 C(min). For PIs, however, predicting VL decreases using the same model and the EC(50,PS) and day 3 C(min) was not successful; a model including LPR values and the EC(50) instead of the EC(50,PS) provided a better prediction of VL decrease. These results are useful for designing phase 1 monotherapy studies for NNPolIs and PIs by clarifying factors driving VL decreases, such as the day 3 C(min) and the EC(50,PS) for NNPolIs or the EC(50) and LPR for PIs. This work provides a framework for understanding the pharmacokinetic/pharmacodynamic relationship for other HCV drug classes. The availability of mechanistic data on processes driving the target concentration, such as liver uptake transporters, should help to improve the predictive power of the approach.
本分析旨在确定丙型肝炎病毒 (HCV) 病毒动力学 (VK) 模型是否可预测感染基因型 1 慢性 HCV 的患者接受为期 3 天的单药治疗研究后,非核苷聚合酶抑制剂 (NNPolIs) 和蛋白酶抑制剂 (PIs) 的病毒载量 (VL) 下降情况。本分析包括 8 种 NNPolIs 和 14 种 PI 的数据,包括 3 天单药治疗的 VL 下降、第 3 天的总血浆谷浓度 (C(min))、复制子数据(50%有效浓度 [EC(50)] 和蛋白移位 EC(50) [EC(50,PS)]),以及对于 PIs,在临床前物种中体内测量的肝/血浆比 (LPR)。VK 模型模拟表明,要实现大于 1 的额外对数 10 VL 下降,需要 C(min) 增加 10 倍。NNPolI 和 PI 数据进一步支持了这一结果。VK 模型成功地基于 EC(50,PS)和第 3 天的 C(min),用于预测 NNPolIs 3 天单药治疗的 VL 下降。然而,对于 PIs,使用相同的模型和 EC(50,PS)和第 3 天的 C(min)来预测 VL 下降并不成功;一个包含 LPR 值和 EC(50)而不是 EC(50,PS)的模型可以更好地预测 VL 下降。这些结果对于设计 NNPolIs 和 PIs 的 1 期单药治疗研究非常有用,因为它阐明了驱动 VL 下降的因素,如 NNPolIs 的第 3 天的 C(min)和 EC(50,PS)或 PIs 的 EC(50)和 LPR。这项工作为理解其他 HCV 药物类别的药代动力学/药效动力学关系提供了一个框架。有关驱动目标浓度的过程的机制数据(如肝摄取转运体)的可用性应有助于提高该方法的预测能力。