A pharmacokinetic-pharmacodynamic model to optimize the phase IIa development program of maraviroc
A pharmacokinetic-pharmacodynamic model to optimize the phase IIa development program of maraviroc
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DOI：
10.1097/01.qai.0000220021.64115.37
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发表时间：
2006-06-01
影响因子：
3.6
通讯作者：
van der Ryst, Elna
中科院分区：
文献类型：
--
作者：
Rosario, Maria C.;Poland, Bill;van der Ryst, Elna
目的：使用病毒动力学模型比较几种剂量马拉韦罗的体内病毒抑制效果（MVC;UK-427，857），并使用建模方法来支持单一疗法研究的设计决策，所述单一疗法研究使用与食物一起和不与食物一起给予的马拉韦罗的各种给药方案。这是一项在44例无症状HIV-1感染患者中进行的随机、双盲、安慰剂对照、多中心马拉韦罗研究。患者接受马拉韦罗的食物限制下，在25毫克，每天一次或50，100，或300毫克，每天两次，或安慰剂为10 days.Methods：抗病毒反应进行了评估，通过测量血浆HIV-1 RNA水平在筛选期间，在随机化，在基线，每天在10天的治疗和第II至15，19，22，25和40天。使用混合效应建模方法，结合患者治疗最后一天的药代动力学特征、随时间推移的HIV-1 RNA水平以及个体病毒易感性，开发了综合药代动力学-药效学模型。使用病毒动力学模型得出的参数计算每个处理组的平均病毒抑制分数、活跃感染细胞的衰减率和基本繁殖比。然后使用Monte Carlo模拟来确定另一项单药治疗研究A4001015中研究的每种方案的模拟患者随时间推移的病毒载量变化分布。结果：300 mg每日两次组的下降率与强效蛋白酶抑制剂单药治疗诱导的下降率相当，但明显慢于接受包括蛋白酶抑制剂和逆转录酶抑制剂的联合治疗的患者。25 mg每日一次剂量组和300 mg每日两次剂量组的体内抑制效力估计范围分别为0.15 - 0.38和0.88 - 0.96。结论：该模型有助于临床数据的分析和解释。使用基于模型的方法来选择剂量可以通过用模拟代替一些手臂或试验来加速药物开发。
Objectives: To use a viral dynamics model to compare the effectiveness of in vivo viral inhibition of several doses of maraviroc (MVC;UK-427,857) and to use a modeling approach to support design decisions for a monotherapy study using various dosing regimens of maraviroc given with and without food.Design: The pharmacokinetic-pharmacodynamic model was developed using clinical data from a first monotherapy study (study A4001007). This was a randomized, double-blind, placebo-controlled, multicenter study of maraviroc in 44 asymptomatic HIV-1-infected patients. Patients received maraviroc under food restrictions at 25 mg once daily or 50, 100, or 300 mg twice daily, or placebo for 10 days.Methods: Antiviral responses were assessed by measuring plasma HIV-1 RNA levels during screening, during randomization, at baseline, and daily during the 10 days of treatment and at days I I to 15, 19, 22, 25, and 40. An integrated pharmacokinetic-pharmacodynamic model was developed using the mixed effects modeling approach with patients' pharmacokinetic profiles on the last day of treatment, HIV-1 RNA levels over time, and the individual viral susceptibility. The parameters derived from the viral dynamic model were used to calculate average viral inhibition fraction, decay rate of actively infected cells, and basic reproductive ratio for each treatment group. Monte Carlo simulation was then used to determine the distribution of viral load change across simulated patients over time for each regimen to be studied in another monotherapy study, A4001015.Results: The decline rate in the 300 mg twice daily group was comparable to that induced by potent protease inhibitor monotherapy, but was significantly slower than that in patients receiving combination therapy including both protease inhibitor and reverse transcriptase inhibitors. The efficacy of inhibition in vivo was estimated to range from 0.15 to 0.38 for the 25 mg once daily dose group and from 0.88 to 0.96 for the 300 mg twice daily dose group. Conclusions: The model has aided the analysis and interpretation of the clinical data. The use of a model-based approach for selecting doses can accelerate drug development by replacing some arms or trials with simulations.