Certara UK Limited, Simcyp Division, Sheffield, UK.
Critical Path Institute, Tucson, Arizona, USA.
CPT Pharmacometrics Syst Pharmacol. 2021 Nov;10(11):1382-1395. doi: 10.1002/psp4.12707. Epub 2021 Oct 8.
Tuberculosis (TB) remains a global health problem and there is an ongoing effort to develop more effective therapies and new combination regimes that can reduce duration of treatment. The purpose of this study was to demonstrate utility of a physiologically-based pharmacokinetic modeling approach to predict plasma and lung concentrations of 11 compounds used or under development as TB therapies (bedaquiline [and N-desmethyl bedaquiline], clofazimine, cycloserine, ethambutol, ethionamide, isoniazid, kanamycin, linezolid, pyrazinamide, rifampicin, and rifapentine). Model accuracy was assessed by comparison of simulated plasma pharmacokinetic parameters with healthy volunteer data for compounds administered alone or in combination. Eighty-four percent (area under the curve [AUC]) and 91% (maximum concentration [C ]) of simulated mean values were within 1.5-fold of the observed data and the simulated drug-drug interaction ratios were within 1.5-fold (AUC) and twofold (C ) of the observed data for nine (AUC) and eight (C ) of the 10 cases. Following satisfactory recovery of plasma concentrations in healthy volunteers, model accuracy was assessed further (where patients' with TB data were available) by comparing clinical data with simulated lung concentrations (9 compounds) and simulated lung: plasma concentration ratios (7 compounds). The 5th-95th percentiles for the simulated lung concentration data recovered between 13% (isoniazid and pyrazinamide) and 88% (pyrazinamide) of the observed data points (Am J Respir Crit Care Med, 198, 2018, 1208; Nat Med, 21, 2015, 1223; PLoS Med, 16, 2019, e1002773). The impact of uncertain model parameters, such as the fraction of drug unbound in lung tissue mass (fu ), is discussed. Additionally, the variability associated with the patient lung concentration data, which was sparse and included extensive within-subject, interlaboratory, and experimental variability (as well interindividual variability) is reviewed. All presented models are transparently documented and are available as open-source to aid further research.
结核病（TB）仍然是一个全球性的健康问题，人们一直在努力开发更有效的治疗方法和新的联合治疗方案，以缩短治疗时间。本研究的目的是展示生理基于药代动力学建模方法在预测用于或正在开发的 11 种结核病治疗药物（贝达喹啉[和 N-去甲基贝达喹啉]、氯法齐明、环丝氨酸、乙胺丁醇、乙硫异烟胺、异烟肼、卡那霉素、利奈唑胺、吡嗪酰胺、利福平、利福喷汀）的血浆和肺部浓度方面的实用性。通过比较单独或联合给药时化合物的模拟血浆药代动力学参数与健康志愿者数据来评估模型准确性。对于 10 种情况中的 9 种（AUC）和 8 种（C ），84%（曲线下面积[AUC]）和 91%（最大浓度[C ]）的模拟平均值在观察数据的 1.5 倍以内，模拟药物相互作用比值在观察数据的 1.5 倍（AUC）和 2 倍（C ）以内。在健康志愿者中血浆浓度恢复满意后，进一步通过比较临床数据与模拟肺部浓度（9 种化合物）和模拟肺部：血浆浓度比值（7 种化合物）来评估模型准确性（在有 TB 患者数据的情况下）。模拟肺部浓度数据的第 5 至 95 百分位数与观察数据点的 13%（异烟肼和吡嗪酰胺）至 88%（吡嗪酰胺）之间恢复（Am J Respir Crit Care Med, 198, 2018, 1208; Nat Med, 21, 2015, 1223; PLoS Med, 16, 2019, e1002773）。讨论了模型参数（如肺组织质量中未结合药物的分数[fu ]）的不确定性的影响。此外，还回顾了与患者肺部浓度数据相关的变异性，这些数据是稀疏的，包括广泛的个体内、实验室间和实验变异性（以及个体间变异性）。所有呈现的模型都有透明的文档记录，并作为开源提供，以帮助进一步的研究。
