Department of Pharmaceutical and Medical Chemistry, Clinical Pharmacy, University of Muenster, Hittorfstraße 58-62, 48149 Muenster, Germany.
Cancer Chemother Pharmacol. 2013 Mar;71(3):749-63. doi: 10.1007/s00280-013-2069-1. Epub 2013 Jan 13.
The aim of the current investigation was to develop a population pharmacokinetic model for doxorubicin and doxorubicinol that could provide improved estimated values for the pharmacokinetic parameters clearance of doxorubicin, volume of distribution of the central compartment, clearance of doxorubicinol and volume of distribution of the metabolite compartment for adults and children older than 3 years. A further aim was to investigate the potential influence of the covariates body surface area, body weight, body height, age, body mass index, sex and lean body mass on the pharmacokinetic parameters.
Three different datasets, two containing data from adults and one containing data from adults and children, were merged and the combined dataset was analysed retrospectively. In total, the combined dataset contained 934 doxorubicin and 935 doxorubicinol plasma concentrations from 82 patients [64 adults and 18 children (<18 years)]. With this combined dataset, a population pharmacokinetic model was developed, using NONMEM(®) 7.2 and a predefined model-building strategy. Different structural models, error models and estimation methods were tested, and the inter-individual and the inter-occasion variability (variability between separate (two or three) doxorubicin infusions) were tested. Using a subset of 52 patients, the influence of different covariates on the pharmacokinetic parameters was investigated. The pharmacokinetic parameter estimates obtained from doxorubicin concentrations with the best model were fixed, and an additional compartment for doxorubicinol was added to the model. With the final model for both substances, a potential age dependency and body mass index dependency of the clearance of doxorubicin and doxorubicinol as well as of the volumes of distribution of the central and the metabolite compartment were evaluated.
A four-compartment model best described the doxorubicin and doxorubicinol data of the combined dataset. This model included a proportional residual error model and an inter-individual variability on the clearance of doxorubicin, on the inter-compartmental clearances of the peripheral compartments, on the clearance of doxorubicinol and on the volumes of distribution of the central, one peripheral and the metabolite compartment. Furthermore, the body surface area as covariate on all pharmacokinetic parameters and an inter-occasion variability for the clearance of doxorubicin and the volume of distribution of the central compartment were incorporated in the model. For a patient with the body surface area of 1.8 m², the clearance of doxorubicin was 53.3 L/h (inter-individual variability 31%, inter-occasion variability 13%) and the volume of distribution of the central compartment was 17.7 L (inter-individual variability 19%, inter-occasion variability 21%), respectively. The residual variability of the model was 22% for doxorubicin and 26% for doxorubicinol. The clearance of doxorubicinol was estimated at 44 L/h (inter-individual variability 50%) and the volume of distribution of the metabolite compartment at 1,150 L (inter-individual variability 57%). The evaluation of a possible age dependency and body mass index dependency showed a trend to a smaller volume of distribution of the central compartment (normalised to the body surface area) and a higher volume of distribution of the metabolite compartment (normalised to the body weight) in younger patients.
A four-compartment NONMEM(®) model for doxorubicin and doxorubicinol adequately described the plasma concentrations in adults and children (>3 years). No pronounced effects of age on the clearance of doxorubicin or doxorubicinol were found, and the analysis did not support the modification of the dosing strategies presently used in children and adults.
本研究旨在开发一种多剂量群体药代动力学模型，用于预测多柔比星及其代谢产物多柔比星醇在成人和 3 岁以上儿童中的药代动力学参数清除率、中央室分布容积、多柔比星醇清除率和代谢产物室分布容积，从而提高这些参数的估计值。此外，本研究还旨在探讨体表面积、体重、身高、年龄、体重指数、性别和瘦体重等协变量对药代动力学参数的潜在影响。
将两个包含成人数据的数据集和一个包含成人和儿童数据的数据集合并，并对合并后的数据集进行回顾性分析。该数据集共包含 82 例患者（64 例成人和 18 例儿童<18 岁）的 934 例多柔比星和 935 例多柔比星醇血药浓度。使用 NONMEM（R）7.2 和预定义的模型构建策略，对该合并数据集进行了群体药代动力学模型的开发。对不同的结构模型、误差模型和估计方法进行了测试，并对个体间和个体间（两次或三次多柔比星输注之间）变异性进行了测试。使用 52 例患者的子集，研究了不同协变量对药代动力学参数的影响。使用最佳模型对多柔比星浓度进行参数估计，然后在模型中添加一个用于多柔比星醇的额外隔室。使用最终的多柔比星和多柔比星醇模型，评估了清除率和分布容积与年龄和体重指数的潜在依赖性。
四室模型能最好地描述合并数据集的多柔比星和多柔比星醇数据。该模型包括一个比例残差模型，以及多柔比星清除率、外周室间清除率、多柔比星醇清除率、中央室、一个外周室和代谢产物室分布容积的个体间变异性。此外，还将体表面积作为所有药代动力学参数的协变量，并将多柔比星清除率和中央室分布容积的个体间变异性纳入模型中。对于体表面积为 1.8 m²的患者，多柔比星的清除率为 53.3 L/h（个体间变异性为 31%，个体间变异性为 13%），中央室分布容积为 17.7 L（个体间变异性为 19%，个体间变异性为 21%）。模型的残留变异性为多柔比星 22%，多柔比星醇 26%。多柔比星醇的清除率估计为 44 L/h（个体间变异性为 50%），代谢产物室的分布容积为 1150 L（个体间变异性为 57%）。对年龄依赖性和体重指数依赖性的评估表明，年轻患者的中央室分布容积（按体表面积归一化）较小，代谢产物室分布容积（按体重归一化）较高。
多柔比星和多柔比星醇的四室 NONMEM（R）模型能够较好地描述成人和儿童（>3 岁）的血浆浓度。未发现年龄对多柔比星或多柔比星醇清除率有明显影响，分析结果不支持对目前在儿童和成人中使用的剂量方案进行修改。
