Pharmacokinetic and -dynamic modelling of G-CSF derivatives in humans.
Pharmacokinetic and -dynamic modelling of G-CSF derivatives in humans.
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DOI：
10.1186/1742-4682-9-32
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发表时间：
2012-07-30
影响因子：
--
通讯作者：
Loeffler M
中科院分区：
文献类型：
--
作者：
Scholz M;Schirm S;Wetzler M;Engel C;Loeffler M
人粒细胞集落刺激因子（G-CSF）通常用于支持细胞毒性化疗过程中粒细胞生成的恢复。然而，药物的最佳使用在很大程度上是未知的。我们在过去表明，人类粒细胞生成的生物数学隔室模型可用于对新的，但未经测试的化疗方案进行临床相关的预测。在本文中，我们的目的是扩展这个模型的两个常用的G-CSF衍生物非格司亭和培非格司亭的详细的药代动力学和动力学建模。模型方程基于我们对药物的生理学理解，这些药物在应用于皮下组织时具有G-CSF的延迟吸收、剂量依赖性生物利用度、非特异性一级消除、依赖于粒细胞计数的特异性消除和可逆的蛋白结合。将非格司亭和培非格司亭之间的药代动力学差异建模为不同的参数集。除了一些额外的假设和简化之外，我们以前的粒细胞生成细胞动力学模型基本上得到了保留。我们假设G-CSF对骨髓的延迟作用，化疗的延迟作用以及非格司亭和培非格司亭之间在骨髓刺激效力方面的差异。此外，我们纳入了培非格司亭和非格司亭或内源性G-CSF的联合作用模型，这些药物通过同时受体结合相互作用。未知的药代动力学或细胞动力学参数通过将模型的预测与G-CSF应用、化疗应用或其组合的可用数据集拟合来确定。模型预测与用于参数估计和验证情景的数据集都拟合良好。确定了一套独特的参数，适用于所考虑的所有情况。非格司亭和培非格司亭之间药代动力学参数估计值的差异始终具有生物学合理性。我们的结论是，我们建立了一个全面的生物数学模型来解释化疗和两种不同的G-CSF衍生物的应用下的粒细胞生成的动力学。我们的目标是将该模型应用于未来的各种化疗方案，以优化相应的G-CSF方案或根据患者的粒细胞毒性风险进行个体化G-CSF治疗。
The human granulocyte colony-stimulating factor (G-CSF) is routinely applied to support recovery of granulopoiesis during the course of cytotoxic chemotherapies. However, optimal use of the drug is largely unknown. We showed in the past that a biomathematical compartment model of human granulopoiesis can be used to make clinically relevant predictions regarding new, yet untested chemotherapy regimen. In the present paper, we aim to extend this model by a detailed pharmacokinetic and -dynamic modelling of two commonly used G-CSF derivatives Filgrastim and Pegfilgrastim. Model equations are based on our physiological understanding of the drugs which are delayed absorption of G-CSF when applied to the subcutaneous tissue, dose-dependent bioavailability, unspecific first order elimination, specific elimination in dependence on granulocyte counts and reversible protein binding. Pharmacokinetic differences between Filgrastim and Pegfilgrastim were modelled as different parameter sets. Our former cell-kinetic model of granulopoiesis was essentially preserved, except for a few additional assumptions and simplifications. We assumed a delayed action of G-CSF on the bone marrow, a delayed action of chemotherapy and differences between Filgrastim and Pegfilgrastim with respect to stimulation potency of the bone marrow. Additionally, we incorporated a model of combined action of Pegfilgrastim and Filgrastim or endogenous G-CSF which interact via concurrent receptor binding. Unknown pharmacokinetic or cell-kinetic parameters were determined by fitting the predictions of the model to available datasets of G-CSF applications, chemotherapy applications or combinations of it. Data were either extracted from the literature or were received from cooperating clinical study groups. Model predictions fitted well to both, datasets used for parameter estimation and validation scenarios as well. A unique set of parameters was identified which is valid for all scenarios considered. Differences in pharmacokinetic parameter estimates between Filgrastim and Pegfilgrastim were biologically plausible throughout. We conclude that we established a comprehensive biomathematical model to explain the dynamics of granulopoiesis under chemotherapy and applications of two different G-CSF derivatives. We aim to apply the model to a large variety of chemotherapy regimen in the future in order to optimize corresponding G-CSF schedules or to individualize G-CSF treatment according to the granulotoxic risk of a patient.
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