Global Clinical Pharmacology and Exploratory Development, Astellas Pharma Global Development Europe, Elisabethhof, 1 2353 EW Leiderdorp, The Netherlands.
Drug Metab Dispos. 2011 Jul;39(7):1278-87. doi: 10.1124/dmd.110.037838. Epub 2011 Apr 12.
The application of model-based drug development in special populations becomes increasingly important for clinical trial optimization, mostly by providing a rationale for dose selection and thereby aiding risk-benefit assessment. In this article, a semiphysiological approach is presented, enabling the extrapolation of the pharmacokinetics from healthy subjects to patients with different disease conditions. This semiphysiological approach was applied to solifenacin, using clinical data on total and free plasma and urine concentrations in healthy subjects. The analysis was performed using nonlinear mixed-effects modeling and relied on the use of a general partitioning framework to account for binding to plasma proteins and to nonplasma tissues together with principles from physiology that apply to the main pharmacokinetic process, i.e., bioavailability, distribution, and elimination. Application of these physiology principles allowed quantification of the impact of key physiological parameters (i.e., body composition, glomerular function, liver enzyme capacity, and liver blood flow) on the pharmacokinetics of solifenacin. The prediction of the time course of the drug concentration in liver- and renal-impaired patients only required adjustment of the physiological parameters that are known to change upon liver and renal dysfunction without modifying the pharmacokinetic model structure and/or its respective parameter estimates. Visual predictive checks showed that the approach applied was able to adequately predict the pharmacokinetics of solifenacin in liver- and renal-impaired patients. In addition, better insight into the pharmacokinetic properties of solifenacin was obtained. In conclusion, the proposed semiphysiological approach is attractive for prediction of altered pharmacokinetics of compounds influenced by liver and renal disease conditions.
基于模型的药物开发在特殊人群中的应用对于临床试验优化变得越来越重要，主要是通过为剂量选择提供依据，从而帮助进行风险-获益评估。本文提出了一种半生理方法，能够将健康受试者的药代动力学数据外推至患有不同疾病的患者。该半生理方法应用于索利那新，使用了健康受试者的总血浆和游离血浆及尿液浓度的临床数据。分析采用非线性混合效应模型，并依赖于使用通用分区框架来考虑与血浆蛋白和非血浆组织的结合，以及适用于主要药代动力学过程（即生物利用度、分布和消除）的生理学原理。应用这些生理学原理可以定量评估关键生理参数（即身体成分、肾小球功能、肝酶能力和肝血流量）对索利那新药代动力学的影响。仅需要调整已知在肝肾功能障碍时发生变化的生理参数，即可预测肝肾功能损害患者的药物浓度时程，而无需修改药代动力学模型结构和/或其各自的参数估计。视觉预测检查表明，应用的方法能够充分预测肝肾功能损害患者的索利那新药代动力学。此外，还可以更好地了解索利那新的药代动力学特性。总之，所提出的半生理方法对于预测受肝肾功能障碍影响的化合物的改变药代动力学具有吸引力。
