Laboratory of Bioinformatics, Mathematical Modelling and Synthetic Biology, Department of Electrical, Computer and Biomedical Engineering, Università degli Studi di Pavia, Via Ferrata 5, 27100, Pavia, Italy.
Centre for Applied Pharmacokinetic Research, Division of Pharmacy & Optometry, The University of Manchester, Stopford Building, Oxford Road, Manchester, M13 9PT, UK.
J Pharmacokinet Pharmacodyn. 2019 Feb;46(1):27-42. doi: 10.1007/s10928-018-9615-8. Epub 2018 Dec 14.
Regulatory agencies have a strong interest in sensitivity analysis for the evaluation of physiologically-based pharmacokinetic (PBPK) models used in pharmaceutical research and drug development and regulatory submissions. One of the applications of PBPK is the prediction of fraction absorbed and bioavailability for drugs following oral administration. In this context, we performed a variance based global sensitivity analysis (GSA) on in-house PBPK models for drug absorption, with the aim of identifying key parameters that influence the predictions of the fraction absorbed and the bioavailability for neutral, acidic and basic compounds. This analysis was done for four different classes of drugs, defined according to the Biopharmaceutics Classification System, differentiating compounds by permeability and solubility. For class I compounds (highly permeable, highly soluble), the parameters that mainly influence the fraction absorbed are related to the formulation properties, for class II compounds (highly permeable, lowly soluble) to the dissolution process, for class III (lowly permeable, highly soluble) to both absorption process and formulation properties and for class IV (lowly permeable, lowly soluble) to both absorption and dissolution processes. Considering the bioavailability, the results are similar to those for the fraction absorbed, with the addition that parameters related to gut wall and liver clearance influence as well the predictions. This work aimed to give a demonstration of the GSA methodology and highlight its importance in improving our understanding of PBPK absorption models and in guiding the choice of parameters that can safely be assumed, estimated or require data generation to allow informed model prediction.
监管机构对于用于药物研究和开发以及监管申报的基于生理学的药代动力学(PBPK)模型的敏感性分析非常感兴趣。PBPK 的应用之一是预测口服给药后药物的吸收分数和生物利用度。在这种情况下,我们对药物吸收的内部 PBPK 模型进行了基于方差的全局敏感性分析(GSA),目的是确定影响吸收分数和生物利用度预测的关键参数,这些参数适用于中性、酸性和碱性化合物。根据生物药剂学分类系统(BCS),我们对四类不同的药物进行了分析,根据渗透性和溶解度对化合物进行区分。对于 I 类化合物(高渗透性、高溶解性),主要影响吸收分数的参数与制剂特性有关;对于 II 类化合物(高渗透性、低溶解性),主要影响溶解过程;对于 III 类化合物(低渗透性、高溶解性),主要影响吸收过程和制剂特性;对于 IV 类化合物(低渗透性、低溶解性),主要影响吸收和溶解过程。考虑到生物利用度,结果与吸收分数的结果相似,此外,与肠壁和肝脏清除相关的参数也会影响预测。这项工作旨在展示 GSA 方法,并强调其在提高我们对 PBPK 吸收模型的理解以及指导选择可以安全假定、估计或需要生成数据以允许明智的模型预测的参数方面的重要性。