Simcyp Limited (A Certara Company) , Blades Enterprise Centre, John Street, Sheffield, S2 4SU, United Kingdom.
Department of Pharmaceutical Technology, Johann Wolfgang Goethe University , Max-von-Laue-Strasse 9, Frankfurt am Main 60438, Germany.
Mol Pharm. 2017 Dec 4;14(12):4305-4320. doi: 10.1021/acs.molpharmaceut.7b00406. Epub 2017 Aug 25.
Mechanistic modeling of in vitro data generated from metabolic enzyme systems (viz., liver microsomes, hepatocytes, rCYP enzymes, etc.) facilitates in vitro-in vivo extrapolation (IVIV_E) of metabolic clearance which plays a key role in the successful prediction of clearance in vivo within physiologically-based pharmacokinetic (PBPK) modeling. A similar concept can be applied to solubility and dissolution experiments whereby mechanistic modeling can be used to estimate intrinsic parameters required for mechanistic oral absorption simulation in vivo. However, this approach has not widely been applied within an integrated workflow. We present a stepwise modeling approach where relevant biopharmaceutics parameters for ketoconazole (KTZ) are determined and/or confirmed from the modeling of in vitro experiments before being directly used within a PBPK model. Modeling was applied to various in vitro experiments, namely: (a) aqueous solubility profiles to determine intrinsic solubility, salt limiting solubility factors and to verify pK; (b) biorelevant solubility measurements to estimate bile-micelle partition coefficients; (c) fasted state simulated gastric fluid (FaSSGF) dissolution for formulation disintegration profiling; and (d) transfer experiments to estimate supersaturation and precipitation parameters. These parameters were then used within a PBPK model to predict the dissolved and total (i.e., including the precipitated fraction) concentrations of KTZ in the duodenum of a virtual population and compared against observed clinical data. The developed model well characterized the intraluminal dissolution, supersaturation, and precipitation behavior of KTZ. The mean simulated AUC of the total and dissolved concentrations of KTZ were comparable to (within 2-fold of) the corresponding observed profile. Moreover, the developed PBPK model of KTZ successfully described the impact of supersaturation and precipitation on the systemic plasma concentration profiles of KTZ for 200, 300, and 400 mg doses. These results demonstrate that IVIV_E applied to biopharmaceutical experiments can be used to understand and build confidence in the quality of the input parameters and mechanistic models used for mechanistic oral absorption simulations in vivo, thereby improving the prediction performance of PBPK models. Moreover, this approach can inform the selection and design of in vitro experiments, potentially eliminating redundant experiments and thus helping to reduce the cost and time of drug product development.
运用代谢酶系统(如肝微粒体、肝细胞、重组 CYP 酶等)产生的体外数据进行机制建模,有助于进行代谢清除的体外-体内外推(IVIV_E),这在成功预测体内生理相关药代动力学(PBPK)模型中的清除率方面起着关键作用。类似的概念也可以应用于溶解度和溶解实验,通过机制建模可以估算用于体内口服吸收模拟的内在参数。然而,这种方法尚未广泛应用于综合工作流程中。我们提出了一种逐步建模方法,该方法用于确定酮康唑(KTZ)的相关生物药剂学参数,并在直接用于 PBPK 模型之前,通过体外实验的建模对其进行确定或验证。该方法应用于各种体外实验,包括:(a)水溶解度曲线以确定内在溶解度、盐限制溶解度因素并验证 pK;(b)生物相关溶解度测量以估算胆汁-胶束分配系数;(c)空腹模拟胃液(FaSSGF)溶解用于制剂崩解特性分析;(d)转运实验以估计过饱和度和沉淀参数。然后,将这些参数用于 PBPK 模型中,以预测虚拟人群十二指肠中 KTZ 的溶解和总浓度(即包括沉淀部分),并与观察到的临床数据进行比较。所开发的模型很好地描述了 KTZ 的腔内溶解、过饱和度和沉淀行为。KTZ 的总浓度和溶解浓度的平均模拟 AUC 与相应的观察到的曲线相似(在 2 倍以内)。此外,所开发的 KTZ PBPK 模型成功描述了过饱和度和沉淀对 200、300 和 400 mg 剂量 KTZ 的全身血浆浓度曲线的影响。这些结果表明,应用于生物药剂学实验的 IVIV_E 可用于理解和建立对输入参数和用于体内口服吸收模拟的机制模型的质量的信心,从而提高 PBPK 模型的预测性能。此外,该方法可以为体外实验的选择和设计提供信息,可能消除多余的实验,从而有助于降低药物产品开发的成本和时间。