Franco Yesenia L, Da Silva Lais, Charbe Nitin, Kinvig Hannah, Kim Soyoung, Cristofoletti Rodrigo
Center for Pharmacometrics & Systems Pharmacology, Department of Pharmaceutics (Lake Nona), University of Florida, Orlando, FL, USA.
Pharm Res. 2023 Feb;40(2):405-418. doi: 10.1007/s11095-023-03478-0. Epub 2023 Feb 14.
Ketoconazole and posaconazole are two weakly basic broad-spectrum antifungals classified as Biopharmaceutics Classification System class II drugs, indicating that they are highly permeable, but exhibit poor solubility. As a result, oral bioavailability and clinical efficacy can be impacted by the formulation performance in the gastrointestinal system. In this work, we have leveraged in vitro biopharmaceutics and clinical data available in the literature to build physiologically based pharmacokinetic (PBPK) models for ketoconazole and posaconazole, to determine the suitability of forward in vitro-in vivo translation for characterization of in vivo drug precipitation, and to predict food effect.
A stepwise modeling approach was utilized to derive key parameters related to absorption, such as drug solubility, dissolution, and precipitation kinetics from in vitro data. These parameters were then integrated into PBPK models for the simulation of ketoconazole and posaconazole plasma concentrations in the fasted and fed states.
Forward in vitro-in vivo translation of intestinal precipitation kinetics for both model drugs resulted in poor predictions of PK profiles. Therefore, a reverse translation approach was applied, based on limited fitting of precipitation-related parameters to clinical data. Subsequent simulations for ketoconazole and posaconazole demonstrated that fasted and fed state PK profiles for both drugs were adequately recapitulated.
The two examples presented in this paper show how middle-out modeling approaches can be used to predict the magnitude and direction of food effects provided the model is verified on fasted state PK data.
酮康唑和泊沙康唑是两种弱碱性广谱抗真菌药物，属于生物药剂学分类系统的II类药物，这表明它们具有高渗透性，但溶解度较差。因此，口服生物利用度和临床疗效可能会受到胃肠道系统中制剂性能的影响。在这项工作中，我们利用文献中可用的体外生物药剂学和临床数据，构建了酮康唑和泊沙康唑的生理药代动力学（PBPK）模型，以确定体外-体内正向翻译用于体内药物沉淀表征的适用性，并预测食物效应。
采用逐步建模方法从体外数据中推导与吸收相关的关键参数，如药物溶解度、溶解和沉淀动力学。然后将这些参数整合到PBPK模型中，以模拟酮康唑和泊沙康唑在禁食和进食状态下的血浆浓度。
两种模型药物肠道沉淀动力学的体外-体内正向翻译对药代动力学特征的预测效果较差。因此，基于将与沉淀相关的参数有限度地拟合到临床数据，应用了反向翻译方法。随后对酮康唑和泊沙康唑的模拟表明，两种药物在禁食和进食状态下的药代动力学特征均得到了充分再现。
本文给出的两个例子表明，只要模型在禁食状态药代动力学数据上得到验证，中间-out建模方法可如何用于预测食物效应的大小和方向。
