Nihan Izat, Jayaprakasam Bolleddula, Pasquale Carione, Leticia Huertas Valentin, Robert S Jones, Priyanka Kulkarni, Darren Moss, Vincent C Peterkin, Dan-Dan Tian, Andrea Treyer, Karthik Venkatakrishnan, Michael A Zientek, Jill Barber, J Brian Houston, Aleksandra Galetin, Daniel Scotcher
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PBPK models were developed for capmatinib, idelalisib, lenvatinib, zaleplon, ziprasidone, and zoniporide, incorporating in vitro functional data from human liver subcellular fractions and human hepatocytes. Prediction of metabolic elimination with/without the additional empirical scaling factors (ESFs) was assessed. Clinical pharmacokinetics, human mass balance, and drug-drug interaction (DDI) studies with CYP3A4 modulators, where available, were used to refine/verify the models. Due to the lack of clinically significant AO-DDIs with known AO inhibitors, the fraction metabolized by AO (fm<sub>AO</sub>) was verified indirectly. Clearance predictions were improved by using ESFs (GMFE ≤1.4-fold versus up to fivefold with physiologically-based scaling only). Observed fm<sub>i</sub> from mass balance studies were crucial for model verification/refinement, as illustrated by capmatinib, where the fm<sub>AO</sub> (40%) was otherwise underpredicted up to fourfold. Subsequently, independent DDI studies with ketoconazole, itraconazole, rifampicin, and carbamazepine verified the fm<sub>CYP3A4</sub>, with predicted ratios of the area under the concentration-time curve (AUCR) within 1.5-fold of the observations. In conclusion, this study provides a novel PBPK-based framework for predicting AO-mediated pharmacokinetics and quantitative assessment of clinical DDI risks for dual AO-CYP substrates within a totality-of-evidence approach.</p>","PeriodicalId":10774,"journal":{"name":"CPT: Pharmacometrics & Systems Pharmacology","volume":" ","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Establishing a physiologically based pharmacokinetic framework for aldehyde oxidase and dual aldehyde oxidase-CYP substrates.\",\"authors\":\"Nihan Izat, Jayaprakasam Bolleddula, Pasquale Carione, Leticia Huertas Valentin, Robert S Jones, Priyanka Kulkarni, Darren Moss, Vincent C Peterkin, Dan-Dan Tian, Andrea Treyer, Karthik Venkatakrishnan, Michael A Zientek, Jill Barber, J Brian Houston, Aleksandra Galetin, Daniel Scotcher\",\"doi\":\"10.1002/psp4.13255\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Aldehyde oxidase (AO) contributes to the clearance of many approved and investigational small molecule drugs, which are often dual substrates of AO and drug-metabolizing enzymes such as cytochrome P450s (CYPs). As such, the lack of established framework for quantitative translation of the clinical pharmacologic correlates of AO-mediated clearance represents an unmet need. This study aimed to evaluate the utility of physiologically based pharmacokinetic (PBPK) modeling in the development of AO and dual AO-CYP substrates. PBPK models were developed for capmatinib, idelalisib, lenvatinib, zaleplon, ziprasidone, and zoniporide, incorporating in vitro functional data from human liver subcellular fractions and human hepatocytes. Prediction of metabolic elimination with/without the additional empirical scaling factors (ESFs) was assessed. Clinical pharmacokinetics, human mass balance, and drug-drug interaction (DDI) studies with CYP3A4 modulators, where available, were used to refine/verify the models. Due to the lack of clinically significant AO-DDIs with known AO inhibitors, the fraction metabolized by AO (fm<sub>AO</sub>) was verified indirectly. Clearance predictions were improved by using ESFs (GMFE ≤1.4-fold versus up to fivefold with physiologically-based scaling only). Observed fm<sub>i</sub> from mass balance studies were crucial for model verification/refinement, as illustrated by capmatinib, where the fm<sub>AO</sub> (40%) was otherwise underpredicted up to fourfold. Subsequently, independent DDI studies with ketoconazole, itraconazole, rifampicin, and carbamazepine verified the fm<sub>CYP3A4</sub>, with predicted ratios of the area under the concentration-time curve (AUCR) within 1.5-fold of the observations. In conclusion, this study provides a novel PBPK-based framework for predicting AO-mediated pharmacokinetics and quantitative assessment of clinical DDI risks for dual AO-CYP substrates within a totality-of-evidence approach.</p>\",\"PeriodicalId\":10774,\"journal\":{\"name\":\"CPT: Pharmacometrics & Systems Pharmacology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2024-10-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CPT: Pharmacometrics & Systems Pharmacology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1002/psp4.13255\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PHARMACOLOGY & PHARMACY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"CPT: Pharmacometrics & Systems Pharmacology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1002/psp4.13255","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 0
摘要
醛氧化酶(AO)有助于清除许多已批准和在研的小分子药物,这些药物通常是 AO 和药物代谢酶(如细胞色素 P450s,CYPs)的双重底物。因此,缺乏对 AO 介导的清除率的临床药理学相关性进行定量转化的既定框架是一项尚未满足的需求。本研究旨在评估基于生理学的药代动力学(PBPK)模型在 AO 和 AO-CYP 双底物开发中的实用性。结合人肝亚细胞组分和人肝细胞的体外功能数据,为卡马替尼、伊德拉利西、来伐替尼、扎来普隆、齐拉西酮和佐尼波利开发了PBPK模型。评估了使用/不使用附加经验缩放因子(ESF)的代谢消除预测。临床药代动力学、人体质量平衡以及与 CYP3A4 调节剂的药物相互作用 (DDI) 研究(如有)被用来完善/验证模型。由于缺乏与已知 AO 抑制剂的具有临床意义的 AO-DDI 研究,因此间接验证了经 AO 代谢的部分(fmAO)。通过使用 ESF,清除率预测得到了改善(GMFE ≤ 1.4 倍,而仅使用基于生理学的缩放比例则高达 5 倍)。质量平衡研究中观察到的 fmi 对模型验证/改进至关重要,卡马替尼就是一例,其 fmAO(40%)被低估了四倍。随后,对酮康唑、伊曲康唑、利福平和卡马西平进行的独立 DDI 研究验证了 fmCYP3A4,预测的浓度-时间曲线下面积(AUCR)比值在观察值的 1.5 倍以内。总之,本研究提供了一种基于 PBPK 的新框架,用于预测 AO 介导的药代动力学,并以证据整体法定量评估 AO-CYP 双底物的临床 DDI 风险。
Establishing a physiologically based pharmacokinetic framework for aldehyde oxidase and dual aldehyde oxidase-CYP substrates.
Aldehyde oxidase (AO) contributes to the clearance of many approved and investigational small molecule drugs, which are often dual substrates of AO and drug-metabolizing enzymes such as cytochrome P450s (CYPs). As such, the lack of established framework for quantitative translation of the clinical pharmacologic correlates of AO-mediated clearance represents an unmet need. This study aimed to evaluate the utility of physiologically based pharmacokinetic (PBPK) modeling in the development of AO and dual AO-CYP substrates. PBPK models were developed for capmatinib, idelalisib, lenvatinib, zaleplon, ziprasidone, and zoniporide, incorporating in vitro functional data from human liver subcellular fractions and human hepatocytes. Prediction of metabolic elimination with/without the additional empirical scaling factors (ESFs) was assessed. Clinical pharmacokinetics, human mass balance, and drug-drug interaction (DDI) studies with CYP3A4 modulators, where available, were used to refine/verify the models. Due to the lack of clinically significant AO-DDIs with known AO inhibitors, the fraction metabolized by AO (fmAO) was verified indirectly. Clearance predictions were improved by using ESFs (GMFE ≤1.4-fold versus up to fivefold with physiologically-based scaling only). Observed fmi from mass balance studies were crucial for model verification/refinement, as illustrated by capmatinib, where the fmAO (40%) was otherwise underpredicted up to fourfold. Subsequently, independent DDI studies with ketoconazole, itraconazole, rifampicin, and carbamazepine verified the fmCYP3A4, with predicted ratios of the area under the concentration-time curve (AUCR) within 1.5-fold of the observations. In conclusion, this study provides a novel PBPK-based framework for predicting AO-mediated pharmacokinetics and quantitative assessment of clinical DDI risks for dual AO-CYP substrates within a totality-of-evidence approach.