Varma Manthena V, Pang K Sandy, Isoherranen Nina, Zhao Ping
Pharmacokinetics, Dynamics and Metabolism, Pfizer Inc, Groton, Connecticut, USA.
Biopharm Drug Dispos. 2015 Mar;36(2):71-92. doi: 10.1002/bdd.1934. Epub 2015 Feb 10.
Unmanageable severe adverse events caused by drug-drug interactions (DDIs), leading to market withdrawals or restrictions in the clinical usage, are increasingly avoided with the improvement in our ability to predict such DDIs quantitatively early in drug development. However, significant challenges arise in the evaluation and/or prediction of complex DDIs caused by inhibitor drugs and/or metabolites that affect not one but multiple pathways of drug clearance. This review summarizes the discussion topics at the 2013 AAPS symposium on "Dealing with the complex drug-drug interactions: towards mechanistic models". Physiologically based pharmacokinetic (PBPK) models, in combination with the established in vitro-to-in vivo extrapolations of intestinal and hepatic disposition, have been successfully applied to predict clinical pharmacokinetics and DDIs, especially for drugs with CYP-mediated metabolism, and to explain transporter-mediated and complex DDIs. Although continuous developments are being made towards improved mechanistic prediction of the transporter-enzyme interplay in the hepatic and intestinal disposition and characterizing the metabolites contribution to DDIs, the prediction of DDIs involving them remains difficult. Regulatory guidelines also recommended use of PBPK modeling for the quantitative prediction and evaluation of DDIs involving multiple perpetrators and metabolites. Such mechanistic modeling approaches culminate to the consensus that modeling is helpful in predicting DDIs or quantitatively rationalizing the clinical findings in complex situations. Furthermore, they provide basis for the prediction and/or understanding the pharmacokinetics in populations like patients with renal impairment, pediatrics, or various ethnic groups where the conduct of clinical studies might not be feasible in early drug development stages and yet some guidance on management of dosage is necessary.
随着我们在药物研发早期对药物相互作用（DDIs）进行定量预测能力的提高，由药物相互作用导致的难以控制的严重不良事件（这些事件会导致药物退出市场或临床使用受限）越来越多地得以避免。然而，在评估和/或预测由抑制剂药物和/或代谢物引起的复杂药物相互作用时，出现了重大挑战，这些抑制剂药物和/或代谢物会影响不止一条而是多条药物清除途径。本综述总结了2013年美国药学协会（AAPS）关于“应对复杂的药物相互作用：建立机制模型”研讨会的讨论主题。基于生理的药代动力学（PBPK）模型，结合已确立的肠道和肝脏处置的体外到体内外推法，已成功应用于预测临床药代动力学和药物相互作用，特别是对于具有细胞色素P450（CYP）介导代谢的药物，并用于解释转运体介导的和复杂的药物相互作用。尽管在改进对肝脏和肠道处置中转运体 - 酶相互作用的机制预测以及表征代谢物对药物相互作用的贡献方面不断取得进展，但涉及它们的药物相互作用的预测仍然困难。监管指南也建议使用PBPK模型对涉及多种作用物和代谢物的药物相互作用进行定量预测和评估。这种机制建模方法最终达成了这样的共识，即建模有助于预测药物相互作用或在复杂情况下对临床发现进行定量合理化解释。此外，它们为预测和/或理解肾功能不全患者、儿科患者或不同种族群体等人群的药代动力学提供了基础，在药物研发早期进行临床研究可能不可行，但仍需要一些剂量管理方面的指导。
