Department of Pharmaceutics, School of Pharmacy, University of Washington, Seattle, Washington, USA.
Clin Transl Sci. 2020 Jul;13(4):693-699. doi: 10.1111/cts.12750. Epub 2020 Feb 27.
A systematic analysis of the inhibition transporter data available in New Drug Applications of drugs approved by the US Food and Drug Administration (FDA) in 2018 (N = 42) was performed. In vitro-to-in vivo predictions using basic models were available for the nine transporters currently recommended for evaluation. Overall, 29 parents and 16 metabolites showed in vitro inhibition of at least one transporter, with the largest number of drugs found to be inhibitors of P-gp followed by BCRP. The most represented therapeutic areas were oncology drugs and anti-infective agents, each comprising 31%. Among drugs with prediction values greater than the FDA recommended cutoffs and further evaluated in vivo, 56% showed positive clinical interactions (area under the concentration-time curve ratio (AUCRs) ≥ 1.25). Although all the observed or simulated inhibitions were weak (AUCRs < 2), seven of the nine interactions (involving five drugs) resulted in labeling recommendations. Interestingly, more than half of the drugs with predictions greater than the cutoffs had no further evaluations, highlighting that current basic models represent a useful, simple first step to evaluate the clinical relevance of in vitro findings, but that multiple other factors are considered when deciding the need for clinical studies. Four drugs had prediction values less than the cutoffs but had clinical evaluations or physiologically-based pharmacokinetic simulations available. Consistent with the predictions, all of them were confirmed not to inhibit these transporters in vivo (AUCRs of 0.94-1.09). Overall, based on the clinical evaluations available, drugs approved in 2018 were found to have a relatively limited impact on drug transporters, with all victim AUCRs < 2.
对 2018 年美国食品和药物管理局（FDA）批准的新药申请（N=42）中可用的抑制转运体数据进行了系统分析。对于目前建议评估的九种转运体，使用基本模型进行了体外-体内预测。总体而言，有 29 种母体药物和 16 种代谢物显示出至少一种转运体的体外抑制作用，其中发现数量最多的药物是 P-糖蛋白（P-gp）抑制剂，其次是乳腺癌耐药蛋白（BCRP）抑制剂。代表性最强的治疗领域是肿瘤药物和抗感染药物，各占 31%。在预测值大于 FDA 推荐截止值并进一步进行体内评估的药物中，有 56%显示出阳性临床相互作用（浓度-时间曲线下面积比（AUCRs）≥1.25）。尽管所有观察到或模拟的抑制作用都很弱（AUCRs<2），但在 9 种相互作用中，有 7 种（涉及 5 种药物）导致了标签推荐。有趣的是，超过一半的预测值大于截止值的药物没有进一步评估，这表明当前的基本模型代表了一种有用的、简单的第一步，可以评估体外发现的临床相关性，但在决定是否需要进行临床研究时，还考虑了多个其他因素。有 4 种药物的预测值低于截止值，但有临床评估或基于生理的药代动力学模拟可用。与预测结果一致，所有这些药物在体内均未被证实抑制这些转运体（AUCRs 为 0.94-1.09）。总体而言，根据可用的临床评估，发现 2018 年批准的药物对药物转运体的影响相对有限，所有受者 AUCRs<2。
