A Proposal for a Pharmacokinetic Interaction Significance Classification System (PISCS) Based on Predicted Drug Exposure Changes and Its Potential Application to Alert Classifications in Product Labelling
A Proposal for a Pharmacokinetic Interaction Significance Classification System (PISCS) Based on Predicted Drug Exposure Changes and Its Potential Application to Alert Classifications in Product Labelling
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DOI：
10.2165/11317220-000000000-00000
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发表时间：
2009-01-01
影响因子：
4.5
通讯作者：
Suzuki, Hiroshi
中科院分区：
文献类型：
--
作者：
Hisaka, Akihiro;Kusama, Makiko;Suzuki, Hiroshi
背景和目的：药代动力学药物相互作用（DDI）是药物治疗中不良事件的主要原因之一，系统预测 DDI 的临床相关性是一个具有重要临床意义的问题。在先前的研究中，利用体内信息成功预测了抑制剂药物共同给药引起的多种细胞色素P450（CYP）3A4底物药物的总暴露量变化。为了在日常药物治疗中利用这些预测，需要仔细评估药代动力学变化的临床意义。本研究的目的是构建一个药代动力学相互作用重要性分类系统（PISCS），其中系统地考虑DDI的临床意义和药代动力学变化。此外，将PISCS提出的分类与当前日本、美国和英国使用的产品标签或产品特性摘要中的警报分类进行了详细比较。方法：通过对预测的两个基本参数分层构成矩阵表：CYP3A4对底物口服清除率（CR）的贡献率和抑制剂的抑制率（IR）。通过关联 CR 和 IR 值来估计表中每个单元格的总暴露增量，并根据暴露增量的大小将单元格分为九个区域。然后，考虑到观察到的暴露变化和产品标签中的当前分类，确定每个药物组的 DDI 显着性和区域之间的对应关系。从三个治疗组中选择的 CYP3A4 底物药物，即 HMG-CoA 还原酶抑制剂（他汀类药物）、钙通道拮抗剂/阻断剂（CCB）和苯二氮卓类药物（BZP），作为代表性实例进行了分析。日本、美国和英国药物的产品标签说明是从各个监管机构的网站获得的。结果：在调查的 220 个药物组合中，41 个组合的估计暴露量变化超过 5 倍，其中 10 个组合至少在一个国家的产品标签中没有警示；这些涉及丁螺环酮、尼索地平和非洛地平作为底物，以及酮康唑、伏立康唑、泰利霉素、克拉霉素和奈法唑酮作为抑制剂。对于这些药物组合，警报分类预计可能不合适。在当前的产品标签中，还注意到许多国家间差异。考虑到先前观察到的暴露变化与当前警报分类之间的关系，“禁忌症”和“警告/注意”之间的界限被确定为他汀类药物和 CCB 的暴露增加 7 倍，BZP 的暴露增加 4 倍。 PISCS 按照确定的边界清晰地区分了这些药物组合。即使对于未来的药物，PISCS 的分类预计也是有效的，因为分类是按区域进行的，而不是通过指定单个药物进行的。结论：目前的分析表明，许多当前的警报分类可能不合适，特别是对于尚未评估药代动力学的药物组合。预计 PISCS 将有助于为广泛的药代动力学 DDI 构建无泄漏警报系统。需要在关键药物组合的临床研究中进一步验证 PISCS，并将其扩展到其他 CYP 和代谢酶仍有待实现。
Background and Objective: Pharmacokinetic drug-drug interactions (DDIs) are one of the major causes of adverse events in pharmacotherapy, and systematic prediction of the clinical relevance of DDIs is an issue of significant clinical importance. In a previous study, total exposure changes of many substrate drugs of cytochrome P450 (CYP) 3A4 caused by coadministration of inhibitor drugs were successfully predicted by using in vivo information. In order to exploit these predictions in daily pharmacotherapy, the clinical significance of the pharmacokinetic changes needs to be carefully evaluated. The aim of the present study was to construct a pharmacokinetic interaction significance classification system (PISCS) in which the clinical significance of DDIs was considered with pharmacokinetic changes in a systematic manner. Furthermore, the classifications proposed by PISCS were compared in a detailed manner with current alert classifications in the product labelling or the summary of product characteristics used in Japan, the US and the UK.Methods: A matrix table was composed by stratifying two basic parameters of the prediction: the contribution ratio of CYP3A4 to the oral clearance of substrates (CR), and the inhibition ratio of inhibitors (IR). The total exposure increase was estimated for each cell in the table by associating CR and IR values, and the cells were categorized into nine zones according to the magnitude of the exposure increase. Then, correspondences between the DDI significance and the zones were determined for each drug group considering the observed exposure changes and the current classification in the product labelling. Substrate drugs of CYP3A4 selected from three therapeutic groups, i.e. HMG-CoA reductase inhibitors (statins), calcium-channel antagonists/blockers (CCBs) and benzodiazepines (BZPs), were analysed as representative examples. The product labelling descriptions of drugs in Japan, US and UK were obtained from the websites of each regulatory body.Results: Among 220 combinations of drugs investigated, estimated exposure changes were more than 5-fold for 41 combinations in which ten combinations were not alerted in the product labelling at least in one country; these involved buspirone, nisoldipine and felodipine as substrates, and ketoconazole, voriconazole, telithromycin, clarithromycin and nefazodone as inhibitors. For those drug combinations, the alert classifications were anticipated as potentially inappropriate. In the current product labelling, many inter-country differences were also noted. Considering the relationships between previously observed exposure changes and the current alert classifications, the boundaries between 'contraindication' and 'warning/caution' were determined as a 7-fold exposure increase for statins and CCBs, and as a 4-fold increase for BZPs. PISCS clearly discriminated these drug combinations in accordance with the determined boundaries. Classifications by PISCS were expected to be valid even for future drugs because the classifications were made by zones, not by designating individual drugs.Conclusion: The present analysis suggested that many current alert classifications were potentially inappropriate especially for drug combinations where pharmacokinetics had not been evaluated. It is expected that PISCS would contribute to constructing a leak-less alerting system for a broad range of pharmacokinetic DDIs. Further validation of PISCS is required in clinical studies with key drug combinations, and its extension to other CYP and metabolizing enzymes remains to be achieved.