Age Related Changes in Fractional Elimination Pathways for Drugs: Assessing the Impact of Variable Ontogeny on Metabolic Drug-Drug Interactions
Age Related Changes in Fractional Elimination Pathways for Drugs: Assessing the Impact of Variable Ontogeny on Metabolic Drug-Drug Interactions
复制标题
DOI：
10.1002/jcph.100
复制
发表时间：
2013-08-01
影响因子：
2.9
通讯作者：
Rostami-Hodjegan, Amin
中科院分区：
文献类型：
--
作者：
Salem, Farzaneh;Johnson, Trevor N.;Rostami-Hodjegan, Amin
任何代谢性药物-药物相互作用（ddi）的程度取决于抑制途径的重要性，与成人相比，幼儿可能不一定相同。系统分析细胞色素P450 （CYP）酶（CYPs 1A2、2B6、2C8、2C9、2C18/19、2D6、2E1、3A4）与肾功能的个体发生模式。Bootstrap方法用于解释变异，并定义每对特定路径之间存在统计差异的年龄范围。模拟了许多DDI （Simcyp Pediatric v12）虚拟化合物，以突出年龄对DDI分数消除的影响和随后的DDI大小。对于在出生时CYP2D6和CYP3A4途径各代谢50%的理论药物，联合使用酮康唑（3mg/kg）导致抑制与未抑制AUC之间的差异为1.65倍，而1岁儿童为2.4倍，成人为3.2倍。相反，在某些情况下，新生儿可能比成年人对DDI更敏感。因此，从成人数据推断可能不适用于所有儿科年龄组。使用基于儿童生理的药代动力学（p-PBPK）模型可能为发现没有现有儿童临床数据的潜在DDI易感性时期提供一个临时解决方案。
The magnitude of any metabolic drug-drug interactions (DDIs) depends on fractional importance of inhibited pathway which may not necessarily be the same in young children when compared to adults. The ontogeny pattern of cytochrome P450 (CYP) enzymes (CYPs 1A2, 2B6, 2C8, 2C9, 2C18/19, 2D6, 2E1, 3A4) and renal function were analyzed systematically. Bootstrap methodology was used to account for variability, and to define the age range over which statistical differences existed between each pair of specific pathways. A number of DDIs were simulated (Simcyp Pediatric v12) for virtual compounds to highlight effects of age on fractional elimination and consequent magnitude of DDI. For a theoretical drug metabolized 50% by each of CYP2D6 and CYP3A4 pathways at birth, co-administration of ketoconazole (3mg/kg) resulted in a 1.65-fold difference between inhibited versus uninhibited AUC compared to 2.4-fold in 1 year olds and 3.2-fold in adults. Conversely, neonates could be more sensitive to DDI than adults in certain scenarios. Thus, extrapolation from adult data may not be applicable across all pediatric age groups. The use of pediatric physiologically based pharmacokinetic (p-PBPK) models may offer an interim solution to uncovering potential periods of vulnerability to DDI where there are no existing clinical data derived from children.