Quantitative Assessment of Elagolix Enzyme-Transporter Interplay and Drug–Drug Interactions Using Physiologically Based Pharmacokinetic Modeling

作者
Manoj Chiney,Juki Ng,John P. Gibbs,Mohamad Shebley
出处
期刊:Clinical Pharmacokinectics [Adis, Springer Healthcare]
卷期号:59 (5): 617-627 被引量:26
标识
DOI:10.1007/s40262-019-00833-6
摘要

Elagolix is approved for the management of moderate-to-severe pain associated with endometriosis. The aim of this analysis was to develop a physiologically based pharmacokinetic (PBPK) model that describes the enzyme-transporter interplay involved in the disposition of elagolix and to predict the magnitude of drug–drug interaction (DDI) potential of elagolix as an inhibitor of P-glycoprotein (P-gp) and inducer of cytochrome P450 (CYP) 3A4. A PBPK model (SimCYP ® version 15.0.86.0) was developed using elagolix data from in vitro, clinical PK and DDI studies. Data from DDI studies were used to quantify contributions of the uptake transporter organic anion transporting polypeptide (OATP) 1B1 and CYP3A4 in the disposition of elagolix, and to quantitatively assess the perpetrator potential of elagolix as a CYP3A4 inducer and P-gp inhibitor. After accounting for the interplay between elagolix metabolism by CYP3A4 and uptake by OATP1B1, the model-predicted PK parameters of elagolix along with the DDI AUC ∞ and C max ratios, were within 1.5-fold of the observed data. Based on model simulations, elagolix 200 mg administered twice daily is a moderate inducer of CYP3A4 (approximately 56% reduction in midazolam AUC ∞ ). Simulations of elagolix 150 mg administered once daily with digoxin predicted an increase in digoxin C max and AUC ∞ by 68% and 19%, respectively. A PBPK model of elagolix was developed, verified, and applied to characterize the disposition interplay between CYP3A4 and OATP1B1, and to predict the DDI potential of elagolix as a perpetrator under dosing conditions that were not tested clinically. PBPK model-based predictions were used to support labeling language for DDI recommendations of elagolix.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
1秒前
aa发布了新的文献求助10
1秒前
1秒前
152455发布了新的文献求助10
1秒前
2秒前
2秒前
CipherSage应助土豆采纳,获得10
3秒前
wanci应助科研通管家采纳,获得30
3秒前
酷波er应助祁忆采纳,获得10
3秒前
小马甲应助科研通管家采纳,获得10
3秒前
molihuakai应助科研通管家采纳,获得10
3秒前
彭于晏应助slimm采纳,获得10
4秒前
搜集达人应助sxystc采纳,获得10
4秒前
桐桐应助科研通管家采纳,获得10
4秒前
xiangdemeilo发布了新的文献求助10
4秒前
Owen应助科研通管家采纳,获得10
4秒前
桐桐应助科研通管家采纳,获得10
4秒前
orixero应助科研通管家采纳,获得10
4秒前
靓丽的魔镜发布了新的文献求助500
4秒前
4秒前
阳光血茗完成签到,获得积分10
4秒前
Owen应助科研通管家采纳,获得10
4秒前
5秒前
skskysky应助科研通管家采纳,获得10
5秒前
5秒前
汉堡包应助科研通管家采纳,获得10
5秒前
金磊应助科研通管家采纳,获得10
5秒前
5秒前
NexusExplorer应助长小右采纳,获得10
5秒前
余咋发布了新的文献求助10
5秒前
我是老大应助科研通管家采纳,获得10
5秒前
红叶再开应助科研通管家采纳,获得10
6秒前
6秒前
JamesPei应助科研通管家采纳,获得10
6秒前
Bot应助自知则知之采纳,获得10
6秒前
Ava应助科研通管家采纳,获得10
6秒前
FashionBoy应助自知则知之采纳,获得10
6秒前
哈哈哈发布了新的文献求助10
6秒前
SciGPT应助科研通管家采纳,获得30
6秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
APA handbook of comparative psychology: Basic concepts, methods, neural substrate, and behavior 1000
全员动态考核,锚定高质量发展:读懂同济大学教师人事改革新政的深层价值 900
Health Psychology 800
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
Römisch-Germanische Forschungen 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7595044
求助须知:如何正确求助?哪些是违规求助? 9171857
关于积分的说明 19633474
捐赠科研通 7172469
什么是DOI,文献DOI怎么找? 3267793
关于科研通互助平台的介绍 2432572
邀请新用户注册赠送积分活动 2260806