A Physiologically Based Pharmacokinetic Model for Optimally Profiling Lamotrigine Disposition and Drug-Drug Interactions

被引:13
|
作者
Conner, Todd M. [1 ]
Reed, Ronald C. [2 ]
Zhang, Tao [1 ]
机构
[1] Husson Univ, Sch Pharm, 1 Coll Circle, Bangor, ME 04401 USA
[2] West Virginia Univ, Sch Pharm, 1124 Hlth Sci Ctr North, Morgantown, WV 26506 USA
关键词
HUMAN UDP-GLUCURONOSYLTRANSFERASE; DIFFUSION-CONTROLLED DISSOLUTION; STEADY-STATE PHARMACOKINETICS; ANTIEPILEPTIC DRUGS; POPULATION PHARMACOKINETICS; IMMEDIATE-RELEASE; EXTENDED-RELEASE; VALPROIC ACID; PHARMACODYNAMIC INTERACTIONS; SPHERICAL-PARTICLES;
D O I
10.1007/s13318-018-0532-4
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Background and ObjectivesLamotrigine (Lamictal((R))) is a broad-spectrum antiepileptic drug available in both immediate-(IR) and extended-release (XR) formulations. Here, we present a new physiologically based pharmacokinetic (PBPK) model for IR and XR formulations of lamotrigine to predict disposition in adults and children, plus drug-drug interactions (DDIs).MethodsModels for lamotrigine IR and XR formulations were constructed using a Simcyp((R)) Simulator. Concentration-time profiles were simulated for lamotrigine IR single (S-D) and steady-state (SS) doses ranging from 25 to 200mg in adults, as well as 2mg/kg (S-D), and 7.7-9.4mg/kg (SS) in children aged between 4 and 17years. Lamotrigine XR profiles were simulated for S-D and SS doses ranging from 250 to 400mg. DDI prediction with lamotrigine was simulated in adults with enzyme-inducing drugs, rifampin(rifampicin) and ritonavir, as well as the enzyme inhibitor, valproic acid.ResultsThe lamotrigine model predicted adult area-under-the-curve (AUC) and peak plasma concentration (C-max) results for IR S-D within 35% of observed data; lamotrigine IR SS dosing was within 10% and 30% of observed data, respectively. Pediatric lamotrigine IR S-D AUC and C-max values were within 10% and 15% of observed data, respectively. AUC and C-max values for lamotrigine XR S-D simulated in adults were within 20% of observed data; similarly lamotrigine XR SS parameters were within 10%. Concerning DDI simulation in adults, predicted-to-observed lamotrigine AUC ratios [AUC(DDI)/AUC(alone)] were within 15% for ritonavir and rifampin, and 20% for valproic acid.ConclusionsOur developed PBPK lamotrigine profile accurately predicts DDIs and lamotrigine IR/XR formulation disposition in adults and children. This PBPK model will be helpful in designing future DDI studies for co-administration of lamotrigine with other drugs and in designing individualized patient dosing regimens.
引用
收藏
页码:389 / 408
页数:20
相关论文
共 50 条
  • [41] A physiologically-based pharmacokinetic precision dosing approach to manage dasatinib drug-drug interactions
    Kovar, Christina
    Loer, Helena Leonie Hanae
    Ruedesheim, Simeon
    Fuhr, Laura Maria
    Marok, Fatima Zahra
    Selzer, Dominik
    Schwab, Matthias
    Lehr, Thorsten
    [J]. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY, 2024, 13 (07): : 1144 - 1159
  • [42] Physiologically Based Pharmacokinetic Modeling of Rosuvastatin to Predict Transporter-Mediated Drug-Drug Interactions
    Hanke, Nina
    Gomez-Mantilla, Jose David
    Ishiguro, Naoki
    Stopfer, Peter
    Nock, Valerie
    [J]. PHARMACEUTICAL RESEARCH, 2021, 38 (10) : 1645 - 1661
  • [43] Physiologically Based Pharmacokinetic Models of Probenecid and Furosemide to Predict Transporter Mediated Drug-Drug Interactions
    Hannah Britz
    Nina Hanke
    Mitchell E. Taub
    Ting Wang
    Bhagwat Prasad
    Éric Fernandez
    Peter Stopfer
    Valerie Nock
    Thorsten Lehr
    [J]. Pharmaceutical Research, 2020, 37
  • [44] QUANTITATIVE PREDICTIONS AND PHYSIOLOGICALLY BASED PHARMACOKINETIC MODELING OF DRUG-DRUG INTERACTIONS BASED ON RETROSPECTIVE LITERATURE DATA
    Zhao, Ping
    [J]. DRUG METABOLISM REVIEWS, 2015, 47 : 9 - 9
  • [45] Ribociclib Drug-Drug Interactions: Clinical Evaluations and Physiologically-Based Pharmacokinetic Modeling to Guide Drug Labeling
    Samant, Tanay S.
    Huth, Felix
    Umehara, Kenichi
    Schiller, Hilmar
    Dhuria, Shyeilla, V
    Elmeliegy, Mohamed
    Miller, Michelle
    Chakraborty, Abhijit
    Heimbach, Tycho
    He, Handan
    Ji, Yan
    [J]. CLINICAL PHARMACOLOGY & THERAPEUTICS, 2020, 108 (03) : 575 - 585
  • [46] Developing a physiologically based pharmacokinetic model of apixaban to predict scenarios of drug-drug interactions, renal impairment and paediatric populations
    Xu, Ruijuan
    Tang, Hong
    Chen, Lin
    Ge, Weihong
    Yang, Jin
    [J]. BRITISH JOURNAL OF CLINICAL PHARMACOLOGY, 2021, 87 (08) : 3244 - 3254
  • [47] Prediction of pharmacokinetic drug-drug interactions causing atorvastatin-induced rhabdomyolysis using physiologically based pharmacokinetic modelling
    Li, Size
    Yu, Yiqun
    Jin, Zhiping
    Dai, Yu
    Lin, Haishu
    Jiao, Zheng
    Ma, Guo
    Cai, Weimin
    Han, Bing
    Xiang, Xiaoqiang
    [J]. BIOMEDICINE & PHARMACOTHERAPY, 2019, 119
  • [48] Prediction of Renal Transporter Mediated Drug-Drug Interactions for Pemetrexed Using Physiologically Based Pharmacokinetic Modeling
    Posada, Maria M.
    Bacon, James A.
    Schneck, Karen B.
    Tirona, Rommel G.
    Kim, Richard B.
    Higgins, J. William
    Pak, Y. Anne
    Hall, Stephen D.
    Hillgren, Kathleen M.
    [J]. DRUG METABOLISM AND DISPOSITION, 2015, 43 (03) : 325 - 334
  • [49] Modeling the complexity of drug-drug interactions: A physiologically-based pharmacokinetic study of Lenvatinib with Schisantherin A/Schisandrin A
    Zheng, Aole
    Yang, Dongsheng
    Pan, Chunyang
    He, Qingfeng
    Zhu, Xiao
    Xiang, Xiaoqiang
    Ji, Peiying
    [J]. EUROPEAN JOURNAL OF PHARMACEUTICAL SCIENCES, 2024, 196
  • [50] PHYSIOLOGICALLY-BASED PHARMACOKINETIC MODELING (PBPK) OF PITAVASTATIN AND ATORVASTATIN TO PREDICT DRUG-DRUG INTERACTIONS (DDIS).
    Duan, P.
    Zhao, P.
    Zhang, L.
    [J]. CLINICAL PHARMACOLOGY & THERAPEUTICS, 2015, 97 : S16 - S17