Retrospective use of PBPK modelling to understand a clinical drug-drug interaction between dextromethorphan and GSK1034702

被引:1
|
作者
Hobbs, Michael J. [1 ]
Bloomer, Jackie [1 ]
Dear, Gordon [1 ]
机构
[1] GlaxoSmithKline, Pk Rd, Ware SG12 0DP, Herts, England
关键词
CYP2D6; dextromethorphan; drug-drug interaction; GSK1034702; in silico modelling; metabolism-dependent inhibition; MECHANISM-BASED INHIBITION; HUMAN LIVER-MICROSOMES; IN-VITRO; DEPENDENT INHIBITION; P-GLYCOPROTEIN; CYP2D6; PREDICTION; PHARMACOKINETICS; METABOLITES; HUMANS;
D O I
10.1080/00498254.2016.1216630
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
1.In a clinical trial, a strong drug-drug interaction (DDI) was observed between dextromethorphan (DM, the object or victim drug) and GSK1034702 (the precipitant or perpetrator drug), following single and repeat doses. This study determined the inhibition parameters of GSK1034702 in vitro and applied PBPK modelling approaches to simulate the clinical observations and provide mechanistic hypotheses to understand the DDI. 2.In vitro assays were conducted to determine the inhibition parameters of human CYP2D6 by GSK1034702. PBPK models were populated with the in vitro parameters and DDI simulations conducted and compared to the observed data from a clinical study with DM and GSK1034702. 3.GSK1034702 was a potent direct and metabolism-dependent inhibitor of human CYP2D6, with inhibition parameters of: IC50=1.6M, K-inact=3.7h(-1) and K-I=0.8M. Incorporating these data into PBPK models predicted a DDI after repeat, but not single, 5mg doses of GSK1034702. 4.The DDI observed with repeat administration of GSK1034702 (5mg) can be attributed to metabolism-dependent inhibition of CYP2D6. Further, in vitro data were generated and several potential mechanisms proposed to explain the interaction observed following a single dose of GSK1034702.
引用
收藏
页码:655 / 666
页数:12
相关论文
共 50 条
  • [41] Drug-drug interaction between isavuconazole and tacrolimus in solid organ transplant recipients, which magnitude in clinical practice?
    Le Bouedec, D.
    Franck, B.
    Boglione-Kerrien, C.
    Verdier, M. C.
    Lemaitre, F.
    Tron, C.
    FUNDAMENTAL & CLINICAL PHARMACOLOGY, 2023, 37 : 148 - 148
  • [42] A systematic review of the drug-drug interaction between statins and colchicine: Patient characteristics, etiologies, and clinical management strategies
    Schwier, Nicholas C.
    Cornelio, Cyrille K.
    Boylan, Paul M.
    PHARMACOTHERAPY, 2022, 42 (04): : 320 - 333
  • [43] Analysis of Clinical Drug-Drug Interaction Data To Predict Magnitudes of Uncharacterized Interactions between Antiretroviral Drugs and Comedications
    Stader, Felix
    Kinvig, Hannah
    Battegay, Manuel
    Khoo, Saye
    Owen, Andrew
    Siccardi, Marco
    Marzolini, Catia
    ANTIMICROBIAL AGENTS AND CHEMOTHERAPY, 2018, 62 (07)
  • [44] Tiered approach to evaluate the CYP3A victim and perpetrator drug-drug interaction potential for vonoprazan using PBPK modeling and clinical data to inform labeling
    Mulford, Darcy J.
    Ramsden, Diane
    Zhang, Liming
    Michon, Ingrid
    Leifke, Eckhard
    Smith, Neila
    Jones, Hannah M.
    Scarpignato, Carmelo
    CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY, 2023, 12 (04): : 532 - 544
  • [45] CLINICAL DRUG-DRUG INTERACTION STUDY INTEGRATED WITH PBPK MODELING PROVIDES INSIGHTS INTO THE INDUCTION POTENTIAL OF MAVACAMTEN ACROSS CYP2C19 PHENOTYPES
    Merali, S.
    Sychterz, C.
    Perera, V.
    Gaohua, L.
    Florea, V.
    Murthy, B.
    CLINICAL PHARMACOLOGY & THERAPEUTICS, 2024, 115 : S82 - S82
  • [46] USAGE OF IN VITRO METABOLISM DATA FOR DRUG-DRUG INTERACTION (DDI) PREDICTION IN PHYSIOLOGICALLY BASED PHARMACOKINETIC (PBPK) MODELING SUBMISSIONS TO OFFICE OF CLINICAL PHARMACOLOGY, US FOOD AND DRUG ADMINISTRATION (FDA).
    Lee, J.
    Yang, Y.
    Zhang, X.
    Fan, J.
    Grimstein, M.
    Zhu, H.
    Wang, Y.
    CLINICAL PHARMACOLOGY & THERAPEUTICS, 2020, 107 : S104 - S104
  • [47] DRUG-DRUG INTERACTION PREDICTION BETWEEN P-AMINO SALICYLIC ACID (PAS) AND TENOFOVIR USING A FULL PHYSIOLOGICALLY BASED PHARMACOKINETIC (PBPK) MODEL.
    Parvez, M.
    Kaisar, N.
    Hasanuzzaman, M.
    Shin, H.
    Jung, J.
    Shin, J. -G.
    CLINICAL PHARMACOLOGY & THERAPEUTICS, 2017, 101 (S1) : S42 - S42
  • [48] Mechanism of the pharmacokinetic interaction between methotrexate and benzimidazoles:: Potential role for breast cancer resistance protein in clinical drug-drug interactions
    Breedveld, P
    Zelcer, N
    Pluim, D
    Sönmezer, Ö
    Tibben, MM
    Beijnen, JH
    Schinkel, AH
    van Tellingen, O
    Borst, P
    Schellens, JHM
    CANCER RESEARCH, 2004, 64 (16) : 5804 - 5811
  • [49] Clinical Drug-Drug Interaction Between Vatiquinone, a 15-Lipoxygenase Inhibitor, and Rosuvastatin, a Breast Cancer Resistance Protein Substrate
    Lee, Lucy
    Murase, Katsuyuki
    Ma, Jiyuan
    Thoolen, Martin
    CLINICAL PHARMACOLOGY IN DRUG DEVELOPMENT, 2023, 12 (03): : 279 - 286
  • [50] Drug-drug interaction predictions with PBPK models and optimal multiresponse sampling time designs: application to midazolam and a phase I compound. Part 2: clinical trial results
    Chenel, Marylore
    Bouzom, Francois
    Cazade, Fanny
    Ogungbenro, Kayode
    Aarons, Leon
    Mentre, France
    JOURNAL OF PHARMACOKINETICS AND PHARMACODYNAMICS, 2008, 35 (06) : 661 - 681