Physiologically based pharmacokinetic modelling to predict drug-drug interactions for encorafenib. Part I. Model building, validation, and prospective predictions with enzyme inhibitors, inducers, and transporter inhibitors

被引:6
作者
Kollipara, Sivacharan [1 ]
Ahmed, Tausif [2 ]
Praveen, Sivadasu [1 ]
机构
[1] Koneru Lakshmaiah Educ Fdn, KL Coll Pharm, Guntur, Andhra Pradesh, India
[2] Integrated Prod Dev Org IPDO, Dr Reddys Labs Ltd, Biopharmaceut Grp, Global Clin Management, Hyderabad, Telangana, India
关键词
Encorafenib; drug-drug interaction; PBPK modelling; inhibition; induction; enzyme-transporter interplay; PBPK; TIME; CETUXIMAB; BINDING; PHASE;
D O I
10.1080/00498254.2023.2250856
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Encorafenib, a potent BRAF kinase inhibitor undergoes significant metabolism by CYP3A4 (83%) and CYP2C19 (16%) and also a substrate of P-glycoprotein (P-gp). Because of this, encorafenib possesses potential for enzyme-transporter related interactions. Clinically, its drug-drug interactions (DDIs) with CYP3A4 inhibitors (posaconazole, diltiazem) were reported and hence there is a necessity to study DDIs with multiple enzyme inhibitors, inducers, and P-gp inhibitors.USFDA recommended clinical CYP3A4, CYP2C19, P-gp inhibitors, CYP3A4 inducers were selected and prospective DDIs were simulated using physiologically based pharmacokinetic modelling (PBPK). Impact of dose (50 mg vs. 300 mg) and staggering of administrations (0-10 h) on the DDIs were predicted.PBPK models for encorafenib, perpetrators simulated PK parameters within twofold prediction error. Clinically reported DDIs with posaconazole and diltiazem were successfully predicted.CYP2C19 inhibitors did not result in significant DDI whereas strong CYP3A4 inhibitors resulted in DDI ratio up to 4.5. Combining CYP3A4, CYP2C19 inhibitors yielded DDI equivalent CYP3A4 alone. Strong CYP3A4 inducers yielded DDI ratio up to 0.3 and no impact of P-gp inhibitors on DDIs was observed. The DDIs were not impacted by dose and staggering of administration. Overall, this work indicated significance of PBPK modelling for evaluating clinical DDIs with enzymes, transporters and interplay.
引用
收藏
页码:366 / 381
页数:16
相关论文
共 46 条
  • [1] Reviewing Data Integrated for PBPK Model Development to Predict Metabolic Drug-Drug Interactions: Shifting Perspectives and Emerging Trends
    Abouir, Kenza
    Samer, Caroline F.
    Gloor, Yvonne
    Desmeules, Jules A.
    Daali, Youssef
    [J]. FRONTIERS IN PHARMACOLOGY, 2021, 12
  • [2] Physiologically based pharmacokinetic modeling of CYP3A4 induction by rifampicin in human: Influence of time between substrate and inducer administration
    Baneyx, Guillaume
    Parrott, Neil
    Meille, Christophe
    Iliadis, Athanassios
    Lave, Thierry
    [J]. EUROPEAN JOURNAL OF PHARMACEUTICAL SCIENCES, 2014, 56 : 1 - 15
  • [3] Dose adjustment of venetoclax when co-administered with posaconazole: clinical drug-drug interaction predictions using a PBPK approach
    Bhatnagar, Sumit
    Mukherjee, Dwaipayan
    Salem, Ahmed Hamed
    Miles, Dale
    Menon, Rajeev M.
    Gibbs, John P.
    [J]. CANCER CHEMOTHERAPY AND PHARMACOLOGY, 2021, 87 (04) : 465 - 474
  • [4] Development and characterization of hyaluronic acid surface scaffolds Encorafenib loaded polymeric nanoparticles for colorectal cancer targeting
    Bhattacharya, Sankha
    Singh, Dilpreet
    Aich, Jyotirmoi
    Ajazuddin
    Shete, Meghanath B.
    [J]. MATERIALS TODAY COMMUNICATIONS, 2022, 31
  • [5] Application of IVIVE and PBPK modeling in prospective prediction of clinical pharmacokinetics: strategy and approach during the drug discovery phase with four case studies
    Chen, Yuan
    Jin, Jin Y.
    Mukadam, Sophie
    Malhi, Vikram
    Kenny, Jane R.
    [J]. BIOPHARMACEUTICS & DRUG DISPOSITION, 2012, 33 (02) : 85 - 98
  • [6] Development of a physiologically based pharmacokinetic (PBPK) population model for Chinese elderly subjects
    Cui, Cheng
    Sia, Jie En Valerie
    Tu, Siqi
    Li, Xiaobei
    Dong, Zhongqi
    Yu, Zhiheng
    Yao, Xueting
    Hatley, Oliver
    Li, Haiyan
    Liu, Dongyang
    [J]. BRITISH JOURNAL OF CLINICAL PHARMACOLOGY, 2021, 87 (07) : 2711 - 2722
  • [7] Simulation of drug-drug interactions between breast cancer chemotherapeutic agents and antiemetic drugs
    Deb, Subrata
    Hopefl, Robert
    [J]. DARU-JOURNAL OF PHARMACEUTICAL SCIENCES, 2023, 31 (02) : 95 - 105
  • [8] Del Frari L., 2023, MIDD 2023 C SIM PLUS
  • [9] Prediction of ARA/PPI Drug-Drug Interactions at the Drug Discovery and Development Interface
    Dodd, Stephanie
    Kollipara, Sivacharan
    Sanchez-Felix, Manuel
    Kim, Hyungchul
    Meng, Qingshuo
    Beato, Stefania
    Heimbach, Tycho
    [J]. JOURNAL OF PHARMACEUTICAL SCIENCES, 2019, 108 (01) : 87 - 101
  • [10] Overall survival in patients with BRAF-mutant melanoma receiving encorafenib plus binimetinib versus vemurafenib or encorafenib (COLUMBUS): a multicentre, open-label, randomised, phase 3 trial
    Dummer, Reinhard
    Ascierto, Paolo A.
    Gogas, Helen J.
    Arance, Ana
    Mandala, Mario
    Liszkay, Gabriella
    Garbe, Claus
    Schadendorf, Dirk
    Krajsova, Ivana
    Gutzmer, Ralf
    Sileni, Vanna Chiarion
    Dutriaux, Caroline
    de Groot, Jan Willem B.
    Yamazaki, Naoya
    Loquai, Carmen
    Moutouh-de Parseval, Laure A.
    Pickard, Michael D.
    Sandor, Victor
    Roberti, Caroline
    Flaherty, Keith T.
    [J]. LANCET ONCOLOGY, 2018, 19 (10) : 1315 - 1327