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Yin X, Cicali B, Rodriguez-Vera L, Lukacova V, Cristofoletti R, Schmidt S. Applying Physiologically Based Pharmacokinetic Modeling to Interpret Carbamazepine's Nonlinear Pharmacokinetics and Its Induction Potential on Cytochrome P450 3A4 and Cytochrome P450 2C9 Enzymes. Pharmaceutics 2024; 16:737. [PMID: 38931859 DOI: 10.3390/pharmaceutics16060737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 05/21/2024] [Accepted: 05/24/2024] [Indexed: 06/28/2024] Open
Abstract
Carbamazepine (CBZ) is commonly prescribed for epilepsy and frequently used in polypharmacy. However, concerns arise regarding its ability to induce the metabolism of other drugs, including itself, potentially leading to the undertreatment of co-administered drugs. Additionally, CBZ exhibits nonlinear pharmacokinetics (PK), but the root causes have not been fully studied. This study aims to investigate the mechanisms behind CBZ's nonlinear PK and its induction potential on CYP3A4 and CYP2C9 enzymes. To achieve this, we developed and validated a physiologically based pharmacokinetic (PBPK) parent-metabolite model of CBZ and its active metabolite Carbamazepine-10,11-epoxide in GastroPlus®. The model was utilized for Drug-Drug Interaction (DDI) prediction with CYP3A4 and CYP2C9 victim drugs and to further explore the underlying mechanisms behind CBZ's nonlinear PK. The model accurately recapitulated CBZ plasma PK. Good DDI performance was demonstrated by the prediction of CBZ DDIs with quinidine, dolutegravir, phenytoin, and tolbutamide; however, with midazolam, the predicted/observed DDI AUClast ratio was 0.49 (slightly outside of the two-fold range). CBZ's nonlinear PK can be attributed to its nonlinear metabolism caused by autoinduction, as well as nonlinear absorption due to poor solubility. In further applications, the model can help understand DDI potential when CBZ serves as a CYP3A4 and CYP2C9 inducer.
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Affiliation(s)
- Xuefen Yin
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL 32827, USA
| | - Brian Cicali
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL 32827, USA
| | - Leyanis Rodriguez-Vera
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL 32827, USA
| | | | - Rodrigo Cristofoletti
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL 32827, USA
| | - Stephan Schmidt
- Center for Pharmacometrics and Systems Pharmacology, Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL 32827, USA
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Rodriguez-Vera L, Yin X, Almoslem M, Romahn K, Cicali B, Lukacova V, Cristofoletti R, Schmidt S. Comprehensive Physiologically Based Pharmacokinetic Model to Assess Drug-Drug Interactions of Phenytoin. Pharmaceutics 2023; 15:2486. [PMID: 37896246 PMCID: PMC10609929 DOI: 10.3390/pharmaceutics15102486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Revised: 10/07/2023] [Accepted: 10/13/2023] [Indexed: 10/29/2023] Open
Abstract
Regulatory agencies worldwide expect that clinical pharmacokinetic drug-drug interactions (DDIs) between an investigational new drug and other drugs should be conducted during drug development as part of an adequate assessment of the drug's safety and efficacy. However, it is neither time nor cost efficient to test all possible DDI scenarios clinically. Phenytoin is classified by the Food and Drug Administration as a strong clinical index inducer of CYP3A4, and a moderate sensitive substrate of CYP2C9. A physiologically based pharmacokinetic (PBPK) platform model was developed using GastroPlus® to assess DDIs with phenytoin acting as the victim (CYP2C9, CYP2C19) or perpetrator (CYP3A4). Pharmacokinetic data were obtained from 15 different studies in healthy subjects. The PBPK model of phenytoin explains the contribution of CYP2C9 and CYP2C19 to the formation of 5-(4'-hydroxyphenyl)-5-phenylhydantoin. Furthermore, it accurately recapitulated phenytoin exposure after single and multiple intravenous and oral doses/formulations ranging from 248 to 900 mg, the dose-dependent nonlinearity and the magnitude of the effect of food on phenytoin pharmacokinetics. Once developed and verified, the model was used to characterize and predict phenytoin DDIs with fluconazole, omeprazole and itraconazole, i.e., simulated/observed DDI AUC ratio ranging from 0.89 to 1.25. This study supports the utility of the PBPK approach in informing drug development.
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Affiliation(s)
- Leyanis Rodriguez-Vera
- Center for Pharmacometrics and System Pharmacology at Lake Nona (Orlando), Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL 32827, USA; (L.R.-V.); (X.Y.); (M.A.); (K.R.); (B.C.)
| | - Xuefen Yin
- Center for Pharmacometrics and System Pharmacology at Lake Nona (Orlando), Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL 32827, USA; (L.R.-V.); (X.Y.); (M.A.); (K.R.); (B.C.)
| | - Mohammed Almoslem
- Center for Pharmacometrics and System Pharmacology at Lake Nona (Orlando), Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL 32827, USA; (L.R.-V.); (X.Y.); (M.A.); (K.R.); (B.C.)
| | - Karolin Romahn
- Center for Pharmacometrics and System Pharmacology at Lake Nona (Orlando), Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL 32827, USA; (L.R.-V.); (X.Y.); (M.A.); (K.R.); (B.C.)
| | - Brian Cicali
- Center for Pharmacometrics and System Pharmacology at Lake Nona (Orlando), Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL 32827, USA; (L.R.-V.); (X.Y.); (M.A.); (K.R.); (B.C.)
| | | | - Rodrigo Cristofoletti
- Center for Pharmacometrics and System Pharmacology at Lake Nona (Orlando), Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL 32827, USA; (L.R.-V.); (X.Y.); (M.A.); (K.R.); (B.C.)
| | - Stephan Schmidt
- Center for Pharmacometrics and System Pharmacology at Lake Nona (Orlando), Department of Pharmaceutics, College of Pharmacy, University of Florida, Orlando, FL 32827, USA; (L.R.-V.); (X.Y.); (M.A.); (K.R.); (B.C.)
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Ekiciler A, Chen WLK, Bo Y, Pugliano A, Donzelli M, Parrott N, Umehara K. Quantitative Cytochrome P450 3A4 Induction Risk Assessment Using Human Hepatocytes Complemented with Pregnane X Receptor-Activating Profiles. Drug Metab Dispos 2023; 51:276-284. [PMID: 36460477 DOI: 10.1124/dmd.122.001132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 11/14/2022] [Accepted: 11/23/2022] [Indexed: 12/05/2022] Open
Abstract
Reliable in vitro to in vivo translation of cytochrome P450 (CYP) 3A4 induction potential is essential to support risk mitigation for compounds during pharmaceutical discovery and development. In this study, a linear correlation of CYP3A4 mRNA induction potential in human hepatocytes with the respective pregnane-X receptor (PXR) activation in a reporter gene assay using DPX2 cells was successfully demonstrated for 13 clinically used drugs. Based on this correlation, using rifampicin as a positive control, the magnitude of CYP3A4 mRNA induction for 71 internal compounds at several concentrations up to 10 µM (n = 90) was predicted within 2-fold error for 64% of cases with only a few false positives (19%). Furthermore, the in vivo area under the curve reduction of probe CYP substrates was reasonably predicted for eight marketed drugs (carbamazepine, dexamethasone, enzalutamide, nevirapine, phenobarbital, phenytoin, rifampicin, and rufinamide) using the static net effect model using both the PXR activation and CYP3A4 mRNA induction data. The liver exit concentrations were used for the model in place of the inlet concentrations to avoid false positive predictions and the concentration achieving twofold induction (F2) was used to compensate for the lack of full induction kinetics due to cytotoxicity and solubility limitations in vitro. These findings can complement the currently available induction risk mitigation strategy and potentially influence the drug interaction modeling work conducted at clinical stages. SIGNIFICANCE STATEMENT: The established correlation of CYP3A4 mRNA in human hepatocytes to PXR activation provides a clear cut-off to identify a compound showing an in vitro induction risk, complementing current regulatory guidance. Also, the demonstrated in vitro-in vivo translation of induction data strongly supports a clinical development program although limitations remain for drug candidates showing complex disposition pathways, such as involvement of auto-inhibition/induction, active transport and high protein binding.
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Affiliation(s)
- Aynur Ekiciler
- Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland (A.E., A.P., M.D., N.P., K.U.) and Roche Pharmaceutical Research and Early Development, China Innovation Center of Roche, Shanghai, China (W.L.K.C., Y.B.)
| | - Wen Li Kelly Chen
- Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland (A.E., A.P., M.D., N.P., K.U.) and Roche Pharmaceutical Research and Early Development, China Innovation Center of Roche, Shanghai, China (W.L.K.C., Y.B.)
| | - Yan Bo
- Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland (A.E., A.P., M.D., N.P., K.U.) and Roche Pharmaceutical Research and Early Development, China Innovation Center of Roche, Shanghai, China (W.L.K.C., Y.B.)
| | - Alessandra Pugliano
- Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland (A.E., A.P., M.D., N.P., K.U.) and Roche Pharmaceutical Research and Early Development, China Innovation Center of Roche, Shanghai, China (W.L.K.C., Y.B.)
| | - Massimiliano Donzelli
- Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland (A.E., A.P., M.D., N.P., K.U.) and Roche Pharmaceutical Research and Early Development, China Innovation Center of Roche, Shanghai, China (W.L.K.C., Y.B.)
| | - Neil Parrott
- Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland (A.E., A.P., M.D., N.P., K.U.) and Roche Pharmaceutical Research and Early Development, China Innovation Center of Roche, Shanghai, China (W.L.K.C., Y.B.)
| | - Kenichi Umehara
- Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland (A.E., A.P., M.D., N.P., K.U.) and Roche Pharmaceutical Research and Early Development, China Innovation Center of Roche, Shanghai, China (W.L.K.C., Y.B.)
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Ramsden D, Fullenwider CL. Characterization of Correction Factors to Enable Assessment of Clinical Risk from In Vitro CYP3A4 Induction Data and Basic Drug-Drug Interaction Models. Eur J Drug Metab Pharmacokinet 2022; 47:467-482. [PMID: 35344159 PMCID: PMC9232448 DOI: 10.1007/s13318-022-00763-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/23/2022] [Indexed: 11/29/2022]
Abstract
Background and Objective Induction of drug-metabolizing enzymes can lead to drug-drug interactions (DDIs); therefore, early assessment is often conducted. Previous reports focused on true positive cytochrome P450 3A (CYP3A) inducers leaving a gap in translation for in vitro inducers which do not manifest in clinical induction. The goal herein was to expand the in vitro induction dataset by including true negative clinical inducers to identify a correction factor to basic DDI models, which reduces false positives without impacting false negatives. Methods True negative clinical inducers were identified through a literature search, in vitro induction parameters were generated in three human hepatocyte donors, and the performance of basic induction models proposed by regulatory agencies, concentration producing twofold induction (F2), basic static model (R3) and relative induction score (RIS), was used to characterize clinical induction risk. Results The data demonstrated the importance of correcting for in vitro binding and metabolism to derive induction parameters. The aggregate analysis indicates that the RIS with a positive cut-off of < 0.7-fold area under the curve ratio (AUCR) provides the best quantitative prediction. Additionally, correction factors of ten and two times the unbound peak plasma concentration at steady state (Cmax,ss,u) can be confidently used to identify true positive inducers when referenced against the concentration resulting in twofold increase in messenger ribonucleic acid (mRNA) or using the R3 equation, respectively. Conclusions These iterative improvements, which reduce the number of false positives, could aid regulatory recommendations and limit unnecessary clinical explorations into CYP3A induction. Graphical abstract ![]()
Supplementary Information The online version contains supplementary material available at 10.1007/s13318-022-00763-y.
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Affiliation(s)
- Diane Ramsden
- Takeda Development Center Americas, Inc., Cambridge, MA, USA. .,Department of Oncology Research and Early Development, Drug Metabolism and Pharmacokinetics, AstraZeneca, 35 Gatehouse Park, Waltham, MA, 02451, USA.
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Savaryn JP, Sun J, Ma J, Jenkins GJ, Stresser DM. Broad application of CYP3A4 LC-MS protein quantification in hepatocyte cytochrome P450 induction assays identifies nonuniformity in mRNA and protein induction responses. Drug Metab Dispos 2021; 50:105-113. [PMID: 34857529 DOI: 10.1124/dmd.121.000638] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 11/30/2021] [Indexed: 11/22/2022] Open
Abstract
Screening for cytochrome P450 (CYP) induction potential is routine in drug development. Induction results in a net increase in CYP protein and is assessed typically by measuring indirect endpoints, i.e., enzyme activity and mRNA in vitro. Recent methodological advancements have made CYP protein quantification by LC-MS in in vitro induction studies more accessible and amenable to routine testing. In this study, we evaluated CYP3A4 concentration dependence of induction response for 11 compounds (rifampin, rifabutin, carbamazepine, efavirenz, nitrendipine, flumazenil, pioglitazone, rosiglitazone, troglitazone, pazopanib, and ticagrelor) in plated hepatocytes from two or three donors incorporating in the assessment all three endpoints. In addition, the time-dependence of the induction was examined over 1, 2 or 3 days of treatment. For most compounds, mRNA, enzyme activity and protein endpoints exhibited similarity in induction responses. Pazopanib and ticagrelor were notable exceptions as neither protein nor enzyme activity were induced despite mRNA induction of a magnitude similar to efavirenz, pioglitazone or rosiglitazone, which clearly induced in all three endpoints. Static modeling of clinical induction responses supported a role for protein as a predictive endpoint. These data highlight the value of including CYP protein quantification as an induction assay endpoint to provide a more comprehensive assessment of induction liability. Significance Statement Direct, LC-MS-based quantification of CYP protein is a desirable induction assay endpoint, however the application of protein as an endpoint has been limited due to inefficient workflows. Here, we incorporate recent advancements in protein quantitation methods to efficiently quantify CYP3A4 protein in in vitro induction assays with 11 compounds in up to 3 donors. The data indicate induction responses from mRNA do not always align with those of protein suggesting assessment of induction liability is more complex than thought previously.
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Affiliation(s)
| | | | - Junli Ma
- Drug Metabolism, Pharmacokinetics and Bioanalysis, AbbVie, United States
| | - Gary J Jenkins
- Drug Metabolism, Pharmacokinetics and Bioanal, AbbVie, United States
| | - David M Stresser
- Drug Metabolism, Pharmacokinetics and Bioanalysis, AbbVie, United States of America, AbbVie, United States
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Tsutsui H, Kuramoto S, Ozeki K. Evaluation of Methods to Assess CYP3A Induction Risk in Clinical Practice Using in Vitro Induction Parameters. Biol Pharm Bull 2021; 44:338-349. [PMID: 33642543 DOI: 10.1248/bpb.b20-00578] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Established guidelines have recommended a number of methods based on in vitro data to assess the CYP3A induction risk of new chemical entities in clinical practice. In this study, we evaluated the predictability of various assessment methods. We collected in vitro parameters from a variety of literature that includes data on 19 batches of hepatocytes. Clinical CYP3A induction was predicted using 3 direct approaches-the fold-change, basic model, and mechanistic static models-as well as 5 correlation approaches, including the relative induction score (RIS) and the relative factor (RF) method. These predictions were then compared with data from 30 clinical inductions. Collected in vitro parameters varied greatly between hepatocyte batches. Direct assessment methods using fixed cut-off values provided a lot of false predictions due to hepatocyte variability, which can overlook induction risk or lead to needless clinical drug-drug interaction (DDI) studies. On the other hand, correlation methods with the cut-off values set for each batch of hepatocytes accurately predicted the induction risk. Among these, the AUCu/inducer concentrations for half the maximum induction (EC50) and the RF methods which use the area under the curve (AUC) of the unbound inducers for calculating induction potential showed an especially good correlation with clinical induction. Correlation methods were better at predicting clinical induction risk than the other methods, regardless of hepatocyte variability. The AUCu/EC50 and the RF methods in particular had a small number of false predictions, and can therefore be used to assess induction risk along with the other correlation methods recommended in guidelines.
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Fuhr LM, Marok FZ, Hanke N, Selzer D, Lehr T. Pharmacokinetics of the CYP3A4 and CYP2B6 Inducer Carbamazepine and Its Drug-Drug Interaction Potential: A Physiologically Based Pharmacokinetic Modeling Approach. Pharmaceutics 2021; 13:270. [PMID: 33671323 PMCID: PMC7922031 DOI: 10.3390/pharmaceutics13020270] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 02/09/2021] [Accepted: 02/11/2021] [Indexed: 12/18/2022] Open
Abstract
The anticonvulsant carbamazepine is frequently used in the long-term therapy of epilepsy and is a known substrate and inducer of cytochrome P450 (CYP) 3A4 and CYP2B6. Carbamazepine induces the metabolism of various drugs (including its own); on the other hand, its metabolism can be affected by various CYP inhibitors and inducers. The aim of this work was to develop a physiologically based pharmacokinetic (PBPK) parent-metabolite model of carbamazepine and its metabolite carbamazepine-10,11-epoxide, including carbamazepine autoinduction, to be applied for drug-drug interaction (DDI) prediction. The model was developed in PK-Sim, using a total of 92 plasma concentration-time profiles (dosing range 50-800 mg), as well as fractions excreted unchanged in urine measurements. The carbamazepine model applies metabolism by CYP3A4 and CYP2C8 to produce carbamazepine-10,11-epoxide, metabolism by CYP2B6 and UDP-glucuronosyltransferase (UGT) 2B7 and glomerular filtration. The carbamazepine-10,11-epoxide model applies metabolism by epoxide hydroxylase 1 (EPHX1) and glomerular filtration. Good DDI performance was demonstrated by the prediction of carbamazepine DDIs with alprazolam, bupropion, erythromycin, efavirenz and simvastatin, where 14/15 DDI AUClast ratios and 11/15 DDI Cmax ratios were within the prediction success limits proposed by Guest et al. The thoroughly evaluated model will be freely available in the Open Systems Pharmacology model repository.
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Affiliation(s)
| | | | | | | | - Thorsten Lehr
- Clinical Pharmacy, Saarland University, 66123 Saarbrücken, Germany; (L.M.F.); (F.Z.M.); (N.H.); (D.S.)
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Wong SG, Ramsden D, Dallas S, Fung C, Einolf HJ, Palamanda J, Chen L, Goosen TC, Siu YA, Zhang G, Tweedie D, Hariparsad N, Jones B, Yates PD. Considerations from the Innovation and Quality Induction Working Group in Response to Drug-Drug Interaction Guidance from Regulatory Agencies: Guidelines on Model Fitting and Recommendations on Time Course for In Vitro Cytochrome P450 Induction Studies Including Impact on Drug Interaction Risk Assessment. Drug Metab Dispos 2020; 49:94-110. [DOI: 10.1124/dmd.120.000055] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Accepted: 10/21/2020] [Indexed: 01/07/2023] Open
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Smits A, Annaert P, Van Cruchten S, Allegaert K. A Physiology-Based Pharmacokinetic Framework to Support Drug Development and Dose Precision During Therapeutic Hypothermia in Neonates. Front Pharmacol 2020; 11:587. [PMID: 32477113 PMCID: PMC7237643 DOI: 10.3389/fphar.2020.00587] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Accepted: 04/16/2020] [Indexed: 12/21/2022] Open
Abstract
Therapeutic hypothermia (TH) is standard treatment for neonates (≥36 weeks) with perinatal asphyxia (PA) and hypoxic-ischemic encephalopathy. TH reduces mortality and neurodevelopmental disability due to reduced metabolic rate and decreased neuronal apoptosis. Since both hypothermia and PA influence physiology, they are expected to alter pharmacokinetics (PK). Tools for personalized dosing in this setting are lacking. A neonatal hypothermia physiology-based PK (PBPK) framework would enable precision dosing in the clinic. In this literature review, the stepwise approach, benefits and challenges to develop such a PBPK framework are covered. It hereby contributes to explore the impact of non-maturational PK covariates. First, the current evidence as well as knowledge gaps on the impact of PA and TH on drug absorption, distribution, metabolism and excretion in neonates is summarized. While reduced renal drug elimination is well-documented in neonates with PA undergoing hypothermia, knowledge of the impact on drug metabolism is limited. Second, a multidisciplinary approach to develop a neonatal hypothermia PBPK framework is presented. Insights on the effect of hypothermia on hepatic drug elimination can partly be generated from in vitro (human/animal) profiling of hepatic drug metabolizing enzymes and transporters. Also, endogenous biomarkers may be evaluated as surrogate for metabolic activity. To distinguish the impact of PA versus hypothermia on drug metabolism, in vivo neonatal animal data are needed. The conventional pig is a well-established model for PA and the neonatal Göttingen minipig should be further explored for PA under hypothermia conditions, as it is the most commonly used pig strain in nonclinical drug development. Finally, a strategy is proposed for establishing and fine-tuning compound-specific PBPK models for this application. Besides improvement of clinical exposure predictions of drugs used during hypothermia, the developed PBPK models can be applied in drug development. Add-on pharmacotherapies to further improve outcome in neonates undergoing hypothermia are under investigation, all in need for dosing guidance. Furthermore, the hypothermia PBPK framework can be used to develop temperature-driven PBPK models for other populations or indications. The applicability of the proposed workflow and the challenges in the development of the PBPK framework are illustrated for midazolam as model drug.
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Affiliation(s)
- Anne Smits
- Neonatal Intensive Care Unit, University Hospitals Leuven, Leuven, Belgium.,Department of Development and Regeneration, KU Leuven, Leuven, Belgium
| | - Pieter Annaert
- Drug Delivery and Disposition, Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium
| | - Steven Van Cruchten
- Applied Veterinary Morphology, Department of Veterinary Sciences, University of Antwerp, Wilrijk, Belgium
| | - Karel Allegaert
- Department of Development and Regeneration, KU Leuven, Leuven, Belgium.,Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium.,Department of Clinical Pharmacy, Erasmus MC-Sophia Children's Hospital, Rotterdam, Netherlands
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Tsutsui H, Kato M, Kuramoto S, Sekiguchi N, Shindoh H, Ozeki K. Quantitative evaluation of hepatic and intestinal induction of CYP3A in clinical practice. Xenobiotica 2019; 50:875-884. [PMID: 31885304 DOI: 10.1080/00498254.2019.1710620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
This is the first report quantitatively evaluating the clinical induction of CYP3A in the liver and the intestine.To evaluate hepatic induction, we collected literature data on endogenous biomarkers of hepatic CYP3A induction which we then used to calculate the fold-induction (inducer-mediated change in biomarker level). Literature data on decreases in the area under the curve (AUC) of alfentanil, a CYP3A substrate, caused by CYP3A inducers were also collected. We used the hepatic intrinsic clearance of alfentanil to calculate the hepatic induction ratio (inducer-mediated change in intrinsic clearance). For intestinal induction, the intestinal bioavailability (Fg) of alfentanil was used to calculate the intestinal induction ratio. We determined in vivo maximum induction (Emax) and the average unbound plasma concentration (Cav,u) required for half the maximum induction (EC50) for inducers using an Emax model analysis.In our results, fold-induction was comparable to the induction ratio at several inducer concentrations, and almost the maximum induction was achieved by a therapeutic dose. Induction ratios in the intestine were similar to the liver.Our findings suggest that, by knowing only hepatic induction ratios for common inducers, we can quantitatively predict the decreases in the AUC of substrates by CYP3A induction.
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Affiliation(s)
- Haruka Tsutsui
- Research division, Chugai Pharmaceutical Co., Ltd, Gotemba, Shizuoka, Japan
| | - Motohiro Kato
- Research division, Chugai Pharmaceutical Co., Ltd, Gotemba, Shizuoka, Japan
| | - Shino Kuramoto
- Research division, Chugai Pharmaceutical Co., Ltd, Gotemba, Shizuoka, Japan
| | - Nobuo Sekiguchi
- Research division, Chugai Pharmaceutical Co., Ltd, Gotemba, Shizuoka, Japan
| | - Hidetoshi Shindoh
- Research division, Chugai Pharmaceutical Co., Ltd, Gotemba, Shizuoka, Japan
| | - Kazuhisa Ozeki
- Research division, Chugai Pharmaceutical Co., Ltd, Gotemba, Shizuoka, Japan
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Advanced In Vitro HepaRG Culture Systems for Xenobiotic Metabolism and Toxicity Characterization. Eur J Drug Metab Pharmacokinet 2018; 44:437-458. [DOI: 10.1007/s13318-018-0533-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
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Uehara S, Higuchi Y, Yoneda N, Yamazaki H, Suemizu H. Expression and inducibility of cytochrome P450s in human hepatocytes isolated from chimeric mice with humanised livers. Xenobiotica 2018; 49:678-687. [PMID: 29969338 DOI: 10.1080/00498254.2018.1495346] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
The evaluation of drug-mediated cytochrome P450 (P450) induction using human hepatocytes is important for predicting drug interactions. In this study, we prepared hepatocytes from chimeric mice with humanised livers (Hu-Liver mice) and evaluated the expression and inducibility of P450s in these hepatocytes. Up to 95% of the Hu-Liver cells stained positive for human leukocyte antigen and the mean viability exceeded 85% (n = 10). Monolayer-cultured Hu-Liver cells displayed a similar morphology to cultures of the corresponding human hepatocytes used as transplantation donors. The mRNA expression levels in Hu-Liver cells of 16 P450 forms belonging to P450 subfamilies 1-4 correlated well with the expression levels of the same enzymes in human hepatocytes. The variations in individual P450 mRNA levels between Hu-Liver cells and the corresponding human hepatocytes were within five-fold for 13 P450 forms. The production of 6β-hydroxytestosterone in Hu-Liver cells was significantly increased (p < .05) following treatment with the CYP3A inducer, rifampicin. Hu-Liver cells have characteristics similar to those of human hepatocytes in terms of mRNA expression levels and the inducibility of the various P450 forms. Thus, Hu-Liver cells can potentially be used for in vitro drug-mediated induction assays of human hepatic P450s.
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Affiliation(s)
- Shotaro Uehara
- a Central Institute for Experimental Animals , Kawasaki , Japan
| | | | - Nao Yoneda
- a Central Institute for Experimental Animals , Kawasaki , Japan
| | - Hiroshi Yamazaki
- b Laboratory of Drug Metabolism and Pharmacokinetics , Showa Pharmaceutical University , Machida , Tokyo , Japan
| | - Hiroshi Suemizu
- a Central Institute for Experimental Animals , Kawasaki , Japan
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Kenny JR, Ramsden D, Buckley DB, Dallas S, Fung C, Mohutsky M, Einolf HJ, Chen L, Dekeyser JG, Fitzgerald M, Goosen TC, Siu YA, Walsky RL, Zhang G, Tweedie D, Hariparsad N. Considerations from the Innovation and Quality Induction Working Group in Response to Drug-Drug Interaction Guidances from Regulatory Agencies: Focus on CYP3A4 mRNA In Vitro Response Thresholds, Variability, and Clinical Relevance. Drug Metab Dispos 2018; 46:1285-1303. [PMID: 29959133 DOI: 10.1124/dmd.118.081927] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2018] [Accepted: 06/18/2018] [Indexed: 01/08/2023] Open
Abstract
The Innovation and Quality Induction Working Group presents an assessment of best practice for data interpretation of in vitro induction, specifically, response thresholds, variability, application of controls, and translation to clinical risk assessment with focus on CYP3A4 mRNA. Single concentration control data and Emax/EC50 data for prototypical CYP3A4 inducers were compiled from many human hepatocyte donors in different laboratories. Clinical CYP3A induction and in vitro data were gathered for 51 compounds, 16 of which were proprietary. A large degree of variability was observed in both the clinical and in vitro induction responses; however, analysis confirmed in vitro data are able to predict clinical induction risk. Following extensive examination of this large data set, the following recommendations are proposed. a) Cytochrome P450 induction should continue to be evaluated in three separate human donors in vitro. b) In light of empirically divergent responses in rifampicin control and most test inducers, normalization of data to percent positive control appears to be of limited benefit. c) With concentration dependence, 2-fold induction is an acceptable threshold for positive identification of in vitro CYP3A4 mRNA induction. d) To reduce the risk of false positives, in the absence of a concentration-dependent response, induction ≥ 2-fold should be observed in more than one donor to classify a compound as an in vitro inducer. e) If qualifying a compound as negative for CYP3A4 mRNA induction, the magnitude of maximal rifampicin response in that donor should be ≥ 10-fold. f) Inclusion of a negative control adds no value beyond that of the vehicle control.
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Affiliation(s)
- Jane R Kenny
- Genentech, South San Francisco, California (J.R.K.); Boehringer Ingelheim, Ridgefield, Connecticut (D.R.); Sekisui-XenoTech LLC, Kansas City, Kansas (D.B.B.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Eli Lilly and Company, Indianapolis, Indiana (M.M.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Amgen Inc., Cambridge, Massachusetts (J.G.D.); Sanofi, Waltham, Massachusetts (M.F.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Eisai, Andover, Massachusetts (Y.A.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.L.W.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); and Merck & Co., Inc., Kenilworth, New Jersey (D.T.)
| | - Diane Ramsden
- Genentech, South San Francisco, California (J.R.K.); Boehringer Ingelheim, Ridgefield, Connecticut (D.R.); Sekisui-XenoTech LLC, Kansas City, Kansas (D.B.B.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Eli Lilly and Company, Indianapolis, Indiana (M.M.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Amgen Inc., Cambridge, Massachusetts (J.G.D.); Sanofi, Waltham, Massachusetts (M.F.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Eisai, Andover, Massachusetts (Y.A.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.L.W.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); and Merck & Co., Inc., Kenilworth, New Jersey (D.T.)
| | - David B Buckley
- Genentech, South San Francisco, California (J.R.K.); Boehringer Ingelheim, Ridgefield, Connecticut (D.R.); Sekisui-XenoTech LLC, Kansas City, Kansas (D.B.B.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Eli Lilly and Company, Indianapolis, Indiana (M.M.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Amgen Inc., Cambridge, Massachusetts (J.G.D.); Sanofi, Waltham, Massachusetts (M.F.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Eisai, Andover, Massachusetts (Y.A.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.L.W.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); and Merck & Co., Inc., Kenilworth, New Jersey (D.T.)
| | - Shannon Dallas
- Genentech, South San Francisco, California (J.R.K.); Boehringer Ingelheim, Ridgefield, Connecticut (D.R.); Sekisui-XenoTech LLC, Kansas City, Kansas (D.B.B.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Eli Lilly and Company, Indianapolis, Indiana (M.M.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Amgen Inc., Cambridge, Massachusetts (J.G.D.); Sanofi, Waltham, Massachusetts (M.F.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Eisai, Andover, Massachusetts (Y.A.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.L.W.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); and Merck & Co., Inc., Kenilworth, New Jersey (D.T.)
| | - Conrad Fung
- Genentech, South San Francisco, California (J.R.K.); Boehringer Ingelheim, Ridgefield, Connecticut (D.R.); Sekisui-XenoTech LLC, Kansas City, Kansas (D.B.B.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Eli Lilly and Company, Indianapolis, Indiana (M.M.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Amgen Inc., Cambridge, Massachusetts (J.G.D.); Sanofi, Waltham, Massachusetts (M.F.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Eisai, Andover, Massachusetts (Y.A.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.L.W.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); and Merck & Co., Inc., Kenilworth, New Jersey (D.T.)
| | - Michael Mohutsky
- Genentech, South San Francisco, California (J.R.K.); Boehringer Ingelheim, Ridgefield, Connecticut (D.R.); Sekisui-XenoTech LLC, Kansas City, Kansas (D.B.B.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Eli Lilly and Company, Indianapolis, Indiana (M.M.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Amgen Inc., Cambridge, Massachusetts (J.G.D.); Sanofi, Waltham, Massachusetts (M.F.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Eisai, Andover, Massachusetts (Y.A.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.L.W.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); and Merck & Co., Inc., Kenilworth, New Jersey (D.T.)
| | - Heidi J Einolf
- Genentech, South San Francisco, California (J.R.K.); Boehringer Ingelheim, Ridgefield, Connecticut (D.R.); Sekisui-XenoTech LLC, Kansas City, Kansas (D.B.B.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Eli Lilly and Company, Indianapolis, Indiana (M.M.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Amgen Inc., Cambridge, Massachusetts (J.G.D.); Sanofi, Waltham, Massachusetts (M.F.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Eisai, Andover, Massachusetts (Y.A.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.L.W.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); and Merck & Co., Inc., Kenilworth, New Jersey (D.T.)
| | - Liangfu Chen
- Genentech, South San Francisco, California (J.R.K.); Boehringer Ingelheim, Ridgefield, Connecticut (D.R.); Sekisui-XenoTech LLC, Kansas City, Kansas (D.B.B.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Eli Lilly and Company, Indianapolis, Indiana (M.M.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Amgen Inc., Cambridge, Massachusetts (J.G.D.); Sanofi, Waltham, Massachusetts (M.F.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Eisai, Andover, Massachusetts (Y.A.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.L.W.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); and Merck & Co., Inc., Kenilworth, New Jersey (D.T.)
| | - Joshua G Dekeyser
- Genentech, South San Francisco, California (J.R.K.); Boehringer Ingelheim, Ridgefield, Connecticut (D.R.); Sekisui-XenoTech LLC, Kansas City, Kansas (D.B.B.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Eli Lilly and Company, Indianapolis, Indiana (M.M.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Amgen Inc., Cambridge, Massachusetts (J.G.D.); Sanofi, Waltham, Massachusetts (M.F.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Eisai, Andover, Massachusetts (Y.A.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.L.W.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); and Merck & Co., Inc., Kenilworth, New Jersey (D.T.)
| | - Maria Fitzgerald
- Genentech, South San Francisco, California (J.R.K.); Boehringer Ingelheim, Ridgefield, Connecticut (D.R.); Sekisui-XenoTech LLC, Kansas City, Kansas (D.B.B.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Eli Lilly and Company, Indianapolis, Indiana (M.M.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Amgen Inc., Cambridge, Massachusetts (J.G.D.); Sanofi, Waltham, Massachusetts (M.F.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Eisai, Andover, Massachusetts (Y.A.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.L.W.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); and Merck & Co., Inc., Kenilworth, New Jersey (D.T.)
| | - Theunis C Goosen
- Genentech, South San Francisco, California (J.R.K.); Boehringer Ingelheim, Ridgefield, Connecticut (D.R.); Sekisui-XenoTech LLC, Kansas City, Kansas (D.B.B.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Eli Lilly and Company, Indianapolis, Indiana (M.M.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Amgen Inc., Cambridge, Massachusetts (J.G.D.); Sanofi, Waltham, Massachusetts (M.F.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Eisai, Andover, Massachusetts (Y.A.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.L.W.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); and Merck & Co., Inc., Kenilworth, New Jersey (D.T.)
| | - Y Amy Siu
- Genentech, South San Francisco, California (J.R.K.); Boehringer Ingelheim, Ridgefield, Connecticut (D.R.); Sekisui-XenoTech LLC, Kansas City, Kansas (D.B.B.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Eli Lilly and Company, Indianapolis, Indiana (M.M.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Amgen Inc., Cambridge, Massachusetts (J.G.D.); Sanofi, Waltham, Massachusetts (M.F.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Eisai, Andover, Massachusetts (Y.A.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.L.W.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); and Merck & Co., Inc., Kenilworth, New Jersey (D.T.)
| | - Robert L Walsky
- Genentech, South San Francisco, California (J.R.K.); Boehringer Ingelheim, Ridgefield, Connecticut (D.R.); Sekisui-XenoTech LLC, Kansas City, Kansas (D.B.B.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Eli Lilly and Company, Indianapolis, Indiana (M.M.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Amgen Inc., Cambridge, Massachusetts (J.G.D.); Sanofi, Waltham, Massachusetts (M.F.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Eisai, Andover, Massachusetts (Y.A.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.L.W.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); and Merck & Co., Inc., Kenilworth, New Jersey (D.T.)
| | - George Zhang
- Genentech, South San Francisco, California (J.R.K.); Boehringer Ingelheim, Ridgefield, Connecticut (D.R.); Sekisui-XenoTech LLC, Kansas City, Kansas (D.B.B.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Eli Lilly and Company, Indianapolis, Indiana (M.M.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Amgen Inc., Cambridge, Massachusetts (J.G.D.); Sanofi, Waltham, Massachusetts (M.F.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Eisai, Andover, Massachusetts (Y.A.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.L.W.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); and Merck & Co., Inc., Kenilworth, New Jersey (D.T.)
| | - Donald Tweedie
- Genentech, South San Francisco, California (J.R.K.); Boehringer Ingelheim, Ridgefield, Connecticut (D.R.); Sekisui-XenoTech LLC, Kansas City, Kansas (D.B.B.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Eli Lilly and Company, Indianapolis, Indiana (M.M.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Amgen Inc., Cambridge, Massachusetts (J.G.D.); Sanofi, Waltham, Massachusetts (M.F.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Eisai, Andover, Massachusetts (Y.A.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.L.W.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); and Merck & Co., Inc., Kenilworth, New Jersey (D.T.)
| | - Niresh Hariparsad
- Genentech, South San Francisco, California (J.R.K.); Boehringer Ingelheim, Ridgefield, Connecticut (D.R.); Sekisui-XenoTech LLC, Kansas City, Kansas (D.B.B.); Janssen R&D, Spring House, Pennsylvania (S.D.); Vertex Pharmaceuticals, Boston, Massachusetts (C.F., N.H.); Eli Lilly and Company, Indianapolis, Indiana (M.M.); Novartis, East Hanover, New Jersey (H.J.E.); GlaxoSmithKline, King of Prussia, Pennsylvania (L.C.); Amgen Inc., Cambridge, Massachusetts (J.G.D.); Sanofi, Waltham, Massachusetts (M.F.); Pfizer Global Research and Development, Groton, Connecticut (T.C.G.); Eisai, Andover, Massachusetts (Y.A.S.); EMD Serono R&D Institute, Inc., Billerica, Massachusetts (R.L.W.); Corning Life Sciences, Woburn, Massachusetts (G.Z.); and Merck & Co., Inc., Kenilworth, New Jersey (D.T.)
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Ramaiahgari SC, Waidyanatha S, Dixon D, DeVito MJ, Paules RS, Ferguson SS. From the Cover: Three-Dimensional (3D) HepaRG Spheroid Model With Physiologically Relevant Xenobiotic Metabolism Competence and Hepatocyte Functionality for Liver Toxicity Screening. Toxicol Sci 2018. [PMID: 28633424 DOI: 10.1093/toxsci/kfx122] [Citation(s) in RCA: 65] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Effective prediction of human responses to chemical and drug exposure is of critical importance in environmental toxicology research and drug development. While significant progress has been made to address this challenge using invitro liver models, these approaches often fail due to inadequate tissue model functionality. Herein, we describe the development, optimization, and characterization of a novel three-dimensional (3D) spheroid model using differentiated HepaRG cells that achieve and maintain physiologically relevant levels of xenobiotic metabolism (CYP1A2, CYP2B6, and CYP3A4/5). This invitro model maintains a stable phenotype over multiple weeks in both 96- and 384-well formats, supports highly reproducible tissue-like architectures and models pharmacologically- and environmentally important hepatic receptor pathways (ie AhR, CAR, and PXR) analogous to primary human hepatocyte cultures. HepaRG spheroid cultures use 50-100× fewer cells than conventional two dimensional cultures, and enable the identification of metabolically activated toxicants. Spheroid size, time in culture and culture media composition were important factors affecting basal levels of xenobiotic metabolism and liver enzyme inducibility with activators of hepatic receptors AhR, CAR and PXR. Repeated exposure studies showed higher sensitivity than traditional 2D cultures in identifying compounds that cause liver injury and metabolism-dependent toxicity. This platform combines the well-documented impact of 3D culture configuration for improved tissue functionality and longevity with the requisite throughput and repeatability needed for year-over-year toxicology screening.
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Affiliation(s)
- Sreenivasa C Ramaiahgari
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, NIH, Durham, North Carolina 27709
| | - Suramya Waidyanatha
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, NIH, Durham, North Carolina 27709
| | - Darlene Dixon
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, NIH, Durham, North Carolina 27709
| | - Michael J DeVito
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, NIH, Durham, North Carolina 27709
| | - Richard S Paules
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, NIH, Durham, North Carolina 27709
| | - Stephen S Ferguson
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, NIH, Durham, North Carolina 27709
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Jonsson-Schmunk K, Schafer SC, Croyle MA. Impact of nanomedicine on hepatic cytochrome P450 3A4 activity: things to consider during pre-clinical and clinical studies. JOURNAL OF PHARMACEUTICAL INVESTIGATION 2017. [DOI: 10.1007/s40005-017-0376-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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16
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Kuramoto S, Kato M, Shindoh H, Kaneko A, Ishigai M, Miyauchi S. Simple Evaluation Method for CYP3A4 Induction from Human Hepatocytes: The Relative Factor Approach with an Induction Detection Limit Concentration Based on the Emax Model. Drug Metab Dispos 2017; 45:1139-1145. [PMID: 28821485 DOI: 10.1124/dmd.117.076349] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2017] [Accepted: 08/03/2017] [Indexed: 01/31/2023] Open
Abstract
We investigated the robustness and utility of the relative factor (RF) approach based on the maximum induction effect (Emax) model, using the mRNA induction data of 10 typical CYP3A4 inducers in cryopreserved human hepatocytes. The RF value is designated as the ratio of the induction detection limit concentration (IDLC) for a standard inducer, such as rifampicin (RIF) or phenobarbital (PB), to that for the compound (e.g., RFRIF is IDLCRIF/IDLCcpd; RFPB is IDLCPB/IDLCcpd). An important feature of the RF approach is that the profiles of the induction response curves on the logarithmic scale remain unchanged irrespective of inducers but are shifted parallel depending on the EC50 values. A key step in the RF approach is to convert the induction response curve by finding the IDLC of a standard inducer. The relative induction score was estimated not only from Emax and EC50 values but also from those calculated by the RF approach. These values showed good correlation, with a correlation coefficient of more than 0.974, which revealed the RF approach to be a robust analysis irrespective of its simplicity. Furthermore, the relationship between RFRIF or RFPB multiplied by the steady-state unbound plasma concentration and the in vivo induction ratio plotted using 10 typical inducers gives adequate thresholds for CYP3A4 drug-drug interaction risk assessment. In light of these findings, the simple RF approach using the IDLC value could be a useful method to adequately assess the risk of CYP3A4 induction in humans during drug discovery and development without evaluation of Emax and EC50.
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Affiliation(s)
- Shino Kuramoto
- Research Division, Chugai Pharmaceutical Co. Ltd., Kanagawa, Japan (S.K., M.K., H.S., A.K., M.I.); and Department of Pharmacokinetics, Toho University School of Pharmaceutical Sciences, Chiba, Japan (S.M.)
| | - Motohiro Kato
- Research Division, Chugai Pharmaceutical Co. Ltd., Kanagawa, Japan (S.K., M.K., H.S., A.K., M.I.); and Department of Pharmacokinetics, Toho University School of Pharmaceutical Sciences, Chiba, Japan (S.M.)
| | - Hidetoshi Shindoh
- Research Division, Chugai Pharmaceutical Co. Ltd., Kanagawa, Japan (S.K., M.K., H.S., A.K., M.I.); and Department of Pharmacokinetics, Toho University School of Pharmaceutical Sciences, Chiba, Japan (S.M.)
| | - Akihisa Kaneko
- Research Division, Chugai Pharmaceutical Co. Ltd., Kanagawa, Japan (S.K., M.K., H.S., A.K., M.I.); and Department of Pharmacokinetics, Toho University School of Pharmaceutical Sciences, Chiba, Japan (S.M.)
| | - Masaki Ishigai
- Research Division, Chugai Pharmaceutical Co. Ltd., Kanagawa, Japan (S.K., M.K., H.S., A.K., M.I.); and Department of Pharmacokinetics, Toho University School of Pharmaceutical Sciences, Chiba, Japan (S.M.)
| | - Seiji Miyauchi
- Research Division, Chugai Pharmaceutical Co. Ltd., Kanagawa, Japan (S.K., M.K., H.S., A.K., M.I.); and Department of Pharmacokinetics, Toho University School of Pharmaceutical Sciences, Chiba, Japan (S.M.)
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17
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Sun Y, Chothe PP, Sager JE, Tsao H, Moore A, Laitinen L, Hariparsad N. Quantitative Prediction of CYP3A4 Induction: Impact of Measured, Free, and Intracellular Perpetrator Concentrations from Human Hepatocyte Induction Studies on Drug-Drug Interaction Predictions. Drug Metab Dispos 2017; 45:692-705. [DOI: 10.1124/dmd.117.075481] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2017] [Accepted: 03/21/2017] [Indexed: 01/14/2023] Open
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18
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Zuo R, Li F, Parikh S, Cao L, Cooper KL, Hong Y, Liu J, Faris RA, Li D, Wang H. Evaluation of a Novel Renewable Hepatic Cell Model for Prediction of Clinical CYP3A4 Induction Using a Correlation-Based Relative Induction Score Approach. Drug Metab Dispos 2017; 45:198-207. [PMID: 28062541 PMCID: PMC5267519 DOI: 10.1124/dmd.116.072124] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2016] [Accepted: 12/01/2016] [Indexed: 01/22/2023] Open
Abstract
Metabolism enzyme induction-mediated drug-drug interactions need to be carefully characterized in vitro for drug candidates to predict in vivo safety risk and therapeutic efficiency. Currently, both the Food and Drug Administration and European Medicines Agency recommend using primary human hepatocytes as the gold standard in vitro test system for studying the induction potential of candidate drugs on cytochrome P450 (CYP), CYP3A4, CYP1A2, and CYP2B6. However, primary human hepatocytes are known to bear inherent limitations such as limited supply and large lot-to-lot variations, which result in an experimental burden to qualify new lots. To overcome these shortcomings, a renewable source of human hepatocytes (i.e., Corning HepatoCells) was developed from primary human hepatocytes and was evaluated for in vitro CYP3A4 induction using methods well established by the pharmaceutical industry. HepatoCells have shown mature hepatocyte-like morphology and demonstrated primary hepatocyte-like response to prototypical inducers of all three CYP enzymes with excellent consistency. Importantly, HepatoCells retain a phenobarbital-responsive nuclear translocation of human constitutive androstane receptor from the cytoplasm, characteristic to primary hepatocytes. To validate HepatoCells as a useful tool to predict potential clinical relevant CYP3A4 induction, we tested three different lots of HepatoCells with a group of clinical strong, moderate/weak CYP3A4 inducers, and noninducers. A relative induction score calibration curve-based approach was used for prediction. HepatoCells showed accurate prediction comparable to primary human hepatocytes. Together, these results demonstrate that Corning HepatoCells is a reliable in vitro model for drug-drug interaction studies during the early phase of drug testing.
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Affiliation(s)
- Rongjun Zuo
- Corning Life Sciences, Bedford, Massachusetts (R.Z., F.L., S.P., L.C., K.L.C.); Corning, Science and Technology, Corning, New York (Y.H., J.L., R.A.F.); and University of Maryland, School of Pharmacy, Baltimore, Maryland (D.L., H.W.)
| | - Feng Li
- Corning Life Sciences, Bedford, Massachusetts (R.Z., F.L., S.P., L.C., K.L.C.); Corning, Science and Technology, Corning, New York (Y.H., J.L., R.A.F.); and University of Maryland, School of Pharmacy, Baltimore, Maryland (D.L., H.W.)
| | - Sweta Parikh
- Corning Life Sciences, Bedford, Massachusetts (R.Z., F.L., S.P., L.C., K.L.C.); Corning, Science and Technology, Corning, New York (Y.H., J.L., R.A.F.); and University of Maryland, School of Pharmacy, Baltimore, Maryland (D.L., H.W.)
| | - Li Cao
- Corning Life Sciences, Bedford, Massachusetts (R.Z., F.L., S.P., L.C., K.L.C.); Corning, Science and Technology, Corning, New York (Y.H., J.L., R.A.F.); and University of Maryland, School of Pharmacy, Baltimore, Maryland (D.L., H.W.)
| | - Kirsten L Cooper
- Corning Life Sciences, Bedford, Massachusetts (R.Z., F.L., S.P., L.C., K.L.C.); Corning, Science and Technology, Corning, New York (Y.H., J.L., R.A.F.); and University of Maryland, School of Pharmacy, Baltimore, Maryland (D.L., H.W.)
| | - Yulong Hong
- Corning Life Sciences, Bedford, Massachusetts (R.Z., F.L., S.P., L.C., K.L.C.); Corning, Science and Technology, Corning, New York (Y.H., J.L., R.A.F.); and University of Maryland, School of Pharmacy, Baltimore, Maryland (D.L., H.W.)
| | - Jin Liu
- Corning Life Sciences, Bedford, Massachusetts (R.Z., F.L., S.P., L.C., K.L.C.); Corning, Science and Technology, Corning, New York (Y.H., J.L., R.A.F.); and University of Maryland, School of Pharmacy, Baltimore, Maryland (D.L., H.W.)
| | - Ronald A Faris
- Corning Life Sciences, Bedford, Massachusetts (R.Z., F.L., S.P., L.C., K.L.C.); Corning, Science and Technology, Corning, New York (Y.H., J.L., R.A.F.); and University of Maryland, School of Pharmacy, Baltimore, Maryland (D.L., H.W.)
| | - Daochuan Li
- Corning Life Sciences, Bedford, Massachusetts (R.Z., F.L., S.P., L.C., K.L.C.); Corning, Science and Technology, Corning, New York (Y.H., J.L., R.A.F.); and University of Maryland, School of Pharmacy, Baltimore, Maryland (D.L., H.W.)
| | - Hongbing Wang
- Corning Life Sciences, Bedford, Massachusetts (R.Z., F.L., S.P., L.C., K.L.C.); Corning, Science and Technology, Corning, New York (Y.H., J.L., R.A.F.); and University of Maryland, School of Pharmacy, Baltimore, Maryland (D.L., H.W.)
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Moore A, Chothe PP, Tsao H, Hariparsad N. Evaluation of the Interplay between Uptake Transport and CYP3A4 Induction in Micropatterned Cocultured Hepatocytes. Drug Metab Dispos 2016; 44:1910-1919. [PMID: 27655038 DOI: 10.1124/dmd.116.072660] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2016] [Accepted: 09/16/2016] [Indexed: 01/06/2023] Open
Abstract
Previously we assessed the inductive response of prototypical inducers in hepatocyte monocultures and the long-term coculture model HepatoPac using cryopreserved hepatocytes from the same donors. We noted that the rifampicin EC50 generated using the HepatoPac model corresponded better to the EC50 based on clinical data compared with data generated in the monoculture system. We postulated that there may be differences in the functioning of uptake transporters between the two systems that may have led to the EC50 difference. In this study, we characterized the functional activity of multiple uptake transporters in the two systems using cryopreserved hepatocytes from the same donors. Our data suggest that uptake transporter activity is higher in HepatoPac compared with the monoculture system. As a follow up to this study, we measured the intracellular concentrations of rifampicin and bosentan, which are known substrates of uptake transporters; we observed significantly higher intracellular concentrations of both compounds in HepatoPac relative to the monoculture system. This finding equated to lower cytochrome P450 isoform 3A4 (CYP3A4) EC50 values in the HepatoPac system compared with the monoculture system for both mRNA and activity. In parallel, no significant EC50 shift was observed for carbamazepine and phenytoin, which are not known to be substrates of uptake transporters. Our data suggest that next generation liver models such as HepatoPac may be a useful in vitro tool to quantitatively predict drug-drug interactions when it is known that the perpetrator is also a substrate of drug transporters.
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Affiliation(s)
- Amanda Moore
- Drug Metabolism and Pharmacokinetics, Vertex Pharmaceuticals Incorporated, Boston, Massachusetts
| | - Paresh P Chothe
- Drug Metabolism and Pharmacokinetics, Vertex Pharmaceuticals Incorporated, Boston, Massachusetts
| | - Hong Tsao
- Drug Metabolism and Pharmacokinetics, Vertex Pharmaceuticals Incorporated, Boston, Massachusetts
| | - Niresh Hariparsad
- Drug Metabolism and Pharmacokinetics, Vertex Pharmaceuticals Incorporated, Boston, Massachusetts
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Dixit V, Moore A, Tsao H, Hariparsad N. Application of Micropatterned Cocultured Hepatocytes to Evaluate the Inductive Potential and Degradation Rate of Major Xenobiotic Metabolizing Enzymes. ACTA ACUST UNITED AC 2015; 44:250-61. [PMID: 26658225 DOI: 10.1124/dmd.115.067173] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2015] [Accepted: 12/08/2015] [Indexed: 12/19/2022]
Abstract
Long-term coculture models of hepatocytes are promising tools to study drug transport, clearance, and hepatoxicity. In this report we compare the basal expression of drug disposition genes and the inductive response of prototypical inducers (rifampin, phenobarbital, phenytoin) in hepatocyte two-dimensional monocultures and the long-term coculture model (HepatoPac). All the inducers used in the study increased the expression and activity of CYP3A4, CYP2B6 and CYP2C enzymes in the HepatoPac cultures. The coculture model showed a consistent and higher induction of CYP2C enzymes compared with the monocultures. The EC50 of rifampin for CYP3A4 and CYP2C9 was up to 10-fold lower in HepatoPac than the monocultures. The EC50 of rifampin calculated from the clinical drug interaction studies correlated well with the EC50 observed in the HepatoPac cultures. Owing to the long-term stability of the HepatoPac cultures, we were able to directly measure a half-life (t1/2) for both CYP3A4 and CYP2B6 using the depletion kinetics of mRNA and functional activity. The t1/2 for CYP3A4 mRNA was 26 hours and that for the functional protein was 49 hours. The t1/2 of CYP2B6 was 38 hours (mRNA) and 68 hours (activity), which is longer than CYP3A4 and shows the differential turnover of these two proteins. This is the first study to our knowledge to report the turnover rate of CYP2B6 in human hepatocytes. The data presented here demonstrate that the HepatoPac cultures have the potential to be used in long-term culture to mimic complex clinical scenarios.
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Affiliation(s)
- Vaishali Dixit
- Drug Metabolism and Pharmacokinetics, Vertex Pharmaceuticals Incorporated, Boston, Massachusetts
| | - Amanda Moore
- Drug Metabolism and Pharmacokinetics, Vertex Pharmaceuticals Incorporated, Boston, Massachusetts
| | - Hong Tsao
- Drug Metabolism and Pharmacokinetics, Vertex Pharmaceuticals Incorporated, Boston, Massachusetts
| | - Niresh Hariparsad
- Drug Metabolism and Pharmacokinetics, Vertex Pharmaceuticals Incorporated, Boston, Massachusetts
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Riley RJ, Wilson CE. Cytochrome P450 time-dependent inhibition and induction: advances in assays, risk analysis and modelling. Expert Opin Drug Metab Toxicol 2015; 11:557-72. [PMID: 25659570 DOI: 10.1517/17425255.2015.1013095] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
INTRODUCTION It is widely accepted that current practice of polypharmacy inevitably increases the incidence of drug-drug interactions (DDIs). Serious DDIs are a major liability for new molecular entities entering the pharmaceutical market. Various strategies are employed to avoid problematic compounds for clinical development. Progress made with reversible CYP DDIs has prompted a switch to study and model time-dependent inhibition and induction interactions. AREAS COVERED An overview of popular experimental practices is presented with discussion of techniques and algorithms used to analyse the clinical DDI risk. Emphasis is placed on the transition from early, simple static equations, via more complex net mechanistic, static models to dynamic approaches involving multiple perpetrators and metabolites, simultaneous inhibition and induction. EXPERT OPINION Inclusion of the more conservative terms for parameters required for DDI evaluation may eliminate promising chemical space, encourages poor practice and hampers innovation. Breakthroughs have originated from understanding of 'outliers' from such analyses where CYP enzyme-transporter interplay may be involved. The role of key transporters in drug disposition is firmly established as the chemistry required to address new targets deviates from traditional 'drug-like' space. Attempts to model more complex interactions for substrates of both CYP enzymes and drug transporters are still in their infancy and will benefit from dynamic modelling.
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Affiliation(s)
- Robert J Riley
- Evotec (UK) Ltd , 114 Innovation Drive, Milton Park, Abingdon, Oxon, OX14 4RZ , UK +44 1235 861561 ; +44 1235 863139 ;
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Cho YY, Jeong HU, Kim JH, Lee HS. Effect of honokiol on the induction of drug-metabolizing enzymes in human hepatocytes. DRUG DESIGN DEVELOPMENT AND THERAPY 2014; 8:2137-45. [PMID: 25395831 PMCID: PMC4224024 DOI: 10.2147/dddt.s72305] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Honokiol, 2-(4-hydroxy-3-prop-2-enyl-phenyl)-4-prop-2-enyl-phenol, an active component of Magnolia officinalis and Magnolia grandiflora, exerts various pharmacological activities such as antitumorigenic, antioxidative, anti-inflammatory, neurotrophic, and antithrombotic effects. To investigate whether honokiol acts as a perpetrator in drug interactions, messenger ribonucleic acid (mRNA) levels of phase I and II drug-metabolizing enzymes, including cytochrome P450 (CYP), UDP-glucuronosyltransferase (UGT), and sulfotransferase 2A1 (SULT2A1), were analyzed by real-time reverse transcription polymerase chain reaction following 48-hour honokiol exposure in three independent cryopreserved human hepatocyte cultures. Honokiol treatment at the highest concentration tested (50 μM) increased the CYP2B6 mRNA level and CYP2B6-catalyzed bupropion hydroxylase activity more than two-fold in three different hepatocyte cultures, indicating that honokiol induces CYP2B6 at higher concentrations. However, honokiol treatment (0.5–50 μM) did not significantly alter the mRNA levels of phase I enzymes (CYP1A2, CYP3A4, CYP2C8, CYP2C9, and CYP2C19) or phase II enzymes (UGT1A1, UGT1A4, UGT1A9, UGT2B7, and SULT2A1) in cryopreserved human hepatocyte cultures. CYP1A2-catalyzed phenacetin O-deethylase and CYP3A4-catalyzed midazolam 1′-hydroxylase activities were not affected by 48-hour honokiol treatment in cryopreserved human hepatocytes. These results indicate that honokiol is a weak CYP2B6 inducer and is unlikely to increase the metabolism of concomitant CYP2B6 substrates and cause pharmacokinetic-based drug interactions in humans.
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Affiliation(s)
- Yong-Yeon Cho
- College of Pharmacy, The Catholic University of Korea, Bucheon, Korea
| | - Hyeon-Uk Jeong
- College of Pharmacy, The Catholic University of Korea, Bucheon, Korea
| | - Jeong-Han Kim
- Department of Agricultural Biotechnology, Seoul National University, Seoul, Korea
| | - Hye Suk Lee
- College of Pharmacy, The Catholic University of Korea, Bucheon, Korea
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