1
|
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: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [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.
Collapse
|
|
7 |
36 |
2
|
Hariparsad N, Ramsden D, Palamanda J, Dekeyser JG, Fahmi OA, Kenny JR, Einolf H, Mohutsky M, Pardon M, Siu YA, Chen L, Sinz M, Jones B, Walsky R, Dallas S, Balani SK, Zhang G, Buckley D, Tweedie D. Considerations from the IQ Induction Working Group in Response to Drug-Drug Interaction Guidance from Regulatory Agencies: Focus on Downregulation, CYP2C Induction, and CYP2B6 Positive Control. Drug Metab Dispos 2017; 45:1049-1059. [PMID: 28646080 DOI: 10.1124/dmd.116.074567] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2017] [Accepted: 06/16/2017] [Indexed: 12/21/2022] Open
Abstract
The European Medicines Agency (EMA), the Pharmaceutical and Medical Devices Agency (PMDA), and the Food and Drug Administration (FDA) have issued guidelines for the conduct of drug-drug interaction studies. To examine the applicability of these regulatory recommendations specifically for induction, a group of scientists, under the auspices of the Drug Metabolism Leadership Group of the Innovation and Quality (IQ) Consortium, formed the Induction Working Group (IWG). A team of 19 scientists, from 16 of the 39 pharmaceutical companies that are members of the IQ Consortium and two Contract Research Organizations reviewed the recommendations, focusing initially on the current EMA guidelines. Questions were collated from IQ member companies as to which aspects of the guidelines require further evaluation. The EMA was then approached to provide insights into their recommendations on the following: 1) evaluation of downregulation, 2) in vitro assessment of CYP2C induction, 3) the use of CITCO as the positive control for CYP2B6 induction by CAR, 4) data interpretation (a 2-fold increase in mRNA as evidence of induction), and 5) the duration of incubation of hepatocytes with test article. The IWG conducted an anonymous survey among IQ member companies to query current practices, focusing specifically on the aforementioned key points. Responses were received from 19 companies. All data and information were blinded before being shared with the IWG. The results of the survey are presented, together with consensus recommendations on downregulation, CYP2C induction, and CYP2B6 positive control. Results and recommendations related to data interpretation and induction time course will be reported in subsequent articles.
Collapse
|
|
8 |
27 |
3
|
Taxak N, Desai PV, Patel B, Mohutsky M, Klimkowski VJ, Gombar V, Bharatam PV. Metabolic-intermediate complex formation with cytochrome P450: theoretical studies in elucidating the reaction pathway for the generation of reactive nitroso intermediate. J Comput Chem 2012; 33:1740-7. [PMID: 22610824 DOI: 10.1002/jcc.23008] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2011] [Revised: 04/16/2012] [Accepted: 04/20/2012] [Indexed: 11/10/2022]
Abstract
Mechanism-based inhibition (MBI) of cytochrome P450 (CYP) can lead to drug-drug interactions and often to toxicity. Some aliphatic and aromatic amines can undergo biotransformation reactions to form reactive metabolites such as nitrosoalkanes, leading to MBI of CYPs. It has been proposed that the nitrosoalkanes coordinate with the heme iron, forming metabolic-intermediate complex (MIC), resulting in the quasi-irreversible inhibition of CYPs. Limited mechanistic details regarding the formation of reactive nitroso intermediate and its coordination with heme-iron have been reported. A quantum chemical analysis was performed to elucidate potential reaction pathways for the generation of nitroso intermediate and the formation of MIC. Elucidation of the energy profile along the reaction path, identification of three-dimensional structures of reactive intermediates and transition states, as well as charge and spin density analyses, were performed using the density functional B3LYP method. The study was performed using Cpd I [iron (IV-oxo] heme porphine with SH(-) as the axial ligand) to represent the catalytic domain of CYP, simulating the biotransformation process. Three pathways: (i) N-oxidation followed by proton shuttle, (ii) N-oxidation followed by 1,2-H shift, and (iii) H-abstraction followed by rebound mechanism, were studied. It was observed that the proton shuttle pathway was more favorable over the whole reaction leading to reactive nitroso intermediate. This study revealed that the MIC formation from a primary amine is a favorable exothermic process, involving eight different steps and preferably takes place on the doublet spin surface of Cpd I. The rate-determining step was identified to be the first N-oxidation of primary amine.
Collapse
|
Research Support, Non-U.S. Gov't |
13 |
27 |
4
|
Ring B, Wrighton SA, Mohutsky M. Reversible mechanisms of enzyme inhibition and resulting clinical significance. Methods Mol Biol 2014; 1113:37-56. [PMID: 24523108 DOI: 10.1007/978-1-62703-758-7_4] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Inhibition of a drug-metabolizing enzyme by the reversible interaction of a drug with the enzyme, thus decreasing the metabolism of another drug, is a major cause of clinically significant drug-drug interactions. This chapter defines the four reversible mechanisms of inhibition exhibited by drugs: competitive, noncompetitive, uncompetitive, and mixed competitive/noncompetitive. An in vitro procedure to determine the potential of a drug to be a reversible inhibitor is also provided. Finally, a number of examples of clinically significant drug-drug interactions resulting from reversible inhibition are described.
Collapse
|
Review |
11 |
22 |
5
|
Abstract
This chapter describes the types of irreversible inhibition of drug-metabolizing enzymes and the methods commonly employed to quantify the irreversible inhibition and subsequently predict the extent and time course of clinically important drug-drug interactions.
Collapse
|
Review |
11 |
16 |
6
|
Ramsden D, Fung C, Hariparsad N, Kenny JR, Mohutsky M, Parrott NJ, Robertson S, Tweedie DJ. Perspectives from the Innovation and Quality Consortium Induction Working Group on Factors Impacting Clinical Drug-Drug Interactions Resulting from Induction: Focus on Cytochrome 3A Substrates. Drug Metab Dispos 2019; 47:1206-1221. [PMID: 31439574 DOI: 10.1124/dmd.119.087270] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Accepted: 08/06/2019] [Indexed: 12/14/2022] Open
Abstract
A recent publication from the Innovation and Quality Consortium Induction Working Group collated a large clinical data set with the goal of evaluating the accuracy of drug-drug interaction (DDI) prediction from in vitro data. Somewhat surprisingly, comparison across studies of the mean- or median-reported area under the curve ratio showed appreciable variability in the magnitude of outcome. This commentary explores the possible drivers of this range of outcomes observed in clinical induction studies. While recommendations on clinical study design are not being proposed, some key observations were informative during the aggregate analysis of clinical data. Although DDI data are often presented using median data, individual data would enable evaluation of how differences in study design, baseline expression, and the number of subjects contribute. Since variability in perpetrator pharmacokinetics (PK) could impact the overall DDI interpretation, should this be routinely captured? Maximal induction was typically observed after 5-7 days of dosing. Thus, when the half-life of the inducer is less than 30 hours, are there benefits to a more standardized study design? A large proportion of CYP3A4 inducers were also CYP3A4 inhibitors and/or inactivators based on in vitro data. In these cases, using CYP3A selective substrates has limitations. More intensive monitoring of changes in area under the curve over time is warranted. With selective CYP3A substrates, the net effect was often inhibition, whereas less selective substrates could discern induction through mechanisms not susceptible to inhibition. The latter included oral contraceptives, which raise concerns of reduced efficacy following induction. Alternative approaches for modeling induction, such as applying biomarkers and physiologically based pharmacokinetic modeling (PBPK), are also considered. SIGNIFICANCE STATEMENT: The goal of this commentary is to stimulate discussion on whether there are opportunities to optimize clinical drug-drug interaction study design. The overall aim is to reduce, understand and contextualize the variability observed in the magnitude of induction across reported clinical studies. A large clinical CYP3A induction dataset was collected and further analyzed to identify trends and gaps. Reporting individual victim PK data, characterizing perpetrator PK and including additional PK assessments for mixed-mechanism perpetrators may provide insights into how these factors impact differences observed in clinical outcomes. The potential utility of biomarkers and PBPK modeling are discussed in considering future directions.
Collapse
|
|
6 |
14 |
7
|
Botts S, Ennulat D, Francke-Carroll S, Graham M, Maronpot RR, Mohutsky M. Introduction to Hepatic Drug Metabolizing Enzyme Induction in Drug Safety Evaluation Studies. Toxicol Pathol 2010; 38:796-8. [DOI: 10.1177/0192623310374330] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
The following three articles represent the output of a combined effort initiated by the Scientific Regulatory Policy Committee of the Society of Toxicologic Pathology to provide a unified review of current scientific practices and relevant literature and provide suggestions regarding the recognition, interpretation, and risk assessment of hepatic drug metabolizing enzyme (DME) induction studies. The core objective was to provide a review that the scientific community including pathologists, regulatory scientists, toxicologists, investigative scientists, and others would find valuable for managing, designing, and interpreting toxicity studies supporting regulatory filings. Three working groups composed of scientists from industry, academia, and regulatory agencies were convened to review the available literature on important aspects of the interpretation and risk assessment of hepatic microsomal DME enzyme induction in three publications. The three reviews are as follows: “Effects of Hepatic Drug Metabolizing Enzyme Induction on Clinical Pathology Parameters in Animals and Man,” Toxicol Pathol “Hepatic Drug Metabolizing Enzyme Induction: Microscopic and Ultrastructural Appearance,” Toxicol Pathol “Hepatic Drug Metabolizing Enzyme Induction and Implications for Preclinical and Clinical Risk Assessment,” Toxicol Pathol The purpose of this introduction is not to summarize the articles but rather to frame the series and to provide a common mechanistic introduction.
Collapse
|
|
15 |
10 |
8
|
Gombar V, Alberts J, Cassidy K, Mattioni B, Mohutsky M. In Silico Metabolism Studies in Drug Discovery: Prediction of Metabolic Stability. Curr Comput Aided Drug Des 2006. [DOI: 10.2174/157340906777441726] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
|
|
19 |
6 |
9
|
Borel A, Fogueri U, Surendradoss J, Moulton R, Goldstein K, Bedwell D, Mohutsky M. The combined application of long term hepatic co-culture and RNA interference for reaction phenotyping: lessons learned. Drug Metab Pharmacokinet 2019. [DOI: 10.1016/j.dmpk.2018.09.173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
|
|
6 |
|
10
|
Kolur A, Hogan A, Hullett S, Sawada G, Mohutsky M, Hillgren K, Guo Y, Morse B. P232 - Prediction of hepatic clearance and partitioning in rat for improved BSEP inhibition risk assessment in humans. Drug Metab Pharmacokinet 2020. [DOI: 10.1016/j.dmpk.2020.04.233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
|
|
5 |
|
11
|
Chen L, Qiu J, Mohutsky M, Moulton R, Pak A, Borel A, Alberts J, Ochoa C, Martell C, Surendradoss J, Hillgren K, Guo Y. P134 - Evaluation of CRISPR-CAS9 and CRISPR-CAS13 in modulating drug metabolizing enzymes. Drug Metab Pharmacokinet 2020. [DOI: 10.1016/j.dmpk.2020.04.135] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
|
|
5 |
|