An examination of IC50 and IC50-shift experiments in assessing time-dependent inhibition of CYP3A4, CYP2D6 and CYP2C9 in human liver microsomes.
TL;DR: The relationship between time-dependent inactivation (TDI) and IC50 is examined using a consolidated method for evaluating CYP450 inhibition during drug discovery and the "shifted IC50" could be used to estimate, the K(I) and TDI potency ratio k(inact)/K( I) to within 2-fold in most cases.
Abstract: The relationship between time-dependent inactivation (TDI) and IC50 is examined using a consolidated method for evaluating CYP450 inhibition during drug discovery. An IC50 fold-shift of >1.5 indicated significant TDI potency. Further, the "shifted IC50" could be used to estimate, the K(I) and TDI potency ratio k(inact)/K(I) to within 2-fold in most cases.
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TL;DR: A team of scientists from 16 pharmaceutical research organizations that are member companies of the Pharmaceutical Research and Manufacturers of America offer a discussion of the phenomenon of TDI with emphasis on the laboratory methods used in its measurement.
Abstract: Time-dependent inhibition (TDI) of cytochrome P450 (P450) enzymes caused by new molecular entities (NMEs) is of concern because such compounds can be responsible for clinically relevant drug-drug interactions (DDI). Although the biochemistry underlying mechanism-based inactivation (MBI) of P450 enzymes has been generally understood for several years, significant advances have been made only in the past few years regarding how in vitro time-dependent inhibition data can be used to understand and predict clinical DDI. In this article, a team of scientists from 16 pharmaceutical research organizations that are member companies of the Pharmaceutical Research and Manufacturers of America offer a discussion of the phenomenon of TDI with emphasis on the laboratory methods used in its measurement. Results of an anonymous survey regarding pharmaceutical industry practices and strategies around TDI are reported. Specific topics that still possess a high degree of uncertainty are raised, such as parameter estimates needed to make predictions of DDI magnitude from in vitro inactivation parameters. A description of follow-up mechanistic experiments that can be done to characterize TDI are described. A consensus recommendation regarding common practices to address TDI is included, the salient points of which include the use of a tiered approach wherein abbreviated assays are first used to determine whether NMEs demonstrate TDI or not, followed by more thorough inactivation studies for those that do to define the parameters needed for prediction of DDI.
264 citations
Cites background or methods from "An examination of IC50 and IC50-shi..."
...5 with a 30-min preincubation (Berry and Zhao, 2008), suggesting the use of such values as a cutoff for identifying a compound as a TDI....
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...Compounds that are known to be TDI showed IC50 shifts of 1.5 with a 30-min preincubation (Berry and Zhao, 2008), suggesting the use of such values as a cutoff for identifying a compound as a TDI....
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TL;DR: It is proposed that the kinact/KI should be employed as a critical parameter to identify covalent inhibitors, interpret structure-activity relationships (SARs), translate activity from biochemical assays to the cell, and more accurately define selectivity.
Abstract: The clinical and commercial success of covalent drugs has prompted a renewed and more deliberate pursuit of covalent and irreversible mechanisms within drug discovery. A covalent mechanism can produce potent inhibition in a biochemical, cellular, or in vivo setting. In many cases, teams choose to focus on the consequences of the covalent event, defined by an IC50 value. In a biochemical assay, the IC50 may simply reflect the target protein concentration in the assay. What has received less attention is the importance of the rate of covalent modification, defined by kinact/KI. The kinact/KI is a rate constant describing the efficiency of covalent bond formation resulting from the potency (KI) of the first reversible binding event and the maximum potential rate (kinact) of inactivation. In this perspective, it is proposed that the kinact/KI should be employed as a critical parameter to identify covalent inhibitors, interpret structure-activity relationships (SARs), translate activity from biochemical assays to the cell, and more accurately define selectivity. It is also proposed that a physiologically relevant kinact/KI and an (unbound) AUC generated from a pharmacokinetic profile reflecting direct exposure of the inhibitor to the target protein are two critical determinants of in vivo covalent occupancy. A simple equation is presented to define this relationship and improve the interpretation of covalent and irreversible kinetics.
184 citations
TL;DR: Structure−Activity Relationships and Discovery Strategies To Mitigate Drug−Drug Interaction Risks and Pharmacokinetics, Dynamics and Metabolism.
Abstract: Structure−Activity Relationships and Discovery Strategies To Mitigate Drug−Drug Interaction Risks Suvi T. M. Orr,† Sharon L. Ripp,‡ T. Eric Ballard,† Jaclyn L. Henderson,† Dennis O. Scott, R. Scott Obach,‡ Hao Sun,‡ and Amit S. Kalgutkar* †Worldwide Medicinal Chemistry and ‡Pharmacokinetics, Dynamics and Metabolism, Pfizer Global Research and Development, Eastern Point Road, Groton, Connecticut 06340, United States Pharmacokinetics, Dynamics and Metabolism, Pfizer Global Research and Development, 620 Memorial Drive, Cambridge, Massachusetts 02139, United States
169 citations
TL;DR: In this paper, the authors derive a relation between potentially time-dependent IC(50) values and K(I), k(inact) parameters for different types of inhibition.
Abstract: The potential of enzyme inhibition of a drug is frequently quantified in terms of IC(50) values. Although this is a suitable quantity for reversible inhibitors, concerns arise when dealing with irreversible or mechanism-based inhibitors (MBIs). IC(50) values of MBIs are time dependent, causing serious problems when aiming at ranking different compounds with respect to their inhibitory potential. As a consequence, most studies and ranking schemes related to MBIs rely on the inhibition constant (K(I)) and the rate of enzyme inactivation (k(inact)) rather than on IC(50) values. In this article, the authors derive a novel relation between potentially time-dependent IC(50) values and K(I), k(inact) parameters for different types of inhibition. This allows for direct estimation of K(I) and k(inact) values from time-dependent IC(50) values, even without the need of additional preincubation experiments. The application of this approach is illustrated using a fluorimetric assay to access the drug-drug interaction potential associated with new chemical entities. The approach can easily be implemented using standard software tools (e.g., XLfit) and may also be suitable for applications where mechanism-based inhibition is a desired mode of action (e.g., at particular pharmacological drug targets).
102 citations
TL;DR: Results of this study show that, although metabolites contribute to in vivo DDIs, their relative abundance in circulation or logP values do not predict their contribution to in vitro DDI risk.
Abstract: The aim of this study was to evaluate the contribution of metabolites to drug-drug interactions (DDI) using the inhibition of CYP2C19 and CYP3A4 by omeprazole and its metabolites as a model. Of the metabolites identified in vivo, 5-hydroxyomeprazole, 5′-O-desmethylomeprazole, omeprazole sulfone, and carboxyomeprazole had a metabolite to parent area under the plasma concentration–time curve (AUCm/AUCp) ratio ≥ 0.25 when either total or unbound concentrations were measured after a single 20-mg dose of omeprazole in a cocktail. All of the metabolites inhibited CYP2C19 and CYP3A4 reversibly. In addition omeprazole, omeprazole sulfone, and 5′-O-desmethylomeprazole were time dependent inhibitors (TDI) of CYP2C19, whereas omeprazole and 5′-O-desmethylomeprazole were found to be TDIs of CYP3A4. The in vitro inhibition constants and in vivo plasma concentrations were used to evaluate whether characterization of the metabolites affected DDI risk assessment. Identifying omeprazole as a TDI of both CYP2C19 and CYP3A4 was the most important factor in DDI risk assessment. Consideration of reversible inhibition by omeprazole and its metabolites would not identify DDI risk with CYP3A4, and with CYP2C19, reversible inhibition values would only identify DDI risk if the metabolites were included in the assessment. On the basis of inactivation data, CYP2C19 and CYP3A4 inhibition by omeprazole would be sufficient to identify risk, but metabolites were predicted to contribute 30–63% to the in vivo hepatic interactions. Therefore, consideration of metabolites may be important in quantitative predictions of in vivo DDIs. The results of this study show that, although metabolites contribute to in vivo DDIs, their relative abundance in circulation or logP values do not predict their contribution to in vivo DDI risk.
84 citations
Cites background from "An examination of IC50 and IC50-shi..."
...A shift $1.5 was considered to indicate irreversible inhibitory potential (Berry and Zhao, 2008; Grimm et al., 2009)....
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...5 was considered to indicate irreversible inhibitory potential (Berry and Zhao, 2008; Grimm et al., 2009)....
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