Comparison of different approaches to predict metabolic drug-drug interactions

Einolf, Heidi J.

doi:10.1080/00498250701620700

Cited by 78 publications

(128 citation statements)

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“…The observed and predicted AUC and C max values of these substrates were generally comparable (Fig. 4); 92% of the predicted C max and 87% of the predicted AUC values fell within 2-fold of the observed values, similar to a previous report (Einolf, 2007). Several significant deviations in the observed and predicted pharmacokinetic values were observed.…”

Section: Resultssupporting

confidence: 71%

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Confidence Assessment of the Simcyp Time-Based Approach and a Static Mathematical Model in Predicting Clinical Drug-Drug Interactions for Mechanism-Based CYP3A Inhibitors

Wang¹

2010

Drug Metab Dispos

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ABSTRACT:Accurate prediction of the extent of mechanism-based CYP3A inhibition is critical in determining the timing of clinical drug interaction studies in drug development. To evaluate the prediction accuracy of the static and Simcyp time-based approaches, 54 clinical drug interactions involving mechanism-based CYP3A inhibitors were predicted using both methods. The Simcyp timebased approach generated better prediction when 0.03 h ؊1 was used as the hepatic CYP3A enzyme degradation rate constant (k deg ) value. Of the predictions 87 and 55% had an error less than 2 and 0. Drug-drug interactions remain an area of focus in drug discovery and development. Mechanism-based inhibition of CYP3A is one of the major causes of clinical drug-drug interactions and generally leads to greater concern, as highlighted by the list of moderate and strong CYP3A inhibitors in the Food and Drug Administration (2006) Drug Interaction Guidance. The inhibitory effects of a mechanism-based CYP3A inhibitor persist long after the compound is eliminated from the body because the recovery of CYP3A enzyme activity requires de novo protein synthesis or slow release of the enzyme from the enzyme-inhibitor complex. Because of the primary role of CYP3A in drug disposition, prediction of the clinical drug interaction potential of a mechanism-based CYP3A inhibitor would be helpful in guiding the timing and design of clinical studies.Several approaches have been developed to predict clinical outcomes of mechanism-based inhibition. The static mathematical model developed by Mayhew et al. (2000) is a commonly used approach to predict mechanism-based drug interactions from in vitro estimated inactivation parameters. Several modifications to the original model have been made to incorporate the effects of intestinal wall metabolism (Wang et al., 2004b), competitive inhibition, and induction (Fahmi et al., 2009). Nonetheless, these static models are only capable of predicting the average magnitude of drug interactions across a population, assuming that the steady state of enzyme inhibition has been reached. Temporal changes in inhibitor concentrations and CYP3A enzyme activities as well as interindividual variability in CYP3A enzyme levels and rate constants of enzyme degradation are not considered. In addition, it is difficult to assess the effects of dosing regimens (e.g., irregular dosing) on the extent of drug interactions using a static model.Several physiologically based pharmacokinetic models (PBPK) were developed to address some of the aforementioned limitations with static models (Kanamitsu et al., 2000;Zhang et al., 2009;Fenneteau et al., 2010). These PBPK models take into account temporal changes in inhibitor and substrate concentrations and enzyme activities as well as the enzyme inhibition concept in the static models. They can be used to simulate drug concentrationtime profiles and to explore the effects of various dosing regimens. Simcyp (Simcyp Limited, Sheffield, UK) is a commercially available absorption, distribution, metabolism, and...

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Section: Resultssupporting

confidence: 71%

“…Several retrospective analyses were conducted to compare the prediction accuracy of the Simcyp models with that of static models (Einolf, 2007;Fahmi et al, 2009). However, only a small portion of the entire dataset in these studies involved mechanism-based inhibitors of CYP3A.…”

Section: Discussionmentioning

confidence: 99%

Confidence Assessment of the Simcyp Time-Based Approach and a Static Mathematical Model in Predicting Clinical Drug-Drug Interactions for Mechanism-Based CYP3A Inhibitors

Wang¹

2010

Drug Metab Dispos

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“…The theoretical basis underlying the quantitative predictions of drug interactions associated with reversible inhibition has been covered comprehensively in the literature (Ito et al, 1998;Rostami-Hodjegan and Tucker, 2004;Brown et al, 2005;Shou, 2005;Obach et al, 2006;Einolf 2007). In brief, the ratio change of AUC in the presence or absence of a P450 inhibitor can be approximated by eq.…”

Section: Methodsmentioning

confidence: 99%

“…The inhibition type has not been fully elucidated for all the inhibitors studied in this work; therefore, in the absence of this information, K i ϭ IC 50 /2 was uniformly applied. As a generic strategy, this is appropriate because in the drug discovery environment, IC 50 rather than K i values are generated initially, and the precise type of reversible inhibition is usually defined later.The theoretical basis underlying the quantitative predictions of drug interactions associated with reversible inhibition has been covered comprehensively in the literature (Ito et al, 1998;Rostami-Hodjegan and Tucker, 2004;Brown et al, 2005;Shou, 2005;Obach et al, 2006;Einolf 2007). In brief, the ratio change of AUC in the presence or absence of a P450 inhibitor can be approximated by eq.…”

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confidence: 99%

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Integrated in Vitro Analysis for the in Vivo Prediction of Cytochrome P450-Mediated Drug-Drug Interactions

McGinnity¹,

Waters²,

Tucker³

et al. 2008

Drug Metab Dispos

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ABSTRACT:Unbound IC 50 (IC 50,u ) values of 15 drugs were determined in eight recombinantly expressed human cytochromes P450 (P450s) and human hepatocytes, and the data were used to simulate clinical area under the plasma concentration-time curve changes (␦AUC) on coadministration with prototypic CYP2D6 substrates. Significant differences in IC 50,u values between enzyme sources were observed for quinidine (0.02 M in recombinant CYP2D6 versus 0.5 M in hepatocytes) and propafenone (0.02 versus 4.1 M). The relative contribution of individual P450s toward the oxidative metabolism of clinical probes desipramine, imipramine, tolterodine, propranolol, and metoprolol was estimated via determinations of intrinsic clearance using recombinant P450s (rP450s). Simulated ␦AUC were compared with those observed in vivo via the ratios of unbound inhibitor concentration at the entrance to the liver to inhibition constants determined against rP450s ([I] in,u /K i ) and incorporating parallel substrate elimination pathways. For this dataset, there were 20% false negatives (observed ␦AUC > 2, predicted ␦AUC < 2), 77% correct predictions, and 3% false positives. Thus, the [I] in,u /K i approach appears relatively successful at estimating the degree of clinical interactions and can be incorporated into drug discovery strategies. Using a Simcyp ADME (absorption, metabolism, distribution, elimination) simulator (Simcyp Ltd., Sheffield, UK), there were 3% false negatives, 94% correct simulations, and 3% false positives. False-negative predictions were rationalized as a result of mechanism-based inhibition, production of inhibitory metabolites, and/or hepatic uptake. Integrating inhibition and reaction phenotyping data from automated rP450 screens have shown applicability to predict the occurrence and degree of in vivo drug-drug interactions, and such data may identify the clinical consequences for candidate drugs as both "perpetrators" and "victims" of P450-mediated interactions.Inhibition of cytochrome P450 (P450) metabolism is recognized as one of the more prevalent mechanisms of clinical drug-drug interactions (DDIs) and may result in serious clinical and toxicological consequences (Nelson, 2002). During the past 2 decades, both in vitro and in vivo assessments of the P450 inhibition potential and disposition of drugs have led to a relatively thorough appreciation of the underlying reasons for certain drug combinations resulting in significant clinical outcomes. Application of this knowledge has led researchers to propose strategies that assess the potential of new chemical entities to cause clinical DDIs via inhibition of P450 metabolism. As a result, in the past decade or so, in vitro screens that determine the degree of P450 inhibition have become commonplace in drug discovery screening cascades. These screens are used to evaluate and optimize potential candidate drugs and to prioritize and design suitable clinical studies.In vitro-in vivo extrapolation (IVIVE) strategies used for P450 inhibition-mediated DDIs range from simple bu...

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Enzyme Inhibition and Inactivation: Cytochrome P450 Enzymes

Obach

2009

Enzyme Inhibition in Drug Discovery and Development

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Comparison of different approaches to predict metabolic drug-drug interactions

Cited by 78 publications

References 130 publications

Confidence Assessment of the Simcyp Time-Based Approach and a Static Mathematical Model in Predicting Clinical Drug-Drug Interactions for Mechanism-Based CYP3A Inhibitors

Confidence Assessment of the Simcyp Time-Based Approach and a Static Mathematical Model in Predicting Clinical Drug-Drug Interactions for Mechanism-Based CYP3A Inhibitors

Integrated in Vitro Analysis for the in Vivo Prediction of Cytochrome P450-Mediated Drug-Drug Interactions

Enzyme Inhibition and Inactivation: Cytochrome P450 Enzymes

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