Prediction of the in Vivo Interaction Between Midazolam and Macrolides Based on in Vitro Studies Using Human Liver Microsomes

K, Ito; Ogihara, Kanako; Kanamitsu, Shin-ichi; Itoh, Tomoo

doi:10.1124/dmd.31.7.945

Cited by 137 publications

(112 citation statements)

References 24 publications

(40 reference statements)

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“…However, in these reports, under-predictions of DDIs for several drugs using reversible inhibition data were made, as a result of these compounds actually being irreversible inactivators of drug-metabolizing enzymes. For individual drugs, others have shown that DDIs caused by irreversible inactivation of P450 enzymes can be predicted (Kanamitsu et al, 2000a;Mayhew et al, 2000;Yamano et al, 2001;Ito et al, 2003;Wang et al, 2004;Venkatakrishnan and Obach, 2005;Galetin et al, 2006). In these reports, the investigators have used various values for the input parameters such as enzyme degradation rate constants de- FIG.…”

Section: Discussionmentioning

confidence: 99%

“…For mechanism-based inactivators, there have been some reports describing the prediction of in vivo DDIs, particularly for CYP3A (Kanamitsu et al, 2000a;Mayhew et al, 2000;Yamano et al, 2001;Ito et al, 2003;Wang et al, 2004;Galetin et al, 2006), as well as one analysis for CYP2D6 . Compared with reversible inhibition, there are some added complexities regarding the prediction of DDIs from inactivation data.…”

Section: Introductionmentioning

confidence: 99%

“…However, the magnitude of predicted DDIs for inducers varies with the source of individual hepatocytes. Recently, in vitro induction data from an immortalized human hepatocyte line, which gives a robust and reliable response, has been shown to yield quantitative predictions of CYP3A induction-based DDIs in vivo (Ripp et al, 2006).For mechanism-based inactivators, there have been some reports describing the prediction of in vivo DDIs, particularly for CYP3A (Kanamitsu et al, 2000a;Mayhew et al, 2000;Yamano et al, 2001;Ito et al, 2003;Wang et al, 2004;Galetin et al, 2006), as well as one analysis for CYP2D6 . Compared with reversible inhibition, there are some added complexities regarding the prediction of DDIs from inactivation data.…”

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confidence: 99%

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Mechanism-Based Inactivation of Human Cytochrome P450 Enzymes and the Prediction of Drug-Drug Interactions

Obach¹,

Walsky²,

2006

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ABSTRACT:The ability to use vitro inactivation kinetic parameters in scaling to in vivo drug-drug interactions (DDIs) for mechanism-based inactivators of human cytochrome P450 (P450) enzymes was examined using eight human P450-selective marker activities in pooled human liver microsomes. These data were combined with other parameters (systemic C max , estimated hepatic inlet C max , fraction unbound, in vivo P450 enzyme degradation rate constants estimated from clinical pharmacokinetic data, and fraction of the affected drug cleared by the inhibited enzyme) to predict increases in exposure to drugs, and the predictions were compared with in vivo DDIs gathered from clinical studies reported in the scientific literature. In general, the use of unbound systemic C max as the inactivator concentration in vivo yielded the most accurate predictions of DDI with a mean -fold error of 1.64. Abbreviated in vitro approaches to identifying mechanism-based inactivators were developed. Testing potential inactivators at a single concentration (IC 25 ) in a 30-min preincubation with human liver microsomes in the absence and presence of NADPH followed by assessment of P450 marker activities readily identified those compounds known to be mechanism-based inactivators and represents an approach that can be used with greater throughput. Measurement of decreases in IC 50 occurring with a 30-min preincubation with liver microsomes and NADPH was also useful in identifying mechanismbased inactivators, and the IC 50 measured after such a preincubation was highly correlated with the k inact /K I ratio measured after a full characterization of inactivation. Overall, these findings support the conclusion that P450 in vitro inactivation data are valuable in predicting clinical DDIs that can occur via this mechanism.The prediction of drug-drug interactions (DDIs) using in vitro enzyme kinetic data has been an area of increasing advances and sophistication. This has proven to be a valuable endeavor because DDIs remain an important issue in clinical practice and the discovery and development of new drugs. The earlier that the potential for DDIs can be identified in new compounds being studied as potential drugs, the greater the likelihood that this deleterious property can be removed through improved design of the molecule. Also, for those compounds already undergoing clinical trials, in vitro DDI data can be leveraged in the design of adequate and appropriate clinical DDI studies. With our increased understanding of drug-metabolizing enzymes and their roles in the metabolism of specific drugs, a mechanistic approach to assessing DDIs can be taken. The results of clinical DDI studies with one drug can be extrapolated to other drugs that are cleared by the same enzyme.The alteration of drug-metabolizing enzyme activities can occur by three main mechanisms: reversible inhibition, mechanism-based inactivation, and induction. Confidence in quantitatively extrapolating in vitro results to in vivo varies with these mechanisms. For reversible inhibitio...

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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confidence: 99%

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Mechanism-Based Inactivation of Human Cytochrome P450 Enzymes and the Prediction of Drug-Drug Interactions

Obach¹,

Walsky²,

2006

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“…The main mechanism underlying interactions between macrolide antibiotics and statins is often ascribed to the inhibition of the drugmetabolizing enzyme CYP3A4. [43][44][45] For this reason, the US Food and Drug Administration (FDA) currently warns against the co-administration of strong CYP3A4 inhibitors, including clarithromycin, with CYP3A4-metabolized 46 However, the inhibition of CYP3A4 cannot explain the increased risk of statin toxicity observed in our study, because we examined interactions with statins not metabolized by CYP3A4.…”

Section: Discussionmentioning

confidence: 46%

Risk of adverse events among older adults following co-prescription of clarithromycin and statins not metabolized by cytochrome P450 3A4

Kim

McArthur

et al. 2014

CMAJ

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“…To specifically address this question, in vitro-in vivo extrapolations were conducted to determine the magnitude of competitive and time-dependent inhibition associated with plasma M2 levels. Conceptually, time-dependent reductions in parent drug CL resulting from inhibitory metabolites could be predicted in a manner analogous to predicting DDIs resulting from coadministered competitive and mechanism-based inhibitors (Mayhew et al, 2000;Ito et al, 2003;Brown et al, 2006). A key parameter used in these models is the inhibitor concentration at the enzyme active site (I u ) (Mayhew et dmd.aspetjournals.org these concentrations cannot be directly measured, surrogates based on plasma levels are often used.…”

Section: Discussionmentioning

confidence: 99%

An Inhibitory Metabolite Leads to Dose- and Time-Dependent Pharmacokinetics of (R)-N-{1-[3-(4-Ethoxy-phenyl)-4-oxo-3,4-dihydro-pyrido[2,3-d]pyrimidin-2-yl]-ethyl}-N-pyridin-3-yl-methyl-2-(4-trifluoromethoxy-phenyl)-acetamide (AMG 487) in Human Subjects After Multiple Dosing

Tonn¹,

Wong²,

Wong³

et al. 2008

Drug Metab Dispos

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(R)-N-{1-[3-(4-Ethoxy-phenyl)-4-oxo-3,4-dihydro-pyrido[2,3-d]-pyrimidin-2-yl]-ethyl}-N-pyridin-3-yl-methyl-2-(4-trifluoromethoxyphenyl)-acetamide (AMG 487) is a potent and selective orally bioavailable chemokine (C-XAMG 487 (Fig. 1) is a potent and selective orally bioavailable chemokine (C-X-C motif) receptor 3 (CXCR3) antagonist . Clinical testing of AMG 487 revealed dose-and timedependent pharmacokinetic changes that were characterized by greater than anticipated increases in AMG 487 concentrations during multiple ascending dose studies (unpublished data). These results were not anticipated based on single-dose experiments that demonstrated near proportional increases in AMG 487 AUC and maximum plasma concentration (C max ) with doses ranging between 25 and 1100 mg (Floren et al., 2003). Moreover, mean terminal half-lives, ranging from 7.9 to 14 h, which were independent of dose (unpublished data), suggested minimal accumulation after once-daily dosing.Assuming linear pharmacokinetics, the rate and extent of accumulation at steady state can be readily predicted on the basis of the Parts of this work were previously presented as follows:

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Prediction of the in Vivo Interaction Between Midazolam and Macrolides Based on in Vitro Studies Using Human Liver Microsomes

Cited by 137 publications

References 24 publications

Mechanism-Based Inactivation of Human Cytochrome P450 Enzymes and the Prediction of Drug-Drug Interactions

Mechanism-Based Inactivation of Human Cytochrome P450 Enzymes and the Prediction of Drug-Drug Interactions

Risk of adverse events among older adults following co-prescription of clarithromycin and statins not metabolized by cytochrome P450 3A4

An Inhibitory Metabolite Leads to Dose- and Time-Dependent Pharmacokinetics of (R)-N-{1-[3-(4-Ethoxy-phenyl)-4-oxo-3,4-dihydro-pyrido[2,3-d]pyrimidin-2-yl]-ethyl}-N-pyridin-3-yl-methyl-2-(4-trifluoromethoxy-phenyl)-acetamide (AMG 487) in Human Subjects After Multiple Dosing

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