CYP-mediated Drug-drug Interactions Research Articles

Prediction of the Pharmacokinetics of Atorvastatin, Cerivastatin, and Indomethacin Using Kinetic Models Applied to Isolated Rat Hepatocytes

The disposition of atorvastatin, cerivastatin, and indomethacin, established substrates of rat hepatic basolateral uptake transporters, has been evaluated in suspended rat hepatocytes. Cell and media concentration-time data were simultaneously fitted to a model incorporating active uptake, permeation, binding, and metabolism. Use of the model to estimate the ratio of intracellular to extracellular steady-state free drug concentrations demonstrated the strong influence of active uptake on the kinetics of atorvastatin (18:1) and cerivastatin (8:1), in comparison with indomethacin (3.5:1). Indomethacin, however, was shown to have a higher uptake clearance (599 +/- 101 microl/min/10(6) cells) than atorvastatin (375 +/- 45 microl/min/10(6) cells) and cerivastatin (413 +/- 47 microl/min/10(6) cells). The high passive permeability of indomethacin (237 +/- 63 microl/min/10(6) cells) clearly negated the effect of the active transport on the overall disposition. An analogous physiological model was constructed that allowed prediction of the in vivo pharmacokinetics, including the free intracellular concentration in liver. Hepatic clearance was well predicted by the model, in contrast to predictions based on standard methods. Volume of distribution was well predicted for indomethacin and predicted reasonably for atorvastatin and cerivastatin and higher than might be expected for an acid compound. Furthermore, the terminal half-life predictions for all three compounds were within 2-fold of the observed values. The ability to estimate the free-intracellular hepatic concentration of uptake substrates has major benefits in terms of predicting pharmacokinetics, potential CYP-mediated drug-drug interactions, and efficacy of hepatically targeted therapeutics.

The Potential for Clinically Significant Drug-Drug Interactions Involving the CYP 2D6 System: Effects with Fluoxetine and Paroxetine versus Sertraline

Patients taking antidepressants are more likely to also be taking multiple medications, increasing the risk of adverse drug-drug interactions (DDIs). Because of substantial inhibition of one or more cytochrome P450 (CYP) enzymes at therapeutic doses, the selective serotonin reuptake inhibitors fluoxetine, fluvoxamine, and paroxetine have a higher risk of CYP-mediated DDIs than citalopram, escitalopram, and sertraline, which do not substantially inhibit any CYP enzyme. Prescribing patterns in 2,779 Veterans Affairs (VA) patients who had a prescription for an antidepressant in the preceding year and a current prescription for at least one systemically active drug were analyzed to determine 1) prevalence of drug combinations with potential to cause CYP-mediated DDIs, 2) frequency of combinations of fluoxetine, paroxetine, or sertraline with drugs whose metabolism is principally dependent on CYP 2D6, and 3) use of reduced doses of CYP 2D6 substrate/drugs with narrow therapeutic indices in patients on fluoxetine or paroxetine compared with sertraline. In 2,779 patients, 55 pairs of drugs with the potential to cause CYP-mediated DDIs occurred in 300 patients (11%), but only 26 of the patients and 6 of the drug pairs were identified by the VA Drug Alert System. Of the 461 patients receiving fluoxetine and/or paroxetine, 39 (8%) were also receiving a CYP 2D6-model substrate/drug with a narrow therapeutic index, 14 (36%) of whom were receiving high enough doses to be at moderate to high risk of a serious DDI. VA patients on fluoxetine, paroxetine, and sertraline were equally likely to be on drugs whose metabolism is dependent on CYP 2D6, including drugs with narrow therapeutic indices. No differences were found in doses of tricyclic antidepressants (i.e., "victim" drugs), which have narrow therapeutic indices and serious dose-dependent toxicity, when co-prescribed with fluoxetine or paroxetine versus sertraline (i.e., "perpetrator" drugs), despite predictable differences in CYP 2D6-mediated clearance of these drugs.

Rational prescription of drugs within similar therapeutic or structural class for gastrointestinal disease treatment: Drug metabolism and its related interactions

To review and summarize drug metabolism and its related interactions in prescribing drugs within the similar therapeutic or structural class for gastrointestinal disease treatment so as to promote rational use of medicines in clinical practice. Relevant literature was identified by performing MEDLINE/Pubmed searches covering the period from 1988 to 2006. Seven classes of drugs were chosen, including gastric proton pump inhibitors, histamine H(2)-receptor antagonists, benzamide-type gastroprokinetic agents, selective 5-HT(3) receptor antagonists, fluoroquinolones, macrolide antibiotics and azole antifungals. They showed significant differences in metabolic profile (i.e., the fraction of drug metabolized by cytochrome P450 (CYP), CYP reaction phenotype, impact of CYP genotype on interindividual pharmacokinetics variability and CYP-mediated drug-drug interaction potential). Many events of severe adverse drug reactions and treatment failures were closely related to the ignorance of the above issues. Clinicians should acquaint themselves with what kind of drug has less interpatient variability in clearance and whether to perform CYP genotyping prior to initiation of therapy. The relevant CYP knowledge helps clinicians to enhance the management of patients with gastrointestinal disease who may require treatment with polytherapeutic regimens.

Optimizing Higher Throughput Methods to Assess Drug–Drug Interactions for CYP1A2, CYP2C9, CYP2C19, CYP2D6, rCYP2D6, and CYP3A4 In Vitro Using a Single Point IC50

Drug-drug interactions involving cytochrome P(450) (CYP) are an important factor in whether a new chemical entity will survive through to the development stage. Therefore, the identification of this potential as early as possible in vitro could save considerable future unnecessary investment. In vitro CYP interaction screening data generated for CYP2C9, CYP2D6, and CYP3A4 were initially analyzed to determine the correlation of IC(50) from 10- and 3-point determinations. A high correlation (r = 0.99) prompted the further assessment of predicting the IC(50) by a single value of percent inhibition at either 10, 3, or 1 microM. Statistical analysis of the initial proprietary compounds showed that there was a strong linear relationship between log IC(50) and percent inhibition at 3 microM, and that it was possible to predict a compound's IC(50) by the percent inhibition value obtained at 3 microM. Additional data for CYP1A2, CYP2C19, and the recombinant CYP2D6 were later obtained and used together with the initial data to demonstrate that a single statistical model could be applicable across different CYPs and different in vitro microsomal systems. Ultimately, the data for all five CYPs and the recombinant CYP2D6 were used to build a statistical model for predicting the IC(50) with a single point. The 95% prediction boundary for the region of interest was about +/- 0.37 on log(10) scale, comparable to the variability of in vitro determinations for positive control IC(50) data. The use of a single inhibitor concentration would enable determination of more IC(50) values on a 96-well plate and result in more economical use of compounds, human liver or expressed enzyme microsomes, substrates, and reagents. This approach would offer the opportunity to increase screening for CYP-mediated drug-drug interactions, which may be important given the challenges provided by the generation of orders of magnitude more new chemical entities in the field of combinatorial chemistry. In addition, the algorithmic approach we propose would obviously be applicable for other in vitro bioactivity and therapeutic target enzyme and receptor screens.

Selective serotonin reuptake inhibitors and cytochrome P-450 mediated drug-drug interactions: an update.

The selective serotonin reuptake inhibitors (SSRIs) have become the most prescribed antidepressants in many countries. Although the SSRIs share a common mechanism of action, they differ substantially in their chemical structure, metabolism, and pharmacokinetics. Perhaps the most important difference between the SSRIs is their potential to cause drug-drug interactions through inhibition of cytochrome-P450 (CYP) isoforms. This paper provides an update on both the in vitro and in vivo evidence with respect to CYP-mediated drug-drug interactions with this class of antidepressants. The available evidence clearly indicates that the individual SSRIs display a distinct profile of cytochrome P450 inhibition. Fluvoxamine is a potent CYP1A2 and CYP2C19 inhibitor, and a moderate CYP2C9, CYP2D6, and CYP3A4 inhibitor. Fluoxetine and paroxetine are potent CYP2D6 inhibitors, whereas fluoxetine's main metabolite, norfluoxetine, has a moderate inhibitory effect on CYP3A4. Sertraline is a moderate CYP2D6 inhibitor; citalopram appears to have little effect on the major CYP isoforms. Fluoxetine deserves special attention as inhibitory effects on CYP-activity can persist for several weeks after fluoxetine discontinuation because of the long half-life of fluoxetine and its metabolite norfluoxetine. Drug combinations with SSRIs should be assessed on an individual basis. Knowledge regarding the CYP-isoforms involved in the metabolism of the co-administered drug may help clinicians to anticipate and avoid potentially dangerous drug-drug interactions. Anticipated interactions can usually be managed by appropriate dose adjustment and titration of the object drug. In some cases, therapeutic drug monitoring can be useful. Equally well, an SSRI with limited interaction potential may be selected to treat depression in patients that receive other medications.