The current study focused on the development of an automated IC50 cocktail assay in a miniaturized 384 well assay format. This was developed in combination with a significantly shorter high pressure liquid chromatography (HPLC) separation and liquid chromatography-mass spectrometry (LC-MS/MS) run-time; than those currently reported in the literature. The 384-well assay used human liver microsomes in conjunction with a cocktail of probe substrates metabolized by the five major CYPs (tacrine for CYP1A2, diclofenac for CYP2C9, (S)-mephenytoin for CYP2C19, dextromethorphan for CYP2D6 and midazolam for CYP3A4). To validate the usefulness of the automated and analytical methodologies, IC50 determinations were performed for a series of test compounds known to exhibit inhibition across these five major P450s. Eight compounds (sertraline, disulfuram, ticlopidine fluconazole, fluvoxamine, ketoconazole, miconazole, paroxetine, flunitrazepam) were studied as part of a cocktail assay, and against each CYPs individually. The data showed that the IC50s generated with cocktail incubations did not differ to a great extent from those obtained in the single probe experiments and hence unlikely to significantly influence the predicted clinical DDI risk. In addition the present method offered a significant advantage over some of the existing cocktail analytical methodology in that separation can be achieved with run times as short as 1 min without compromising data integrity. Although numerous studies have been reported to measure CYP inhibition in a cocktail format the need to support growing discovery libraries not only relies on higher throughput assays but quicker analytical run times. The current study reports a miniaturized high-throughput cocktail IC50 assay, in conjunction with a robust, rapid resolution LC-MS/MS end-point offered increased sample throughput without compromising analytical sensitivity or analyte resolution.
Journal of Pharmaceutical and Biomedical Analysis 06/2008; 48(1):92-9. DOI:10.1016/j.jpba.2008.05.011 · 2.83 Impact Factor