UGT2B17 Genetic Polymorphisms Dramatically Affect the Pharmacokinetics of MK-7246 in Healthy Subjects in a First-in-Human Study

MK-7246, an antagonist of the chemoattractant receptor on T helper type 2 (Th2) cells, is being developed for the treatment of respiratory diseases. In a first-in-human study, we investigated whether genetic polymorphisms contributed to the marked intersubject variability in the pharmacokinetics of MK-7246 and its glucuronide metabolite M3. Results from in vitro enzyme kinetic studies suggested that UGT2B17 is probably the major enzyme responsible for MK-7246 metabolism in both the liver and the intestine. As compared with those with the UGT2B17*1/*1 wild-type genotype, UGT2B17*2/*2 carriers, who possess no UGT2B17 protein, had 25- and 82-fold greater mean dose-normalized values of area under the plasma concentration–time curve (AUC) and peak concentration of MK-7246, respectively, and a 24-fold lower M3-to-MK-7246 AUC ratio. The apparent half-life of MK-7246 was not as variable between these two genotypes. Therefore, the highly variable pharmacokinetics of MK-7246 is attributable primarily to the impact of UGT2B17 genetic polymorphisms and extensive first-pass metabolism of MK-7246

A Review of Time Courses and Predictors of Lipid Changes with Fenofibric Acid-Statin Combination

Fibrates activate peroxisome proliferator activated receptor α and exert beneficial effects on triglycerides, high-density lipoprotein cholesterol, and low density lipoprotein subspecies. Fenofibric acid (FA) has been studied in a large number of patients with mixed dyslipidemia, combined with a low- or moderate-dose statin. The combination of FA with simvastatin, atorvastatin and rosuvastatin resulted in greater improvement of the overall lipid profile compared with the corresponding statin dose. The long-term efficacy of FA combined with low- or moderate- dose statin has been demonstrated in a wide range of patients, including patients with type 2 diabetes mellitus, metabolic syndrome, or elderly subjects. The FA and statin combination seems to be a reasonable option to further reduce cardiovascular risk in high-risk populations, although trials examining cardiovascular disease events are missing

Current Industrial Practices in Assessing CYP450 Enzyme Induction: Preclinical and Clinical

Induction of drug metabolizing enzymes, such as the cytochromes P450 (CYP) is known to cause drug-drug interactions due to increased elimination of co-administered drugs. This increased elimination may lead to significant reduction or complete loss of efficacy of the co-administered drug. Due to the significance of such drug interactions, many pharmaceutical companies employ screening and characterization models which predict CYP enzyme induction to avoid or attenuate the potential for drug interactions with new drug candidates. The most common mechanism of CYP induction is transcriptional gene activation. Activation is mediated by nuclear receptors, such as AhR, CAR, and PXR that function as transcription factors. Early high throughput screening models utilize these nuclear hormone receptors in ligand binding or cell-based transactivation/reporter assays. In addition, immortalized hepatocyte cell lines can be used to assess enzyme induction of specific drug metabolizing enzymes. Cultured primary human hepatocytes, the best established in vitro model for predicting enzyme induction and most accepted by regulatory agencies, is the predominant assay used to evaluate induction of a wide variety of drug metabolizing enzymes. These in vitro models are able to appropriately predict enzyme induction in patients when compared to clinical drug-drug interactions. Finally, transgenic animal models and the cynomolgus monkey have also been shown to recapitulate human enzyme induction and may be appropriate in vivo animal models for predicting human drug interactions

Tubular transport mechanisms of quinapril and quinaprilat in the isolated perfused rat kidney: Effect of organic anions and cations

The clearance mechanisms of quinapril and quinaprilat were probed using an isolated perfused rat kidney model. Sixty-four experiments were performed with drug in the absence and presence of classic inhibitors of the organic acid (i.e., probenecid and p-aminohippurate) and organic base (i.e., tetraethylammonium and quinine) transport systems of the proximal tubule. Initial perfusate concentrations of quinapril and quinaprilat were approximately 2.36 μM (or 1000 ng/ml), and transport inhibitors were coperfused at 100–10,000 times the drugs' initial μM concentrations. Quinapril and quinaprilat concentrations were determined in perfusate, urine, and perfusate ultrafiltrate using a reversed-phase HPLC procedure with radiochemical detection, coupled to liquid scintillation spectrometry. Perfusate protein binding was determined using an ultrafiltration method at 37°C. Overall, the clearance ratios of quinapril (total renal clearance divided by fu·GFR ) and quinaprilat (urinary clearance divided by fu·GFR ) were significantly reduced, and in a dose-dependent manner, by the coperfusion of organic acids but not organic bases. The data demonstrate that the organic anionic secretory system is the primary mechanism by which quinapril and quinaprilat are transported into and across renal proximal cells.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45053/1/10928_2006_Article_BF02353517.pd

Simvastatin Sodium Salt and Fluvastatin Interact with Human Gap Junction Gamma-3 Protein

Finding pleiomorphic targets for drugs allows new indications or warnings for treatment to be identified. As test of concept, we applied a new chemical genomics approach to uncover additional targets for the widely prescribed lipid-lowering pro-drug simvastatin. We used mRNA extracted from internal mammary artery from patients undergoing coronary artery surgery to prepare a viral cardiovascular protein library, using T7 bacteriophage. We then studied interactions of clones of the bacteriophage, each expressing a different cardiovascular polypeptide, with surface-bound simvastatin in 96-well plates. To maximise likelihood of identifying meaningful interactions between simvastatin and vascular peptides, we used a validated photo-immobilisation method to apply a series of different chemical linkers to bind simvastatin so as to present multiple orientations of its constituent components to potential targets. Three rounds of biopanning identified consistent interaction with the clone expressing part of the gene GJC3, which maps to Homo sapiens chromosome 7, and codes for gap junction gamma-3 protein, also known as connexin 30.2/31.3 (mouse connexin Cx29). Further analysis indicated the binding site to be for the N-terminal domain putatively ‘regulating’ connexin hemichannel and gap junction pores. Using immunohistochemistry we found connexin 30.2/31.3 to be present in samples of artery similar to those used to prepare the bacteriophage library. Surface plasmon resonance revealed that a 25 amino acid synthetic peptide representing the discovered N-terminus did not interact with simvastatin lactone, but did bind to the hydrolysed HMG CoA inhibitor, simvastatin acid. This interaction was also seen for fluvastatin. The gap junction blockers carbenoxolone and flufenamic acid also interacted with the same peptide providing insight into potential site of binding. These findings raise key questions about the functional significance of GJC3 transcripts in the vasculature and other tissues, and this connexin’s role in therapeutic and adverse effects of statins in a range of disease states