ABSTRACT:Glucuronidation is a listed clearance mechanism for 1 in 10 of the top 200 prescribed drugs. The objective of this article is to encourage those studying ligand interactions with UDP-glucuronosyltransferases (UGTs) to adequately consider the potential consequences of in vitro UGT inhibition in humans. Spurred on by interest in developing potent and selective inhibitors for improved confidence around UGT reaction phenotyping, and the increased availability of recombinant forms of human UGTs, several recent studies have reported in vitro inhibition of UGT enzymes. In some cases, the observed potency of UGT inhibitors in vitro has been interpreted as having potential relevance in humans via pharmacokinetic drug-drug interactions. Although there are reported examples of clinically relevant drug-drug interactions for UGT substrates, exposure increases of the aglycone are rarely greater than 100% in the presence of an inhibitor relative to its absence (i.e., AUC i /AUC <2). This small magnitude in change is in contrast to drugs primarily cleared by cytochrome P450 enzymes, where exposures have been reported to increase as much as 35-fold on coadministration with an inhibitor (e.g., ketoconazole inhibition of CYP3A4-catalyzed terfenadine metabolism). In this article the evidence for purported clinical relevance of potent in vitro inhibition of UGT enzymes will be assessed, taking the following into account: in vitro data on the enzymology of glucuronide formation from aglycone, pharmacokinetic principles based on empirical data for inhibition of metabolism, and clinical data on the pharmacokinetic drug-drug interactions of drugs primarily cleared by glucuronidation.

ABSTRACT:(R)-3-[1-(2,6-Dichloro-3-fluoro-phenyl)-ethoxy]-5-(1-piperidin-4-yl-1H-pyrazol-4-yl)-pyridin-2-ylamine (PF02341066) was identified as an orally available, ATP-competitive small molecule inhibitor of cMet receptor tyrosine kinase. The objectives of the present studies were to characterize 1) the pharmacokinetic-pharmacodynamic relationship of the plasma concentrations of PF02341066 to cMet phosphorylation in tumor (biomarker) and 2) the relationship of cMet phosphorylation to antitumor efficacy (pharmacological response). Athymic mice implanted with GTL16 gastric carcinoma or U87MG glioblastoma xenografts were treated with PF02341066 once daily at doses selected to encompass ED 50 values. Plasma concentrations of PF02341066 were best described by a one-compartment pharmacokinetic model. A time-delay (hysteresis) was observed between the plasma concentrations of PF02341066 and the cMet phosphorylation response. A link model was therefore used to account for this hysteresis. The model fitted the time courses of cMet phosphorylation well, suggesting that the main reason for the hysteresis is a rate-limiting distribution from plasma into tumor. The EC 50 and EC 90 values were estimated to be 19 and 167 ng/ml, respectively. For tumor growth inhibition, the exponential tumor growth model fitted the time courses of individual tumor growth inhibition well. The EC 50 for the GTL16 tumor growth inhibition was estimated to be 213 ng/ml. Thus, the EC 90 for the inhibition of cMet phosphorylation corresponded to the EC 50 for the tumor growth inhibition, suggesting that near-complete inhibition of cMet phosphorylation (>90%) is required to significantly inhibit tumor growth (>50%). The present results will be helpful in determining the appropriate dosing regimen and in guiding dose escalation to rapidly achieve efficacious systemic exposure in the clinic.Pharmacokinetic-pharmacodynamic (PKPD) modeling is increasingly being applied in drug discovery and development. Specific applications include 1) the selection of drug candidates with most favorable PKPD properties and 2) the prediction of exposure response in patients with the aim of optimizing the design of early clinical trials. The increased understanding of drug action derived from PKPD-based drug development leads to more information, especially with regard to the identification of drug dosage regimen that results in optimal therapeutic outcome (Derendorf et al., 2000;Lesko et al., 2000;Chien et al., 2005). The use of PKPD modeling in this context relies on prediction of the time course of drug effects in patients, using information from preclinical investigation. Preclinical studies are useful alternatives to investigate PKPD relationships to get insight into the in vivo mechanism of drug action. The integration of PKPD modeling and simulation in drug development has provided opportunities to accelerate the evaluation of new chemical entities in the clinic. Thus, the PKPD investigation could contribute to shortening the overall period of drug development.

The idea of model-based drug development championed by Lewis Sheiner, in which pharma

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Troglitazone is a new thiazolidinedione oral antidiabetic agent approved for use to improve glycaemic control in patients with type 2 diabetes. It is rapidly absorbed with an absolute bioavailability of between 40 and 50%. Food increases the absorption by 30 to 80%. The pharmacokinetics of troglitazone are linear over the clinical dosage range of 200 to 600 mg once daily. The mean elimination half-life ranges from 7.6 to 24 hours, which facilitates a once daily administration regimen. The pharmacokinetics of troglitazone are similar between patients with type 2 diabetes and healthy individuals. In humans, troglitazone undergoes metabolism by sulfation, glucuronidation and oxidation to form a sulfate conjugate (M1), glucuronide conjugate (M2) and quinone metabolite (M3), respectively. M1 and M3 are the major metabolites in plasma, and M2 is a minor metabolite. Age, gender, type 2 diabetes, renal impairment, smoking and race do not appear to influence the pharmacokinetics of troglitazone and its 2 major metabolites. In patients with hepatic impairment the plasma concentrations of troglitazone, M1 and M3 increase by 30%, 4-fold, and 2-fold, respectively. Cholestyramine decreases the absorption of troglitazone by 70%. Troglitazone may enhance the activities of cytochrome P450 (CYP) 3A and/or transporter(s) thereby reducing the plasma concentrations of terfenadine, cyclosporin, atorvastatin and fexofenadine. It also reduces the plasma concentrations of the oral contraceptive hormones ethinylestradiol, norethindrone and levonorgestrel. Troglitazone does not alter the pharmacokinetics of digoxin, glibenclamide (glyburide) or paracetamol (acetaminophen). There is no pharmacodynamic interaction between troglitazone and warfarin or alcohol (ethanol). Pharmacodynamic modelling showed that improvement in fasting glucose and triglyceride levels increased with dose from 200 to 600 mg. Knowledge of systemic troglitazone exposure within a dose group does not improve the prediction of glucose lowering response or adverse effects beyond those based on the administered dose.