The influence of androgen deprivation therapy on dihydrotestosterone levels in the prostatic tissue of patients with prostate cancer.

PURPOSE: The influence of androgen deprivation therapy on dihydrotestosterone levels in the prostatic tissue is not clearly known. Changes in dihydrotestosterone levels in the prostatic tissue during androgen deprivation therapy in the same patients have not been reported. We analyzed dihydrotestosterone levels in prostatic tissue before and after androgen deprivation therapy. EXPERIMENTAL DESIGN: A total of 103 patients who were suspected of having prostate cancer underwent prostatic biopsy. Sixty-nine patients were diagnosed as having prostate cancer whereas the remaining 34 were negative. Serum samples were collected before biopsy or prostatectomy. Dihydrotestosterone levels in prostatic tissue and serum were analyzed using liquid chromatography/electrospray ionization-mass spectrometry after polar derivatization. In 30 of the patients with prostate cancer, dihydrotestosterone levels in prostatic tissue were determined by performing rebiopsy or with prostate tissues excised after 6 months on androgen deprivation therapy with castration and flutamide. RESULTS: Dihydrotestosterone levels in prostate tissue after androgen deprivation therapy remained at approximately 25% of the amount measured before androgen deprivation therapy. Dihydrotestosterone levels in serum decreased to approximately 7.5% after androgen deprivation therapy. The level of dihydrotestosterone in prostatic tissue before androgen deprivation therapy was not correlated with the serum level of testosterone. Serum levels of adrenal androgens were reduced to approximately 60% after androgen deprivation therapy. CONCLUSIONS: The source of dihydrotestosterone in prostatic tissue after androgen deprivation therapy involves intracrine production within the prostate, converting adrenal androgens to dihydrotestosterone. Dihydrotestosterone still remaining in prostate tissue after androgen deprivation therapy may require new therapies such as treatment with a combination of 5alpha-reductase inhibitors and antiandrogens, as well as castration.     

Assessment of oral bioavailability and preclinical pharmacokinetics of DRF-6196, a novel oxazolidinone analogue, in comparison to linezolid.

The aim of this study was to determine the bioavailability of a novel oxazolidinone, DRF-6196, in mice and rats following intravenous (i.v) and oral dosing and to compare the pharmacokinetics with those obtained following linezolid dosing. Blood samples were drawn at predetermined intervals up to 24 h post-dose after either DRF-6196 or linezolid administration. The concentrations of DRF-6196 and linezolid in various plasma samples were determined by a HPLC method. Following oral administration maximum concentrations of DRF-6196 were achieved within 0.5 h irrespective of the species. While the doses increased in the ratio of 1 : 3 : 10, mean Cmax and AUC(0-infinity) values in mice for DRF-6196 increased in the ratio of 1 : 3.87 : 8.53 and 1 : 2.51 : 9.24, respectively. Both the Cmax and AUC(0-infinity) values increased almost proportional to the dose administered in mice. Following i.v administration, the concentration of DRF-6196 declined in a bi-exponential fashion with terminal elimination half-life of 1.5 h irrespective of the species. The systemic clearance and volume of distribution of DRF-6196 in mice were 1.14 L/h/kg and 0.66 L/kg, respectively after i.v administration, while the respective values in rats were 0.61 L/h/kg and 0.41L/kg, respectively. Elimination half-life ranged between 0.8-1.5 h. Absolute oral bioavailability of DRF-6196 was found to be 80-96% across the test dose range. Although plasma levels of DRF-6196 were lesser compared to linezolid in the initial hours, it may not have any consequences on the clinical effectiveness of the molecule.     

New chiral reverse phase HPLC method for enantioselective analysis of ketorolac using chiral AGP column

A simple, specific, precise, sensitive and rapid reverse phase-HPLC method was developed for determination of ketorolac enantiomers, a potent nonnarcotic analgesic in pharmaceutical formulations. The method was developed on a chiral AGP column. Mobile phase was 0.1 M sodium phosphate buffer (pH 4.5): Isopropanol (98:2, v/v), at a flow rate of 1 mL/min with run time of 15 min. Ultraviolet detection was made at 322 nm. The linearity range was 0.02–10 μg/mL for each of the enantiomers. The mobile phase composition was systematically studied to find the optimum chromatographic conditions. Validation of the method under the conditions selected showed that it was selective and precise and that the detector response was linear function of ketorolac.     

Modelling and simulation of placebo effect: application to drug development in schizophrenia

High and variable placebo effect (PE) within and among clinical trials can substantially affect conclusions about the efficacy of new drugs in the treatment of schizophrenia and other neuropsychiatric disorders. In recent years, it has become increasingly difficult to prove drug efficacy against placebo, and one of the reasons is that the placebo response has increased over recent years. The increased placebo response over the years is partly explained by unidentified parallel interventions, patient factors, issues with trial designs, and regional variability or demographic differences. In addition, a nocebo effect, which is undesirable effects a subject manifests after receiving placebo, e.g. extrapyramidal side effects, in placebo arms of antipsychotic trials could also influence the PE and clinical trial outcomes. Placebo effects (PEs) are a natural phenomenon and cannot be avoided completely in clinical trials. However, accounting for the PE via mixed effects modelling approaches could reduce bias in quantifying the overall effect size of the drug treatment. This review article focuses on the PE and its impact on schizophrenia clinical trial outcomes. The authors briefly describe the factors that lead to high and variable PE. Next, pharmacometric approaches to account for the PE and dropouts in schizophrenia clinical trials are described. Finally, some points are provided that could be considered while designing and optimizing antipsychotic trials via simulation approaches.