Gentamicin sulphate permeation through porcine intestinal epithelial cell monolayer

Gentamicin is an aminoglycoside antibiotic widely used in combination with dimethyl sulphoxide (DMSO) in topical drug formulations. It is not known, however, whether DMSO can enhance the permeation of gentamicin through biological membranes, leading to oto- and nephrotoxic side effects. A simple and reliable high-performance liquid chromatographic (HPLC) method was applied for the quantitative determination of gentamicin collected from the apical and basolateral compartments of the porcine intestinal epithelial cell line IPEC-J2 cell monolayer using fluorometric derivatisation of the analyte with fluorenylmethyloxycarbonyl chloride (FMOC) prior to chromatographic run in the presence and absence of 1% DMSO. The lack of change in transepithelial electrical resistance (TER) demonstrated that gentamicin and 1% DMSO did not affect IPEC-J2 cell monolayer integrity via the disruption of cell membranes. Chromatographic data also ascertained that gentamicin penetration across the cell monolayer even in the presence of 1% DMSO was negligible at 6 h after the beginning of apical gentamicin administration. This study further indicates that the addition of this organic solvent does not increase the incidence of toxic effects related to gentamicin permeation

Stir bar-sorptive extraction, solid phase extraction and liquid-liquid extraction for levetiracetam determination in human plasma: comparing recovery rates

Levetiracetam (LEV), an antiepileptic drug (AED) with favorable pharmacokinetic profile, is increasingly being used in clinical practice, although information on its metabolism and disposition are still being generated. Therefore a simple, robust and fast liquid-liquid extraction (LLE) followed by high-performance liquid chromatography method is described that could be used for both pharmacokinetic and therapeutic drug monitoring (TDM) purposes. Moreover, recovery rates of LEV in plasma were compared among LLE, stir bar-sorptive extraction (SBSE), and solid-phase extraction (SPE). Solvent extraction with dichloromethane yielded a plasma residue free from usual interferences such as commonly co-prescribed AEDs, and recoveries around 90% (LLE), 60% (SPE) and 10% (SBSE). Separation was obtained using reverse phase Select B column with ultraviolet detection (235 nm). Mobile phase consisted of methanol:sodium acetate buffer 0.125 M pH 4.4 (20:80, v/v). The method was linear over a range of 2.8-220.0 µg mL-1. The intra- and inter-assay precision and accuracy were studied at three concentrations; relative standard deviation was less than 10%. The limit of quantification was 2.8 µg mL-1. This robust method was successfully applied to analyze plasma samples from patients with epilepsy and therefore might be used for pharmacokinetic and TDM purposes.</p

Drug dosing during pregnancy—opportunities for physiologically based pharmacokinetic models

Drugs can have harmful effects on the embryo or the fetus at any point during pregnancy. Not all the damaging effects of intrauterine exposure to drugs are obvious at birth, some may only manifest later in life. Thus, drugs should be prescribed in pregnancy only if the expected benefit to the mother is thought to be greater than the risk to the fetus. Dosing of drugs during pregnancy is often empirically determined and based upon evidence from studies of non-pregnant subjects, which may lead to suboptimal dosing, particularly during the third trimester. This review collates examples of drugs with known recommendations for dose adjustment during pregnancy, in addition to providing an example of the potential use of PBPK models in dose adjustment recommendation during pregnancy within the context of drug-drug interactions. For many drugs, such as antidepressants and antiretroviral drugs, dose adjustment has been recommended based on pharmacokinetic studies demonstrating a reduction in drug concentrations. However, there is relatively limited (and sometimes inconsistent) information regarding the clinical impact of these pharmacokinetic changes during pregnancy and the effect of subsequent dose adjustments. Examples of using pregnancy PBPK models to predict feto-maternal drug exposures and their applications to facilitate and guide dose assessment throughout gestation are discussed

Evidence of CYP3A Allosterism In Vivo: Analysis of Interaction Between Fluconazole and Midazolam

The allosteric effect of fluconazole (effector) on the formation of 1′–hydroxymidazolam (1′–OH–MDZ) and 4–hydroxymidazolam (4–OH–MDZ) from midazolam (MDZ), a substrate of CYP3A4/5—members of the cytochrome P450 superfamily of enzymes—was examined in healthy volunteers. Following pretreatment with fluconazole, the ratio of the areas under the curve (AUCs) for 4–OH–MDZ and MDZ (AUC4–OH/AUCMDZ) increased by 35–62%, whereas the ratio AUC1′–OH/AUCMDZ decreased by 5–37%; the ratio AUC1′–OH/AUC4–OH decreased by 46–58% after fluconazole administration and had no association with the CYP3A5 genotype. The in vitro formation of 1′–OH–MDZ was more susceptible to inhibition by fluconazole than that of 4–OH–MDZ. Fluconazole decreased the intrinsic formation–clearance ratio of 1′–OH–MDZ/4–OH–MDZ to an extent that was quantitatively comparable to in vivo observations. The elimination clearance of MDZ metabolites appeared unaffected by fluconazole. This study demonstrated that fluconazole alters formation of MDZ metabolites, both in vivo and in vitro, in a manner consistent with an allosteric interaction. The 1′–OH–MDZ/4–OH–MDZ ratio may serve as a biomarker of such interactions among MDZ, CYP3A4/5, and other putative effectors. Clinical Pharmacology & Therapeutics (2012); 91 3, 442–449. doi:10.1038/clpt.2011.17

Identification of Tazarotenic Acid as the First Xenobiotic Substrate of Human Retinoic Acid Hydroxylase CYP26A1 and CYP26B1

International audienc

Objective Identification of Cannabis Use Levels in Clinical Populations Is Critical for Detecting Pharmacological Outcomes

Introduction: Cannabis is widely used for recreational and medical purposes, but its therapeutic efficacy remains unresolved for many applications as data from retrospective studies show dramatic discrepancy. We hypothesized that false self-reporting of cannabis use and lack of differentiation of heavy users from light or occasional users contribute to the conflicting outcomes. Objective: The goal of this study was to develop an objective biomarker of cannabis use and test how application of such biomarker impacts clinical study outcomes and dose-response measures. Methods and Analysis: Population pharmacokinetic (PK) models of (-)-trans-Δ9-tetrahydrocannabinol (THC) and its metabolites 11-hydroxy-Δ9-tetrahydrocannabinol (11-OH-THC) and 11-nor-9-carboxy-Δ9-tetrahydrocannabinol (11-COOH-THC) were developed based on published studies reporting cannabinoid disposition in individual subjects following intravenous administration or smoking of cannabis. Plasma 11-COOH-THC concentration distributions in different cannabis user groups smoking cannabis were generated via Monte Carlo simulations, and plasma concentration cutoff values of 11-COOH-THC were developed to differentiate light and heavy daily cannabis users in clinical studies. The developed cutoff value was then applied to a retrospective study that assessed the impact of cannabis use on T cell activation in subjects with HIV who self-reported as either nonuser or daily user of cannabis. Results: The developed population PK models established plasma 11-COOH-THC concentration of 73.1 μg/L as a cutoff value to identify heavy daily users, with a positive predictive value of 80% in a mixed population of equal proportions of once daily and three times a day users. The stratification allowed detection of changes in T cell activation in heavy users which was not detected based on self-reporting or detectability of plasma cannabinoids. A proof-of-concept power analysis demonstrated that implementation of such cutoff value greatly increases study power and sensitivity to detect pharmacological effects of cannabis use. Conclusions: This study shows that the use of plasma 11-COOH-THC concentration cutoff value as an objective measure to classify cannabis use in target populations is critical for study sensitivity and specificity and provides much needed clarity for addressing dose-response relationships and therapeutic effects of cannabis

Discovery and Visualization of Uncharacterized Drug-Protein Adducts Using Mass Spectrometry.

Drugs are often metabolized to reactive intermediates that form protein adducts. Adducts can inhibit protein activity, elicit immune responses, and cause life-threatening adverse drug reactions. The masses of reactive metabolites are frequently unknown, rendering traditional mass spectrometry-based proteomics approaches incapable of adduct identification. Here, we present Magnum, an open-mass search algorithm optimized for adduct identification, and Limelight, a web-based data processing package for analysis and visualization of data from all existing algorithms. Limelight incorporates tools for sample comparisons and xenobiotic-adduct discovery. We validate our tools with three drug/protein combinations and apply our label-free workflow to identify novel xenobiotic-protein adducts in CYP3A4. Our new methods and software enable accurate identification of xenobiotic-protein adducts with no prior knowledge of adduct masses or protein targets. Magnum outperforms existing label-free tools in xenobiotic-protein adduct discovery, while Limelight fulfills a major need in the rapidly developing field of open-mass searching, which until now lacked comprehensive data visualization tools