The Role of Transporters in the Pharmacokinetics of Orally Administered Drugs

Drug transporters are recognized as key players in the processes of drug absorption, distribution, metabolism, and elimination. The localization of uptake and efflux transporters in organs responsible for drug biotransformation and excretion gives transporter proteins a unique gatekeeper function in controlling drug access to metabolizing enzymes and excretory pathways. This review seeks to discuss the influence intestinal and hepatic drug transporters have on pharmacokinetic parameters, including bioavailability, exposure, clearance, volume of distribution, and half-life, for orally dosed drugs. This review also describes in detail the Biopharmaceutics Drug Disposition Classification System (BDDCS) and explains how many of the effects drug transporters exert on oral drug pharmacokinetic parameters can be predicted by this classification scheme

Efficacy and Safety of Three Antiretroviral Regimens for Initial Treatment of HIV-1: A Randomized Clinical Trial in Diverse Multinational Settings

Background:Antiretroviral regimens with simplified dosing and better safety are needed to maximize the efficiency of antiretroviral delivery in resource-limited settings. We investigated the efficacy and safety of antiretroviral regimens with once-daily compared to twice-daily dosing in diverse areas of the world.Methods and Findings:1,571 HIV-1-infected persons (47% women) from nine countries in four continents were assigned with equal probability to open-label antiretroviral therapy with efavirenz plus lamivudine-zidovudine (EFV+3TC-ZDV), atazanavir plus didanosine-EC plus emtricitabine (ATV+DDI+FTC), or efavirenz plus emtricitabine-tenofovir-disoproxil fumarate (DF) (EFV+FTC-TDF). ATV+DDI+FTC and EFV+FTC-TDF were hypothesized to be non-inferior to EFV+3TC-ZDV if the upper one-sided 95% confidence bound for the hazard ratio (HR) was ≤1.35 when 30% of participants had treatment failure.An independent monitoring board recommended stopping study follow-up prior to accumulation of 472 treatment failures. Comparing EFV+FTC-TDF to EFV+3TC-ZDV, during a median 184 wk of follow-up there were 95 treatment failures (18%) among 526 participants versus 98 failures among 519 participants (19%; HR 0.95, 95% CI 0.72-1.27; p = 0.74). Safety endpoints occurred in 243 (46%) participants assigned to EFV+FTC-TDF versus 313 (60%) assigned to EFV+3TC-ZDV (HR 0.64, CI 0.54-0.76; p<0.001) and there was a significant interaction between sex and regimen safety (HR 0.50, CI 0.39-0.64 for women; HR 0.79, CI 0.62-1.00 for men; p = 0.01). Comparing ATV+DDI+FTC to EFV+3TC-ZDV, during a median follow-up of 81 wk there were 108 failures (21%) among 526 participants assigned to ATV+DDI+FTC and 76 (15%) among 519 participants assigned to EFV+3TC-ZDV (HR 1.51, CI 1.12-2.04; p = 0.007).Conclusion: EFV+FTC-TDF had similar high efficacy compared to EFV+3TC-ZDV in this trial population, recruited in diverse multinational settings. Superior safety, especially in HIV-1-infected women, and once-daily dosing of EFV+FTC-TDF are advantageous for use of this regimen for initial treatment of HIV-1 infection in resource-limited countries. ATV+DDI+FTC had inferior efficacy and is not recommended as an initial antiretroviral regimen.Trial Registration:http://www.ClinicalTrials.gov NCT00084136

Ligand Promiscuity between the Efflux Pumps Human P-Glycoprotein and S. aureus

[Image: see text] Thirty-two diverse compounds were evaluated for their ability to inhibit both Pgp-mediated efflux in mouse T-lymphoma L5178 MDR1 and NorA-mediated efflux in S. aureus SA-1199B. Only four compounds were strong inhibitors of both efflux pumps. Three compounds were found to inhibit Pgp exclusively and strongly, while seven compounds inhibited only NorA. These results demonstrate that Pgp and NorA inhibitors do not necessarily overlap, opening the way to safer therapeutic use of effective NorA inhibitors

BDDCS Class Prediction for New Molecular Entities

The Biopharmaceutics Drug Disposition Classification System (BDDCS) was successfully employed for predicting drug-drug interactions (DDIs) with respect to drug metabolizing enzymes (DMEs), drug transporters and their interplay. The major assumption of BDDCS is that the extent of metabolism (EoM) predicts high versus low intestinal permeability rate, and vice versa, at least when uptake transporters or paracellular transport are not involved. We recently published a collection of over 900 marketed drugs classified for BDDCS. We suggest that a reliable model for predicting BDDCS class, integrated with in vitro assays, could anticipate disposition and potential DDIs of new molecular entities (NMEs). Here we describe a computational procedure for predicting BDDCS class from molecular structures. The model was trained on a set of 300 oral drugs, and validated on an external set of 379 oral drugs, using 17 descriptors calculated or derived from the VolSurf+ software. For each molecule, a probability of BDDCS class membership was given, based on predicted EoM, FDA solubility (FDAS) and their confidence scores. The accuracy in predicting FDAS was 78% in training and 77% in validation, while for EoM prediction the accuracy was 82% in training and 79% in external validation. The actual BDDCS class corresponded to the highest ranked calculated class for 55% of the validation molecules, and it was within the top two ranked more than 92% of the times. The unbalanced stratification of the dataset didn’t affect the prediction, which showed highest accuracy in predicting classes 2 and 3 with respect to the most populated class 1. For class 4 drugs a general lack of predictability was observed. A linear discriminant analysis (LDA) confirmed the degree of accuracy for the prediction of the different BDDCS classes is tied to the structure of the dataset. This model could routinely be used in early drug discovery to prioritize in vitro tests for NMEs (e.g., affinity to transporters, intestinal metabolism, intestinal absorption and plasma protein binding). We further applied the BDDCS prediction model on a large set of medicinal chemistry compounds (over 30,000 chemicals). Based on this application, we suggest that solubility, and not permeability, is the major difference between NMEs and drugs. We anticipate that the forecast of BDDCS categories in early drug discovery may lead to a significant R&D cost reduction

The Resistance to Tyrosine Kinase Inhibitors in Chronic Myeloid Leukemia: An Overview

The introduction in the clinical practice during the last decade of the tyrosine kinase inhibitors (TKI) have signifi cantly improved the outcome of patients affected by chronic myeloid leukemia (CML). Nevertheless, about one third of them still must stop or change treatment because of toxicity or resistance. Resistance could be “primary”, when patients don’t reach the established goals at the fi xed timepoints (see ELN or NCCN guidelines), or “secondary”, when patients lose the previously achieved hematological, cytogenetic or molecular response. At the basis of resistance many different mechanisms can be considered: the ABL1 mutations (rare at diagnosis but increasing at the progression, especially the T315I), the chromosomal adjunctive aberrations, but also the activation of other pathways able to sustain the growth of the progenitor leukemic stem cell, such as the Wnt, catenin, Scr, PI3K, and Hedgehog pathways. Moreover, also the epigenetic control of disease must be considered as a cause of resistance (such as that exerted by the Polycomb family). Finally, TKIs are often substrates of different transmembrane transporters; their polymorphisms and expression would explain either their possible lower effi cacy or higher toxicities. All these causes of resistance to TKIs are discussed in this paper