Matrix model and β-deformation of N = 4 Yang-Mills theory

We present the result of the determination of the effective coupling constant for the low-energy (abelian) degrees of freedom in the so-called β-deformed N = 4 model, by means of the deep connection between supersymmetric gauge field theories and matrix models

Validation of computational approaches for antiretroviral dose optimization

Strategies for reducing antiretroviral doses and drug costs can support global access, and numerous options are being investigated. Efavirenz pharmacokinetic simulation data generated with a bottom-up physiologically based model were successfully compared with data obtained from the ENCORE (Exercise and Nutritional Interventions for Cardiovascular Health) I clinical trial (efavirenz at 400 mg once per day versus 600 mg once per day). These findings represent a pivotal paradigm for the prediction of pharmacokinetics resulting from dose reductions. Validated computational models constitute a valuable resource for optimizing therapeutic options and predicting complex clinical scenarios

Interactions of antiretroviral drugs with the SLC22A1 (OCT1) drug transporter

The SLC22A1 influx transporter is expressed on the basolateral membrane of hepatocytes and is involved in the excretion of numerous cations. Inhibition of SLC22A1 by several antiretrovirals, such as the protease inhibitor darunavir, has not previously been determined. In order to better understand and predict drug-SLC22A1 interactions, a range of antiretrovirals were screened for SLC22A1-associated inhibition and transport. Stable SLC22A1-expressing KCL22 cells were produced previously by nucleofection. Control KCL22 cells were transfected with the empty vector pcDNA3.1. Accumulation of tetraethylammonium (5.5 μM, 30 min) was determined in SLC22A1-expressing and mock-transfected cells with and without 50 μM of SLC22A1 inhibitor prazosin, or 50 μM of each antiretroviral drug. SLC22A1 IC50 values for efavirenz, darunavir, and prazosin were determined. Cellular accumulation of efavirenz and darunavir was also assessed in SLC22A1-expressing KCL22 cells and reversibility of this accumulation was assessed using prazosin. Tetraethylammonium accumulation was higher in SLC22A1-expressing cells compared to mock-transfected cells (10.6 ± 0.8 μM vs. 0.3 ± 0.004 μM, p = 0.009) and was significantly reduced in SLC22A1-expressing cells when co-incubated with all antiretrovirals tested except atazanavir, lamivudine, tenofovir, zidovudine, and raltegravir. Particularly noticeable was the predominance of SLC22A1 inhibitors in the protease inhibitor and non-nucleoside reverse transcriptase inhibitor classes. Absolute SLC22A1 IC50 values for efavirenz, darunavir, and prazosin were 21.8, 46.2, and 2.8 μM, respectively. Efavirenz accumulation was higher in SLC22A1-expressing cells compared to mock-transfected cells (17% higher, p = 0.009) which was reversed using prazosin, whereas no difference was observed for darunavir (p = 0.86). These data inform the mechanistic basis for disposition, drug-drug interactions and pharmacogenetic candidate gene selection for antiretroviral drugs

Applications of physiologically based pharmacokinetic modeling for the optimization of anti-infective therapies

Introduction: The pharmacokinetic properties of anti-infective drugs are a determinant part of treatment success. Pathogen replication is inhibited if adequate drug levels are achieved in target sites, whereas excessive drug concentrations linked to toxicity are to be avoided. Anti-infective distribution can be predicted by integrating in vitro drug properties and mathematical descriptions of human anatomy in physiologically based pharmacokinetic models. This method reduces the need for animal and human studies and is used increasingly in drug development and simulation of clinical scenario such as, for instance, drug–drug interactions, dose optimization, novel formulations and pharmacokinetics in special populations. Areas covered: We have assessed the relevance of physiologically based pharmacokinetic modeling in the anti-infective research field, giving an overview of mechanisms involved in model design and have suggested strategies for future applications of physiologically based pharmacokinetic models. Expert opinion: Physiologically based pharmacokinetic modeling provides a powerful tool in anti-infective optimization, and there is now no doubt that both industry and regulatory bodies have recognized the importance of this technology. It should be acknowledged, however, that major challenges remain to be addressed and that information detailing disease group physiology and anti-infective pharmacodynamics is required if a personalized medicine approach is to be achieved

Development and validation of an LC-MS/MS assay for the quantification of efavirenz in different biological matrices

Aim: The non-nucleoside reverse transcriptase inhibitor efavirenz is one of the most prescribed antiretroviral therapeutics. Efavirenz-containing therapy has become associated with the occurrence of CNS side effects, including sleep disturbances, depression and even psychosis. Results: The investigation of efavirenz distribution required the development of a versatile and sensitive method. In addition to plasma, quantification was required in brain tissue and phosphate-buffered saline. The assay presented here was linear from 1.9 to 500 ng/ml. Accuracy and precision ranged between 93.7 and 99.5%, and 1.5 and 5.6%, respectively. Discussion: The method developed here represents a versatile, sensitive and easy-to-use assay. The assay has been applied to in vitro and in vivo samples demonstrating reliable efavirenz quantification in multiple matrices

Design of a Base-Board for arrays of closely-packed Multi-Anode Photo-Multipliers

We describe the design of a Base-Board to house Multi-Anode Photo-Multipliers for use in large-area arrays of light sensors. The goals, the design, the results of tests on the prototypes and future developments are presented.Comment: 16 pages, 5 figures, submitted to Nucl. Instrum. and Meth.