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Selected Drugs (selected + drug)
Selected AbstractsUnified QSAR & network-based computational chemistry approach to antimicrobials.JOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 1 2010Abstract In the previous work, we reported a multitarget Quantitative Structure-Activity Relationship (mt-QSAR) model to predict drug activity against different fungal species. This mt-QSAR allowed us to construct a drug,drug multispecies Complex Network (msCN) to investigate drug,drug similarity (González-Díaz and Prado-Prado, J Comput Chem 2008, 29, 656). However, important methodological points remained unclear, such as follows: (1) the accuracy of the methods when applied to other problems; (2) the effect of the distance type used to construct the msCN; (3) how to perform the inverse procedure to study species,species similarity with multidrug resistance CNs (mdrCN); and (4) the implications and necessary steps to perform a substructural Triadic Census Analysis (TCA) of the msCN. To continue the present series with other important problem, we developed here a mt-QSAR model for more than 700 drugs tested in the literature against different parasites (predicting antiparasitic drugs). The data were processed by Linear Discriminate Analysis (LDA) and the model classifies correctly 93.62% (1160 out of 1239 cases) in training. The model validation was carried out by means of external predicting series; the model classified 573 out of 607, that is, 94.4% of cases. Next, we carried out the first comparative study of the topology of six different drug,drug msCNs based on six different distances such as Euclidean, Chebychev, Manhattan, etc. Furthermore, we compared the selected drug,drug msCN and species,species mdsCN with random networks. We also introduced here the inverse methodology to construct species,species msCN based on a mt-QSAR model. Last, we reported the first substructural analysis of drug,drug msCN using Triadic Census Analysis (TCA) algorithm. © 2009 Wiley Periodicals, Inc. J Comput Chem 2010 [source] Overview of the use of antimicrobials for the treatment of bacterial infections in horsesEQUINE VETERINARY EDUCATION, Issue 8 2008E. F. Haggett Summary Use of antimicrobial drugs is central to the treatment of primary and secondary bacterial infection in horses. When selecting an antimicrobial to treat confirmed or suspected bacterial infection multiple factors should be considered, including: the likely infectious agent; distribution and dosage of selected drugs; mechanisms of action; and potential side effects. Many of these issues will be covered in subsequent articles in this series. The aim of this paper is to aid the clinician in the rational selection of antimicrobials by reviewing the mode of action, spectrum of activity, pharmacokinetics, pharmacodynamics, indications and potential side effects of the main classes of antimicrobial drugs. Extralabel use of drugs is common in veterinary medicine due to a lack of licensed products. This increases the importance of a thorough understanding of antimicrobials and their possible adverse effects. [source] Extrapolating in vitro metabolic interactions to isolated perfused liver: Predictions of metabolic interactions between R -bufuralol, bunitrolol, and debrisoquineJOURNAL OF PHARMACEUTICAL SCIENCES, Issue 10 2010Sami Haddad Abstract Drug,drug interactions (DDIs) are a great concern to the selection of new drug candidates. While in vitro screening assays for DDI are a routine procedure in preclinical research, their interpretation and relevance for the in vivo situation still represent a major challenge. The objective of the present study was to develop a novel mechanistic modeling approach to quantitatively predict DDI solely based upon in vitro data. The overall strategy consisted of developing a model of the liver with physiological details on three subcompartments: the sinusoidal space, the space of Disse, and the cellular matrix. The substrate and inhibitor concentrations available to the metabolizing enzyme were modeled with respect to time and were used to relate the in vitro inhibition constant (Ki) to the in vivo situation. The development of the liver model was supported by experimental studies in a stepwise fashion: (i) characterizing the interactions between the three selected drugs (R -bufuralol (BUF), bunitrolol (BUN), and debrisoquine (DBQ)) in microsomal incubations, (ii) modeling DDI based on binary mixtures model for all the possible pairs of interactions (BUF,BUN, BUF,DBQ, BUN,DBQ) describing a mutual competitive inhibition between the compounds, (iii) incorporating in the binary mixtures model the related constants determined in vitro for the inhibition, metabolism, transport, and partition coefficients of each compound, and (iv) validating the overall liver model for the prediction of the perfusate kinetics of each drug determined in isolated perfused rat liver (IPRL) for the single and paired compounds. Results from microsomal coincubations showed that competitive inhibition was the mechanism of interactions between all three compounds, as expected since those compounds are all substrates of rat CYP2D2. For each drug, the Ki values estimated were similar to their Km values for CYP2D2 indicative of a competition for the same substrate-binding site. Comparison of the performance between the novel liver physiologically based pharmacokinetic (PBPK) model and published empirical models in simulating the perfusate concentration,time profile was based on the area under the curve (AUC) and the shape of the curve of the perfusate time course. The present liver PBPK model was able to quantitatively predict the metabolic interactions determined during the perfusions of mixtures of BUF,DBQ and BUN,DBQ. However, a lower degree of accuracy was obtained for the mixtures of BUF,BUN, potentially due to some interindividual variability in the relative proportion of CYP2D1 and CYP2D2 isoenzymes, both involved in BUF metabolism. Overall, in this metabolic interaction prediction exercise, the PBPK model clearly showed to be the best predictor of perfusate kinetics compared to more empirical models. The present study demonstrated the potential of the mechanistic liver model to enable predictions of metabolic DDI under in vivo condition solely from in vitro information. © 2010 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 99:4406,4426, 2010 [source] Physiologically based predictions of the impact of inhibition of intestinal and hepatic metabolism on human pharmacokinetics of CYP3A substratesJOURNAL OF PHARMACEUTICAL SCIENCES, Issue 1 2010Frederique Fenneteau Abstract The first objective of the present study was to predict the pharmacokinetics of selected CYP3A substrates administered at a single oral dose to human. The second objective was to predict pharmacokinetics of the selected drugs in presence of inhibitors of the intestinal and/or hepatic CYP3A activity. We developed a whole-body physiologically based pharmacokinetics (WB-PBPK) model accounting for presystemic elimination of midazolam (MDZ), alprazolam (APZ), triazolam (TRZ), and simvastatin (SMV). The model also accounted for concomitant administration of the above-mentioned drugs with CYP3A inhibitors, namely ketoconazole (KTZ), itraconazole (ITZ), diltiazem (DTZ), saquinavir (SQV), and a furanocoumarin contained in grape-fruit juice (GFJ), namely 6,,7,-dihydroxybergamottin (DHB). Model predictions were compared to published clinical data. An uncertainty analysis was performed to account for the variability and uncertainty of model parameters when predicting the model outcomes. We also briefly report on the results of our efforts to develop a global sensitivity analysis and its application to the current WB-PBPK model. Considering the current criterion for a successful prediction, judged satisfied once the clinical data are captured within the 5th and 95th percentiles of the predicted concentration,time profiles, a successful prediction has been obtained for a single oral administration of MDZ and SMV. For APZ and TRZ, however, a slight deviation toward the 95th percentile was observed especially for Cmax but, overall, the in vivo profiles were well captured by the PBPK model. Moreover, the impact of DHB-mediated inhibition on the extent of intestinal pre-systemic elimination of MDZ and SMV has been accurately predicted by the proposed PBPK model. For concomitant administrations of MDZ and ITZ, APZ and KTZ, as well as SMV and DTZ, the in vivo concentration,time profiles were accurately captured by the model. A slight deviation was observed for SMV when coadministered with ITZ, whereas more important deviations have been obtained between the model predictions and in vivo concentration,time profiles of MDZ coadministered with SQV. The same observation was made for TRZ when administered with KTZ. Most of the pharmacokinetic parameters predicted by the PBPK model were successfully predicted within a two-fold error range either in the absence or presence of metabolism-based inhibition. Overall, the present study demonstrated the ability of the PBPK model to predict DDI of CYP3A substrates with promising accuracy. © 2009 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 99:486,514, 2010 [source] FDA drug prescribing warnings: is the black box half empty or half full?,PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, Issue 6 2006Anita K. Wagner PharmD Abstract Purpose Black box warnings (BBWs) are the Food and Drug Administration's (FDA) strongest labeling requirements for high-risk medicines. It is unknown how frequently physicians prescribe BBW drugs and whether they do so in compliance with the warnings. The purpose of the present study was to assess the frequency of use of BBW medications in ambulatory care and prescribing compliance with BBW recommendations. Methods This retrospective study used automated claims data of 929,958 enrollees in 10 geographically diverse health plans in the United States to estimate frequency of use in ambulatory care of 216 BBW drugs/drug groups between 1/1/99 and 31/6/01. We assessed dispensing compliance with the BBW requirements for selected drugs. Results During a 30-month period, more than 40% of enrollees received at least one medication that carried a BBW that could potentially apply to them. We found few instances of prescribing during pregnancy of BBW drugs absolutely contra-indicated in pregnancy. There was almost no co-prescribing of contra-indicated drugs with the two QT-interval-prolonging BBW drugs evaluated. Most non-compliance occurred with recommendations for baseline laboratory monitoring (49.6% of all therapy initiations that should have been accompanied by baseline laboratory monitoring were not). Conclusions Many individuals receive drugs considered to carry the potential for serious risk. For some of these drugs, use is largely consistent with their BBW, while for others it is not. Since it will not be possible to avoid certain drug- associated risks, it will be important to develop effective methods to use BBWs and other methods to minimize risks. Copyright © 2005 John Wiley & Sons, Ltd. [source] The characterization of selected drugs with infrared laser desorption/tunable synchrotron vacuum ultraviolet photoionization mass spectrometryRAPID COMMUNICATIONS IN MASS SPECTROMETRY, Issue 16 2008Yang Pan Some selected drugs including captopril, fudosteine and racecadotril have been analyzed by infrared (IR) laser desorption/tunable synchrotron vacuum ultraviolet (VUV) photoionization mass spectrometry (PIMS). The molecular ions of captopril and racecadotril are exclusively observed without any fragments at near threshold single-photon ionization (SPI). However, fudosteine easily forms fragments even at a photon energy near the ionization threshold, indicating the instability of its molecular ion. For these drugs, a number of fragments are yielded with the increase of photon energy. The structures of such fragments proposed by IR LD/VUV PIMS are supported by electron ionization time-of-flight mass spectrometry (EI-TOFMS) results. Fragmentation pathways are discussed in detail. Copyright © 2008 John Wiley & Sons, Ltd. [source] | |||||||||||||