The Pharmacists’ Potential to Provide Targets for Interventions to Optimize Pharmacotherapy in Patients With Asthma.

The pharmacists’ potential to provide targets for interventions to optimize pharmacotherapy in patients with asthma.

Int J Clin Pharm. 2013 Jul 26;
van Boven JF, Hiddink EG, Stuurman-Bieze AG, Schuiling-Veninga CC, Postma MJ, Vegter S

Background Despite of pharmacists’ specialized knowledge of medication and his/her regular contact with patients, the expertise of the pharmacist may not be used enough yet. Furthermore, the potential of pharmacy dispensing data is underestimated. Objective To provide targets for tailored interventions in asthma patients and to illustrate the potential value of pharmacists in the identification of these targets using individual pharmacy dispensing data. Setting We performed a cross sectional retrospective analysis assessing the quality of asthma patients’ pharmacotherapeutic treatment. Method Drug dispensing data from 2008 to 2009 were retrieved from a Dutch pharmacy database. All asthma patients were screened for potential suboptimal pharmacotherapy in 2009. Results were projected to a single community pharmacy to provide an estimate of the number of patients eligible for potential interventions. Main outcome measures (1) frequent use of short-acting ?-agonists without preventive medication, (2) concomitant use of ?-blockers, (3) multiple short courses of oral corticosteroids without using inhaled corticosteroids and 4) use of long-acting ?-agonist without inhaled corticosteroids. Results A total of 8,504 patients were eligible for analysis of the quality of their asthma treatment. 20.9 % of all asthma patients used >100 DDD short-acting ?-agonists per year, whereas between 21.2 % (?400 DDD) and 31.4 % (100-199 DDD) of these patients did not receive preventive medication. Approximately 5.2 % of the asthma patients are using ?-blockers concomitantly and 21.8 % of them received non-cardioselective ?-blockers. 6.3 % of the asthma patients received two or more oral courses of corticosteroids in 2008 and 17.4 % of these patients did not receive inhaled corticosteroids in 2009. 2.9 % of the patients used a long-acting ?-agonists without inhaled corticosteroids. 8.4 % of the asthma patients using both long-acting ?-agonists and inhaled corticosteroids received these drugs in two separate inhalers. We estimated that about 400 asthma patients could be identified in an average pharmacy population (8,000 patients) and 33 (95 % CI 22-44) of these patients would be eligible for interventions. Conclusion This study shows the potential for pharmacists to use their own pharmacy records to identify suboptimal therapy of asthma patients, who may be targets for tailored interventions. HubMed – drug

Qualification and application of a liquid chromatography-tandem mass spectrometric method for the determination of human A?1-40 and A?1-42 peptides in transgenic mouse plasma using micro-elution solid phase extraction.

Arch Pharm Res. 2013 Jul 26;
Shin YG, Hamm L, Murakami S, Buirst K, Buonarati MH, Cox A, Regal K, Hunt KW, Scearce-Levie K, Watts RJ, Liu X

A liquid chromatographic-tandem mass spectrometric (LC-MS/MS) method was developed and applied for the determination of human A?1-40 and A?1-42 peptides in transgenic mouse plasma to support preclinical pharmacodynamics studies. The method consisted of micro-elution solid phase extraction for sample preparation and LC-MS/MS analysis in the negative ion mode using electrospray ionization for analysis. (15)N53-A?1-40 and (15)N55-A?1-42 peptides were used as internal standards. A quadratic regression (weighted 1/concentrations), with an equation y = ax (2) + bx + c, was used to fit calibration curves over the concentration range of 0.500-100 ng/mL for both A?1-40 and A?1-42 peptides. For quality control samples at 6.00, 40.0 and 80.0 ng/mL from the qualification experiment, the within-run accuracy ranged from -2.69 to 0.583 % with precision values ?8.23 % for A?1-40. Within-run accuracy ranged from -4.83 to 10.1 % with precision values ?8.87 % for A?1-42. Samples from a pharmacodynamics study using Tg2576 transgenic mice were analyzed by this qualified LC-MS/MS method and concentrations were compared to those generated by ELISA. The two methods were shown to be comparable for A?1-40 quantification of samples from the Tg2576 amyloid precursor protein transgenic mouse model, but varied slightly for A?1-42. HubMed – drug

Emergence of drug resistance-associated mutations in HIV-1 subtype C protease gene in north India.

Virus Genes. 2013 Jul 26;
Azam M, Malik A, Rizvi M, Singh S, Gupta P, Rai A

A major cause of anti-retroviral therapy (ART) failure is the drug resistance-associated mutations in polymerase gene of HIV-1. Paucity of data regarding potential drug resistance to protease inhibitors (PIs) prompted us to carry out this study. Drug resistance (DR) genotyping of the entire protease gene was performed in 104 HIV-1 ART-naive and first-line ART-experienced patients. The DR pattern was analyzed using the Stanford HIV-DR database, International AIDS Society-USA mutation list and REGA algorithm version 8.0. Subtyping was done using Mega 4 and REGA HIV-1 subtyping tool-v2.01. Majority of our sequences 98 (96 %) were subtype C and remaining four (3.92 %) were subtype A1. In three (2.9 %) DE patients, major DR-associated mutation at D30 N and M46I positions were detected. Approximately 70 % polymorphisms as minor mutations were observed in protease gene, of which 14 distinct amino acids changes were linked to partial DR such as G16E, K20R, M36I, D60E, I62V, L63P, I64M, H69K, T74A/S, V77I, V82I, I85V, L89M, and I93L. The two major and several minor mutations detected in this study confer low/intermediate levels of resistance to most PIs independently or together. Our results conclude that resistance testing in HIV-1-infected patients should be performed before the initiation of PI therapy for better therapeutic outcome in this region. This information not only will shed light on the extent of current DR in HIV strains but also will aid in patient treatment and drug designing. HubMed – drug

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