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A tiered analytical approach for investigating poor quality emergency contraceptives.

ABSTRACT: Reproductive health has been deleteriously affected by poor quality medicines. Emergency contraceptive pills (ECPs) are an important birth control method that women can use after unprotected coitus for reducing the risk of pregnancy. In response to the detection of poor quality ECPs commercially available in the Peruvian market we developed a tiered multi-platform analytical strategy. In a survey to assess ECP medicine quality in Peru, 7 out of 25 different batches showed inadequate release of levonorgestrel by dissolution testing or improper amounts of active ingredient. One batch was found to contain a wrong active ingredient, with no detectable levonorgestrel. By combining ultrahigh performance liquid chromatography-ion mobility spectrometry-mass spectrometry (UHPLC-IMS-MS) and direct analysis in real time MS (DART-MS) the unknown compound was identified as the antibiotic sulfamethoxazole. Quantitation by UHPLC-triple quadrupole tandem MS (QqQ-MS/MS) indicated that the wrong ingredient was present in the ECP sample at levels which could have significant physiological effects. Further chemical characterization of the poor quality ECP samples included the identification of the excipients by 2D Diffusion-Ordered Nuclear Magnetic Resonance Spectroscopy (DOSY 1H NMR) indicating the presence of lactose and magnesium stearate.

SUBMITTER: Monge ME

PROVIDER: S-EPMC3991657 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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A tiered analytical approach for investigating poor quality emergency contraceptives.

Monge María Eugenia ME Dwivedi Prabha P Zhou Manshui M Payne Michael M Harris Chris C House Blaine B Juggins Yvonne Y Cizmarik Peter P Newton Paul N PN Fernández Facundo M FM Jenkins David D

PloS one 20140418 4

Reproductive health has been deleteriously affected by poor quality medicines. Emergency contraceptive pills (ECPs) are an important birth control method that women can use after unprotected coitus for reducing the risk of pregnancy. In response to the detection of poor quality ECPs commercially available in the Peruvian market we developed a tiered multi-platform analytical strategy. In a survey to assess ECP medicine quality in Peru, 7 out of 25 different batches showed inadequate release of l ...[more]

PMID: 24748219

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Project description:Radiology department as a service provider organization requires realization of quality concept concerning service provisioning knowledge, satisfaction and all issues relating to the customer as well as quality assurance and improvement issues. At present, radiology departments in hospitals are regarded as income generating units and they should continuously seek performance improvement so that they can survive in the changing and competitive environment of the health care sector.The aim of this study was to propose a method for ranking of radiology departments in selected hospitals of Tehran city using analytical hierarchical process (AHP) and quality evaluation of their service in 2015.This study was an applied and cross-sectional study, carried out in radiology departments of 6 Tehran educational hospitals in 2015. The hospitals were selected using non-probability and purposeful method. Data gathering was performed using customized joint commission international (JCI) standards. Expert Choice 10.0 software was used for data analysis. AHP method was used for prioritization."Management and empowerment of human resources'' (weight = 0.465) and "requirements and facilities" (weight = 0.139) were of highest and lowest significance respectively in the overall ranking of the hospitals. MS (weight = 0.316), MD (weight = 0.259), AT (weight = 0.14), TS (weight = 0.108), MO (weight = 0.095), and LH (0.082) achieved the first to sixth rankings respectively.The use of AHP method can be promising for fostering the evaluation method and subsequently promotion of the efficiency and effectiveness of the radiology departments. The present model can fill in the gap in the accreditation system of the country's hospitals in respect with ranking and comparing them considering the significance and value of each individual criteria and standard. Accordingly, it can predict an integration of qualitative and quantitative criteria involved and thereby take a decisive step towards further efficiency and effectiveness of the health care evaluation systems.

Project description:Drug repositioning is the process of identifying new uses for existing drugs. Computational drug repositioning methods can reduce the time, costs and risks of drug development by automating the analysis of the relationships in pharmacology networks. Pharmacology networks are large and heterogeneous. Clustering drugs into small groups can simplify large pharmacology networks, these subgroups can also be used as a starting point for repositioning drugs. In this paper, we propose a two-tiered drug-centric unsupervised clustering approach for drug repositioning, integrating heterogeneous drug data profiles: drug-chemical, drug-disease, drug-gene, drug-protein and drug-side effect relationships.The proposed drug repositioning approach is threefold; (i) clustering drugs based on their homogeneous profiles using the Growing Self Organizing Map (GSOM); (ii) clustering drugs based on drug-drug relation matrices based on the previous step, considering three state-of-the-art graph clustering methods; and (iii) inferring drug repositioning candidates and assigning a confidence value for each identified candidate. In this paper, we compare our two-tiered clustering approach against two existing heterogeneous data integration approaches with reference to the Anatomical Therapeutic Chemical (ATC) classification, using GSOM. Our approach yields Normalized Mutual Information (NMI) and Standardized Mutual Information (SMI) of 0.66 and 36.11, respectively, while the two existing methods yield NMI of 0.60 and 0.64 and SMI of 22.26 and 33.59. Moreover, the two existing approaches failed to produce useful cluster separations when using graph clustering algorithms while our approach is able to identify useful clusters for drug repositioning. Furthermore, we provide clinical evidence for four predicted results (Chlorthalidone, Indomethacin, Metformin and Thioridazine) to support that our proposed approach can be reliably used to infer ATC code and drug repositioning.The proposed two-tiered unsupervised clustering approach is suitable for drug clustering and enables heterogeneous data integration. It also enables identifying reliable repositioning drug candidates with reference to ATC therapeutic classification. The repositioning drug candidates identified consistently by multiple clustering algorithms and with high confidence have a higher possibility of being effective repositioning candidates.

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A tiered analytical approach for investigating poor quality emergency contraceptives.

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A tiered analytical approach for investigating poor quality emergency contraceptives.

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