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1.
SLAS Discov ; 26(8): 1065-1070, 2021 09.
Artigo em Inglês | MEDLINE | ID: mdl-34142592

RESUMO

The storage of screening collections in DMSO is commonplace in the pharmaceutical industry. To ensure a high-quality screening collection, and hence effective and efficient high-throughput screening, all compounds entering the GlaxoSmithKline (GSK) screening collection undergo a liquid chromatography-mass spectrometry (LC-MS) quality control (QC). It is generally accepted that even under optimal conditions, a small percentage of these compounds are unstable after prolonged storage in DMSO. This article presents how these QC data can be mined using a data-driven clustering algorithm to identify chemical substructures likely to cause degradation in DMSO. This knowledge provides new structural filters for use in excluding compounds with these undesirable substructures from the collection. This information also suggests an efficient, targeted approach to compound collection clean-up initiatives. Stability studies are also designed to maintain a high-quality screening collection. To define the best practice for the storage and handling of solution samples, GSK has undertaken stability experiments for two decades, initially to support the implementation of new automated liquid stores and, subsequently, to enhance storage and use of compounds in solution through an understanding of compound degradation under storage and assay conditions.


Assuntos
Indústria Farmacêutica/métodos , Estabilidade de Medicamentos , Armazenamento de Medicamentos/métodos , Ensaios de Triagem em Larga Escala/métodos , Cromatografia Líquida , Dimetil Sulfóxido , Humanos , Espectrometria de Massas , Controle de Qualidade , Solventes
2.
Pediatrics ; 139(2)2017 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-28077623

RESUMO

BACKGROUD AND OBJECTIVE: Ensuring safe human milk in the NICU is a complex process with many potential points for error, of which one of the most serious is administration of the wrong milk to the wrong infant. Our objective was to describe a quality improvement initiative that was associated with a reduction in human milk administration errors identified over a 6-year period in a typical, large NICU setting. METHODS: We employed a quasi-experimental time series quality improvement initiative by using tools from the model for improvement, Six Sigma methodology, and evidence-based interventions. Scanned errors were identified from the human milk barcode medication administration system. Scanned errors of interest were wrong-milk-to-wrong-infant, expired-milk, or preparation errors. The scanned error rate and the impact of additional improvement interventions from 2009 to 2015 were monitored by using statistical process control charts. RESULTS: From 2009 to 2015, the total number of errors scanned declined from 97.1 per 1000 bottles to 10.8. Specifically, the number of expired milk error scans declined from 84.0 per 1000 bottles to 8.9. The number of preparation errors (4.8 per 1000 bottles to 2.2) and wrong-milk-to-wrong-infant errors scanned (8.3 per 1000 bottles to 2.0) also declined. CONCLUSIONS: By reducing the number of errors scanned, the number of opportunities for errors also decreased. Interventions that likely had the greatest impact on reducing the number of scanned errors included installation of bedside (versus centralized) scanners and dedicated staff to handle milk.


Assuntos
Alimentação com Mamadeira , Unidades de Terapia Intensiva Neonatal , Erros Médicos/prevenção & controle , Leite Humano , Melhoria de Qualidade/organização & administração , Hospitais Pediátricos , Humanos , Recém-Nascido , Sistemas de Medicação no Hospital , Ohio , Gestão de Riscos/organização & administração
3.
J Adolesc ; 35(5): 1111-22, 2012 Oct.
Artigo em Inglês | MEDLINE | ID: mdl-22460236

RESUMO

The study tested three theoretically/conceptually hypothesized longitudinal models of academic processes leading to academic performance. Based on a longitudinal sample of 1866 high-school students across two consecutive years of high school (Time 1 and Time 2), the model with the most superior heuristic value demonstrated: (a) academic motivation and self-concept positively predicted attitudes toward school; (b) attitudes toward school positively predicted class participation and homework completion and negatively predicted absenteeism; and (c) class participation and homework completion positively predicted test performance whilst absenteeism negatively predicted test performance. Taken together, these findings provide support for the relevance of the self-system model and, particularly, the importance of examining the dynamic relationships amongst engagement factors of the model. The study highlights implications for educational and psychological theory, measurement, and intervention.


Assuntos
Escolaridade , Motivação , Absenteísmo , Adolescente , Atitude , Análise Fatorial , Feminino , Humanos , Masculino , Autoimagem
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