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In this paper the process from experimental design (e.g. ruggedness test) to uncertainty estimation is described. The uncertainty estimate was calculated for the peak area of insulin plus A21 desamido insulin resulting from an HPLC analysis of a sample of an injectable human insulin preparation, Actrapid HM 100 IU ml(-1) (Novo Nordisk A/S). The analytical method used was the European Pharmacopoeia assay. (4) An expanded uncertainty (1) of 1.8% (of the area from the HPLC analysis) at an approximately 95% confidence level was found and confirmed by a validation study. This uncertainty refers to the peak area of the analyte from a single injection of the sample. The input parameters to the uncertainty estimate were found from a factorial experimental design (e.g. ruggedness test) consisting of 9 factors applied to the HPLC analysis. The input parameters were chosen to cover the probable contributors to the variability of the measured area of the HPLC analysis, including the sample preparation, but excluding uncertainty deriving from the reference material(s).
In this paper the process from experimental design (e.g. ruggedness test) to uncertainty estimation is described. The uncertainty estimate was calculated for the peak area of insulin plus A21 desamido insulin resulting from an HPLC analysis of a sample of an injectable human insulin preparation, Actrapid HM 100 IU ml(-1) (Novo Nordisk A/S). The analytical method used was the European Pharmacopoeia assay. (4) An expanded uncertainty (1) of 1.8% (of the area from the HPLC analysis) at an approximately 95% confidence level was found and confirmed by a validation study. This uncertainty refers to the peak area of the analyte from a single injection of the sample. The input parameters to the uncertainty estimate were found from a factorial experimental design (e.g. ruggedness test) consisting of 9 factors applied to the HPLC analysis. The input parameters were chosen to cover the probable contributors to the variability of the measured area of the HPLC analysis, including the sample preparation, but excluding uncertainty deriving from the reference material(s).
Realizar una estimación de la incertidumbre de forma global para la determinación de humedad en platos preparados por gravimetría aprovechando los datos obtenidos en el proceso de validación. Material y métodos: Se analiza, mediante un diseño anidado, un material de referencia certificado (MRC) con un contenido de humedad certificado de 61,8 ±0,7 g/100g. La estimación de la incertidumbre combinada, se halla aplicando la ley de propagación de la incertidumbre. La incertidumbre expandida se obtiene aplicando un factor de cobertura K=2 (nivel de confianza del 95%). Mediante la aproximación SUMU se añade el sesgo a la incertidumbre expandida. Resultados: El límite de repetibilidad y reproductibilidad, para un nivel de confianza del 95%, es igual a 0,58 % y 1,21 %, respectivamente. Se obtienen los siguientes valores de incertidumbre: duplicados (0,12%), precisión (0,44 %), trazabilidad/ sesgo (0,39 %), incertidumbre combinada (0,60 %) e incertidumbre expandida corregida (1,38 %). Conclusiones: El uso de un diseño anidado (analista, instrumento, día, replicado), permite variar los factores de una forma ordenada, entre cada serie, y estimar la precisión intermedia debida a varios factores. El cálculo de la incertidumbre de forma global supone una ventaja en cuanto a simplicidad, especialmente para laboratorios con pocos recursos humanos y materiales. La inclusión del sesgo experimental no significativo como un componente de la incertidumbre tiende a evitar la infraestimación de la incertidumbre de los resultados. PALABRAS CLAVE. Incertidumbre global. Humedad. Platos preparados. Nutritional analysis in ready meals (individual combat rations), Calculation of Uncertainty global estimated in a procedure for determination of moisture by gravimetric technique. SUMMARY Objectives: The aim of this article was to estimate the uncertainty total for the determination of moisture in ready meals by gravimetric using data obtained in the validation process. Material and methods: Samples were analyzed by gravimetric method in certified reference material (CRM) (moisture certificate content: 61.8 ± 0.7 a 100 g.) in nested design. The combined uncertainty was estimated by applying the law of propagation of uncertainty. The expanded uncertainty was obtained by applying a coverage factor K = 2 (confidence level 95%). Bias was added to the expanded uncertainty by the approximation SUMU. Results: The repeatability and reproducibility limit for a confidence level of 95% is equal to 0.58% and 1.21% respectively. You get the following values of uncertainty: duplicate (0.12%), precision (0.44%), traceability / bias (0.39%) combined uncertainty (0.60%) and revised expanded uncertainty (1.38 %). Conclusions: Using a nested design (analyst, instrument, day, replicated), can vary the factors in an orderly manner, between each series, and intermediate precision estimate due to several factors. Calculation of a global uncertainty is an advantage in terms of simplicity, especially for laboratories with limited human and material resources. Inclusion o...
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