Sentence examples for analytical robustness from inspiring English sources

Thus, this method improved the analytical throughput, reduced the amount of analyte required, and increased the analytical robustness and accuracy.

The sensitivity at disease onset (61.1 %) and the specificity (97.3 %) of the ZnT8A assay in our series of paediatric T1D were in line with previous studies [9, 17, 18] and comparable with those of the other major known diabetes autoantibodies, confirming the analytical robustness and the clinical usefulness of this test and supporting its widespread integration in other Italian laboratories.

However, subsequent work investigated analytical robustness and suitability of this concept for biological applications [119].

Thus, the improved accuracy in RT prediction increased overall analytical robustness and allowed for the use of a shortened RT window in the scheduled MRM analysis.

After proper normalization, 123 out of 671 miRNAs showed a good correlation of their expression data between FFPE and FF tissue, and sufficient analytical robustness (they are expressed in at least one-third of FFPE samples).

This section considers how analytical robustness of patient-reported safety outcomes can be preserved within these more real-world settings, as well as more controlled settings such as pre-approval clinical trials.

For evaluation of analytical method robustness, Plackett-Burman design was employed and for sample preparation method robustness Fractional Factorial design was used.

Different capillary coatings have been proposed to improve the analytical performance (robustness, resolution, reproducibility), however due to coating instability none of these techniques has been routinely used [96].

Complex-step derivative approximation [ 100] was used to calculate numerical derivatives of the reactions in the model to achieve near analytical accuracy, robustness and easy implementation.

Recently, requirements for demonstrating utility of a tumor biomarker were established that include not only clinical validity, but also analytical reproducibility and robustness [ 22, 23].

In recent years, mathematical systems theory has developed an analytical framework, called 'Robustness Analysis and Robust Control', encompassing also algorithms and numerical tools.