Spotting the Outliers and New Peaks in MAM Runs Automatically
Using Deep Query and Dashboards, and Detecting New Peaks
LC-MS data produces some of the most valuable data possible for biotherapeutic research, development, and production, and has been increasingly used to characterize and monitor critical quality attributes of therapeutic proteins. When mass spectrometry is used as a Multi-Attribute Method in a more routine setup, the method needs to not only identify and quantify known CQAs, but must also be capable of detecting new, unexpected peaks.
Advanced enterprise data systems allow organizations to curate, interrogate, and faithfully share the obtained analytical information for timely decision making. For quality attribute analysis and to quickly assess trends observed from the LC-MS data, deep querying available within Protein Metrics BYOSPHERE platform offers visualization of the processed and extracted information with intelligent dashboards. In this webinar we present the power of dashboards through the analysis of the MAM Round Robin dataset.