Micromass UK Limited

Waters Technologies Ireland Limited

Richard Chapman

Martin Raymond Green

Steven Derek Pringle

Keith George Richardson

John Brian Hoyes

Emrys Jones

Richard Denny

Simon Meffan-Main

Peter Nixon

Tracy Hibbs

A method of correcting mass spectral data comprises making calibration measurements of first intrinsic components (A, B, C) at one or more calibration times (t1) using calibrants which have known mass to charge ratio (m/z) values or previously mass measured mass to charge ratio (m/z) values, making a list of second intrinsic components (D, E, F) which are present during more than one acquisition periods, wherein the second intrinsic components have mass to charge ratio (m/z) values that were not present or observed during or close to the one or more calibration times (t1) but which do overlap in time with the first intrinsic components (A, B, C), and utilising the list to calculate a mass or mass to charge ratio (m/z) correction factor for one or more acquisition periods which are not close or adjacent in time to an acquisition period containing a directly calibrated mass to charge ratio (m/z) value.

Adaptive intrinsic lock mass correction

Exemplary embodiments provide methods, mediums, and systems for visualization and advanced data science on information collected in an analytical data system. Embodiments identify correlations and patterns in chromatography metadata around areas of potential user error. Correlations between these data sources may point to compliance risk areas. Metadata from the analytical system may be combined with other data sources and/or analytical data to correlate an analytical outcome with compliance artifacts. Supervised and/or unsupervised machine learning techniques may be used to combine these data source and learn correlations between them and compliance risks. The results of these analyses may be displayed on a dashboard, allowing a user to visualize compliance risks across an entire enterprise or supply chain. Automatic notifications of compliance risks may be generated and presented on a user interface. A system may also use pattern recognition to provide insights around potential compliance risks that have not yet occurred.

Methods, mediums, and systems for linking chromatography data and metadata to compliance risks

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Westborough, MA, United States of America

Richard Chapman