SCIEX, EluciData agree to address metabolomics research challenges

24 June 2019 (Last Updated June 24th, 2019 14:13)

Life science analytical technologies company SCIEX has announced a co-marketing agreement with disruptive integrated Omics platform company EluciData to address the challenges faced by metabolomics researchers.

Life science analytical technologies company SCIEX has announced a co-marketing agreement with disruptive integrated Omics platform company EluciData to address the challenges faced by metabolomics researchers.

The agreement between the parties will allow the researchers to properly process all their metabolomics data from a range of workflows.

Furthermore, they will be able to advance the fields of target identification and validation and deeply characterise the underlying biology by interpreting the results in a biological context.

SCIEX Strategic Market Management director Mark Cafazzo said: “Improving the efficiency of metabolomics workflows is critical if academic researchers and pharma customers want to advance precision medicine.

“The use of Polly with SCIEX metabolomics workflows accelerates their capabilities and empowers them with spending more time on the biology than crunching data through fragmented software tools.”

Under the terms of the agreement, EluciData’s integrated Omics platform Polly will be promoted in conjunction with SCIEX technologies, including TripleTOF, X500R, and QTRAP, and Differential Ion Mobility. The end-to-end, vendor-neutral platform standardises and streamlines metabolomics data analysis workflows to better understand cellular phenotype.

EluciData’s Polly MetScape metabolomics profiling data analysis workflow is compatible with data acquired in SWATH Acquisition mode.

The PollyPhi Workflow enables hypothesis validation and allows researchers to go from pathways to highlighting changes in enzyme function by assessing the flow of labels through metabolites.

EluciData CEO Dr Abhishek Jha said: “The combined capabilities of our two companies will enable scientists to extract superior biological insights from raw metabolomics data generated from various workflows.”