SGS Expands Biomarker Services with Validation of a New Multiplex Pro-Inflammatory Panel for Testing Clinical Samples

SGS Life Science Services has announced that its laboratory in Poitiers, France, has successfully completed a full analytical validation of the novel Meso Scale Discovery (MSD) V-PLEX 10-plex Proinflammatory Panel I, for use with human plasma samples. The validation included measurement of accuracy, recovery, dilutional linearity, and stability, using a set of in-house, as well as the manufacturer’s surrogate validation quality controls.
 

This new service offering, complementing SGS’s existing biomarker portfolio, will enable the laboratory to generate more information by quantification of multiple biomarkers, and as 10 assays can be conducted in parallel, save on the volume of clinical samples required, while reducing turnaround time and cost for customers.
 

The Panel measures 10 cytokines that are important in inflammatory response and immune system regulation, as well as numerous other biological processes. These assays can detect biomarkers produced in a variety of tissues and body fluids, where over- or under-expression may indicate a shift in biological equilibrium. It also includes assays for many of the Th1/Th2 pathway biomarkers and measures biomarkers that are implicated in various disorders, including rheumatoid arthritis, Alzheimer’s disease, asthma, atherosclerosis, allergies, systemic lupus erythematosus, obesity, cancer, depression, multiple sclerosis, diabetes, psoriasis and Crohn’s disease.

“We have deep understanding and expertise in the use of  multiplex platforms as one of the routine bioanalytical procedures for clinical testing,” commented Dr Rabia Hidi, SGS Life Science Services Director of Biomarkers & Biopharmaceutical Testing. She added: “We can produce robust data and fully validate multiplexing methods to offer both quality of data and cost convenience, while using the minimum sample volumes. Where SGS differentiates itself in this space, is that our multiplexing methods can be fully validated and used in decision making studies.”