Abstract Background The Vectra® DA test measures serum levels of 12 protein biomarkers associated with rheumatoid arthritis (RA) and uses these levels in an algorithmic calculation to generate a numeric score that represents RA disease activity where established categories are low for scores 1 to 29, moderate for 30 to 44, and high for 45 to 100. LabCorp Specialty Lab in Calabasas, CA completed the quantitative analytical validations of 12 Vectra biomarkers (SAA, CRP, VCAM-1, IL-6, TNF-RI, EGF, VEGF-A, Leptin, Resistin, MMP-1, MMP-3, and YKL-40) and the clinical verification of the Vectra score algorithm. Methods The Vectra test consists of the quantitative measurements of EGF, Leptin, MMP-1, TNF-R1, VEGF, MMP-3, Resistin, VCAM, YKL-40, CRP, SAA and IL-6 using multiplex immunoassay platforms. The data acquired from each biomarker assay is processed through an algorithm where a composite Vectra score adjusted based on age, gender, and adiposity of the patient is computed. Analytical parameters validated for each biomarkers include sensitivity, precision, accuracy, specificity and stability. Precision was validated using pooled human serum controls at low, moderate, and high Vectra score levels. Method comparison was performed using 584 clinically defined serum samples. Quantitatively measured analyte values and computed Vectra scores by the Labcorp Vectra assay were compared with Vectra data produced by Myriad laboratory. Results Intra- and inter-assay sample precision of the final Vectra score was <13% and <18%, respectively. Sample stability using freshly collected serum subject to ambient and refrigerated temperature up to 14 days and frozen up to 364 days and up to 6 freeze-thaw cycles were acceptable. Of 584 clinical Vectra data compared, Labcorp vs Myriad, 96% of data were comparable within the acceptable criteria. Correlation of Vectra score from Labcorp and Myriad was excellent. A linear least square model resulted in a correlation coefficient (R) of 0.981 and a Deming slope of 1.009. Qualitative method comparison of Vectra scores resulted in excellent agreement of risk of radiographic progression and rheumatoid arthritis disease activity. A 91% agreement of risk category match between Labcorp and Myriad and 100% agreement of Vectra scores within 1 risk category was achieved. Conclusions We validated the Vectra® DA multiplex assay for measuring serum levels of 12 protein biomarkers associated with RA. Vectra combines biomarker levels into a personalized disease score that represents a patient’s RA inflammation and predict their risk of radiographic progression. High Vectra® DA scores (> 44) have been associated with a 20% 1-year risk of radiographic progression while low scores (< 30) carry only a 1% risk. Thus, the Vectra score provides an objective measurement of RA disease activity that can be used in combination with existing assessment tools to aid physicians to manage patients with RA.