In previous work (23 ), we carried out a series of studies to develop the MBDA algorithm (Vectra DA). Starting with 396 candidate biomarkers, we analyzed existing literature and samples from several cohorts to evaluate measurability, association with disease activity, and the incremental independent information contributed to multivariate models associating the biomarkers with clinical disease activity. These efforts led to the development of an algorithm that combines the levels of 12 biomarkers – epidermal growth factor (EGF), vascular endothelial growth factor A (VEGF-A), leptin, interleukin 6 (IL-6), serum amyloid A (SAA), CRP, vascular cell adhesion molecule 1 (VCAM-1), matrix metalloproteinase 1 (MMP-1), matrix metalloproteinase 3 (MMP-3), tumor necrosis factor receptor superfamily member 1A (TNF-RI), human cartilage glycoprotein 39 (YKL-40), and resistin – into a composite MBDA score. Results obtained during algorithm verification indicated that the MBDA score was significantly associated with the DAS28-CRP (33 ).