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Next generation diagnostic tool for identification of rheumatoid arthritis patients to improve treatment

Reference number
Coordinator Vacara AB - Vacara AB, STOCKHOLM
Funding from Vinnova SEK 1 000 000
Project duration June 2017 - December 2018
Status Completed
Venture Swelife and Medtech4Health- Project proposals to improve health
Call SWElife and Medtech4Health- Project proposals to improve health 2017

Purpose and goal

Occurrence of autoantibodies in sera is associated with the development of rheumatoid arthritis (RA). However, the prognostic value of the current autoantibody tests used in clinic is limited. We have generated a first prototype of the Joint-ID Test, a Luminex-based multiplex assay for qualitative detection of autoantibodies requiring only one microliter of human serum. In order to reach the TRL5, the kit has been validated and certified by notified body at Research Institute of Sweden (RISE).

Expected results and effects

The Joint-ID Test has been clinical validated by using large human cohorts of RA patients (n=1120) and an independent cohort of healthy controls (n=398). We identified 17 peptides with a potential prognostic value in newly diagnosed RA patients, which is limited with the established and commercially available tests. These results imply that patients positive for these peptides are not responding well to standard treatment and may benefit from personalized treatment strategies. We have also identified 6 peptides with a potential diagnostic value.

Planned approach and implementation

Vacara AB has together with the other partners (Medical Inflammation Research at Karolinska Institutet, RISE and Sahlgrenska Universitetsjukhuset in Gothenburg) developed a second generation of the Joint-ID Test. A productive collaboration with Institute Pasteur of Shanghai and Shanghai Guanghua Integrative Medicine Hospital has been established to validate the Joint-ID kit in large human cohorts of pre-RA and RA patients in China. The large number of patients and heterogeneity in treatment practices will be of particular interest to predict treatment outcome.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 9 January 2019

Reference number 2017-01452

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