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An agreement to develop new biomarkers for rheumatoid arthritis

The Institut de Recerca Hospital Universitari Vall d'Hebron (VHIR) has signed a strategic agreement with the company TcLand Expression to develop new biomarkers to predict response to treatment of rheumatoid arthritis (RA). As a result of this agreement, TcLand Expression will ensure exclusive global access to the intellectual property of VHIR regarding biomarkers that predicts the response to TNF blockers for Rheumatoid Arthritis.

30 june 2010

The relationship between both entities is based on the experience of the rheumatologist Dr. Sara Marsal, head of the Rheumatology Research Group of the Institute. The research of Dr. Marsal has been recently highlighted in an article which describes a gene expression profile which is predictive of the response to anti-TNF therapy in patients with rheumatoid arthritis (Julià et al., PLoS One, 2009 October 22, 4 (10): e7556.)


“Personalized medicine is becoming a reality in many diseases, including autoimmune diseases such as rheumatoid arthritis. New genomic tools are helping us to discover molecular patterns that are associated with disease processes and that, in some cases, can be tools of prediction in clinical practice. We are very pleased to begin this collaboration for the development of a predictive tool for the response to anti-TNF alpha treatment in RA. We are confident that with this great alliance and with the experience of TcLand Expression in the development of biomarkers, we will achieve the ultimate goal of personalizing this treatment for RA. This prediction system will reduce the socioeconomic costs associated with these therapies and, above all, improve the quality of life of patients with rheumatoid arthritis,” says Dr. Marsal.

Rheumatoid Arthritis

Rheumatoid arthritis is the most common type of serious inflammatory arthritis. It affects the young and, most prevalently, women. Since chronic inflammation in RA leads to joint destruction and is associated with high cardiovascular risk, the disease itself becomes a major health problem. Despite significant progress in the last 10 years in the treatment of RA with the introduction of TNF-alpha blockers, there is a significant number of patients unresponsive to these therapies. In this group of patients who did not respond, joint destruction can not be controlled, and today there are no means to recover the affected tissue. Moreover, like any other therapy, anti-TNF alpha blockers may be toxic or have adverse effects. For these reasons, the identification of a predictor to the response to anti-TNF therapy will not only mean a reduction in health costs associated with these therapies, but it is also a key step in personalized medicine for RA.





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