SBIR/STTR Research Award

Development of an RA Molecular Diagnostic to Predict Disease Activity and Respons

Award identifier a4da412654cc714373a2f32e8cc489a274521c818adb698d042dfa3ca3b7af08Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$195,684

Program and phase

SBIR · Phase I

Award year

2006

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
SOURCE PRECISION MEDICINE
Proposal award date
Not reported
Contract end date
Not reported
UEI
Not reported
Solicitation number
PHS2006-2
Topic code
Not reported

Research abstract

DESCRIPTION (provided by applicant): Rheumatoid arthritis (RA) is a serious autoimmune disease that affects some 5 million people worldwide (Firestein, 2005) and results in billions of dollars in treatment costs annually. RA is characterized by chronic inflammation and destruction of cartilage and bone in the joints. Joint erosion is a long-term condition, leading to loss of function and eventual deformity. As the disease progresses, multiple organ systems may be affected, leading to premature death. Given the progressive nature of RA, detection in its earliest stages is extremely important, as that is when intervention is the most effective. Unfortunately, early detection is rarely achieved with existing techniques. Additionally, the current tests and measurements do not reliably predict onset of flares, the extent of underlying damage, and/or identify patients that respond to specific therapies. Given that the current tests lack adequate predictive value, there is a need for a simple, low-cost screening and monitoring test that can initially detect RA in its earliest stages and can also predict a patient's future course, including both exacerbations and response to treatment. A predictive test would allow early intervention before significant joint and/or organ deterioration has occurred, or would allow adjustment of medications that are/are not effective altered gene-expression patterns precede synthesis and release of cytokine proteins and other immunologically important signals. Therefore, analysis of specific mRNA species associated with these changes, particularly with an autoimmune response in RA, may provide the earliest possible diagnostic warning of disease progression allowing for improved treatment. Additionally, gene expression could target a sub-population of RA patients, such as patients that will be unresponsive to methotrexate or other DMARDs and could instead benefit from anti- TNF therapy. The major goal of Source MDx is to prove the validity of this hypothesis and the feasibility of an associated test and to then develop and commercialize a system of high-precision molecular analysis of gene expression, powerful databases and biomedical algorithms that can be applied to detection and prognosis of RA. One Specific Aim of the Phase I research is to demonstrate that distinct patterns of gene expression correlate with clinical indicators of RA disease. The second Specific Aim is to show that these changes in gene-expression patterns occur prior to a change in clinical symptoms when treatment can be adjusted to reduce disease progression. RA accounts for an estimated 250,000 hospitalizations and 9 million physician visits each year (ACR subcommittee, 2002). Annually in the US, medical costs and indirect expenses due to lost wages for RA are estimated at over $3 billion (Wong et al., 2001) and less than 50 percent of working age adults with RA remain employed 10 years after disease onset (Sokka, 2003). Mortality rates for people with RA are double that of the general population (Young et al., 2002; Wong et al., 2001). Successful development and commercialization of a molecular diagnostic via the full, multi-phase SBIR project has the potential to substantially reduce disability and suffering caused by RA, as well as the mortality rate and long-term treatment costs.

Technology keywords

Not reported

Agency intelligence

Department of Health and Human Services

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