Pronostics has signed a deal with University of Birmingham Medical School (UBMS) to provide next generation autoimmune testing services for its clinical immunology service
As part of the deal, Pronostics will provide UBMS clinical immunology service with its fully automated UltraPlex system and ANA Assay for the diagnosis of autoimmune disease.
This follows an independent trial at UBMS in 2007 which compared Pronostics's UltraPlex ANA assay with existing testing methods employed.
The UltraPlex solution eliminates the possibility of subjective errors, removes non-specific positive results and focuses on clinically significant results, with known disease association.
Its introduction will also significantly reduce test turn-a-round times.
The UltraPlex ANA assay, consists of 11 tests in one, providing valuable time and cost savings compared to serial testing approaches or current multiplexing methods.
It allows hospitals and laboratories to perform fully automated tests on patient samples and gives both quantitative and qualitative results for antibodies in autoimmune diseases.
UltraPlex is an exceptionally accurate, digital multiplexing solution which enables tens to hundreds of tests to be performed simultaneously in a single assay using a microscopic bar coding system.
Over the coming year Pronostics will be launching assays in the cardiovascular and cancer disease areas to supplement its autoimmune range which currently includes ANA, Coeliac and Thyroid assays.
Timothy Plant, laboratory manager for UBMS clinical immunology services said: ''We are very pleased to have signed this deal with Pronostics and look forward to enjoying the benefits the UltraPlex platform has to offer'.
Rob Booth, CEO of Pronostics added: "This deal highlights the benefits of the UltraPlex ANA and we look forward to providing additional assays to UBMS as our relationship progresses.
"The great thing about UltraPlex is that it provides significant time and cost savings which benefit hospitals and patients alike.
"Hospitals save money, waiting times are reduced and patients are diagnosed sooner."
