N-of-One has signed a business partner agreement to provide copy number variation (CNV) analysis interpretation for Affymetrix’s OncoScan assay kit customers.

Under the agreement, N-of-One will work closely with Affymetrix to ensure data from the OncoScan assay, combined with its interpretation, optimise the value of tumour profiling based on CNV analysis for clinicians.

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Based on Affymetrix’s novel molecular inversion probe (MIP) technology, OncoScan assay helps in obtaining genome-wide copy number and loss-of-heterozygosity (LOH) profiles from degraded formalin-fixed, paraffin-embedded-derived tumour DNA samples.

Affymetrix Clinical Business senior vice-president Kim Caple said: "Affymetrix selected N-of-One because of their extensive experience delivering high-quality clinical interpretation, which provides valuable insights to clinicians.

"Under the agreement, N-of-One will work closely with Affymetrix to ensure data from the OncoScan assay, combined with its interpretation, optimise the value of tumour profiling based on CNV analysis for clinicians."

"The combination of OncoScan assay and N-of-One interpretation will provide highly valuable intelligence to aid clinicians as they decide individual treatment options for their clinical research."

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N-of-One CEO Chris Cournoyer said: "We are focused on partnering with Affymetrix to meet the growing demand for OncoScan assay by delivering high-quality, cost-effective and scalable interpretation that meets their business objectives."

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N-of-One provides highly scalable, cost-effective interpretation that is patient specific and can be adapted to requirements of each organisation.

The partnership is expected to deliver the understanding of CNV analysis that is required by clinicians to help in the identification of targeted therapeutic strategies in clinical research and trials.

According to the company, analysis of copy number aberrations has been shown to inform therapeutic strategies in oncology. Combining whole-genome copy number analysis, LOH and somatic mutation data is believed to allow for a deeper understanding of each patient’s cancer.