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Companion Diagnostics Space Warms Up with Collaboration


Companion Diagnostics is a hot market set to reach up to $6.51 billion by 2022, according to a report from Markets and Markets. The products have the potential to show how a therapy can be effective during a clinical trial and weed out patients that might not benefit from the treatment.

 

As a result, many pharmaceutical companies are partnering with diagnostic firms to develop these combination products. The latest collaboration is between Bristol-Myers Squibb (BMS) and Illumina. The two are joining forces to develop companion diagnostics for oncology immunotherapies.

 

The companies plan to develop a diagnostic version of the Illumina TruSight Oncology 500 assay to measure potentially predictive genomic biomarkers, including Tumor Mutation Burden (TMB). San Diego, CA-based Illumina’s TruSight Oncology 500 assay is being developed to detect most of the known biomarkers for oncology therapeutics, including TMB and Microsatellite Instability for immunotherapies.

 

The identification of biomarkers for targeted therapies is emerging as a key part of a cancer patient’s journey, from treatment selection through response monitoring and allows physicians to follow the evolution of a patient’s tumor over time,” Garret Hampton, PhD, executive vice president of clinical genomics at Illumina, said in a release. “Next-generation sequencing assays, such as a companion diagnostic (CDx) version of TruSight Oncology 500, are ideally suited to the comprehensive interrogation of a patient’s cancer. With BMS’ leading position in immunotherapy development, we see tremendous promise in this partnership to co-develop next-generation sequencing-based diagnostics that can identify effective therapeutic combinations and provide global access to these targeted drugs.”

 

New York, NY-based BMS’ clinical development program includes 24 clinical-stage molecules designed to target different immune system pathways across more than 50 types of cancers, and through its translational capabilities, has identified a number of potentially predictive biomarkers, including PD-L1, TMB, MSI-H/dMMR and LAG-3.

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