Personalized multi-tumor test provides potential new option for the rapid and sensitive identification of residual disease and clinical relapse.
Initial application in pharmaceutical clinical trial settings.
Research Triangle Park, NC, USA and Cambridge, UK - Inivata, a leader in liquid biopsy announces the availability of RaDaR™, an assay for the detection and monitoring of residual disease and recurrence in the plasma samples of patients previously diagnosed with cancer. RaDaR is designed to be complementary to tumor profiling assays including Inivata’s InVisionFirst®-Lung and will initially be used in a clinical trial setting for patients who have already received a cancer diagnosis.
The RaDaR assay is built on Inivata’s proven InVision® liquid biopsy platform technology. This next-generation sequencing platform incorporates built-in controls and error-correction for highly sensitive and specific variant detection. RaDaR is a personalized assay that tracks a set of up to 48 tumor-specific variants in a patient using a liquid biopsy with exceptional sensitivity, allowing both detection of residual disease following curative intent or definitive treatment, and early detection of relapse. With a turnaround time of seven calendar days for monitoring, RaDaR will be added to the range of assays offered through Inivata’s CAP/ CLIA lab.
Initial applications for RaDaR will be in clinical research. The availability of an assay with a level of sensitivity that exceeds current fixed panel approaches will allow accurate patient selection for enriched clinical trial populations. This specific patient selection approach may allow for more focused clinical trials with faster recruitment rates. In addition, the ability to track therapeutic treatment success through accurate liquid biopsy will allow earlier visibility of drug efficacy.
Clive Morris, Chief Executive Officer at Inivata, commented:
RaDaR is a highly sensitive, personalized test which will allow for the detection of residual disease in multiple tumor types, providing uniquely valuable insights into a patient’s disease state. This information can be used to speed recruitment into clinical trials with a more accurate selection of eligible patients, whilst driving efficiency of the trials themselves. We look forward to applying our technology through partnerships with pharmaceutical companies and to bringing its benefits to patients.