Labcorp and Community Clinical Oncology Research Network (CCORN) have partnered to gain improved insights into the effect of disparities in precision medicine for cancer.
The companies expect that data from a patient registry and biobank can aid in designing oncology clinical trials in diverse patient populations in the future.
Patient registries are observational studies that gather standardised information on a group of patients with the same condition or experience.
As part of the collaboration, the PREFER patient registry will enrol up to 2,500 advanced solid tumour cancer patients at several sites in the US starting next month.
This registry is set to offer important insights from clinical and lab data about the unmet needs among cancer patients from diverse populations.
Labcorp and CCORN will use a genomic and immune-profiling, tissue-based test called OmniSeq INSIGHTsm, which leverages next-generation sequencing technology, to detect the incidence of actionable biomarkers and driver mutations exclusive to various ethnicities.
The companies will also develop a biobank to provide access to real-world evidence and recognise the source of disparities.
The patient registry and biobank information could help enhance the design of cancer trials, aid patient enrolment and promote the growth of genomic profiling testing in diverse populations, Labcorp said.
CCORN founder and chairman Dr Kashyap Patel said: “Drug development processes have been relatively unsuccessful in reflecting demographic diversity in clinical trials, which further contributes to disparities in care and outcomes for those groups.
“It’s imperative that we determine how and why disparities occur, and this collaboration with Labcorp will be a major step in this regard.”
According to a 2020 report by American Association for Cancer Research, 34% of cancer-related deaths could be avoided in adults aged 25 to 74 years in the US if disparities in trial participation were addressed.
In March this year, Labcorp extended its alliance with PathAI to enable the deployment of the latter’s algorithms in prospective trials of cancer and other diseases.
