University Hospitals Seidman Cancer Center in the US has selected GenomOncology’s Precision Decision and GO Connect solutions to streamline the matching of patients to the increasing number of clinical trials and therapies.

The platform will help University Hospitals to help scale its precision oncology programme and streamlines a complicated process to assist patients and doctors.

University Hospitals selected the new platform as it needed access to all curated biomarker-based and institutional non-biomarker clinical trials.

GenomOncology’s platform also provides the capability to identify cohorts of patients within the institution eligible for clinical trials and novel therapies.

Additionally, it allows University Hospitals to conduct feasibility analysis to launch new clinical trials across all of its locations wholly-owned by Seidman Cancer Center.

University Hospitals Seidman Cancer Center president and scientific director Dr Theodoros Teknos said: “Due to the speed and complexity of genetic and biomarker discoveries, it is virtually impossible for any oncologist to remain current on all the clinical trials and newly approved cancer therapies.

“Through this partnership with GenomOncology, we have leveraged the power of computing to process incredible amounts of data and identify the optimal care for every patient.”

University Hospitals will use GenomOncology’s Precision Decision and GO Connect solutions to efficiently match patients to therapies, as well as relevant, open clinical trials.

The solution will also be used to ingest data from the institutions’ clinical data warehouse and clinical trial matching system and transform it into usable information available within GenomOncology’s Precision Decision product.

University Hospitals will also be able to identify and interact with all therapies and curated clinical trials in a single dashboard, through which users can search for eligible patients at their institution.

The University Hospitals team can also examine their internal database of clinical and molecular profiles of patients to determine the feasibility of opening new clinical trials.