PCR Oncology and Deep Lens have announced a strategic alliance that will combine AI-based clinical trial screening along with an enrollment platform- VIPER™ into its PCR Oncology ecosystem. Notably, VIPER utilizes novel cloud-based technology to carry out and accelerate the clinical study recruitment process.
Through the partnership, PCR Oncology will be able to identify and screen people suffering from oncology to precision-based clinical trials. It must be mentioned that the VIPER technology has been designed to help clinical trial sites with complexities that include patient recruitment and enrollment, which will allow oncology teams to mainly focus on offering effective patient care.
According to David Palchak, M.D., PCR Oncology, their firm is focusing on improving its cancer research and prioritizing developments in the clinical trial program to offer a wide range of studies to their patient pool.
David further added that the advanced VIPER platform will not only accelerate the process of matching patients to the current trials but also help in extending additional trials to the PCR network, thereby enhancing the care for cancer patients across the Central Coast.
Citing reports, PCR Oncology has a strong clinical study and research program. It is the first in California which is participating in the Cancer Moonshot program by National Cancer Institute, a five-year effort developed to improve the awareness and treatment of cancer through the collection and study from various patients across the U.S.
Greg Andreola, Chief Revenue Officer, Deep Lens, was reportedly quoted stating that the company is working closely with PCR Oncology to add value to their clinical studies. The VIPER technology has been developed to help sites with complexities involved in the recruitment and enrollment of patients, allowing teams to focus on patient care.
Seemingly, VIPER automates the clinical trial process and matches the candidates at the time of treatment to an appropriate trial through the ingestion and analysis of personalized genomic data, pathology data, and electronic medical records.