Deep Lens and Pacific Cancer Care Enter Strategic Partnership to Improve Clinical Trial Matching for Oncology Patients
Pacific Cancer Care and Deep Lens announced that they are collaborating to optimize clinical trial matching and accelerate enrollment at the Monterey-based practice through the use of Deep Lens’ artificial-intelligence (AI) based solutions and other services. Pacific Cancer Care is the largest hematology and oncology practice on the California Central Coast. Deep Lens is a digital healthcare company that helps community oncology practices improve and expand clinical research programs through the use of their proprietary AI solution, VIPER. This partnership will expand Pacific Cancer Care’s existing clinical trial offering to patients by more accurately and effectively identifying eligible patients for trials, improving communications between patient care teams and bringing more trials to the practice.
“Clinicals trials are not only critical to the advancement of new therapeutic options for cancer, but they present a unique opportunity for patients to access novel treatments well in advance of their commercialization, some of which may help positively impact the state of their disease,” said Zach Koontz, M.D., oncologist at Pacific Cancer Care. “We are excited to partner with Deep Lens to broaden our clinical research program through an increased number of trials that we can offer onsite and by expediting the time we can get patients into these trials. We have a very busy practice and we look forward to leveraging other Deep Lens services to help alleviate some of the administrative tasks associated with clinical trial recruitment, so that our staff can focus more exclusively on patient care.”
Recommended AI News: Talon Launches First Corporate Secure Browser for the Hybrid Work Era Backed by Renowned Cyber Security Industry Leaders
It is estimated that more than 15,000 oncology clinical trials are actively recruiting patients; however, fewer than 1 in 30 patients participate in a clinical trial. Limited trial site resources make it time-consuming to identify eligible patients, especially as trial protocols increase in complexity. VIPER supports care teams by automating the identification of potentially eligible patients at the time of diagnosis and easily matching them to relevant trials.
“Pacific Cancer Care already has an extremely comprehensive clinical research program – they’ve been the first site to offer access to certain therapies via clinical trials and they place great importance on the role that clinical research plays in the overall acceleration of our knowledge and treatment of cancer,” said Simon Arkell, president and co-founder at Deep Lens. “We are thrilled to align with such a prominent, reputable practice that is just as passionate as Deep Lens about innovation and the potential of precision therapies for the treatment of cancer. We look forward to helping this practice better serve the Central Coast oncology community.”
Recommended AI News: A-LIGN Delivers Industry’s Most Comprehensive Ransomware Preparedness Assessment Service
Deep Lens’ VIPER will pre-screen all patients from Pacific Cancer Care’s EMR (OncoEMR) and integrate molecular data feeds from Caris Life Sciences, Foundation Medicine and Guardant Health as well as all pathology feeds to automatically identify qualified patients for clinical trials. Deep Lens pre-screening and clinical trial matching solution is provided at no cost to oncology practices.
Deep Lens is working with a significant number of community oncology practices representing every region in the U.S. It is estimated that approximately 85 percent of cancer patients are diagnosed and treated at local, community-based oncology practices. Deep Lens is committed to expanding important oncology research by making trials more accessible to a larger and more diverse population within these local community settings.
Recommended AI News: Palo Alto Networks Partners with Ingram Micro to Bring Okyo Garde to Small Businesses
[To share your insights with us, please write to sghosh@martechseries.com]
Comments are closed.