FDA clears Canary Foundation to test molecular imaging agent

The FDA has approved an exploratory investigational new drug (eIND) for Canary Foundation research in the testing of molecular imaging agent 18F- FPPRGD2 for lung cancer.

Canary also received the National Cancer Institute Early Detection Research Network (EDRN) Biomarker Development Laboratory (BDL) grant for prostate cancer.

The research that stems from each of these awards will be conducted at the Canary Center at Stanford for Early Cancer Detection in Palo Alto, Calif.

The foundation said its imaging agent 18F-FPPRGD2 has excelled in safety and efficacy studies and with the FDA-approved eIND, clinical trials can be performed. The Stanford Nuclear Medicine group is now testing 18F-FPPRGD2 in lung cancer patients for the first time.

Sanjiv Sam Gambhir, MD, PhD, a professor of radiology and bioengineering and head of the molecular Imaging Program at Stanford University in Stanford, Calif., and James Brooks, MD, associate professor in urology, were awarded the a five-year EDRN BDL grant for their project in prostate cancer.

The intent of the EDRN BDL Project is to adapt the newly-developed magneto-nano sensor to multiplex blood biomarkers for prostate cancer detection and prognostication (in vitro) and subsequently adapt ultrasound technology using tumor angiogenesis-targeted microbubbles to image prostate cancer (in vivo).

The Canary Center at Stanford hopes to combine these in vitro and in vivo platforms in an integrated approach that will lead to a blood test for the early detection and prognostication of prostate cancer, along with an imaging strategy that will enable the accurate localization and biopsy of prostate lesions.

Around the web

The new technology shows early potential to make a significant impact on imaging workflows and patient care. 

Richard Heller III, MD, RSNA board member and senior VP of policy at Radiology Partners, offers an overview of policies in Congress that are directly impacting imaging.
 

The two companies aim to improve patient access to high-quality MRI scans by combining their artificial intelligence capabilities.