Skip to main content
Premium Trial:

Request an Annual Quote

C-Path, FDA, NCI to Develop Standards for Evaluating Companion Dx/Rx Submissions

NEW YORK (GenomeWeb News) — The Critical Path Institute will use a $2.1 million Arizona state grant to work with the US Food and Drug Administration and the National Cancer Institute to standardize how companion diagnostics and therapies for cancer are evaluated.  
 
“Currently, there is no proven development pathway for FDA approval of the necessary companion diagnostic tests and their associated targeted therapies,” said Ventana Medical Systems, which will test the resulting process. “The goal of this collaboration is to establish the performance standards that would serve as the model for future FDA co-submissions of these companion diagnostic tests and their targeted drug therapies.”
 
The collaboration intends to establish performance standards that the FDA could use for future co-submissions of companion diagnostics and cancer drugs. The first test to which the groups plan to apply the standards will be a Ventana-made diagnostic for lung cancer, the company said.
 
“The ultimate goal of the project is to guide the choice of targeted therapy so that patients receive the most effective treatments," C-Path CEO Raymond Woolsey said in a statement.
 
C-Path is a publicly funded non-profit based in Tucson, Ariz., that aims to help the FDA implement its Critical Path Initiative. The $2.1 million grant was awarded by Science Foundation Arizona.

The Scan

Study Links Genetic Risk for ADHD With Alzheimer's Disease

A higher polygenic risk score for attention-deficit/hyperactivity disorder is also linked to cognitive decline and Alzheimer's disease, a new study in Molecular Psychiatry finds.

Study Offers Insights Into Role of Structural Variants in Cancer

A new study in Nature using cell lines shows that structural variants can enable oncogene activation.

Computer Model Uses Genetics, Health Data to Predict Mental Disorders

A new model in JAMA Psychiatry finds combining genetic and health record data can predict a mental disorder diagnosis before one is made clinically.

Study Tracks Off-Target Gene Edits Linked to Epigenetic Features

Using machine learning, researchers characterize in BMC Genomics the potential off-target effects of 19 computed or experimentally determined epigenetic features during CRISPR-Cas9 editing.