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Heartening predictors in diabetes

How the diabetes and CV fields should organize to gain new biomarkers

New biomarkers of cardiovascular risk could relieve a decade-old bottleneck for diabetes drug development, but validating them will require companies to invest in strategic trial designs, and public and private stakeholders to pool thinking.

As diabetes companies await new FDA guidelines that might do away with the blanked requirement for costly post-market cardiovascular outcomes trials (CVOT) that have hampered progress over the last ten years, they also anticipate increased pre-market CV requirements that could negate some of the savings, making it unclear how much new development the change will spur (see “Cashing Out CVOT”).

Better biomarkers for predicting major adverse cardiac events (MACE) could trim development costs for both pre- and postmarket diabetes trials. Translational research is starting to identify candidates that, if validated, could enable smaller, shorter trials through improved enrichment for high-risk patients.

A common refrain among experts interviewed by BioCentury is that the CV field needs to take a page from the cancer playbook in its approach to biomarkers.

“There are examples in oncology, for example in breast cancer treatment, where biomarkers are not only used for diagnosis, but also for establishing prognosis and selection of specific therapies,” said James Januzzi, professor of medicine at Harvard Medical School and cardiologist at Massachusetts General Hospital. “In cardiovascular disease, there’s no reason why we could not do the same.”

“What we’ve seen repeatedly is these machine learning-leveraged, multiple-marker panels out-perform traditional single biomarkers every single time.”

James Januzzi, Harvard Medical School

According to Januzzi, the key to predictive power will be measuring multiple signals at once.

“What we’ve seen repeatedly is

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