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Researchers, led by Thazin Nwe Aung, PhD, in the laboratory of David Rimm, MD, PhD, have developed a way to predict how lung cancer cells will respond to different therapies, allowing people with the most common form of lung cancer to receive more effective individualized treatment.

Regarding finding the right drug for the right patient, the reality of cancer management is far more complex than a single genetic mutation, according to David Rimm, MD, PhD.

It may be time for precision medicine to expand beyond the genomics realm and enter the protein space in the management of melanoma and other cancers, according to David Rimm, MD, PhD.

Dr. David Rimm spoke with Cancer Network on his latest research.

David Rimm, MD, PhD, Anthony N. Brady Professor of Pathology and professor of medicine at Yale School of Medicine, discussed two important developments to come out of his lab.

Yale Cancer Center researchers are trying to figure out if artificial intelligence can help people with cancer. They found that AI-based scoring of melanoma tumor-infiltrating immune cells, significantly outperforms traditional pathologist eyeballing.

Yale Cancer Center researcher David Rimm, MD, PhD, who is the Anthony N. Brady Professor of Pathology, and colleagues developed a novel assay to measure HER2 and TROP2 levels in patients with breast cancer. These data could help physicians decide which antibody-drug conjugates should be used in each individual case.

Yale pathology researchers created a dependable test that precisely measures key proteins found in breast cancer cells that can help oncologists choose the most effective targeted therapies for patients, says a report published July 16 in Precision Oncology, a journal of the American Society of Clinical Oncology.

A new Yale study found that open-source AI tools outperformed traditional, visual methods for measuring the abundance of melanoma biomarkers.