Using precision medicine can lead to better survival rates and improve the quality of life for patients with cancer. However, while there have been major breakthroughs in using this approach to treat cancer and test new drugs, the tools used to identify disease phenotypes have lagged.

Currently, identifying these phenotypes often requires expensive tests, such as those that examine molecular markers, use special stains on tissue samples, or sequence a person’s genetic material. Because of this barrier, many of the potential benefits of precision medicine remain out of reach for many patients.

Recently, a research team based at the University of Arizona developed a faster and more affordable way to identify disease phenotypes in pancreatic cancer. Their work, published in Biophotonics Discovery, describes a new method for disease phenotyping using label-free optical microscopy and artificial intelligence (AI).