By Steve Graff
Editor’s Note: This article was originally published by Penn Medicine News.
When the biotech company Biogen stopped a clinical trial investigating a drug known as aducanumab to slow Alzheimer’s, disappointment swept through the neurology community. “This one hurts,” one neurologist told CNN in March. “Alzheimer’s patients just can’t get a break.” The drug, which reduces amyloid, a nefarious protein believed to drive the disease, had slowed cognitive decline in animals. But studies in humans showed the intervention was too late. Damage—likely from the early buildup of the protein—had already been done, and patients’ outcomes weren’t improving as the trial progressed. Other promising drugs remain in the pipeline, but that trial—which included several Penn patients—was yet another reminder of the staggering complexity of Alzheimer’s.
“This a disease that can start up to 20 years before any symptoms become obvious,” said Yong Fan, PhD, an assistant professor of Radiology in the Center for Biomedical Imaging Computing and Analytics at Penn. “So if you could predict the disease earlier, you would have a better chance to cure it with drugs.”
Fortunately, the field of detection has made significant strides over the years to help get there. Researchers are consistently finding better ways to track rogue proteins and predict the progression of cognitive decline with biomarkers, neuroimaging, and more recently and arguably most impressively, the rapidly advancing technology touching nearly every part of medicine today: artificial intelligence.