What if clinical trials for new Alzheimer’s disease treatments could be made quicker, more efficient and more accurate? Jeff Kaye, M.D., director of OHSU’s Layton Center for Aging and Alzheimer’s Disease Center, has found a way, using new technology to track the behaviors of patients. Kaye and his team of researchers determined that gathering and analyzing rich daily data points from trial participants significantly reduced the sample size required for clinical trials conducted to research treatments for the disease. Where the new technology comes in is how the data is collected. Through unobtrusive continuously monitored in-home sensors, researchers are able to gather information that more closely reflects people’s actual day-to-day performance of tasks and activities, including sleep habits, mobility, telephone use, and participants’ time away from the house.
This approach not only significantly reduces the need to enroll thousands of patients and follow them for many years at great cost, but provides more accurate data than twice-a-year memory tests. Using the current standard assessment, the memory test, an estimated sample size of 2,000 individuals followed over four years is required to see a meaningful treatment effect. When walking speed was used as the measurement, just 262 participants were needed. Similarly, when the measurement was computer use, 26 participants were needed. What this means is more accurate and speedy clinical trials, which, in turn, provides a quicker, more efficient route toward treatments for Alzheimer’s.