Modeling amyloid plaque turnover dynamics improves characterization of drug effects

The article presents a mathematical model to better understand how Alzheimer’s drugs reduce amyloid-β plaques in the brain. Instead of just looking at plaque changes over time in clinical trials, which can vary widely across studies, the model treats plaque levels as a balance between how quickly plaques form and how quickly they are cleared. By applying this approach to data from both a BACE1 inhibitor (which reduces plaque formation) and several monoclonal antibodies (which accelerate plaque removal), the researchers were able to quantify and directly compare how strongly each therapy affects these mechanisms. The model also revealed that amyloid plaques naturally clear extremely slowly, on the scale of years, helping explain why treatment effects take time to appear and why earlier intervention may work better. Overall, the study shows that this turnover-based modeling can offer clearer insight into how different anti-amyloid drugs work, improve cross-trial comparisons, and support smarter design of future Alzheimer’s treatment strategies.