Understanding quantitative effects of anti-amyloid therapies on tau biomarkers and functional outcome

In this paper, we use a mechanistic quantitative systems pharmacology (QSP) model to quantify how anti-amyloid therapies impact tau biomarkers and cognitive outcomes in Alzheimer’s disease. By integrating amyloid biology, neuronal activity, and clinical data, the model explains a large proportion of observed changes in plasma p-tau181 and functional decline, and identifies this accessible biomarker as a potential alternative to PET imaging for monitoring treatment response. The findings highlight that treatment benefit varies by drug mechanism, disease stage, and baseline tau burden, with the greatest cognitive improvements seen in earlier-stage patients. These insights demonstrate how model-informed drug development can optimize clinical trial design, enable patient stratification, and support more efficient development of Alzheimer’s therapies.