A. Przekwas, Carly Norris, H. T. Garimella
2026.2.10Frontiers in Aging Neuroscience
tlooto Summary
The model described in this work provides a basis for personalized precision neurology with the potential to facilitate pre-symptomatic AD diagnosis, thereby establishing early prevention strategies, and accelerating identification of optimal therapeutic interventions.
Abstract
The use of mechanistic models to support personalized medicine and precision diagnostics offers transformative potential for neurology. In this study, we developed a mechanistic model of Alzheimer's Disease progression (mAD) that integrates amyloid precursor protein (APP) processing, Aβ peptide generation, Aβ aggregation pathway modeling, Aβ transport, and whole-body biomarker kinetics (BxK) of Aβ40 and Aβ42 peptides, including enzymatic and microglial clearance mechanisms. The purpose of this work was to formulate an integrated, multiscale quantitative systems pharmacology (QSP) mechanistic model of Alzheimer's progression to advance neuroscience QSP frameworks. The model described in this work provides a basis for personalized precision neurology with the potential to facilitate pre-symptomatic AD diagnosis, thereby establishing early prevention strategies, and accelerating identification of optimal therapeutic interventions.
Citation format
PRZEKWAS, A.; NORRIS, Carly; GARIMELLA, H. T. Mechanistic modeling of amyloid dynamics relating to alzheimer's disease progression. Frontiers in Aging Neuroscience, 2026, 18: 1730480.