Systematic in silico analysis of clinically tested drugs for reducing amyloid‐beta plaque accumulation in Alzheimer's disease

Introduction Despite strong evidence linking amyloid beta (A beta) to Alzheimer's disease, most clinical trials have shown no clinical efficacy for reasons that remain unclear. To understand why, we developed a quantitative systems pharmacology (QSP) model for seven therapeutics: aducanumab, crenezumab, solanezumab, bapineuzumab, elenbecestat, verubecestat, and semagacestat. Methods Ordinary differential equations were used to model the production, transport, and aggregation of A beta; pharmacology of the drugs; and their impact on plaque. Results The calibrated model predicts that endogenous plaque turnover is slow, with an estimated half-life of 2.75 years. This is likely why beta-secretase inhibitors have a smaller effect on plaque reduction. Of the mechanisms tested, the model predicts binding to plaque and inducing antibody-dependent cellular phagocytosis is the best approach for plaque reduction. Discussion A QSP model can provide novel insights to clinical results. Our model explains the results of clinical trials and provides guidance for future therapeutic development.