Learning from amyloid trials in Alzheimer's disease. A virtual patient analysis using a quantitative systems pharmacology approach.

Abstract

BackgroundMany trials of amyloid‐modulating agents fail to improve cognitive outcome in Alzheimer's disease despite substantial reduction of amyloid β levels.MethodsWe applied a mechanism‐based Quantitative Systems Pharmacology model exploring the pharmacodynamic interactions of apolipoprotein E (APOE), Catechol ‐O ‐methyl Transferase (COMTVal158Met), and 5‐HT transporter (5‐HTTLPR) rs25531 genotypes and aducanumab.ResultsThe model predicts large clinical variability. Anticipated placebo differences on Alzheimer's Disease Assessment Scale (ADAS)‐COG in the aducanumab ENGAGE and EMERGE ranged from 0.77 worsening to 1.56 points improvement, depending on the genotype‐comedication combination. 5‐HTTLPR L/L subjects are found to be the most resilient. Virtual patient simulations suggest improvements over placebo between 4% and 20% at the 10 mg/kg dose, depending on the imbalance of the 5‐HTTLPR genotype and exposure. In the Phase II PRIME trial, maximal anticipated placebo difference at 10 mg/kg ranges from 0.3 worsening to 5.3 points improvement.DiscussionThese virtual patient simulations, once validated against clinical data, could lead to better informed future clinical trial designs.