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Learning from amyloid trials in Alzheimer's disease. A virtual patient analysis using a quantitative systems pharmacology approach
Author(s) -
Geerts Hugo,
Spiros Athan
Publication year - 2020
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1002/alz.12082
Subject(s) - placebo , clinical trial , pharmacodynamics , apolipoprotein e , donepezil , medicine , oncology , pharmacology , virtual patient , disease , psychology , pharmacokinetics , psychiatry , dementia , pathology , alternative medicine
Background Many trials of amyloid‐modulating agents fail to improve cognitive outcome in Alzheimer's disease despite substantial reduction of amyloid β levels. Methods We 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. Results The 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. Discussion These virtual patient simulations, once validated against clinical data, could lead to better informed future clinical trial designs.