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Drug Development.

Viswanath Devanarayan1,2, Yuanqing Ye1, Michael C Donohue3

  • 1Eisai Inc., Nutley, NJ, USA.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|December 25, 2025
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Summary
This summary is machine-generated.

Predicting cognitive decline in preclinical Alzheimer's disease (AD) using baseline biomarkers like tau PET can improve clinical trial efficiency. This approach enhances treatment effect estimates and reduces necessary sample sizes for future AD trials.

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Area of Science:

  • Neuroscience
  • Biomarkers
  • Clinical Trials

Background:

  • Cognitive decline variability in preclinical Alzheimer's disease (AD) complicates treatment evaluation.
  • Developing predictive models for cognitive progression is crucial for enhancing clinical trial precision.

Purpose of the Study:

  • To develop and validate models forecasting cognitive decline in preclinical AD.
  • To assess the potential of these models to improve treatment effect estimates in clinical trials.

Main Methods:

  • Utilized data from the Solanezumab Phase III trial in amyloid-positive preclinical AD.
  • Developed a predictive model for Preclinical Alzheimer's Cognitive Composite (PACC) decline using demographics, APOE ε4, and baseline clinical data.
  • Evaluated the added value of amyloid PET Centiloid (CL), plasma pTau217, MRI, and tau PET measures.

Main Results:

  • A model incorporating demographics, CL, and clinical assessments explained 16% of PACC decline.
  • Adding MRI improved prediction to 23%; plasma pTau217 or tau PET increased it to 25% and 42%, respectively.
  • Baseline tau PET was the strongest predictor; simulations showed using predicted PACC decline as an Alzheimer's Prognostic Covariate (APC) reduced variance by 20.3% and increased power to 88%.

Conclusions:

  • Baseline tau PET is the most significant predictor of cognitive decline in preclinical AD.
  • Implementing baseline-predicted PACC decline as an APC enhances treatment effect estimation.
  • This predictive approach improves the efficiency of clinical trials for preclinical Alzheimer's disease.