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Cognitive Go/No-Go decision-making criteria in Alzheimer's disease drug development

Alette M Wessels1, Chris J Edgar2, Pradeep J Nathan3

  • 1Eli Lilly and Company, Indianapolis, Indiana, USA.

Drug Discovery Today
|January 24, 2021
PubMed

Insights

Making Go/No-Go decisions in early Alzheimer's disease clinical trials is difficult. This review highlights using cognitive data to improve these decisions, considering trial context for better drug development outcomes.

Area of Science:

  • Neuroscience
  • Clinical Pharmacology
  • Drug Development

Background:

  • Alzheimer's disease drug development faces challenges in early phase clinical trials, often due to lack of efficacy and safety concerns.
  • Demonstrated target engagement in Alzheimer's trials has infrequently led to significant clinical efficacy.
  • Cognitive data offers potential insights for Go/No-Go decision-making throughout the drug development process.

Purpose of the Study:

  • To provide insights into the utilization of cognitive data for Go/No-Go decisions in Alzheimer's disease drug development.
  • To emphasize how cognitive criteria for Go/No-Go decisions vary based on context, including development stage, mechanism of action, and trial design.

Main Methods:

  • This review synthesizes current understanding and proposes a framework for integrating cognitive data into decision-making.
  • It analyzes the nuances of applying cognitive endpoints across different phases and types of Alzheimer's disease clinical trials.

Main Results:

  • Cognitive data can serve as a valuable tool for Go/No-Go decisions in early phase Alzheimer's trials.
  • The interpretation and application of cognitive data must be tailored to the specific context of the trial.
  • A priori defined, robust decision-making criteria are essential for effective use of cognitive data.

Conclusions:

  • Implementing context-specific cognitive criteria can enhance the rigor of Go/No-Go decisions in Alzheimer's drug development.
  • Strategic use of cognitive data may help mitigate risks associated with trial failures.
  • This approach supports more informed and efficient progression of potential Alzheimer's therapeutics.

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