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Related Experiment Video

Updated: May 17, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

Improving risk assessment.

Donna M Dambach1, Hirdesh Uppal

  • 1Safety Assessment, Development Sciences, Genentech, South San Francisco, CA 94080, USA.

Science Translational Medicine
|November 9, 2012
PubMed
Summary
This summary is machine-generated.

Sharing clinical trial data and developing advanced cell models can enhance the prediction of adverse drug events. These approaches promise to improve drug safety assessments.

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Last Updated: May 17, 2026

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

Area of Science:

  • Pharmacology and Toxicology
  • Biomedical Engineering
  • Clinical Research

Background:

  • Adverse drug events pose significant risks in clinical practice.
  • Current methods for predicting drug toxicity have limitations.
  • The need for improved predictive models in drug development is critical.

Purpose of the Study:

  • To explore the potential of data sharing and novel cell models for predicting adverse drug events.
  • To highlight advancements in nonclinical models for human biological mimicry.

Main Methods:

  • Analysis of shared clinical trial data.
  • Engineering of nonclinical cell-based models.
  • Integration of data and model outputs for predictive analysis.

Main Results:

  • Potential for improved prediction accuracy of drug-related adverse events.
  • Enhanced understanding of drug-specific toxicological profiles.

Conclusions:

  • Widespread data sharing and advanced cell-based models are promising strategies for enhancing drug safety.
  • These initiatives can lead to more reliable predictions of adverse drug reactions, improving patient outcomes.