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Cytotoxic T Cells-mediated Immune Response01:27

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Using interactive platforms to encode, manage and explore immune-related adverse outcome pathways.

Alexander Mazein1, Muhammad Shoaib1, Miriam Alb2

  • 1Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg.

Journal of Immunotoxicology
|December 10, 2024
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Summary
This summary is machine-generated.

This study introduces a systems immunotoxicology workflow to predict adverse outcomes from immunomodulatory therapies. It integrates adverse outcome pathways and systems medicine disease maps for enhanced safety assessments.

Keywords:
AOPCAR T cellsCRSadverse outcome pathwaychimeric antigen receptorcytokine release syndromedisease mechanismsimmunomodulatory therapiessystems biology

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Area of Science:

  • Toxicology
  • Systems Biology
  • Immunology

Background:

  • Improving nonclinical safety assessments for immunomodulatory therapies is crucial.
  • Current methods need enhanced predictive capabilities for adverse outcomes in immunotoxicology.

Purpose of the Study:

  • To develop and illustrate a systems immunotoxicology workflow for modeling and predicting adverse outcomes.
  • To integrate the adverse outcome pathway (AOP) concept with systems medicine disease maps.

Main Methods:

  • Expanding linear AOPs into molecular interaction models using systems biology formats.
  • Utilizing the chimeric antigen receptor (CAR) T cell treatment as a use case.
  • Developing a knowledge integration and management system for immunotoxic events.

Main Results:

  • A structured, digital representation of AOPs is created, moving beyond graphical illustrations.
  • The workflow enables integration, encoding, management, and exploration of immunotoxicology knowledge.
  • An online, interactive map is available via the MINERVA Platform for community use.

Conclusions:

  • The developed workflow transforms AOPs into a standardized, computable format supporting reproducible research.
  • The system facilitates the expansion and updating of knowledge as research evolves.
  • This approach enhances the predictive assessment of immunomodulatory therapy safety.