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Updated: Jun 11, 2026
09:47
DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data
Published on: December 15, 2023
[Could idiosyncratic thinking fit with << omics >>?]
Céline Narjoz1, Philippe Beaune, Isabelle de Waziers
1Université Paris-Descartes et Inserm U775, 75006 Paris, France. celine.narjoz@parisdescartes.fr
Medecine Sciences : M/S
|July 13, 2010
Summary
Idiosyncratic drug toxicity, though rare, can be fatal. Genomic and transcriptomic studies offer potential biomarkers to predict and prevent these severe adverse drug reactions in susceptible patients.
Area of Science:
- Pharmacogenomics
- Toxicology
- Biomarker Discovery
Context:
- Idiosyncratic toxicity represents rare but severe adverse drug reactions.
- Current preclinical and clinical development methods fail to predict these post-marketing issues.
- Prevention strategies include identifying predisposed individuals and utilizing predictive biomarkers.
Purpose:
- To review genomic and transcriptomic data for predicting idiosyncratic drug reactions.
- To explore the potential of omics technologies in identifying biomarkers for adverse drug events.
- To understand the biological mechanisms underlying drug-induced toxicity.
Summary:
- Genomic studies have identified genetic factors associated with idiosyncratic reactions, enabling clinical risk assessment.
- Transcriptomic studies provide insights into cellular processes affected by drug treatments.
- Integrating these omics data can aid in the discovery of toxicity biomarkers.
Impact:
- Potential to prevent serious adverse drug reactions in susceptible populations.
- Facilitates personalized medicine approaches by identifying at-risk patients.
- Advances the understanding of drug toxicity mechanisms for improved drug safety.
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