AI-driven Discovery of Morphomolecular Signatures in Toxicology.

ABSTRACT: Early identification of drug toxicity is essential yet challenging in drug development. At the preclinical stage, toxicity is assessed with histopathological examination of tissue sections from animal models to detect morphological lesions. To complement this analysis, toxicogenomics is increasingly employed to understand the mechanism of action of the compound and ultimately identify lesion-specific safety biomarkers for which in vitro assays can be designed. However, existing works that aim to identify morphological correlates of expression changes rely on qualitative or semi-quantitative morphological characterization and remain limited in scale or morphological diversity. Artificial intelligence (AI) offers a promising approach for quantitatively modeling this relationship at an

SUBMITTER: Jaume G 

PROVIDER: S-EPMC11291055 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature