Drug toxicity prediction based on genotype-phenotype differences between preclinical models and humans.

ABSTRACT:

Background

A major hurdle in drug development is the poor translatability of preclinical toxicity findings to human outcomes, largely due to biological differences between humans and model organisms. This gap leads to high clinical trial attrition and post-marketing drug withdrawals. Existing toxicity prediction methods primarily rely on chemical properties and typically overlook these inter-species (or -organism) differences.

Methods

We developed a machine learning framework that incorporates genotype-phenotype differences (GPD) between preclinical models (cell lines and mice) and humans to improve the prediction of human drug toxicity. Clinical risk information on drugs (e.g., clinical trials or post-marketing surveillance) was obtained without bias from published reports,

SUBMITTER: Park M 

PROVIDER: S-EPMC12597050 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature