BMDx2: A Tool for Integrating Toxicogenomics-Based Dose-Dependency Analysis and AOP-Based Mechanistic Insights

Area of Science:

• Toxicology
• Computational Biology
• Genomics

Background:

• Regulatory toxicology struggles to integrate omics data for mechanism-anchored safety assessments.
• Gene-centric analyses often fail to connect molecular changes to adverse outcomes.
• Bridging this gap requires quantitative, mechanistic metrics from toxicogenomics data.

Purpose of the Study:

• To develop BMDx2, an open-source tool for transforming multi-dose toxicogenomics datasets into quantitative, mechanistic evidence for chemical safety assessment.
• To enable mechanism-anchored metrics for regulatory toxicology by coupling benchmark-dose modeling with Adverse Outcome Pathway (AOP) enrichment.
• To illustrate the versatility of BMDx2 in characterizing chemical mechanisms of action through case studies.

Main Methods:

• BMDx2 couples benchmark-dose modeling with Adverse Outcome Pathway (AOP) enrichment.
• The tool derives transcriptomic-based points of departure from multi-dose toxicogenomics data (microarray, RNA sequencing).
• Case studies involving carbon nanotubes and bleomycin exposures were used to demonstrate BMDx2's capabilities.

Main Results:

• BMDx2 processes diverse toxicogenomics data to derive mechanistic insights.
• Case studies demonstrated BMDx2's ability to identify cellular reprogramming in fibrosis (carbon nanotubes) and map transcriptomics to AOPs (bleomycin).
• The tool enables potency ranking, chemical prioritization, and mechanistically anchored explanations.

Conclusions:

• BMDx2 facilitates the regulatory application of toxicogenomics by providing mechanism-based evidence.
• The tool accelerates mechanism-based chemical safety evaluations.
• BMDx2 supports standardized, regulatory-appropriate use of transcriptomic data for safety assessment.