ToxDB: pathway-level interpretation of drug-treatment data

Area of Science:

• Pharmacogenomics
• Toxicology
• Computational Biology

Background:

• Gene expression data from drug treatments are used for biomarker discovery but often lack robustness.
• Supervised expression patterns based on pathway concepts offer more reliable toxicity assessment than unsupervised methods.

Purpose of the Study:

• To develop a comprehensive database, ToxDB, for analyzing drug-induced functional consequences at the pathway level.
• To improve the robustness and reliability of toxicity prediction and compound classification.

Main Methods:

• Collected 2694 pathway concepts and computed numerical response scores for 437 drugs/chemicals across 7464 experimental conditions.
• Developed ToxDB with tools for visualization and differential analysis of pathway responses.
• Integrated toxicity annotation and chemical information with pathway response data.

Main Results:

• ToxDB provides a centralized resource for exploring pathway-level drug responses.
• The database facilitates comparisons across different treatment parameters and experimental conditions.
• Enables linking pathway data with toxicity and chemical information for comprehensive analysis.

Conclusions:

• ToxDB offers a robust platform for understanding drug effects and predicting toxicity.
• Pathway-based analysis in ToxDB improves upon traditional methods for biomarker discovery.
• Facilitates more reliable classification of compounds and assessment of drug-induced toxicity.