Integrating QSAR and read-across for environmental assessment

Area of Science:

• Toxicology and Cheminformatics
• Computational Toxicology
• Environmental Chemistry

Background:

• Read-across and Quantitative Structure-Activity Relationship (QSAR) models are vital for chemical safety assessment but face challenges.
• Subjectivity in data evaluation and defining chemical similarity are critical drawbacks.
• Integrating these methods can improve reliability and reduce uncertainty.

Purpose of the Study:

• To address subjectivity in read-across and QSAR assessments.
• To explore synergistic integration of read-across and QSAR approaches.
• To introduce a novel, transparent read-across program, ToxRead.

Main Methods:

• Development and application of the ToxRead program for read-across.
• Comparison and integration of ToxRead outputs with QSAR model predictions.
• Weight-of-evidence strategy for combining results.

Main Results:

• ToxRead offers a transparent and reproducible approach to read-across.
• Integration of ToxRead and QSAR outputs provides complementary support.
• Demonstrated application in assessing chemical bioconcentration factors.

Conclusions:

• The ToxRead program enhances the reliability of read-across assessments.
• Combining read-across and QSAR within a weight-of-evidence framework improves chemical safety evaluations.
• Promotes transparency and reproducibility in computational toxicology.