OrbiTox: a visualization platform for NAMs and read-across exploration of multi-domain data

Area of Science:

• Toxicology and Chemical Safety
• Computational Biology
• Data Science

Background:

• Next-generation risk assessment (NGRA) requires integrating diverse mechanistic data from in vitro and in silico studies.
• Current data aggregation tools are insufficient for navigating disparate datasets in chemical safety evaluations.
• A unified approach is needed to combine multiple data streams for a coherent weight-of-evidence case.

Purpose of the Study:

• To develop OrbiTox, a platform for consolidating and visualizing complex chemical data.
• To support comprehensive chemical assessments by integrating various data domains.
• To facilitate data-driven chemical safety evaluations.

Main Methods:

• Consolidation of millions of data points (chemical properties, genes, pathways, bioactivities) into a 3D visualization platform.
• Incorporation of hundreds of quantitative structure-activity relationship (QSAR) models for gap-filling.
• Facilitation of read-across by retrieving data-rich chemical analogs with similar structures and metabolic profiles.

Main Results:

• OrbiTox provides an intuitive and interactive 3D platform for navigating integrated chemical data.
• The platform supports robust gap-filling for key endpoints using QSAR models.
• OrbiTox enables efficient retrieval of chemical analogs for read-across assessments.

Conclusions:

• OrbiTox unifies experimental data and predictive models within a user-friendly interface.
• The platform addresses the need for effective tools in chemical safety assessment.
• OrbiTox facilitates data-driven decision-making in regulatory evaluations.