SkinSensDB: a curated database for skin sensitization assays

Area of Science:

• Toxicology
• Computational Chemistry
• Biotechnology

Background:

• Skin sensitization is a critical toxicological endpoint for chemical safety.
• Traditional assessment relied on animal models, but alternative in vitro assays and adverse outcome pathways (AOPs) are reshaping evaluations.
• Existing computational models often lack integration of in vitro data within an AOP framework.

Purpose of the Study:

• To address the scarcity of integrated databases for skin sensitization.
• To facilitate the development of AOP-based computational models for predicting skin sensitization.
• To provide a publicly accessible resource for chemical safety assessment.

Main Methods:

• Curated data from published AOP-related skin sensitization assays.
• Developed the SkinSensDB database, integrating both in vivo and in vitro data.
• Implemented browsing and search functionalities for compound assessment.

Main Results:

• Successfully constructed SkinSensDB, a comprehensive skin sensitization database.
• The database integrates diverse assay data relevant to the AOP for skin sensitization.
• Provides tools for assessing new compounds based on structural similarity.

Conclusions:

• SkinSensDB supports the development of improved AOP-based prediction models for skin sensitization.
• The database enhances chemical hazard determination and safety assessment by integrating in vitro and in vivo data.
• Public availability of SkinSensDB promotes advancements in toxicological research and chemical safety.