Applying quantitative structure-activity relationship approaches to nanotoxicology: current status and future...

Area of Science:

• Nanotoxicology
• Computational Chemistry
• Risk Assessment

Background:

• Engineered nanoparticles are increasingly used across industries, raising concerns about their potential environmental and health impacts.
• Predicting nanomaterial toxicity efficiently is crucial for mitigating risks associated with their large-scale production and use in consumer products.
• The structure-toxicity paradigm offers a predictive approach based on physicochemical properties, reducing reliance on animal testing.

Purpose of the Study:

• To review recent advancements in Quantitative Structure-Activity Relationship (QSAR) modeling for nanomaterial toxicity.
• To identify critical research gaps hindering the widespread adoption of QSAR methods in nanotoxicology.
• To propose a future research agenda for developing robust QSAR models suitable for regulatory applications.

Main Methods:

• Literature review of QSAR applications in nanomaterial toxicity assessment.
• Analysis of current research trends and limitations in the field.
• Synthesis of findings to outline a strategic roadmap for future research.

Main Results:

• QSAR modeling is a rapidly advancing field for predicting nanomaterial hazards.
• Significant gaps exist in data availability, model validation, and regulatory acceptance of QSAR approaches.
• The physicochemical properties of nanomaterials are key determinants of their toxicological profiles.

Conclusions:

• QSAR models hold significant potential for cost-effective and ethical assessment of nanomaterial risks.
• Further research is needed to enhance data quality, refine modeling techniques, and establish validation frameworks for regulatory use.
• A collaborative roadmap is essential to accelerate the development and implementation of QSAR for nanomaterial safety assessment.