A functional assay-based strategy for nanomaterial risk forecasting.

Area of Science:

• Environmental Health and Safety (EHS)
• Nanomaterial Science
• Toxicology

Background:

• Current nanoEHS research often assumes exposure and hazard can be predicted from nanomaterial physical-chemical properties.
• This approach has limited success in providing actionable guidelines for nanomaterial risk assessment, except for inherently toxic materials.
• Predicting outcomes directly from intrinsic properties faces challenges in complex environmental and biological systems.

Purpose of the Study:

• To address the limitations of predicting nanoEHS outcomes solely from nanomaterial properties.
• To propose a novel framework for organizing data and designing integrated experiments using functional assays (FAs).
• To establish FAs as intermediary measures bridging nanomaterial properties and system-specific outcomes.

Main Methods:

• Proposed a framework based on functional assays (FAs) with three components: standardized protocols, theoretical context, and reference systems.
• Identified surface affinity and dissolution rate as critical FAs for characterizing nanomaterial behavior.
• Illustrated the use of FAs to predict bioaccumulation and toxicity for silver nanoparticles in *Caenorhabditis elegans*.

Main Results:

• Functional assays provide a semi-empirical approach to link nanomaterial properties with potential impacts.
• Reference systems are proposed for applying FAs and benchmarking results across different experimental complexities.
• Demonstrated the utility of FAs in predicting bioaccumulation and toxicity for both initial and aged silver nanoparticles.

Conclusions:

• A functional assay-based framework is proposed to improve nanoEHS research strategies.
• FAs, particularly surface affinity and dissolution rate, are crucial for understanding nanomaterial behavior and risk.
• This approach offers a more robust method for predicting environmental fate, effects, bioaccumulation, and toxicity of nanomaterials.