Integrated approaches to testing and assessment for grouping nanomaterials following dermal exposure

Abstract

Exposure to different nanoforms (NFs) via the dermal route is expected in occupational and consumer settings and thus it is important to assess their dermal toxicity and the contribution of dermal exposure to systemic bioavailability. We have formulated four grouping hypotheses for dermal toxicity endpoints which allow NFs to be grouped to streamline and facilitate risk assessment. The grouping hypotheses are developed based on insight into how physicochemical properties of NFs (i.e. composition, dissolution kinetics, size, and flexibility) influence their fate and hazard following dermal exposure. Each hypothesis is accompanied by a tailored Integrated Approach to Testing and Assessment (IATA) that is structured as a decision tree and tiered testing strategies (TTS) for each relevant question (at decision nodes) that indicate what information is needed to guide the user to accept or reject the grouping hypothesis. To develop these hypotheses and IATAs, we gathered and analyzed existing information on skin irritation, skin sensitization, and dermal penetration of NFs from the published literature and performed experimental work to generate data on NF dissolution in sweat simulant fluids. We investigated the dissolution of zinc oxide and silicon dioxide NFs in different artificial sweat fluids, demonstrating the importance of using physiologically relevant conditions for dermal exposure. All existing and generated data informed the formulation of the grouping hypotheses, the IATAs, and the design of the TTS. It is expected that the presented IATAs will accelerate the NF risk assessment for dermal toxicity via the application of read-across.

Keywords:

• Artificial sweat fluids
• dissolution
• read across
• nanoform

Disclosure statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data availability statement

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Additional information

Funding

This work has received funding from the European Commission Horizon 2020, for the project Gracious (ID: 760840).