SciRAPnano: a pragmatic and harmonized approach for quality evaluation of in vitro toxicity data to support risk assessment of nanomaterials

Front Toxicol. 2023 Nov 17:5:1319985. doi: 10.3389/ftox.2023.1319985. eCollection 2023.

Abstract

Large amounts of nanotoxicity data from alternative non-animal (in vitro) test methods have been generated, but there is a lack of harmonized quality evaluation approaches for these types of data. Tools for scientifically sound and structured evaluation of the reliability and relevance of in vitro toxicity data to effectively inform regulatory hazard assessment of nanomaterials (NMs), are needed. Here, we present the development of a pragmatic approach to facilitate such evaluation. The tool was developed based on the Science in Risk Assessment and Policy (SciRAP) tool currently applicable to quality evaluation of chemical toxicity studies. The approach taken to develop the tool, referred to as SciRAPnano, included refinement of the original SciRAP in vitro tool through implementation of identified NM-relevant criteria, and further refined based on a set of case studies involving evaluation of 11 studies investigating in vitro toxicity of nano-sized titanium dioxide. Parameters considered cover key physicochemical properties as well as assay-specific aspects that impact NM toxicity, including NM interference with test methods and NM transformation. The final SciRAPnano tool contains 38 criteria for reporting quality, 19 criteria for methodological quality, and 4 guidance items to evaluate relevance. The approach covers essential parameters for pragmatic and harmonized evaluation of NM in vitro toxicity studies and allows for structured use of in vitro data in regulatory hazard assessment of NMs, including transparency on data quality.

Keywords: data quality; in vitro toxicity testing; nanomaterials; relevance; reliability; risk assessment.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This research was funded by the Swedish Fund for Research without Animal Experiments (F2022-0003; PN).