How to formulate hypotheses and IATAs to support grouping and read-across of nanoforms

Manufacturing and functionalizing materials at the nanoscale has led to the generation of a whole array of nanoforms (NFs) of substances varying in size, morphology, and surface characteristics. Due to financial, time, and ethical considerations, testing every unique NF for adverse effects is virtually impossible. Use of hypothesis-driven grouping and read-across approaches, as supported by the GRACIOUS Framework, represents a promising alternative to case-by-case testing that will make the risk assessment process more efficient. Through application of appropriate grouping hypotheses, the Framework facilitates the assessment of similarity between NFs, thereby supporting grouping and read-across of information, minimizing the need for new testing, and aligning with the 3R principles of replacement, reduction, and refinement of animals in toxicology studies. For each grouping hypothesis an integrated approach to testing and assessment (IATA) guides the user in data gathering and acquisition to test the hypothesis, following a structured format to facilitate efficient decision-making. Here we present the template used to generate the GRACIOUS grouping hypotheses encompassing information relevant to “Lifecycle, environmental release, and human exposure”, “What they are: physicochemical characteristics”, “Where they go: environmental fate, uptake, and toxicokinetics”, and “What they do: human and environmental toxicity”. A summary of the template-derived hypotheses focusing on human health is provided, along with an overview of the IATAs generated by the GRACIOUS project. We discuss the application and flexibility of the template, providing the opportunity to expand the application of grouping and read-across in a logical, evidence-based manner to a wider range of NFs and substances.