Abstract

Limited studies of quantitative toxicity-toxicity relationship (QTTR) modeling have been conducted to predict interspecies toxicity of engineered nanomaterials (ENMs) between aquatic test species. A meta-analysis of 66 publications providing acute toxicity data of silver nanoparticles (AgNPs) to daphnia and fish was performed, and the toxicity data, physicochemical properties, and experimental conditions were collected and curated. Based on Euclidean distance (ED) grouping, a meaningful correlation of logarithmic lethal concentrations between daphnia and fish was derived for bare (R2bare = 0.47) and coated AgNPs (R2coated = 0.48) when a distance of 10 was applied. The correlation of coated AgNPs was improved (R2coated = 0.55) by the inclusion of descriptors of the coating materials. The correlations were further improved by R2bare = 0.57 and R2coated = 0.81 after additionally considering particle size only, and by R2bare = 0.59 and R2coated = 0.92 after considering particle size and zeta potential simultaneously. The developed ED-based nano-QTTR model demonstrated that inclusion of the coating material descriptors and physicochemical properties improved the goodness-of-fit to predict interspecies aquatic toxicity of AgNPs between daphnia and fish. This study provides insight for future in silico research on QTTR model development in ENM toxicology.

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