Status Quo in Data Availability and Predictive Models of Nano-Mixture Toxicity.

ABSTRACT: Co-exposure of nanomaterials and chemicals can cause mixture toxicity effects to living organisms. Predictive models might help to reduce the intensive laboratory experiments required for determining the toxicity of the mixtures. Previously, concentration addition (CA), independent action (IA), and quantitative structure-activity relationship (QSAR)-based models were successfully applied to mixtures of organic chemicals. However, there were few studies concerning predictive models for toxicity of nano-mixtures before June 2020. Previous reviews provided comprehensive knowledge of computational models and mechanisms for chemical mixture toxicity. There is a gap in the reviewing of datasets and predictive models, which might cause obstacles in the toxicity assessment of nano-mixtures by usin

SUBMITTER: Trinh TX 

PROVIDER: S-EPMC7826902 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature