A high throughput imaging database of toxicological effects of nanomaterials tested on HepaRG cells

Abstract

The large amount of existing nanomaterials demands rapid and reliable methods for testing their potential toxicological effect on human health, preferably by means of relevant in vitro techniques in order to reduce testing on animals. Combining high throughput workflows with automated high content imaging techniques allows deriving much more information from cell-based assays than the typical readouts (i.e. one measurement per well) with optical plate-readers. We present here a dataset including data based on a maximum of 14 different read outs (including viable cell count, cell membrane permeability, apoptotic cell death, mitochondrial membrane potential and steatosis) of the human hepatoma HepaRG cell line treated with a large set of nanomaterials, coatings and supernatants at different concentrations. The database, given its size, can be utilized in the development of in silico hazard assessment and prediction tools or can be combined with toxicity results from other in vitro test systems.

Abstract

Design Type(s)	compound treatment design • factorial design
Measurement Type(s)	toxicity
Technology Type(s)	high content screening
Factor Type(s)	concentration • coating • nanomaterial
Sample Characteristic(s)	Homo sapiens • Hepa-RG cell

Machine-accessible metadata file describing the reported data (ISA-Tab format)