A novel model integrated concentration addition with independent action for the prediction of toxicity of multi-component mixture.

Concentration addition (CA) and independent action (IA) have been used to describe the mixture of components having similar and dissimilar mode of action (MOA), respectively. Environmentally relevant mixture does, however, not follow the strictly similar or dissimilar MOA. A novel model, which integrated CA with IA based on the multiple linear regression (ICIM), was proposed for predicting the toxicity of noninteractive mixture. The predictive power of the ICIM model was validated by data set 1 including 13 mixtures of nine components and data set 2 including six mixtures of six components. For data set 1, ten uniform design with fixed concentration ratio ray (UDCR) mixtures was used as a training set to build an ICIM model, and the model was used to predict the toxicity of the test set consisting of three equivalent-effect concentration ratio (EECR) mixtures. For data set 2, the ICIM model based on four UDCR mixtures was used to predict the remaining two EECR mixtures. It is concluded that the ICIM model shows a strong predictive power for the mixture toxicities in the two data sets, and its prediction is better than CA and IA where the two models deviate from the concentration-response data of the mixtures. Thus, ICIM model is a powerful tool to evaluate and predict mixture toxicity, and maybe offer an important approach in risk assessment of mixture toxicity.