By investigating 119 combination products, the present study aims to extend the assessment of compliance between mixture toxicity prediction and observation to a broader range of combinations of pesticides, and specifically to those combinations that are present in commercially applied pesticide mixtures.
The use of ECx values for the growth inhibition of Lemna and algae (a chronic endpoint) resulted in an overall good compliance between mixture toxicity prediction and observation.
The finding of few but large deviations between mixture toxicity prediction and observation for these commercial pesticide mixtures warns against simply extrapolating conclusions on uncertainty derived from data obtained in well-designed scientific studies to the regulatory risk assessment context as this may easily overestimate the reliability of decisions.
Compliance between the predicted mixture toxicity and the observed toxicity of the combination product was overall very good in the present study, with the majority of cases (53.6% in the first data set) showing a less than twofold deviation as long as the predictions were based on non-censored EC50 values.
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.
Quantitative applications such as QSARs, mixture toxicity, and regulatory chemical grouping can be compromised.
In the larger context of salmon conservation, a future priority will be to establish a quantitative connection between the mixture toxicity observed in this study and higher biological scales via effects on growth and survival.
The strong underrepresentation of fungicides in previous meta-studies [14, 15] may therefore at least partly explain their finding of a higher compliance between CA prediction and mixture toxicity observation.
Hence, the difference between the prediction concepts cannot explain much of the deviation between predicted and measured mixture toxicity observed here for the investigated combination products, which contained mostly two and at maximum four components (i.e., active substances).
The higher frequency and larger degree of deviation between predicted and observed mixture toxicity found in the present study in comparison to previous results [14, 15] suggests that the rather high degree of reliability of mixture toxicity predictions established so far in the scientific literature cannot be directly transferred to the regulatory context.
