Prediction of No Observed Adverse Effect Concentration for inhalation toxicity using Monte Carlo approach

ABSTRACT

Ideal correlation is one variable model based on so-called optimal descriptors calculated with simplified molecular input-line entry systems (SMILES). The optimal descriptor is calculated according to the index of ideality of correlation, a new criterion of predictive potential of quantitative structure–property/activity relationships (QSPRs/QSARs). The aim of the present study was the building and estimation of models for inhalation toxicity as No Observed Adverse Effect Concentration (NOAEC) based on the OECD guidelines 413. Three random distributions into the training set and validation set were examined. In practice, a structured training set that contains active training set, passive training set and calibration set is used as the training set. The statistical characteristics of the best model for negative logarithm of NOAEC (pNOAEC) are for training set n = 108, average r² = 0.52 + 0.62 + 0.76/3 = 0.63 and for validation set n = 35, r² = 0.73.

KEYWORDS:

• NOAEC
• inhalation toxicity
• QSAR
• Monte Carlo method
• index of ideality of correlation
• CORAL software

Acknowledgements

The authors are grateful for the contribution of the project LIFE-CONCERT (LIFE17 GIE/IT/000461) and Optitox (OC/EFSA/SCER/2018/01) for financial support.

Author contributions

All the authors have read and approved the final manuscript. Authors have contributed equally to this work.

Disclosure statement

Authors declare that there are no conflicts of interest.

Additional information

Funding

This work was supported by the European Food Safety Authority [OC/EFSA/SCER/2018/01]; LIFE programme [LIFE17 GIE/IT/000461].