Carcinogenicity prediction using the index of ideality of correlation

ABSTRACT

Carcinogenicity testing is necessary to protect human health and comply with regulations, but testing it with the traditionally used two-year rodent studies is time-consuming and expensive. In certain cases, such as for impurities, alternative methods may be convenient. Thus there is an urgent need for alternative approaches for reliable and robust assessments of carcinogenicity. The Monte Carlo technique with CORAL software is a tool to tackle this task for unknown compounds using available experimental data for a representative set of compounds. The models can be constructed with the simplified molecular input line entry system without additional physicochemical descriptors. We describe here a model based on a data set of 1167 substances. Matthew’s correlation coefficient values for calibration and validation sets are 0.747 and 0.577, respectively. Double bonds between carbon atoms and double bonds of oxygen atoms are the molecular features that indicate the carcinogenic potential of a compound.

KEYWORDS:

• SAR
• Monte Carlo method
• carcinogenicity
• index of ideality of correlation
• CORAL software

Acknowledgements

This work was supported by LIFE CONCERT (LIFE17 GIE/IT/000461).

Data availability

The data used in this work and the models developed are freely available: see supplementary material.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Supplementary material

Supplemental data for this article can be accessed at: https://doi.org/10.1080/1062936X.2022.2076736

Additional information

Funding

This work was supported by the LIFE-CONCERT contract [LIFE17 GIE/IT/000461].