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

Andrey A ToropovAlla P ToropovaGianluca SelvestrelDiego BadernaEmilio Benfenati
Published in: SAR and QSAR in environmental research (2020)
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 r 2 = 0.52 + 0.62 + 0.76/3 = 0.63 and for validation set n = 35, r 2 = 0.73.
Keyphrases
  • virtual reality
  • healthcare
  • oxidative stress
  • high resolution
  • monte carlo
  • quality improvement
  • neural network