Prediction of the effect of formulation on the toxicity of chemicals

Pritesh Mistry, Daniel Neagu, Antonio Sanchez-Ruiz, Paul R. Trundle, Jonathan D. Vessey, John Paul Gosling

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


Two approaches for the prediction of which of two vehicles will result in lower toxicity for anticancer agents are presented. Machine-learning models are developed using decision tree, random forest and partial least squares methodologies and statistical evidence is presented to demonstrate that they represent valid models. Separately, a clustering method is presented that allows the ordering of vehicles by the toxicity they show for chemically-related compounds.
Original languageEnglish
Pages (from-to)42-53
Number of pages12
JournalToxicology Research
Issue number1
Early online date1 Nov 2016
Publication statusPublished - 1 Jan 2017
Externally publishedYes


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