- Alternative methods are being explored to predict the toxicity of chemicals to reduce use of animals.
- Laboratory/Animal tests are costly in time and money
- • Cheminformatics (QSTR) presents a good alternative to animal testing
- Once the model is ready, predictions can be made quickly
Why Artificial Neural Network Ensemble (ANNE)?
- Toxicity prediction is a tough problem
- Multiple underlying mechanisms of action
- Datasets studied (e.g., rat LD50) are large and chemically diverse
- Multiple and wide variety of data sources
- Simple regression methods like MLR may prove insufficient
- Ensemble methods, such as ANNE and Random Forest, have proven to be robust enough to tackle this intensive task
- Five endpoints were provided to model
- Rat LD50 and “Very Toxic”, “Non Toxic”, “EPA Cat” & “GHS Cat”
- The labels in the four end-points are dependent upon rat LD50
Society of Toxicology 54th Annual Meeting and ToxExpo, March 22-26, 2015, San Diego, California
By Pankaj R. Daga, Michael Lawless, Marvin Waldman, Robert Fraczkiewicz, Robert D. Clark, John DiBella, and Michael B. Bolger