A survey of the Predictive Toxicology Challenge 2000-2001.
BACKGROUND
The Predictive Toxicology Challenge (PTC) was initiated to stimulate the development of advanced techniques for predictive toxicology models. The goal of this challenge was to compare different approaches for the prediction of rodent carcinogenicity, based on the experimental results of the US National Toxicology Program (NTP).


RESULTS
111 sets of predictions for 185 compounds have been evaluated on quantitative and qualitative scales to select the most predictive models and those with the highest toxicological relevance. The accuracy of the submitted predictions was between 25 and 79 %. An evaluation of the most accurate models by toxicological experts showed, that it is still hard for domain experts to interpret the submitted models and to put them into relation with toxicological knowledge.


BACKGROUND
PTC details and data can be found at: http://www.predictive-toxicology.org/ptc/.
Helma
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Machine Learning Lab, University Freiburg, D-79110 Freiburg, Germany. helma@informatik.uni-freiburg.de
Kramer
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D000818:Animals; D015197:Carcinogenicity Tests / Q000379:methods*; D002273:Carcinogens / Q000737:chemistry* / Q000633:toxicity*; D003625:Data Collection; D016208:Databases, Factual; D004781:Environmental Exposure / Q000009:adverse effects; D006078:Government Programs / Q000458:organization & administration; D051379:Mice; D008954:Models, Biological; D009369:Neoplasms / Q000139:chemically induced*; D051381:Rats; D018570:Risk Assessment / Q000379:methods*; D013329:Structure-Activity Relationship; D014116:Toxicology / Q000379:methods*; D014481:United States
D002273:Carcinogens