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The Validation of Toxicological Prediction Models

The Validation of Toxicological Prediction Models An alternative method is shown to consist of two parts: the test system itself; and a prediction model for converting in vitro endpoints into predictions of in vivo toxicity. For the alternative method to be relevant and reliable, it is important that its prediction model component is of high predictive power and is sufficiently robust against sources of data variability. In other words, the prediction model must be subjected to criticism, leading successful models to the state of confirmation. It is shown that there are certain circumstances in which a new prediction model may be introduced without the necessity to generate new test system data. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Alternatives to Laboratory Animals SAGE

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References (7)

Publisher
SAGE
Copyright
© 1997 Fund for the Replacement of Animals in Medical Experiments
ISSN
0261-1929
eISSN
2632-3559
DOI
10.1177/026119299702500507
Publisher site
See Article on Publisher Site

Abstract

An alternative method is shown to consist of two parts: the test system itself; and a prediction model for converting in vitro endpoints into predictions of in vivo toxicity. For the alternative method to be relevant and reliable, it is important that its prediction model component is of high predictive power and is sufficiently robust against sources of data variability. In other words, the prediction model must be subjected to criticism, leading successful models to the state of confirmation. It is shown that there are certain circumstances in which a new prediction model may be introduced without the necessity to generate new test system data.

Journal

Alternatives to Laboratory AnimalsSAGE

Published: Sep 1, 1997

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