Computer-Based Prediction Models in Regulatory Toxicology
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The increasing regulatory safety demands for the submission and registration of chemicals, pesticides, or pharmaceuticals as well as tightening animal protection legislation have exacerbated the dilemma of regulatory toxicology, where on the one hand the required scientific contributions for the protection of workers, consumers, or patients are constantly augmented while on the other hand the number of experimental animal studies should be reduced.
One way to resolve this dilemma could be the use of computer-assisted systems to predict toxic effects. These so-called “in silico” tools have experienced improvements in their performance and predictive power over the past three decades. They are therefore able to contribute to hazard identification and risk assessment at least for some toxicological endpoints. However, knowledge of how these systems work, the importance of the underlying data quality, and their respective limitations are prerequisites for a sensible application.
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