title: Computational predictive programs (expert systems) in toxicology.
abstract: The increasing number of pollutants in the environment raises the problem of the toxicological risk evaluation of these chemicals. Several so called expert systems (ES) have been claimed to be able to predict toxicity of certain chemical structures. Different approaches are currently used for these ES, based on explicit rules derived from the knowledge of human experts that compiled lists of toxic moieties for instance in the case of programs called HazardExpert and DEREK or relying on statistical approaches, as in the CASE and TOPKAT programs. Here we describe and compare these and other intelligent computer programs because of their utility in obtaining at least a first rough indication of the potential toxic activity of chemicals.
authors.affiliation: Istituto di Ricerche Farmacologiche Mario Negri, Milano, Italy. benfenati@irfmn.mnegri.it
authors.forename: E
authors.initials: E
authors.lastname: Benfenati
authors.forename: G
authors.initials: G
authors.lastname: Gini
mesh_terms: D000818:Animals; D001185:Artificial Intelligence; D005103:Expert Systems; D006801:Humans; D012984:Software; D013329:Structure-Activity Relationship; D018675:Toxicity Tests / Q000379:methods*