title: Prediction of organ toxicity endpoints by QSAR modeling based on precise chemical-histopathology annotations.
abstract: The ability to accurately predict the toxicity of drug candidates from their chemical structure is critical for guiding experimental drug discovery toward safer medicines. Under the guidance of the MetaTox consortium (Thomson Reuters, CA, USA), which comprised toxicologists from the pharmaceutical industry and government agencies, we created a comprehensive ontology of toxic pathologies for 19 organs, classifying pathology terms by pathology type and functional organ substructure. By manual annotation of full-text research articles, the ontology was populated with chemical compounds causing specific histopathologies. Annotated compound-toxicity associations defined histologically from rat and mouse experiments were used to build quantitative structure-activity relationship models predicting subcategories of liver and kidney toxicity: liver necrosis, liver relative weight gain, liver lipid accumulation, nephron injury, kidney relative weight gain, and kidney necrosis. All models were validated using two independent test sets and demonstrated overall good performance: initial validation showed 0.80-0.96 sensitivity (correctly predicted toxic compounds) and 0.85-1.00 specificity (correctly predicted non-toxic compounds). Later validation against a test set of compounds newly added to the database in the 2 years following initial model generation showed 75-87% sensitivity and 60-78% specificity. General hepatotoxicity and nephrotoxicity models were less accurate, as expected for more complex endpoints.
authors.affiliation: Thomson Reuters, Carlsbad, CA 92008, USA.
authors.forename: Eugene
authors.initials: E
authors.lastname: Myshkin
authors.forename: Richard
authors.initials: R
authors.lastname: Brennan
authors.forename: Tatiana
authors.initials: T
authors.lastname: Khasanova
authors.forename: Tatiana
authors.initials: T
authors.lastname: Sitnik
authors.forename: Tatiana
authors.initials: T
authors.lastname: Serebriyskaya
authors.forename: Elena
authors.initials: E
authors.lastname: Litvinova
authors.forename: Alexey
authors.initials: A
authors.lastname: Guryanov
authors.forename: Yuri
authors.initials: Y
authors.lastname: Nikolsky
authors.forename: Tatiana
authors.initials: T
authors.lastname: Nikolskaya
authors.forename: Svetlana
authors.initials: S
authors.lastname: Bureeva
mesh_terms: D000818:Animals; D056486:Chemical and Drug Induced Liver Injury / Q000473:pathology*; D016208:Databases, Factual; D064420:Drug-Related Side Effects and Adverse Reactions / Q000473:pathology*; D007668:Kidney / Q000187:drug effects* / Q000473:pathology; D007674:Kidney Diseases / Q000139:chemically induced*; D008099:Liver / Q000187:drug effects* / Q000473:pathology; D051379:Mice; D008954:Models, Biological; D004364:Pharmaceutical Preparations / Q000737:chemistry*; D021281:Quantitative Structure-Activity Relationship; D051381:Rats
chemical_list: D004364:Pharmaceutical Preparations