title: Mechanistic applicability domains for nonanimal-based prediction of toxicological end points: general principles and application to reactive toxicity.
abstract: In light of new legislation (e.g., the REACH program in the European Union), several initiatives have recently emerged to increase acceptance of (quantitative) structure-activity relationships [(Q)SARs] to reduce reliance on animal (in vivo) testing. Among the principles for assessing the validity of (Q)SARs is the need for a defined domain of applicability, i.e., identification of the range of compounds for which the (Q)SAR can confidently be applied for purposes of toxicity prediction. Here, we attempt to develop a "natural" classification into applicability domains based on considering how a compound and the target organism between them "decide" on the nature and extent of the toxic effect. With particular emphasis on reactive toxicity, we present rules, based on organic reaction mechanistic principles, for classifying reactive toxicants into their appropriate mechanistic applicability domains.
authors.affiliation: SEAC, Unilever Colworth, Sharnbrook, Bedford, MK44 1LQ, England. nora.aptula@unilever.com
authors.forename: Aynur O
authors.initials: AO
authors.lastname: Aptula
authors.forename: David W
authors.initials: DW
authors.lastname: Roberts
mesh_terms: D000826:Animal Testing Alternatives; D023381:Endpoint Determination; D008962:Models, Theoretical; D015394:Molecular Structure; D009930:Organic Chemicals / Q000737:chemistry / Q000633:toxicity*; D011237:Predictive Value of Tests; D021281:Quantitative Structure-Activity Relationship; D012867:Skin / Q000187:drug effects; D018675:Toxicity Tests / Q000379:methods* / Q000592:standards
chemical_list: D009930:Organic Chemicals