title: In silico approaches to predicting cancer potency for risk assessment of genotoxic impurities in drug substances.
abstract: The current risk assessment approach for addressing the safety of very small concentrations of genotoxic impurities (GTIs) in drug substances is the threshold of toxicological concern (TTC). The TTC is based on several conservative assumptions because of the uncertainty associated with deriving an excess cancer risk when no carcinogenicity data are available for the impurity. It is a default approach derived from a distribution of carcinogens and does not take into account the properties of a specific chemical. The purpose of the study was to use in silico tools to predict the cancer potency (TD(50)) of a compound based on its structure. Structure activity relationship (SAR) models (classification/regression) were developed from the carcinogenicity potency database using MultiCASE and VISDOM. The MultiCASE classification models allowed the prediction of carcinogenic potency class, while the VISDOM regression models predicted a numerical TD(50). A step-wise approach is proposed to calculate predicted numerical TD(50) values for compounds categorized as not potent. This approach for non-potent compounds can be used to establish safe levels greater than the TTC for GTIs in a drug substance.
authors.affiliation: Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN 46285, USA. jpbercu@lilly.com
authors.forename: Joel P
authors.initials: JP
authors.lastname: Bercu
authors.forename: Stuart M
authors.initials: SM
authors.lastname: Morton
authors.forename: J Thom
authors.initials: JT
authors.lastname: Deahl
authors.forename: Vijay K
authors.initials: VK
authors.lastname: Gombar
authors.forename: Courtney M
authors.initials: CM
authors.lastname: Callis
authors.forename: Robert B L
authors.initials: RB
authors.lastname: van Lier
mesh_terms: D000818:Animals; D016208:Databases, Factual; D004340:Drug Contamination; D005544:Forecasting; D051379:Mice; D008962:Models, Theoretical; D009153:Mutagens / Q000633:toxicity*; D009369:Neoplasms / Q000139:chemically induced*; D004364:Pharmaceutical Preparations / Q000737:chemistry / Q000145:classification / Q000592:standards; D051381:Rats; D018570:Risk Assessment; D012984:Software; D013329:Structure-Activity Relationship
chemical_list: D009153:Mutagens; D004364:Pharmaceutical Preparations