title: Selection of appropriate tumour data sets for Benchmark Dose Modelling (BMD) and derivation of a Margin of Exposure (MoE) for substances that are genotoxic and carcinogenic: considerations of biological relevance of tumour type, data quality and uncertainty assessment.
abstract: This article addresses a number of concepts related to the selection and modelling of carcinogenicity data for the calculation of a Margin of Exposure. It follows up on the recommendations put forward by the International Life Sciences Institute - European branch in 2010 on the application of the Margin of Exposure (MoE) approach to substances in food that are genotoxic and carcinogenic. The aims are to provide practical guidance on the relevance of animal tumour data for human carcinogenic hazard assessment, appropriate selection of tumour data for Benchmark Dose Modelling, and approaches for dealing with the uncertainty associated with the selection of data for modelling and, consequently, the derived Point of Departure (PoD) used to calculate the MoE. Although the concepts outlined in this article are interrelated, the background expertise needed to address each topic varies. For instance, the expertise needed to make a judgement on biological relevance of a specific tumour type is clearly different to that needed to determine the statistical uncertainty around the data used for modelling a benchmark dose. As such, each topic is dealt with separately to allow those with specialised knowledge to target key areas of guidance and provide a more in-depth discussion on each subject for those new to the concept of the Margin of Exposure approach.
authors.affiliation: German Cancer Research Centre (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. Electronic address: edler@dkfz.de.
authors.forename: Lutz
authors.initials: L
authors.lastname: Edler
authors.affiliation: The Food and Environment Research Agency - FERA, Sand Hutton, YO41 1LZ York, United Kingdom. Electronic address: andy.hart@fera.gsi.gov.uk.
authors.forename: Andy
authors.initials: A
authors.lastname: Hart
authors.affiliation: Department of Cancer Studies and Molecular Medicine, University of Leicester, LE2 7LX Leicester, United Kingdom. Electronic address: pg29@leicester.ac.uk.
authors.forename: Peter
authors.initials: P
authors.lastname: Greaves
authors.affiliation: Unilever, Colworth House Sharnbrook, MK44 1LQ Bedfordshire, United Kingdom. Electronic address: philip.carthew@unilever.com.
authors.forename: Philip
authors.initials: P
authors.lastname: Carthew
authors.affiliation: Nestlé Research Centre, Vers-Chez-Les-Blanc, 1000 Lausanne, Switzerland. Electronic address: myriam.coulet@rdls.nestle.com.
authors.forename: Myriam
authors.initials: M
authors.lastname: Coulet
authors.affiliation: Imperial College, Hammersmith Campus, Ducane Road, W12 0NN London, United Kingdom. Electronic address: a.boobis@imperial.ac.uk.
authors.forename: Alan
authors.initials: A
authors.lastname: Boobis
authors.affiliation: New York Medical College, Basic Science Building, Room 413, Valhalla, NY 10595, United States. Electronic address: gary_williams@nymc.edu.
authors.forename: Gary M
authors.initials: GM
authors.lastname: Williams
authors.affiliation: Firmenich, Rue de la Bergere 7, 1217-Meyrin 2, Switzerland. Electronic address: benjamin.smith@firmenich.com.
authors.forename: Benjamin
authors.initials: B
authors.lastname: Smith
mesh_terms: D000818:Animals; D002273:Carcinogens / Q000633:toxicity*; D004249:DNA Damage / Q000187:drug effects*; D016208:Databases, Factual; D004195:Disease Models, Animal; D004305:Dose-Response Relationship, Drug; D015386:Hazardous Substances / Q000633:toxicity; D006801:Humans; D008954:Models, Biological; D015233:Models, Statistical; D009369:Neoplasms / Q000139:chemically induced / Q000473:pathology; D012015:Reference Standards; D012107:Research Design; D018570:Risk Assessment; D035501:Uncertainty
chemical_list: D002273:Carcinogens; D015386:Hazardous Substances
keywords: Benchmark Dose Modelling; Data selection; Genotoxic carcinogen; Margin of Exposure; Tumour relevance; Uncertainty assessment