Skip to main content
SpringerLink
Log in

Benchmark Dose Approach in Regulatory Toxicology

  • Living reference work entry
  • First Online:
Regulatory Toxicology

  • 52 Accesses

Abstract

The Benchmark-Dose (BMD) approach aims at determining an exposure level/dose corresponding to a predefined change in response, the Benchmark Response (BMR), usually defined over background using all available dose–response (DR) information by fitting mathematical models to the dose–response data. The statistical confidence interval of the BMD (BMD-CI) accounts for the statistical uncertainty and the lower (one-sided) confidence limit, denoted BMDL, is used as reference point (RP) or point-of-departure (PoD) for the characterization of the risk of hazardous compounds replacing the no-observed-adverse-effect level (NOAEL) when sufficient DR data are available. Concept, scope of application, prerequisites for conduct, and key check points of the application of the BMD approach are presented and guidance is given for regulatory practice. The use of the BMD-CI for establishing a Health Based Guidance Value (HBGV) or a Margin of Exposure (MoE) is outlined.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

References

  • Abt E, Rodricks JV, Levy JI, Zeise L, Burke TA (2010) Science and decisions: advancing risk assessment. Risk Anal 30:1028–1036

    Article  Google Scholar 

  • Barlow SM, Dybing E, Edler L, Eisenbrand G, Kroes R, van den Brandt PA (2002) Food Safety in Europe (FOSIE): risk assessment of chemicals in food and diet. Food Chem Toxicol 40(2/3):137–428

    Google Scholar 

  • Crump KS (1984) A new method for determining allowable daily intakes. Fundam Appl Toxicol 4:854–871

    Article  CAS  Google Scholar 

  • Crump KS (1995) Calculation of benchmark doses for continuous data. Risk Anal 15:75–90

    Google Scholar 

  • Crump KS, Chen C, Louis T (2010) The future use of in vitro data in risk assessment to set human exposure standards: challenging problems and familiar solutions. Environ Health Perspect 118:1350–1354. https://doi.org/10.1289/ehp.1001931

    Article  PubMed  PubMed Central  Google Scholar 

  • Davis JA, Gift JS, Jay Zhao Q (2010) Introduction to benchmark dose methods and U.S. EPA’s benchmark dose software (BMDS) version 2.1.1. Toxicol Appl Pharmacol 254:181–191

    Article  Google Scholar 

  • Dourson ML, Hertzberg RC, Hartung R, Blackburn K (1985) Novel approaches for the estimation of acceptable daily intake. Toxicol Ind Health 1:23–41

    Article  CAS  Google Scholar 

  • Edler L, Poirier K, Dourson M, Kleiner J, Mileson B, Nordmann H, Renwick A, Slob W, Walton K, Würtzen G (2002) Mathematical modelling and quantitative methods. Food Chem Toxicol 40:283–326

    Article  CAS  Google Scholar 

  • Edler L, Hart A, Greaves P, Carthew P, Coulet M, Boobis A, Williams GM, Smith B (2014) 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. Food Chem Toxicol 70:264–289. https://doi.org/10.1016/j.fct.2013.10.030

    Article  CAS  PubMed  Google Scholar 

  • EFSA (2005) Opinion of the Scientific Committee on a request from EFSA related to a harmonised approach for risk assessment of substances which are both genotoxic and carcinogenic. EFSA J 3(10):282. 33pp. https://doi.org/10.2903/j.efsa.2005.282

    Article  Google Scholar 

  • EFSA (2009) Use of the benchmark dose approach in risk assessment. Guidance of the Scientific Committee. EFSA J 7(6):1150. 72pp. https://doi.org/10.2903/j.efsa.2009.1150

    Article  Google Scholar 

  • EFSA (2011) Use of BMDS and PROAST software packages by EFSA Scientific Panels and Units for applying the Benchmark Dose (BMD) approach in risk assessment. EN-113. p 190. First published 14 February 2011. https://doi.org/10.2903/sp.efsa.2011.EN-113

  • EFSA (2013) Scientific opinion on the risk for public and animal health related to the presence of sterigmatocystin in food and feed. EFSA J 11(6):3254. https://doi.org/10.2903/j.efsa.2013.3254

    Article  Google Scholar 

  • EFSA, EFSA CONTAM Panel (EFSA Panel on Contaminants in the Food Chain), Knutsen HK, Alexander J, Barregard L, Bignami M, Brüschweiler B, Ceccatelli S, Cottrill B, Dinovi M, Grasl-Kraupp B, Hogstrand C, Hoogenboom LR, Nebbia CS, Oswald IP, Petersen A, Rose M, Roudot A-C, Schwerdtle T, Vleminckx C, Vollmer G, Wallace H, De Saeger S, Eriksen GS, Farmer P, Fremy J-M, Gong YY, Meyer K, Naegeli H, Parent-Massin D, Rietjens I, van Egmond H, Altieri A, Eskola M, Gergelova P, Ramos-Bordajandi L, Benkova B, Dörr B, Gkrillas A, Gustavsson N, van Manen M, Edler L (2017a) Scientific opinion on the risks to human and animal health related to the presence of deoxynivalenol and its acetylated and modified forms in food and feed. EFSA J 15(9):4718. 345 pp. https://doi.org/10.2903/j.efsa.2017.4718

    Article  CAS  Google Scholar 

  • EFSA, EFSA European Food Safety Authority Scientific Committee, Hardy A, Benford D, Halldorsson T, Jeger MJ, Knutsen KH, More S, Mortensen A, Naegeli H, Netborn H, Ockleford C, Ricci A, Rychen S, Silano V, Solecki R, Turck D, Aerts M, Bodin L, Davis A, Edler L, Gundert-Remy U, Sand S, Slob W, Bottex B, Abrahantes JC, Marques DC, Kass G, Schlatter JR (2017b) Update guidance on the use of the benchmark dose approach in risk assessment. EFSA J 15(1):4658. 41pp. https://doi.org/10.2903/j.efsa.2017.4658

    Article  Google Scholar 

  • EFSA, EFSA European Food Safety Authority Scientific Committee, Benford D, Halldorsson T, Jeger MJ, Knutsen HK, More S, Naegeli H, Noteborn H, Ockleford C, Ricci A, Rychen G, Schlatter JR, Silano V, Solecki R, Turck D, Younes M, Craig P, Hart A, Von Goetz N, Koutsoumanis K, Mortensen A, Ossendorp B, Martino L, Merten C, Mosbach-Schulz O, Hardy A (2018) Guidance on uncertainty analysis in scientific assessments. EFSA J 16(1):5123. 39 pp. https://doi.org/10.2903/j.efsa.2018.5123

    Article  Google Scholar 

  • Falk Filipsson A, Sand S, Nilsson J (2003) The benchmark dose method – review of available models, and recommendations for application in health risk assessment. Crit Rev Toxicol 33:505–542. https://doi.org/10.1080/10408440390242360

    Article  CAS  Google Scholar 

  • FAO/WHO (2009) Principles and methods for the risk assessment of chemicals in food. Geneva: World Health Organization (Environmental Health Criteria 240). WHO Press, Geneva. https://www.who.int/publications/i/item/9789241572408

  • FAO/WHO (2017) Evaluation of certain contaminants in food, 83rd report of the joint FAO/WHO Expert Committee on Food Additives. WHO technical report series 1002. ISBN 978-92-4-121007-7

    Google Scholar 

  • Gaylor DW, Slikker W Jr (1990) Risk assessment for neurotoxic effects. Neurotoxicology 11:211–218

    CAS  PubMed  Google Scholar 

  • Herz-Piccioto I (1995) Epidemiology and quantitative risk assessment: a bridge from science to policy. Am J Public Health 85:484–490

    Article  Google Scholar 

  • Klimisch H-J, Andreae M, Tillmann U (1997) A systematic approach for evaluating the quality of experimental toxicological and ecotoxicological data. Regul Toxicol Pharmacol 25:1–5

    Article  CAS  Google Scholar 

  • Long AS, Wills JW, Krolak D, Guo M, Dertinger SD, Arlt VM, White PA (2018) Benchmark dose analyses of multiple genetic data toxicity experiments permit robust, cross-tissue comparisons of MutaMouse responses to orally delivered benzo(a)pyrene. Arch Toxicol 92:967–982. https://doi.org/10.1007/s00204-017-2099-2

    Article  CAS  PubMed  Google Scholar 

  • Maekawa A, Kajiwara T, Odashima S, Kurata H (1979) Hepatic changes in male ACI/N rats on low dietary levels of sterigmatocystin. Gann 70:777–781

    CAS  PubMed  Google Scholar 

  • Murrell JA, Portier CJ, Morris RW (1998) Characterizing does-response I. Critical assessment of the benchmark dose concept. Risk Anal 18:13–26

    Article  CAS  Google Scholar 

  • NRC (1983) Risk assessment in the Federal Government: managing the process. National Research Council. National Academy of Sciences Press, Washington, DC

    Google Scholar 

  • PROAST (2020) PROAST Rijkinstituut voor Volksgesondheid an Milieu (RIVM)/National Institute for Public Health and the Environment. Ministry of Health Welfare and Sport, The Netherlands. https://www.rivm.nl/en/proast, https://proastweb.rvim.nl. Accessed 20 Apr 2020

  • Renwick A, Barlow SM, Herz-Picottio I, Boobis AR, Dybing E, Edler L, Eisenbrand G, Greig JB, Kleiner J, Lambe J, Müller DJG, Smith MR, Tritscher A, Tuijtelaars S, van den Brandt PA, Walker R, Kroes R (2003) Risk characterization of chemicals in food and diet. Food Chem Toxicol 41:1211–1271. https://doi.org/10.1016/S0278-6915(03)00064-4

    Article  CAS  PubMed  Google Scholar 

  • Schneider K, Schwarz M, Burkholder I, Kopp-Schneider A, Edler L, Kinsner-Ovaskainenc A, Hartung T, Hoffmann S (2009) “ToxRTool”, a new tool to assess the reliability of toxicological data. Toxicol Lett 189:138–144

    Article  CAS  Google Scholar 

  • Shao K, Shapiro AJ (2018) A web-based system for bayesian benchmark dose estimation. Environ Health Perspect 126(1):017002. https://doi.org/10.1289/EHP1289

    Article  PubMed  PubMed Central  Google Scholar 

  • Slob W (2002) Dose–response modelling of continuous endpoints. Toxicol Sci 66:298–312

    Article  CAS  Google Scholar 

  • Slob W (2017) A general theory of effect size, and its consequences for defining benchmark response (BMR) for continuous endpoints. Crit Rev Toxicol 47:343–361. https://doi.org/10.1080/104084444.2016.1241756

    Article  Google Scholar 

  • Steenland K, Deddens JA (2004) A practical guide to dose-response analyses and risk assessment in occupational epidemiology. Epidemiology 15:63–70. https://doi.org/10.1097/01.ede.0000100287.45004.e7

    Article  PubMed  Google Scholar 

  • U.S. EPA (1995) The use of the benchmark dose method in health risk assessment. Risk assessment forum.Washington, DC, EPA/630/R-94/007. http://www.epa.gov/raf/pubalpha.htm

  • U.S. EPA (2012) Benchmark dose technical guidance. Risk Assessment Forum, U.S. Environmental Protection Agency, Washington, DC, 20460, EPA/100/R-12/00. http://www.epa.gov/raf/publications/pdfs/benchmark_dose_guidance.pdf

  • U.S. EPA (2021) Benchmark dose software (BMDS). Version 3. https://www.epw.gov/bmds

  • van den Brandt P, Voorrips L, Hertz-Picciotto I, Shuker D, Boeing H, Speijers G, Guittard C, Kleiner J, Knowles M, Wolk A, Goldbohm A (2002) The contribution of epidemiology to risk assessment of chemicals in food and diet. Food Chem Toxicol 40:387–424

    Article  Google Scholar 

  • Varewyck M, Verbeke T (2017) Software for benchmark dose modelling. EFSA supporting publication 2017:EN-1170. 15pp. https://doi.org/10.2903/sp.efsa.2017.EN-1170

  • Wheeler MW, Bailer AJ (2007) Properties of model-averaged BMDLs: a study of model averaging in dichotomous response risk estimation. Risk Anal 27:659–670. https://doi.org/10.1111/j.1539-6924.2007.00920.x

    Article  PubMed  Google Scholar 

  • Wheeler MW, Bailer AJ (2008) Model averaging software for dichotomous dose- response risk estimation. J Stat Softw 26(5):1–15. https://doi.org/10.18637/jss.v026.i05

    Article  Google Scholar 

  • Wheeler MW, Bailer AJ (2009) Comparing model averaging with other model selection strategies for benchmark dose estimation. Environ Ecol Stat 16:37.51. https://doi.org/10.1007/s10651-007-0071-7

    Article  Google Scholar 

  • Yang L, Allen BC, Thomas RS (2007) BMDExpress: a software tool for the benchmark dose analyses of gemomic data. BMC Genomics 8:387. https://doi.org/10.1186/1471-2164-8-387

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Biostatistical Consultant, Am Schafgarten 27, Dudenhofen, Germany

    Lutz Edler

  2. Formerly: Division of Biostatistics, German Cancer Research Center-DKFZ, Heidelberg, Germany

    Lutz Edler

Authors
  1. Lutz Edler
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Universität München Inst. Pharmakologie und Toxikologie, München, Germany

    Franz-Xaver Reichl

  2. Tübingen, Germany

    Michael Schwenk

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer-Verlag GmbH Germany, part of Springer Nature

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Edler, L. (2021). Benchmark Dose Approach in Regulatory Toxicology. In: Reichl, FX., Schwenk, M. (eds) Regulatory Toxicology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36206-4_93-2

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-36206-4_93-2

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36206-4

  • Online ISBN: 978-3-642-36206-4

  • eBook Packages: Springer Reference Biomedicine and Life SciencesReference Module Biomedical and Life Sciences

Publish with us

Policies and ethics

Search

Navigation