1
|
Menz J, Götz ME, Gündel U, Gürtler R, Herrmann K, Hessel-Pras S, Kneuer C, Kolrep F, Nitzsche D, Pabel U, Sachse B, Schmeisser S, Schumacher DM, Schwerdtle T, Tralau T, Zellmer S, Schäfer B. Genotoxicity assessment: opportunities, challenges and perspectives for quantitative evaluations of dose-response data. Arch Toxicol 2023; 97:2303-2328. [PMID: 37402810 PMCID: PMC10404208 DOI: 10.1007/s00204-023-03553-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Accepted: 06/21/2023] [Indexed: 07/06/2023]
Abstract
Genotoxicity data are mainly interpreted in a qualitative way, which typically results in a binary classification of chemical entities. For more than a decade, there has been a discussion about the need for a paradigm shift in this regard. Here, we review current opportunities, challenges and perspectives for a more quantitative approach to genotoxicity assessment. Currently discussed opportunities mainly include the determination of a reference point (e.g., a benchmark dose) from genetic toxicity dose-response data, followed by calculation of a margin of exposure (MOE) or derivation of a health-based guidance value (HBGV). In addition to new opportunities, major challenges emerge with the quantitative interpretation of genotoxicity data. These are mainly rooted in the limited capability of standard in vivo genotoxicity testing methods to detect different types of genetic damage in multiple target tissues and the unknown quantitative relationships between measurable genotoxic effects and the probability of experiencing an adverse health outcome. In addition, with respect to DNA-reactive mutagens, the question arises whether the widely accepted assumption of a non-threshold dose-response relationship is at all compatible with the derivation of a HBGV. Therefore, at present, any quantitative genotoxicity assessment approach remains to be evaluated case-by-case. The quantitative interpretation of in vivo genotoxicity data for prioritization purposes, e.g., in connection with the MOE approach, could be seen as a promising opportunity for routine application. However, additional research is needed to assess whether it is possible to define a genotoxicity-derived MOE that can be considered indicative of a low level of concern. To further advance quantitative genotoxicity assessment, priority should be given to the development of new experimental methods to provide a deeper mechanistic understanding and a more comprehensive basis for the analysis of dose-response relationships.
Collapse
Affiliation(s)
- Jakob Menz
- Department of Food Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Str. 8-10, 10589, Berlin, Germany.
| | - Mario E Götz
- Department of Food Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Str. 8-10, 10589, Berlin, Germany
| | - Ulrike Gündel
- Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Str. 8-10, 10589, Berlin, Germany
| | - Rainer Gürtler
- Department of Food Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Str. 8-10, 10589, Berlin, Germany
| | - Kristin Herrmann
- Department of Pesticides Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Str. 8-10, 10589, Berlin, Germany
| | - Stefanie Hessel-Pras
- Department of Food Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Str. 8-10, 10589, Berlin, Germany
| | - Carsten Kneuer
- Department of Pesticides Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Str. 8-10, 10589, Berlin, Germany
| | - Franziska Kolrep
- Department of Safety in the Food Chain, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Str. 8-10, 10589, Berlin, Germany
| | - Dana Nitzsche
- Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Str. 8-10, 10589, Berlin, Germany
| | - Ulrike Pabel
- Department of Safety in the Food Chain, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Str. 8-10, 10589, Berlin, Germany
| | - Benjamin Sachse
- Department of Food Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Str. 8-10, 10589, Berlin, Germany
| | - Sebastian Schmeisser
- Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Str. 8-10, 10589, Berlin, Germany
| | - David M Schumacher
- Department of Safety in the Food Chain, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Str. 8-10, 10589, Berlin, Germany
| | - Tanja Schwerdtle
- German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Str. 8-10, 10589, Berlin, Germany
| | - Tewes Tralau
- Department of Pesticides Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Str. 8-10, 10589, Berlin, Germany
| | - Sebastian Zellmer
- Department of Chemical and Product Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Str. 8-10, 10589, Berlin, Germany
| | - Bernd Schäfer
- Department of Food Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Str. 8-10, 10589, Berlin, Germany
| |
Collapse
|
2
|
Högberg J, Järnberg J. Approaches for the setting of occupational exposure limits (OELs) for carcinogens. Crit Rev Toxicol 2023:1-37. [PMID: 37366107 DOI: 10.1080/10408444.2023.2218887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 05/12/2023] [Accepted: 05/22/2023] [Indexed: 06/28/2023]
Abstract
This article addresses issues of importance for occupational exposure limits (OELs) and chemical carcinogens with a focus on non-threshold carcinogens. It comprises scientific as well as regulatory issues. It is an overview, not a comprehensive review. A central topic is mechanistic research and insights, and its implications for cancer risk assessment. Alongside scientific advancements, the approaches of hazard identification and qualitative and quantitative risk assessment have developed over the years. The key steps in a quantitative risk assessment are outlined, with special attention given to the dose-response assessment and the derivation of an OEL using risk calculations or default assessment factors. The work procedures of several bodies performing cancer hazard identifications and quantitative risk assessments, as well as regulatory procedures to derive OELs for non-threshold carcinogens, are presented. Non-threshold carcinogens for which the European Union (EU) introduced binding OELs in 2017-2019 serve as illustrations together with some currently used strategies in the EU and elsewhere. Available knowledge supports the derivation of health-based OELs (Hb-OELs) for non-threshold carcinogens, and the use of a risk-based approach with low-dose linear extrapolation (linear non-threshold, LNT) as the default for non-threshold carcinogens. However, there is a need to develop methods that allow recent years' advances in cancer research to be used for improving risk estimates. It is recommended that defined risk levels (terminology and numerical values) are harmonised, and that both collective and individual risks are considered and clearly communicated. Socioeconomic aspects should be dealt with transparently and separated from the scientific health risk assessment.
Collapse
Affiliation(s)
- Johan Högberg
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | | |
Collapse
|
3
|
More SJ, Bampidis V, Benford D, Bragard C, Halldorsson TI, Hernández‐Jerez AF, Bennekou SH, Koutsoumanis K, Lambré C, Machera K, Mennes W, Mullins E, Nielsen SS, Schrenk D, Turck D, Younes M, Aerts M, Edler L, Sand S, Wright M, Binaglia M, Bottex B, Abrahantes JC, Schlatter J. Guidance on the use of the benchmark dose approach in risk assessment. EFSA J 2022; 20:e07584. [PMID: 36304832 PMCID: PMC9593753 DOI: 10.2903/j.efsa.2022.7584] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022] Open
Abstract
The Scientific Committee (SC) reconfirms that the benchmark dose (BMD) approach is a scientifically more advanced method compared to the no-observed-adverse-effect-level (NOAEL) approach for deriving a Reference Point (RP). The major change compared to the previous Guidance (EFSA SC, 2017) concerns the Section 2.5, in which a change from the frequentist to the Bayesian paradigm is recommended. In the former, uncertainty about the unknown parameters is measured by confidence and significance levels, interpreted and calibrated under hypothetical repetition, while probability distributions are attached to the unknown parameters in the Bayesian approach, and the notion of probability is extended to reflect uncertainty of knowledge. In addition, the Bayesian approach can mimic a learning process and reflects the accumulation of knowledge over time. Model averaging is again recommended as the preferred method for estimating the BMD and calculating its credible interval. The set of default models to be used for BMD analysis has been reviewed and amended so that there is now a single set of models for quantal and continuous data. The flow chart guiding the reader step-by-step when performing a BMD analysis has also been updated, and a chapter comparing the frequentist to the Bayesian paradigm inserted. Also, when using Bayesian BMD modelling, the lower bound (BMDL) is to be considered as potential RP, and the upper bound (BMDU) is needed for establishing the BMDU/BMDL ratio reflecting the uncertainty in the BMD estimate. This updated guidance does not call for a general re-evaluation of previous assessments where the NOAEL approach or the BMD approach as described in the 2009 or 2017 Guidance was used, in particular when the exposure is clearly lower (e.g. more than one order of magnitude) than the health-based guidance value. Finally, the SC firmly reiterates to reconsider test guidelines given the wide application of the BMD approach.
Collapse
|
4
|
Krewski D, Saunders-Hastings P, Baan RA, Barton-Maclaren TS, Browne P, Chiu WA, Gwinn M, Hartung T, Kraft AD, Lam J, Lewis RJ, Sanaa M, Morgan RL, Paoli G, Rhomberg L, Rooney A, Sand S, Schünemann HJ, Straif K, Thayer KA, Tsaioun K. Development of an Evidence-Based Risk Assessment Framework. ALTEX 2022; 39:667-693. [PMID: 36098377 PMCID: PMC10080579 DOI: 10.14573/altex.2004041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Accepted: 06/29/2021] [Indexed: 11/23/2022]
Abstract
Assessment of potential human health risks associated with environmental and other agents requires careful evaluation of all available and relevant evidence for the agent of interest, including both data-rich and data-poor agents. With the advent of new approach methodologies in toxicological risk assessment, guidance on integrating evidence from mul-tiple evidence streams is needed to ensure that all available data is given due consideration in both qualitative and quantitative risk assessment. The present report summarizes the discussions among academic, government, and private sector participants from North America and Europe in an international workshop convened to explore the development of an evidence-based risk assessment framework, taking into account all available evidence in an appropriate manner in order to arrive at the best possible characterization of potential human health risks and associated uncertainty. Although consensus among workshop participants was not a specific goal, there was general agreement on the key consider-ations involved in evidence-based risk assessment incorporating 21st century science into human health risk assessment. These considerations have been embodied into an overarching prototype framework for evidence integration that will be explored in more depth in a follow-up meeting.
Collapse
Affiliation(s)
- Daniel Krewski
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada
- McLaughlin Centre for Population Health Risk Assessment, University of Ottawa, Ottawa, Canada
- Risk Sciences International, Ottawa, Canada
| | | | - Robert A. Baan
- The IARC Monographs Programme, International Agency for Research on Cancer, Lyon, France (retired)
| | | | - Patience Browne
- Organization for Economic Cooperation and Development, Paris, France
| | - Weihsueh A. Chiu
- Department of Veterinary Physiology and Pharmacology, Texas A&M University, College Station, Texas, USA
| | - Maureen Gwinn
- Office of Research and Development, US Environmental Protection Agency, Research Triangle Park, USA
| | - Thomas Hartung
- Chair for Evidence-based Toxicology and Center for Alternatives to Animal Testing (CAAT), Johns Hopkins University, Baltimore, USA
- CAAT-Europe, University of Konstanz, Konstanz, Germany
| | - Andrew D. Kraft
- Center for Public Health and Environmental Assessment, Chemical & Pollutant Assessment Division, US EPA, DC, USA
| | - Juleen Lam
- Department of Public Health at California State University, East Bay, USA
| | - R. Jeffrey Lewis
- ExxonMobil Biomedical Sciences, Annandale, New Jersey, USA (retired)
| | - Moez Sanaa
- Agence Nationale Sécurité Sanitaire Alimentaire Nationale, Paris, France
| | | | - Greg Paoli
- Risk Sciences International, Ottawa, Canada
| | | | - Andrew Rooney
- Integrative Health Assessments Branch, National Toxicology Program, US National Institute of Environmental Health Sciences, Research Triangle Park, USA
| | - Salomon Sand
- Department of Risk and Benefit Assessment, Swedish Food Agency, Uppsala, Sweden
| | | | - Kurt Straif
- The IARC Monographs Programme, International Agency for Research on Cancer, Lyon, France (retired)
| | - Kristina A Thayer
- Center for Public Health and Environmental Assessment, Chemical & Pollutant Assessment Division, US EPA, NC, USA
| | - Katya Tsaioun
- Boston College, Chestnut Hill, MA, USA ISGlobal, Barcelona, Spain
| |
Collapse
|
5
|
Tang X, Chen Y, Zhu X, Miao Y, Wang D, Zhang J, Li R, Zhang L, Chen J. Alternariol monomethyl ether toxicity and genotoxicity in male Sprague-Dawley rats: 28-Day in vivo multi-endpoint assessment. MUTATION RESEARCH. GENETIC TOXICOLOGY AND ENVIRONMENTAL MUTAGENESIS 2022; 873:503435. [PMID: 35094809 DOI: 10.1016/j.mrgentox.2021.503435] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Revised: 11/29/2021] [Accepted: 11/30/2021] [Indexed: 01/08/2023]
Abstract
Alternariol monomethyl ether (AME), a typical Alternaria toxin, has often been detected in grains. We have measured the general toxicity and genotoxicity of AME with a 28-day multi-endpoint (Pig-a assay + in vivo micronucleus [MN] test + comet assay) platform. Male Sprague-Dawley rats were administered AME (1.84, 3.67, or 7.35 μg/kg body weight/day), N-Ethyl-N-nitrosourea (40 mg/kg body weight/day), or corn oil by gavage for 28 consecutive days. Another group (AME-high-dose + recovery) was maintained for a further 14 days after the end of the AME administration. Hematology and serum biochemistry results suggested that AME might compromise the immune system. The histopathology results indicated that AME can cause liver (inflammatory cell infiltration, steatosis, and edema), kidney (renal glomerular atrophy), and spleen (white pulp atrophy) damage. The genotoxicity results showed that AME can induce gene mutations, chromosome breakage, and DNA damage, but the effects were diminished after the recovery period. According to point-of-departure analysis (BMDL10), the risk to the population of exposure to AME cannot be ignored and further assessment is needed.
Collapse
Affiliation(s)
- Xinyao Tang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China; Food Safety Monitoring and Risk Assessment Key Laboratory of Sichuan Province, Chengdu, Sichuan, China.
| | - Yiyi Chen
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China; Chenghua Center for Disease Control and Prevention, Chengdu, Sichuan, China.
| | - Xia Zhu
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China; Food Safety Monitoring and Risk Assessment Key Laboratory of Sichuan Province, Chengdu, Sichuan, China.
| | - Yeqiu Miao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China; Food Safety Monitoring and Risk Assessment Key Laboratory of Sichuan Province, Chengdu, Sichuan, China.
| | - Dongxia Wang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China; Food Safety Monitoring and Risk Assessment Key Laboratory of Sichuan Province, Chengdu, Sichuan, China.
| | - Jing Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China; Food Safety Monitoring and Risk Assessment Key Laboratory of Sichuan Province, Chengdu, Sichuan, China.
| | - Ruirui Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China; Food Safety Monitoring and Risk Assessment Key Laboratory of Sichuan Province, Chengdu, Sichuan, China.
| | - Lishi Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China; Food Safety Monitoring and Risk Assessment Key Laboratory of Sichuan Province, Chengdu, Sichuan, China.
| | - Jinyao Chen
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China; Food Safety Monitoring and Risk Assessment Key Laboratory of Sichuan Province, Chengdu, Sichuan, China.
| |
Collapse
|
6
|
Lindqvist R, Langerholc T, Ranta J, Hirvonen T, Sand S. A common approach for ranking of microbiological and chemical hazards in foods based on risk assessment - useful but is it possible? Crit Rev Food Sci Nutr 2019; 60:3461-3474. [PMID: 31760761 DOI: 10.1080/10408398.2019.1693957] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
This article compares and contrasts microbial and chemical risk assessment methodologies in order to evaluate the potential for a common framework for ranking of risk of chemical and microbiological hazards, and developments needed for such a framework. An overview of microbial (MRA) and chemical (CRA) risk assessment is presented and important differences are highlighted. Two microbiological and two chemical hazard-food combinations were ranked based on both a margin of exposure and a risk assessment approach. The comparisons illustrated that it is possible to rank chemical and microbiological hazard-food combinations with traditional approaches from each domain and indicated that the rank order but not the absolute measures is similar using either approach. Including severity in the assessment using DALY reduced differences between hazards and affected the outcome more than which approach was used. Ranking frameworks should include assessment of uncertainty as an integral part of the ranking, and be based on assessment of risk, not safety, and expressed in a common health metric such as disease burden. Necessary simplifications to address data gaps can involve the use of default scenarios. Challenges include comparisons of case-based vs. non-case-based health-endpoints, e.g. biomarker concentration, and integration of the severity of health effects into ranking.
Collapse
Affiliation(s)
- R Lindqvist
- Department of Risk Benefit Assessment, Swedish Food Agency, Uppsala, Sweden
| | - T Langerholc
- Faculty of Agriculture and Life Sciences, University of Maribor, Maribor, Slovenia
| | - J Ranta
- Risk Assessment Research Unit, Finnish Food Safety Authority, Evira, Helsinki, Finland
| | - T Hirvonen
- Risk Assessment Research Unit, Finnish Food Safety Authority, Evira, Helsinki, Finland
| | - S Sand
- Department of Risk Benefit Assessment, Swedish Food Agency, Uppsala, Sweden
| |
Collapse
|
7
|
Sand S, Lindqvist R, von Rosen D, Ilbäck NG. Dose-Related Severity Sequence, and Risk-Based Integration, of Chemically Induced Health Effects. Toxicol Sci 2018; 165:74-89. [PMID: 29897534 PMCID: PMC6190798 DOI: 10.1093/toxsci/kfy124] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
Risk assessment of chemical hazards is typically based on single critical health effects. This work aims to expand the current approach by characterizing the dose-related sequence of the development of multiple (lower- to higher-order) toxicological health effects caused by a chemical. To this end a "reference point profile" is defined as the relation between benchmark doses for considered health effects, and a standardized severity score determined for these effects. For a given dose of a chemical or mixture the probability for exceeding the reference point profile, thereby provoking lower- to higher-order effects, can be assessed. The overall impact at the same dose can also be derived by integrating contributions across all health effects following severity-weighting. In its generalized form the new impact metric relates to the probability of response for the most severe health effects. Reference points (points of departure) corresponding to defined levels of response can also be estimated. The proposed concept, which is evaluated for dioxin-like chemicals, provides an alternative for characterizing the low-dose region below the reference point for a severe effect like cancer. The shape and variability of the reference point profile add new dimensions to risk assessment, which for example extends the characterization of chemical potency, and the concept of acceptable effect sizes for individual health effects. Based on the present data the method shows high stability at low doses/responses, and is also robust to differences in severity categorization of effects. In conclusion, the novel method proposed enables risk-based integration of multiple dose-related health effects. It provides a first step towards a more comprehensive characterization of chemical toxicity, and suggests a potential for improved low-dose risk assessment.
Collapse
Affiliation(s)
- Salomon Sand
- Department of Risk-Benefit Assessment, Swedish National Food Agency, SE-75126 Uppsala, Sweden
| | - Roland Lindqvist
- Department of Risk-Benefit Assessment, Swedish National Food Agency, SE-75126 Uppsala, Sweden
| | - Dietrich von Rosen
- Department of Energy and Technology, Swedish University of Agricultural Sciences, SE-75007 Uppsala, Sweden
- Department of Mathematics, Linköping University, SE-581 83 Linköping, Sweden
| | - Nils-Gunnar Ilbäck
- Department of Risk-Benefit Assessment, Swedish National Food Agency, SE-75126 Uppsala, Sweden
| |
Collapse
|
8
|
Haber LT, Dourson ML, Allen BC, Hertzberg RC, Parker A, Vincent MJ, Maier A, Boobis AR. Benchmark dose (BMD) modeling: current practice, issues, and challenges. Crit Rev Toxicol 2018. [PMID: 29516780 DOI: 10.1080/10408444.2018.1430121] [Citation(s) in RCA: 113] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Benchmark dose (BMD) modeling is now the state of the science for determining the point of departure for risk assessment. Key advantages include the fact that the modeling takes account of all of the data for a particular effect from a particular experiment, increased consistency, and better accounting for statistical uncertainties. Despite these strong advantages, disagreements remain as to several specific aspects of the modeling, including differences in the recommendations of the US Environmental Protection Agency (US EPA) and the European Food Safety Authority (EFSA). Differences exist in the choice of the benchmark response (BMR) for continuous data, the use of unrestricted models, and the mathematical models used; these can lead to differences in the final BMDL. It is important to take confidence in the model into account in choosing the BMDL, rather than simply choosing the lowest value. The field is moving in the direction of model averaging, which will avoid many of the challenges of choosing a single best model when the underlying biology does not suggest one, but additional research would be useful into methods of incorporating biological considerations into the weights used in the averaging. Additional research is also needed regarding the interplay between the BMR and the UF to ensure appropriate use for studies supporting a lower BMR than default values, such as for epidemiology data. Addressing these issues will aid in harmonizing methods and moving the field of risk assessment forward.
Collapse
Affiliation(s)
- Lynne T Haber
- a Risk Science Center , University of Cincinnati , Cincinnati , OH , USA
| | - Michael L Dourson
- a Risk Science Center , University of Cincinnati , Cincinnati , OH , USA
| | | | - Richard C Hertzberg
- c Department of Environmental Health , Emory University , Atlanta , GA , USA
| | - Ann Parker
- a Risk Science Center , University of Cincinnati , Cincinnati , OH , USA
| | - Melissa J Vincent
- a Risk Science Center , University of Cincinnati , Cincinnati , OH , USA
| | - Andrew Maier
- a Risk Science Center , University of Cincinnati , Cincinnati , OH , USA
| | | |
Collapse
|
9
|
Cartus A, Schrenk D. Current methods in risk assessment of genotoxic chemicals. Food Chem Toxicol 2017; 106:574-582. [DOI: 10.1016/j.fct.2016.09.012] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2016] [Revised: 09/06/2016] [Accepted: 09/08/2016] [Indexed: 12/15/2022]
|
10
|
Sand S, Parham F, Portier CJ, Tice RR, Krewski D. Comparison of Points of Departure for Health Risk Assessment Based on High-Throughput Screening Data. ENVIRONMENTAL HEALTH PERSPECTIVES 2017; 125:623-633. [PMID: 27384688 PMCID: PMC5381992 DOI: 10.1289/ehp408] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2016] [Revised: 04/25/2016] [Accepted: 06/13/2016] [Indexed: 05/05/2023]
Abstract
BACKGROUND The National Research Council's vision for toxicity testing in the 21st century anticipates that points of departure (PODs) for establishing human exposure guidelines in future risk assessments will increasingly be based on in vitro high-throughput screening (HTS) data. OBJECTIVES The aim of this study was to compare different PODs for HTS data. Specifically, benchmark doses (BMDs) were compared to the signal-to-noise crossover dose (SNCD), which has been suggested as the lowest dose applicable as a POD. METHODS Hill models were fit to > 10,000 in vitro concentration-response curves, obtained for > 1,400 chemicals tested as part of the U.S. Tox21 Phase I effort. BMDs and lower confidence limits on the BMDs (BMDLs) corresponding to extra effects (i.e., changes in response relative to the maximum response) of 5%, 10%, 20%, 30%, and 40% were estimated for > 8,000 curves, along with BMDs and BMDLs corresponding to additional effects (i.e., absolute changes in response) of 5%, 10%, 15%, 20%, and 25%. The SNCD, defined as the dose where the ratio between the additional effect and the difference between the upper and lower bounds of the two-sided 90% confidence interval on absolute effect was 1, 0.67, and 0.5, respectively, was also calculated and compared with the BMDLs. RESULTS The BMDL40, BMDL25, and BMDL18, defined in terms of extra effect, corresponded to the SNCD1.0, SNCD0.67, and SNCD0.5, respectively, at the median. Similarly, the BMDL25, BMDL17, and BMDL13, defined in terms of additional effect, corresponded to the SNCD1.0, SNCD0.67, and SNCD0.5, respectively, at the median. CONCLUSIONS The SNCD may serve as a reference level that guides the determination of standardized BMDs for risk assessment based on HTS concentration-response data. The SNCD may also have application as a POD for low-dose extrapolation.
Collapse
Affiliation(s)
- Salomon Sand
- Department of Risk Benefit Assessment, National Food Agency, Uppsala, Sweden
- McLaughlin Centre for Population Health Risk Assessment, University of Ottawa, Ottawa, Ontario, Canada
- Address correspondence to S. Sand, National Food Agency, P.O. Box 622, SE-751 26 Uppsala, Sweden. Phone: 46-18-17-5335. E-mail:
| | - Fred Parham
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA
| | | | - Raymond R. Tice
- Division of the National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA
| | - Daniel Krewski
- McLaughlin Centre for Population Health Risk Assessment, University of Ottawa, Ottawa, Ontario, Canada
- Risk Sciences International, Ottawa, Ontario, Canada
| |
Collapse
|
11
|
Dose–response relationship of temozolomide, determined by the Pig-a, comet, and micronucleus assay. Arch Toxicol 2017; 91:2443-2453. [DOI: 10.1007/s00204-016-1923-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2016] [Accepted: 12/20/2016] [Indexed: 11/25/2022]
|
12
|
Milton B, Farrell PJ, Birkett N, Krewski D. Modeling U-Shaped Exposure-Response Relationships for Agents that Demonstrate Toxicity Due to Both Excess and Deficiency. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2017; 37:265-279. [PMID: 27043736 DOI: 10.1111/risa.12603] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Essential elements such as copper and manganese may demonstrate U-shaped exposure-response relationships due to toxic responses occurring as a result of both excess and deficiency. Previous work on a copper toxicity database employed CatReg, a software program for categorical regression developed by the U.S. Environmental Protection Agency, to model copper excess and deficiency exposure-response relationships separately. This analysis involved the use of a severity scoring system to place diverse toxic responses on a common severity scale, thereby allowing their inclusion in the same CatReg model. In this article, we present methods for simultaneously fitting excess and deficiency data in the form of a single U-shaped exposure-response curve, the minimum of which occurs at the exposure level that minimizes the probability of an adverse outcome due to either excess or deficiency (or both). We also present a closed-form expression for the point at which the exposure-response curves for excess and deficiency cross, corresponding to the exposure level at which the risk of an adverse outcome due to excess is equal to that for deficiency. The application of these methods is illustrated using the same copper toxicity database noted above. The use of these methods permits the analysis of all available exposure-response data from multiple studies expressing multiple endpoints due to both excess and deficiency. The exposure level corresponding to the minimum of this U-shaped curve, and the confidence limits around this exposure level, may be useful in establishing an acceptable range of exposures that minimize the overall risk associated with the agent of interest.
Collapse
Affiliation(s)
- Brittany Milton
- Carleton University, School of Mathematics and Statistics, Ottawa, Ontario, Canada
| | - Patrick J Farrell
- Carleton University, School of Mathematics and Statistics, Ottawa, Ontario, Canada
- RS McLaughlin Centre for Population Health Risk Assessment, University of Ottawa, Ottawa, Ontario, Canada
| | - Nicholas Birkett
- School of Epidemiology, Public Health and Population Medicine, Ottawa, Ontario, Canada
- RS McLaughlin Centre for Population Health Risk Assessment, University of Ottawa, Ottawa, Ontario, Canada
| | - Daniel Krewski
- Carleton University, School of Mathematics and Statistics, Ottawa, Ontario, Canada
- School of Epidemiology, Public Health and Population Medicine, Ottawa, Ontario, Canada
- RS McLaughlin Centre for Population Health Risk Assessment, University of Ottawa, Ottawa, Ontario, Canada
| |
Collapse
|
13
|
Hardy A, Benford D, Halldorsson T, Jeger MJ, Knutsen KH, More S, Mortensen A, Naegeli H, Noteborn H, Ockleford C, Ricci A, Rychen G, 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. Update: use of the benchmark dose approach in risk assessment. EFSA J 2017; 15:e04658. [PMID: 32625254 PMCID: PMC7009819 DOI: 10.2903/j.efsa.2017.4658] [Citation(s) in RCA: 180] [Impact Index Per Article: 25.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The Scientific Committee (SC) reconfirms that the benchmark dose (BMD) approach is a scientifically more advanced method compared to the NOAEL approach for deriving a Reference Point (RP). Most of the modifications made to the SC guidance of 2009 concern the section providing guidance on how to apply the BMD approach. Model averaging is recommended as the preferred method for calculating the BMD confidence interval, while acknowledging that the respective tools are still under development and may not be easily accessible to all. Therefore, selecting or rejecting models is still considered as a suboptimal alternative. The set of default models to be used for BMD analysis has been reviewed, and the Akaike information criterion (AIC) has been introduced instead of the log-likelihood to characterise the goodness of fit of different mathematical models to a dose-response data set. A flowchart has also been inserted in this update to guide the reader step-by-step when performing a BMD analysis, as well as a chapter on the distributional part of dose-response models and a template for reporting a BMD analysis in a complete and transparent manner. Finally, it is recommended to always report the BMD confidence interval rather than the value of the BMD. The lower bound (BMDL) is needed as a potential RP, and the upper bound (BMDU) is needed for establishing the BMDU/BMDL per ratio reflecting the uncertainty in the BMD estimate. This updated guidance does not call for a general re-evaluation of previous assessments where the NOAEL approach or the BMD approach as described in the 2009 SC guidance was used, in particular when the exposure is clearly smaller (e.g. more than one order of magnitude) than the health-based guidance value. Finally, the SC firmly reiterates to reconsider test guidelines given the expected wide application of the BMD approach.
Collapse
|
14
|
Mattison DR, Milton B, Krewski D, Levy L, Dorman DC, Aggett PJ, Roels HA, Andersen ME, Karyakina NA, Shilnikova N, Ramoju S, McGough D. Severity scoring of manganese health effects for categorical regression. Neurotoxicology 2016; 58:203-216. [PMID: 27637608 DOI: 10.1016/j.neuro.2016.09.001] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2016] [Revised: 08/24/2016] [Accepted: 09/04/2016] [Indexed: 11/29/2022]
Abstract
Characterizing the U-shaped exposure response relationship for manganese (Mn) is necessary for estimating the risk of adverse health from Mn toxicity due to excess or deficiency. Categorical regression has emerged as a powerful tool for exposure-response analysis because of its ability to synthesize relevant information across multiple studies and species into a single integrated analysis of all relevant data. This paper documents the development of a database on Mn toxicity designed to support the application of categorical regression techniques. Specifically, we describe (i) the conduct of a systematic search of the literature on Mn toxicity to gather data appropriate for dose-response assessment; (ii) the establishment of inclusion/exclusion criteria for data to be included in the categorical regression modeling database; (iii) the development of a categorical severity scoring matrix for Mn health effects to permit the inclusion of diverse health outcomes in a single categorical regression analysis using the severity score as the outcome variable; and (iv) the convening of an international expert panel to both review the severity scoring matrix and assign severity scores to health outcomes observed in studies (including case reports, epidemiological investigations, and in vivo experimental studies) selected for inclusion in the categorical regression database. Exposure information including route, concentration, duration, health endpoint(s), and characteristics of the exposed population was abstracted from included studies and stored in a computerized manganese database (MnDB), providing a comprehensive repository of exposure-response information with the ability to support categorical regression modeling of oral exposure data.
Collapse
Affiliation(s)
- Donald R Mattison
- Risk Sciences International, 55 Metcalfe Street, Suite 700, K1P 6L5, Ottawa, Canada; R. Samuel McLaughlin Centre for Population Health Risk Assessment, Faculty of Medicine, University of Ottawa, 118-850 Peter Morand Drive, Canada.
| | - Brittany Milton
- Risk Sciences International, 55 Metcalfe Street, Suite 700, K1P 6L5, Ottawa, Canada
| | - Daniel Krewski
- Risk Sciences International, 55 Metcalfe Street, Suite 700, K1P 6L5, Ottawa, Canada; R. Samuel McLaughlin Centre for Population Health Risk Assessment, Faculty of Medicine, University of Ottawa, 118-850 Peter Morand Drive, Canada
| | - Len Levy
- Institute of Environment and Health, Cranfield University, College Road, Cranfield MK43 0AL, Bedfordshire, United Kingdom
| | - David C Dorman
- College of Veterinary Medicine, North Carolina State University, 1060 William Moore Drive, Raleigh, NC 27607, USA
| | - Peter J Aggett
- School of Medicine and Health, Lancaster University, Bailrigg, Lancaster, LA1 4YW, United Kingdom
| | - Harry A Roels
- Louvain Centre for Toxicology and Applied Pharmacology (LTAP), Université catholique de Louvain, Avenue Mounier 53.02, 1200 Brussels, Belgium
| | - Melvin E Andersen
- ScitoVation, 6 Davis Drive, PO Box 110566, Research Triangle Park, NC, 27709-2137, USA
| | - Nataliya A Karyakina
- Risk Sciences International, 55 Metcalfe Street, Suite 700, K1P 6L5, Ottawa, Canada; R. Samuel McLaughlin Centre for Population Health Risk Assessment, Faculty of Medicine, University of Ottawa, 118-850 Peter Morand Drive, Canada
| | - Natalia Shilnikova
- Risk Sciences International, 55 Metcalfe Street, Suite 700, K1P 6L5, Ottawa, Canada; R. Samuel McLaughlin Centre for Population Health Risk Assessment, Faculty of Medicine, University of Ottawa, 118-850 Peter Morand Drive, Canada
| | - Siva Ramoju
- Risk Sciences International, 55 Metcalfe Street, Suite 700, K1P 6L5, Ottawa, Canada
| | - Doreen McGough
- International Manganese Institute, 17 rue Duphot, 75001 Paris, France.
| |
Collapse
|
15
|
Zeller A, Tang L, Dertinger SD, Funk J, Duran-Pacheco G, Guérard M. A proposal for a novel rationale for critical effect size in dose–response analysis based on a multi-endpointin vivostudy with methyl methanesulfonate. Mutagenesis 2015; 31:239-53. [DOI: 10.1093/mutage/gev077] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
|
16
|
Bourdon-Lacombe JA, Moffat ID, Deveau M, Husain M, Auerbach S, Krewski D, Thomas RS, Bushel PR, Williams A, Yauk CL. Technical guide for applications of gene expression profiling in human health risk assessment of environmental chemicals. Regul Toxicol Pharmacol 2015; 72:292-309. [PMID: 25944780 DOI: 10.1016/j.yrtph.2015.04.010] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2015] [Revised: 04/10/2015] [Accepted: 04/13/2015] [Indexed: 01/14/2023]
Abstract
Toxicogenomics promises to be an important part of future human health risk assessment of environmental chemicals. The application of gene expression profiles (e.g., for hazard identification, chemical prioritization, chemical grouping, mode of action discovery, and quantitative analysis of response) is growing in the literature, but their use in formal risk assessment by regulatory agencies is relatively infrequent. Although additional validations for specific applications are required, gene expression data can be of immediate use for increasing confidence in chemical evaluations. We believe that a primary reason for the current lack of integration is the limited practical guidance available for risk assessment specialists with limited experience in genomics. The present manuscript provides basic information on gene expression profiling, along with guidance on evaluating the quality of genomic experiments and data, and interpretation of results presented in the form of heat maps, pathway analyses and other common approaches. Moreover, potential ways to integrate information from gene expression experiments into current risk assessment are presented using published studies as examples. The primary objective of this work is to facilitate integration of gene expression data into human health risk assessments of environmental chemicals.
Collapse
Affiliation(s)
| | - Ivy D Moffat
- Water and Air Quality Bureau, Health Canada, Ottawa, ON, Canada.
| | - Michelle Deveau
- Water and Air Quality Bureau, Health Canada, Ottawa, ON, Canada
| | - Mainul Husain
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada
| | - Scott Auerbach
- Biomolecular Screening Branch, Division of the National Toxicology Program, National Institute of Environmental Health Sciences, Research Triangle Park, NC, United States
| | - Daniel Krewski
- McLaughlin Centre for Population Health Risk Assessment, University of Ottawa, Ottawa, ON, Canada
| | - Russell S Thomas
- National Centre for Computational Toxicology, U.S. Environmental Protection Agency, Research Triangle Park, NC, United States
| | - Pierre R Bushel
- Biostatistics and Computational Biology Branch, Division of Intramural Research, National Institute of Environmental Health Sciences, Research Triangle Park, NC, United States
| | - Andrew Williams
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada
| | - Carole L Yauk
- Environmental Health Science and Research Bureau, Health Canada, Ottawa, ON, Canada
| |
Collapse
|
17
|
Developing tools for defining and establishing pathways of toxicity. Arch Toxicol 2015; 89:809-12. [PMID: 25851822 PMCID: PMC4396705 DOI: 10.1007/s00204-015-1512-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2015] [Accepted: 03/19/2015] [Indexed: 11/21/2022]
|
18
|
Scinicariello F, Portier C. A simple procedure for estimating pseudo risk ratios from exposure to non-carcinogenic chemical mixtures. Arch Toxicol 2015; 90:513-23. [PMID: 25667015 DOI: 10.1007/s00204-015-1467-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2014] [Accepted: 01/13/2015] [Indexed: 10/24/2022]
Abstract
Non-cancer risk assessment traditionally assumes a threshold of effect, below which there is a negligible risk of an adverse effect. The Agency for Toxic Substances and Disease Registry derives health-based guidance values known as Minimal Risk Levels (MRLs) as estimates of the toxicity threshold for non-carcinogens. Although the definition of an MRL, as well as EPA reference dose values (RfD and RfC), is a level that corresponds to "negligible risk," they represent daily exposure doses or concentrations, not risks. We present a new approach to calculate the risk at exposure to specific doses for chemical mixtures, the assumption in this approach is to assign de minimis risk at the MRL. The assigned risk enables the estimation of parameters in an exponential model, providing a complete dose-response curve for each compound from the chosen point of departure to zero. We estimated parameters for 27 chemicals. The value of k, which determines the shape of the dose-response curve, was moderately insensitive to the choice of the risk at the MRL. The approach presented here allows for the calculation of a risk from a single substance or the combined risk from multiple chemical exposures in a community. The methodology is applicable from point of departure data derived from quantal data, such as data from benchmark dose analyses or from data that can be transformed into probabilities, such as lowest-observed-adverse-effect level. The individual risks are used to calculate risk ratios that can facilitate comparison and cost-benefit analyses of environmental contamination control strategies.
Collapse
Affiliation(s)
- Franco Scinicariello
- National Center for Environmental Health/Agency for Toxic Substances and Disease Registry, Centers for Disease Control and Prevention, 4770 Buford Hwy, MS F57, Atlanta, GA, 30341, USA.
| | - Christopher Portier
- National Center for Environmental Health/Agency for Toxic Substances and Disease Registry, Centers for Disease Control and Prevention, 4770 Buford Hwy, MS F57, Atlanta, GA, 30341, USA.
| |
Collapse
|
19
|
Wheeler M, Park RM, Bailer AJ, Whittaker C. Historical Context and Recent Advances in Exposure-Response Estimation for Deriving Occupational Exposure Limits. JOURNAL OF OCCUPATIONAL AND ENVIRONMENTAL HYGIENE 2015; 12 Suppl 1:S7-17. [PMID: 26252067 PMCID: PMC4685605 DOI: 10.1080/15459624.2015.1076934] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2015] [Revised: 07/16/2015] [Accepted: 07/23/2015] [Indexed: 05/22/2023]
Abstract
Virtually no occupational exposure standards specify the level of risk for the prescribed exposure, and most occupational exposure limits are not based on quantitative risk assessment (QRA) at all. Wider use of QRA could improve understanding of occupational risks while increasing focus on identifying exposure concentrations conferring acceptably low levels of risk to workers. Exposure-response modeling between a defined hazard and the biological response of interest is necessary to provide a quantitative foundation for risk-based occupational exposure limits; and there has been considerable work devoted to establishing reliable methods quantifying the exposure-response relationship including methods of extrapolation below the observed responses. We review several exposure-response modeling methods available for QRA, and demonstrate their utility with simulated data sets.
Collapse
Affiliation(s)
- M.W. Wheeler
- Centers for Disease Control and Prevention (CDC), National Institute for Occupational Safety and Health (NIOSH), Education and Information Division, Cincinnati, Ohio
- Address correspondence to Matthew W. Wheeler, Centers for Disease Control and Prevention (CDC), National Institute for Occupational Safety and Health (NIOSH), Education and Information Division, 1090 Tusculum Ave, MS C-15, Cincinnati, Ohio45226. E-mail:
| | - R. M. Park
- Centers for Disease Control and Prevention (CDC), National Institute for Occupational Safety and Health (NIOSH), Education and Information Division, Cincinnati, Ohio
| | - A. J. Bailer
- Department of Statistics, Miami University, Oxford, Ohio
| | - C. Whittaker
- Centers for Disease Control and Prevention (CDC), National Institute for Occupational Safety and Health (NIOSH), Education and Information Division, Cincinnati, Ohio
| |
Collapse
|
20
|
Maxim L. A systematic review of methods of uncertainty analysis and their applications in the assessment of chemical exposures, effects, and risks. INTERNATIONAL JOURNAL OF ENVIRONMENTAL HEALTH RESEARCH 2014; 25:522-550. [PMID: 25409755 DOI: 10.1080/09603123.2014.980782] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/26/2014] [Accepted: 09/23/2014] [Indexed: 06/04/2023]
Abstract
Methods of uncertainty analysis are being included increasingly in regulatory chemical risk assessment. Although best practices have been established by several safety agencies in Europe and the United States, they exist only in the grey literature - there has been no comprehensive analysis of the scientific, peer-reviewed literature on these methods. We therefore conducted a systematic review of the recent peer-reviewed literature (2007-2013) on uncertainty analysis relevant to chemical risks. The main objective was to determine whether current methods are robust enough for regulatory use, because the methods used to protect public health must meet the most stringent scientific standards. Based on 297 papers, we concluded that the peer-reviewed literature is much more critical about the disadvantages of those methods, compared to the grey literature. Furthermore, uncertainty analyses can be influenced significantly by subjective expert judgment. As a suggested improvement, we developed guidelines for transparent reporting of uncertainty assessment results.
Collapse
Affiliation(s)
- Laura Maxim
- a Institut des Sciences de la Communication (UMS 3665), CNRS (Centre National de la Recherche Scientifique) , Université Paris Sorbonne, UPMC (Université Pierre et Marie Curie) , Paris , France
| |
Collapse
|
21
|
Krewski D, Westphal M, Andersen ME, Paoli GM, Chiu WA, Al-Zoughool M, Croteau MC, Burgoon LD, Cote I. A framework for the next generation of risk science. ENVIRONMENTAL HEALTH PERSPECTIVES 2014; 122:796-805. [PMID: 24727499 PMCID: PMC4123023 DOI: 10.1289/ehp.1307260] [Citation(s) in RCA: 70] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2013] [Accepted: 04/09/2014] [Indexed: 05/19/2023]
Abstract
OBJECTIVES In 2011, the U.S. Environmental Protection Agency initiated the NexGen project to develop a new paradigm for the next generation of risk science. METHODS The NexGen framework was built on three cornerstones: the availability of new data on toxicity pathways made possible by fundamental advances in basic biology and toxicological science, the incorporation of a population health perspective that recognizes that most adverse health outcomes involve multiple determinants, and a renewed focus on new risk assessment methodologies designed to better inform risk management decision making. RESULTS The NexGen framework has three phases. Phase I (objectives) focuses on problem formulation and scoping, taking into account the risk context and the range of available risk management decision-making options. Phase II (risk assessment) seeks to identify critical toxicity pathway perturbations using new toxicity testing tools and technologies, and to better characterize risks and uncertainties using advanced risk assessment methodologies. Phase III (risk management) involves the development of evidence-based population health risk management strategies of a regulatory, economic, advisory, community-based, or technological nature, using sound principles of risk management decision making. CONCLUSIONS Analysis of a series of case study prototypes indicated that many aspects of the NexGen framework are already beginning to be adopted in practice.
Collapse
Affiliation(s)
- Daniel Krewski
- McLaughlin Centre for Population Health Risk Assessment, University of Ottawa, Ottawa, Ontario, Canada
| | | | | | | | | | | | | | | | | |
Collapse
|
22
|
Peng J, Robichaud M, Alsubie AQ. Simultaneous confidence bands for low-dose risk estimation with quantal data. Biom J 2014; 57:27-38. [DOI: 10.1002/bimj.201300250] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2013] [Revised: 04/04/2014] [Accepted: 04/05/2014] [Indexed: 12/18/2022]
Affiliation(s)
- Jianan Peng
- Department of Mathematics and Statistics; Acadia University; Wolfville NS B4P 2R6 Canada
| | - Megan Robichaud
- Department of Mathematics and Statistics; Acadia University; Wolfville NS B4P 2R6 Canada
| | - Abdelaziz Q. Alsubie
- Department of Mathematics and Statistics; Acadia University; Wolfville NS B4P 2R6 Canada
| |
Collapse
|
23
|
Wignall JA, Shapiro AJ, Wright FA, Woodruff TJ, Chiu WA, Guyton KZ, Rusyn I. Standardizing benchmark dose calculations to improve science-based decisions in human health assessments. ENVIRONMENTAL HEALTH PERSPECTIVES 2014; 122:499-505. [PMID: 24569956 PMCID: PMC4014768 DOI: 10.1289/ehp.1307539] [Citation(s) in RCA: 72] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2013] [Accepted: 02/24/2014] [Indexed: 05/20/2023]
Abstract
BACKGROUND Benchmark dose (BMD) modeling computes the dose associated with a prespecified response level. While offering advantages over traditional points of departure (PODs), such as no-observed-adverse-effect-levels (NOAELs), BMD methods have lacked consistency and transparency in application, interpretation, and reporting in human health assessments of chemicals. OBJECTIVES We aimed to apply a standardized process for conducting BMD modeling to reduce inconsistencies in model fitting and selection. METHODS We evaluated 880 dose-response data sets for 352 environmental chemicals with existing human health assessments. We calculated benchmark doses and their lower limits [10% extra risk, or change in the mean equal to 1 SD (BMD/L10/1SD)] for each chemical in a standardized way with prespecified criteria for model fit acceptance. We identified study design features associated with acceptable model fits. RESULTS We derived values for 255 (72%) of the chemicals. Batch-calculated BMD/L10/1SD values were significantly and highly correlated (R2 of 0.95 and 0.83, respectively, n = 42) with PODs previously used in human health assessments, with values similar to reported NOAELs. Specifically, the median ratio of BMDs10/1SD:NOAELs was 1.96, and the median ratio of BMDLs10/1SD:NOAELs was 0.89. We also observed a significant trend of increasing model viability with increasing number of dose groups. CONCLUSIONS BMD/L10/1SD values can be calculated in a standardized way for use in health assessments on a large number of chemicals and critical effects. This facilitates the exploration of health effects across multiple studies of a given chemical or, when chemicals need to be compared, providing greater transparency and efficiency than current approaches.
Collapse
|
24
|
Kuiper RM, Gerhard D, Hothorn LA. Identification of the Minimum Effective Dose for Normally Distributed Endpoints Using a Model Selection Approach. Stat Biopharm Res 2014. [DOI: 10.1080/19466315.2013.847384] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
|
25
|
Parfett C, Williams A, Zheng J, Zhou G. Gene batteries and synexpression groups applied in a multivariate statistical approach to dose–response analysis of toxicogenomic data. Regul Toxicol Pharmacol 2013; 67:63-74. [DOI: 10.1016/j.yrtph.2013.06.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2013] [Accepted: 06/26/2013] [Indexed: 12/28/2022]
|
26
|
Dourson M, Becker RA, Haber LT, Pottenger LH, Bredfeldt T, Fenner-Crisp PA. Advancing human health risk assessment: integrating recent advisory committee recommendations. Crit Rev Toxicol 2013; 43:467-92. [PMID: 23844697 PMCID: PMC3725687 DOI: 10.3109/10408444.2013.807223] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2012] [Revised: 05/16/2013] [Accepted: 05/17/2013] [Indexed: 11/13/2022]
Abstract
Over the last dozen years, many national and international expert groups have considered specific improvements to risk assessment. Many of their stated recommendations are mutually supportive, but others appear conflicting, at least in an initial assessment. This review identifies areas of consensus and difference and recommends a practical, biology-centric course forward, which includes: (1) incorporating a clear problem formulation at the outset of the assessment with a level of complexity that is appropriate for informing the relevant risk management decision; (2) using toxicokinetics and toxicodynamic information to develop Chemical Specific Adjustment Factors (CSAF); (3) using mode of action (MOA) information and an understanding of the relevant biology as the key, central organizing principle for the risk assessment; (4) integrating MOA information into dose-response assessments using existing guidelines for non-cancer and cancer assessments; (5) using a tiered, iterative approach developed by the World Health Organization/International Programme on Chemical Safety (WHO/IPCS) as a scientifically robust, fit-for-purpose approach for risk assessment of combined exposures (chemical mixtures); and (6) applying all of this knowledge to enable interpretation of human biomonitoring data in a risk context. While scientifically based defaults will remain important and useful when data on CSAF or MOA to refine an assessment are absent or insufficient, assessments should always strive to use these data. The use of available 21st century knowledge of biological processes, clinical findings, chemical interactions, and dose-response at the molecular, cellular, organ and organism levels will minimize the need for extrapolation and reliance on default approaches.
Collapse
Affiliation(s)
- Michael Dourson
- Toxicology Excellence for Risk Assessment, Cincinnati, OH, USA.
| | | | | | | | | | | |
Collapse
|
27
|
Abramsson-Zetterberg L, Carlsson R, Sand S. The use of immunomagnetic separation of erythrocytes in the in vivo flow cytometer-based micronucleus assay. MUTATION RESEARCH-GENETIC TOXICOLOGY AND ENVIRONMENTAL MUTAGENESIS 2013; 752:8-13. [DOI: 10.1016/j.mrgentox.2012.12.010] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2012] [Revised: 10/27/2012] [Accepted: 12/15/2012] [Indexed: 11/16/2022]
|
28
|
Kalantari F, Bergkvist C, Berglund M, Fattore E, Glynn A, Håkansson H, Sand S. Establishment of the cumulative margin of exposure for a group of polychlorinated biphenyl (PCB) congeners using an improved approach that accounts for both variability and uncertainty. Regul Toxicol Pharmacol 2013; 65:325-33. [DOI: 10.1016/j.yrtph.2013.01.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2012] [Revised: 01/15/2013] [Accepted: 01/17/2013] [Indexed: 02/05/2023]
|
29
|
Davis M, Boekelheide K, Boverhof DR, Eichenbaum G, Hartung T, Holsapple MP, Jones TW, Richard AM, Watkins PB. The new revolution in toxicology: The good, the bad, and the ugly. Ann N Y Acad Sci 2013; 1278:11-24. [DOI: 10.1111/nyas.12086] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Myrtle Davis
- Toxicology and Pharmacology Branch, Developmental Therapeutics Program Division of Cancer Treatment and Diagnosis; The National Cancer Institute, National Institutes of Health; Bethesda; Maryland
| | - Kim Boekelheide
- Deparment of Pathology and Laboratory Medicine; Brown University; Providence; Rhode Island
| | - Darrell R. Boverhof
- Toxicology and Environmental Research and Consulting; The Dow Chemical Company; Midland; Michigan
| | - Gary Eichenbaum
- Department of Drug Safety Science; Johnson & Johnson Pharmaceutical R&D, LLC; Raritan; NJ
| | - Thomas Hartung
- Department of Environmental Health Sciences. Johns Hopkins Bloomberg School of Public Health; Baltimore; Maryland
| | | | - Thomas W. Jones
- Department of Toxicology and Pathology; Elil Lilly and Company; Indianapolis; Indiana
| | - Ann M. Richard
- National Center for Computational Toxicology; Environmental Protection Agency, Research Triangle Park; North Carolina
| | - Paul B. Watkins
- Institute for Drug Safety Sciences; Hamner University of North Carolina, Research Triangle Park; North Carolina
| |
Collapse
|
30
|
Chiu WA, Guyton KZ, Hogan K, Jinot J. Approaches to human health risk assessment based on the signal-to-noise crossover dose. ENVIRONMENTAL HEALTH PERSPECTIVES 2012; 120:a264-a265. [PMID: 22760062 PMCID: PMC3404684 DOI: 10.1289/ehp.1205212r] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
|
31
|
Chiu WA, Guyton KZ, Hogan K, Jinot J. Approaches to human health risk assessment based on the signal-to-noise crossover dose. ENVIRONMENTAL HEALTH PERSPECTIVES 2012; 120:a264; author reply a264-5. [PMID: 22760062 PMCID: PMC3404683 DOI: 10.1289/ehp.1205212] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2023]
|