TY - JOUR
T1 - Considerations for application of benchmark dose modeling in radiation research
T2 - workshop highlights
AU - Chauhan, Vinita
AU - Yu, Jihang
AU - Vuong, Ngoc
AU - Haber, Lynne T.
AU - Williams, Andrew
AU - Auerbach, Scott S.
AU - Beaton, Danielle
AU - Wang, Yi
AU - Stainforth, Robert
AU - Wilkins, Ruth C.
AU - Azzam, Edouard I.
AU - Richardson, Richard B.
AU - Khan, Md Gulam Musawwir
AU - Jadhav, Ashok
AU - Burtt, Julie J.
AU - Leblanc, Julie
AU - Randhawa, Kristi
AU - Tollefsen, Knut Erik
AU - Yauk, Carole L.
N1 - Funding Information:
This work was supported by Federal Nuclear Technology Initiative and Genomic research and development initiative. This work was supported by the Genomics Research and Development Initiative and the Atomic Energy of Canada Limited’s Federal Nuclear Science & Technology Program. The authors are grateful to Dr. Holly Laakso and Dr. Lindsay Beaton and Dr. Kathleen Cooke for critical review of the manuscript. The contents of this manuscript neither constitute, nor necessarily reflect the views of the institutions of the authors. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.
Funding Information:
This work was supported by the Genomics Research and Development Initiative and the Atomic Energy of Canada Limited’s Federal Nuclear Science & Technology Program. The authors are grateful to Dr. Holly Laakso and Dr. Lindsay Beaton and Dr. Kathleen Cooke for critical review of the manuscript. The contents of this manuscript neither constitute, nor necessarily reflect the views of the institutions of the authors. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.
Publisher Copyright:
© 2023 Copyright of the Crown in Canada. Health Canada. Published with license by Taylor & Francis Group, LLC.
PY - 2023
Y1 - 2023
N2 - Background: Exposure to different forms of ionizing radiation occurs in diverse occupational, medical, and environmental settings. Improving the accuracy of the estimated health risks associated with exposure is therefore, essential for protecting the public, particularly as it relates to chronic low dose exposures. A key aspect to understanding health risks is precise and accurate modeling of the dose-response relationship. Toward this vision, benchmark dose (BMD) modeling may be a suitable approach for consideration in the radiation field. BMD modeling is already extensively used for chemical hazard assessments and is considered statistically preferable to identifying low and no observed adverse effects levels. BMD modeling involves fitting mathematical models to dose-response data for a relevant biological endpoint and identifying a point of departure (the BMD, or its lower bound). Recent examples in chemical toxicology show that when applied to molecular endpoints (e.g. genotoxic and transcriptional endpoints), BMDs correlate to points of departure for more apical endpoints such as phenotypic changes (e.g. adverse effects) of interest to regulatory decisions. This use of BMD modeling may be valuable to explore in the radiation field, specifically in combination with adverse outcome pathways, and may facilitate better interpretation of relevant in vivo and in vitro dose-response data. To advance this application, a workshop was organized on June 3rd, 2022, in Ottawa, Ontario that brought together BMD experts in chemical toxicology and the radiation scientific community of researchers, regulators, and policy-makers. The workshop’s objective was to introduce radiation scientists to BMD modeling and its practical application using case examples from the chemical toxicity field and demonstrate the BMDExpress software using a radiation dataset. Discussions focused on the BMD approach, the importance of experimental design, regulatory applications, its use in supporting the development of adverse outcome pathways, and specific radiation-relevant examples. Conclusions: Although further deliberations are needed to advance the use of BMD modeling in the radiation field, these initial discussions and partnerships highlight some key steps to guide future undertakings related to new experimental work.
AB - Background: Exposure to different forms of ionizing radiation occurs in diverse occupational, medical, and environmental settings. Improving the accuracy of the estimated health risks associated with exposure is therefore, essential for protecting the public, particularly as it relates to chronic low dose exposures. A key aspect to understanding health risks is precise and accurate modeling of the dose-response relationship. Toward this vision, benchmark dose (BMD) modeling may be a suitable approach for consideration in the radiation field. BMD modeling is already extensively used for chemical hazard assessments and is considered statistically preferable to identifying low and no observed adverse effects levels. BMD modeling involves fitting mathematical models to dose-response data for a relevant biological endpoint and identifying a point of departure (the BMD, or its lower bound). Recent examples in chemical toxicology show that when applied to molecular endpoints (e.g. genotoxic and transcriptional endpoints), BMDs correlate to points of departure for more apical endpoints such as phenotypic changes (e.g. adverse effects) of interest to regulatory decisions. This use of BMD modeling may be valuable to explore in the radiation field, specifically in combination with adverse outcome pathways, and may facilitate better interpretation of relevant in vivo and in vitro dose-response data. To advance this application, a workshop was organized on June 3rd, 2022, in Ottawa, Ontario that brought together BMD experts in chemical toxicology and the radiation scientific community of researchers, regulators, and policy-makers. The workshop’s objective was to introduce radiation scientists to BMD modeling and its practical application using case examples from the chemical toxicity field and demonstrate the BMDExpress software using a radiation dataset. Discussions focused on the BMD approach, the importance of experimental design, regulatory applications, its use in supporting the development of adverse outcome pathways, and specific radiation-relevant examples. Conclusions: Although further deliberations are needed to advance the use of BMD modeling in the radiation field, these initial discussions and partnerships highlight some key steps to guide future undertakings related to new experimental work.
KW - Benchmark dose modeling
KW - adverse outcome pathway
KW - gene expression responses
KW - low dose
KW - radiation risk assessment
UR - http://www.scopus.com/inward/record.url?scp=85150469021&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85150469021&partnerID=8YFLogxK
U2 - 10.1080/09553002.2023.2181998
DO - 10.1080/09553002.2023.2181998
M3 - Article
C2 - 36881459
AN - SCOPUS:85150469021
SN - 0955-3002
VL - 99
SP - 1320
EP - 1331
JO - International Journal of Radiation Biology
JF - International Journal of Radiation Biology
IS - 9
ER -