scholarly journals Peak Exposures in Epidemiologic Studies and Cancer Risks: Considerations for Regulatory Risk Assessment

Risk Analysis ◽  
2019 ◽  
Author(s):  
Harvey Checkoway ◽  
Peter S. J. Lees ◽  
Linda D. Dell ◽  
P. Robinan Gentry ◽  
Kenneth A. Mundt
Keyword(s):  
Risk Assessment ◽  
Epidemiologic Studies ◽  
Cancer Risks ◽  
Regulatory Risk Assessment

Statistical Analysis of Avian Reproduction Studies

2021 ◽  
Author(s):  
John W Green ◽  
Manousos Foudoulakis ◽  
Timothy Fredricks ◽  
Tiffany Carro ◽  
Jonathan Maul ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Study Design ◽  
Model Averaging ◽  
Study Data ◽  
Design Elements ◽  
Avian Reproduction ◽  
Reproduction Study ◽  
Data Points ◽  
Set Up ◽  
Regulatory Risk Assessment

Abstract Avian reproduction studies for regulatory risk assessment are undergoing review by regulatory authorities, often leading to requests for statistical re-analysis of older studies using newer methods, sometimes with older study data that do not support these newer methods. We propose detailed statistical protocols with updated statistical methodology for use with both new and older studies and recommend improvements in experimental study design to set-up future studies for robust statistical analyses. There is increased regulatory and industry attention to the potential use of benchmark dose (BMD) methodology to derive the point of departure in avian reproduction studies, to be used as the endpoint in regulatory risk assessment. We present benefits and limitations of this BMD approach for older studies being re-evaluated and for new studies designed for with BMD analysis anticipated. Model averaging is recommended as preferable to model selection for BMD analysis. Even for a new study following the modified experimental design analyses with BMD methodology will only be possible for a restricted set of response variables. The judicious use of historical control data, identification of outlier data points, increased use of distributions more consistent with the nature of the data collected as opposed to forcing normality-based methods, and trend-based hypothesis tests are shown to be effective for many studies, but limitations on their applicability are also recognized and explained. Updated statistical methodologies are illustrated with case studies conducted under existing regulatory guidelines that have been submitted for product registrations. Through the adoption of improved avian reproduction study design elements combined with the suggested revised statistical methodologies the conduct, analyses, and utility of avian reproduction studies for avian risk assessments can be improved.

scholarly journals Wild Bee Toxicity Data for Pesticide Risk Assessments

Data ◽  
2019 ◽  
Vol 4 (3) ◽  
pp. 98 ◽  
Author(s):  
Kathleen A Lewis ◽  
John Tzilivakis
Keyword(s):  
Risk Assessment ◽  
Dietary Exposure ◽  
Risk Assessments ◽  
Toxicity Data ◽  
Wild Bees ◽  
Pollination Services ◽  
Wild Bee ◽  
Long Time ◽  
Pollinating Insects ◽  
Regulatory Risk Assessment

Pollination services are vital for agriculture, food security and biodiversity. Although many insect species provide pollination services, honeybees are thought to be the major provider of this service to agriculture. However, the importance of wild bees in this respect should not be overlooked. Whilst regulatory risk assessment processes have, for a long time, included that for pollinators, using honeybees (Apis mellifera) as a protective surrogate, there are concerns that this approach may not be sufficiently adequate particularly because of global declines in pollinating insects. Consequently, risk assessments are now being expanded to include wild bee species such as bumblebees (Bombus spp.) and solitary bees (Osmia spp.). However, toxicity data for these species is scarce and are absent from the main pesticide reference resources. The aim of the study described here was to collate data relating to the acute toxicity of pesticides to wild bee species (both topical and dietary exposure) from published regulatory documents and peer reviewed literature, and to incorporate this into one of the main online resources for pesticide risk assessment data: The Pesticide Properties Database, thus ensuring that the data is maintained and continuously kept up to date. The outcome of this study is a dataset collated from 316 regulatory and peer reviewed articles that contains 178 records covering 120 different pesticides and their variants which includes 142 records for bumblebees and a further 115 records for other wild bee species.

Intelligent Testing Strategies for Chemicals Testing — A Case of More Haste, Less Speed?

2005 ◽  
Vol 33 (3) ◽  
pp. 289-297 ◽  
Author(s):  
Robert Combes ◽  
Michael Balls
Keyword(s):  
Risk Assessment ◽  
Information Needs ◽  
Computational Modelling ◽  
In Vitro Tests ◽  
Production Volume ◽  
Culture Methods ◽  
Chemical Risk Assessment ◽  
Testing Strategies ◽  
Regulatory Risk Assessment

The prospects for using (Q)SAR modelling, read-across (chemical) and other non-animal approaches as part of integrated testing strategies for chemical risk assessment, within the framework of the EU REACH legislation, are considered. The potential advantages and limitations of (Q)SAR modelling and read-across methods for chemical regulatory risk assessment are reviewed. It is concluded that it would be premature to base a testing strategy on chemical-based computational modelling approaches, until such time as criteria to validate them for their reliability and relevance by using independent and transparent procedures, have been agreed. This is mainly because of inherent problems in validating and accepting (Q)SARs for regulatory use in ways that are analogous to those that have been developed and applied for in vitro tests. Until this issue has been resolved, it is recommended that testing strategies should be developed which comprise the integrated use of computational and read-across approaches. These should be applied in a cautious and judicious way, in association with available tissue culture methods, and in conjunction with metabolism and biokinetic studies. Such strategies should be intelligently applied by being driven by exposure information (based on bioavailability, not merely on production volume) and hazard information needs, in preference to a tick-box approach. In the meantime, there should be increased efforts to develop improved (Q)SARs, expert systems and new in vitro methods, and, in particular, ways to expedite their validation and acceptance must be found and prospectively agreed with all major stakeholders.

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