Author
Steven H. Robison
Bio: Steven H. Robison is an academic researcher from Procter & Gamble. The author has contributed to research in topics: Biomonitoring & Population. The author has an hindex of 12, co-authored 16 publications receiving 3492 citations.
Papers
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TL;DR: A newly developed probabilistic model, the Creme RIFM model, is used to estimate aggregate exposure to fragrance ingredients using the example of 2-phenylethanol (PEA) to demonstrate the utility of the model in determining systemic and dermal exposure to fragrances from individual products, and aggregate exposure.
1,108 citations
TL;DR: The data and modelling methods presented show potential as a means of performing ingredient safety assessments for personal care and cosmetics products, and the robustness and ability to estimate aggregate consumer product exposure are presented.
1,057 citations
TL;DR: The Creme RIFM model offers a very comprehensive and powerful tool for estimating aggregate exposure to fragrance ingredients, suggesting that deterministic models overestimate exposure by 11.5–25 fold.
1,050 citations
TL;DR: The development of Phase 2 Creme RIFM model is described by expanding the previously developed Phase 1 model to include an additional six product types, which covers a broader range of product categories and includes all relevant routes of exposure.
1,026 citations
TL;DR: The data-rich chemical benzene was selected for use in a case study to assess whether refinement of the Common Criteria framework was necessary, and to gain additional perspective on approaches for integrating biomonitoring data into a risk-based context.
Abstract: A framework of “Common Criteria” (i.e. a series of questions) has been developed to inform the use and evaluation of biomonitoring data in the context of human exposure and risk assessment. The data-rich chemical benzene was selected for use in a case study to assess whether refinement of the Common Criteria framework was necessary, and to gain additional perspective on approaches for integrating biomonitoring data into a risk-based context. The available data for benzene satisfied most of the Common Criteria and allowed for a risk-based evaluation of the benzene biomonitoring data. In general, biomarker (blood benzene, urinary benzene and urinary S-phenylmercapturic acid) central tendency (i.e. mean, median and geometric mean) concentrations for non-smokers are at or below the predicted blood or urine concentrations that would correspond to exposure at the US Environmental Protection Agency reference concentration (30 µg/m3), but greater than blood or urine concentrations relating to the air conc...
117 citations
Cited by
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Research Institute for Fragrance Materials1, Columbia University Medical Center2, Malmö University3, University of Nebraska–Lincoln4, University of São Paulo5, University of Würzburg6, Oregon Health & Science University7, International Flavors & Fragrances, Inc.8, Symrise9, Vanderbilt University10, Kyoto University11, Takasago International Corporation12, University of Tennessee13, University of Arizona14
TL;DR: This publication is designed to update the RifM safety assessment process, which follows a series of decision trees, reflecting advances in approaches in risk assessment and new and classical toxicological methodologies employed by RIFM over the past ten years.
1,148 citations
TL;DR: A newly developed probabilistic model, the Creme RIFM model, is used to estimate aggregate exposure to fragrance ingredients using the example of 2-phenylethanol (PEA) to demonstrate the utility of the model in determining systemic and dermal exposure to fragrances from individual products, and aggregate exposure.
1,108 citations
TL;DR: The data and modelling methods presented show potential as a means of performing ingredient safety assessments for personal care and cosmetics products, and the robustness and ability to estimate aggregate consumer product exposure are presented.
1,057 citations
TL;DR: The Creme RIFM model offers a very comprehensive and powerful tool for estimating aggregate exposure to fragrance ingredients, suggesting that deterministic models overestimate exposure by 11.5–25 fold.
1,050 citations
TL;DR: The development of Phase 2 Creme RIFM model is described by expanding the previously developed Phase 1 model to include an additional six product types, which covers a broader range of product categories and includes all relevant routes of exposure.
1,026 citations