Publications

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Comiskey, Api, Barrett, Ellis, McNamara, O’Mahony, Robison, Rose, Safford, Smith, Tozer
Regul Toxicol Pharmacol. 2017 Aug;88:144-156. doi: 10.1016/j.yrtph.2017.05.017. Epub 2017 May 27.
27/05/2017

Integrating habits and practices data for soaps, cosmetics and air care products into an existing aggregate exposure model.

In order to accurately assess aggregate exposure to a fragrance material in consumers, data are needed on consumer habits and practices, as well as the concentration of the fragrance material in those products. The present study describes the development of Phase 2 Creme RIFM model by expanding the previously developed Phase 1 model to include an additional six product types. Using subject-matching algorithms, the subjects in the Phase 1 Creme RIFM database were paired with subjects in the SUPERB and BodyCare surveys based on age and gender. Consumption of the additional products was simulated to create a seven day diary allowing full data integration in a consistent format. The inhalation route was also included for air care and other products where a fraction of product used is inhaled, derived from the RIFM 2-box model. The expansion of the Phase 1 Creme RIFM model has resulted in a more extensive and refined model, which covers a broader range of product categories and now, includes all relevant routes of exposure. An evaluation of the performance of the model has been carried out in an accompanying publication to this one.

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Safford B & A.M.Api, C.Barratt, D.Comiskey, G.Ellis, C.McNamara, C.O’Mahony, S.Robison, J.Rose, B.Smith, S.Tozeri
Regulatory Toxicology and Pharmacology Volume 86, June 2017, Pages 148-156
28/02/2017

Application of the expanded Creme RIFM consumer exposure model to fragrance ingredients in cosmetic, personal care and air care products

As part of a joint project between the Research Institute for Fragrance Materials (RIFM) and Creme Global, a Monte Carlo model (here named the Creme RIFM model) has been developed to estimate consumer exposure to ingredients in personal care products. Details of the model produced in Phase 1 of the project have already been published. Further data on habits and practises have been collected which enable the model to estimate consumer exposure from dermal, oral and inhalation routes for 25 product types. . In addition, more accurate concentration data have been obtained which allow levels of fragrance ingredients in these product types to be modelled. Described is the use of this expanded model to estimate aggregate systemic exposure for eight fragrance ingredients. Results are shown for simulated systemic exposure (expressed as μg/kg bw/day) for each fragrance ingredient in each product type, along with simulated aggregate exposure. Highest fragrance exposure generally occurred from use of body lotions, body sprays and hydroalcoholic products. For the fragrances investigated, aggregate exposure calculated using this model was 11.5–25 fold lower than that calculated using deterministic methodology. The Creme RIFM model offers a very comprehensive and powerful tool for estimating aggregate exposure to fragrance ingredients.

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Comiskey D., Api AM2, Barratt C3, Daly EJ1, Ellis G4, McNamara C1, O’Mahony C1, Robison SH5, Safford B6, Smith B7, Tozer S8.
Regul Toxicol Pharmacol. 2015 Aug;72(3):660-72. doi: 10.1016/j.yrtph.2015.05.012. Epub 2015 May 19
19/05/2015

Novel database for exposure to fragrance ingredients in cosmetics and personal care products.

Exposure of fragrance ingredients in cosmetics and personal care products to the population can be determined by way of a detailed and robust survey. The frequency and combinations of products used at specific times during the day will allow the estimation of aggregate exposure for an individual consumer, and to the sample population. In the present study, habits and practices of personal care and cosmetic products have been obtained from market research data for 36,446 subjects across European countries and the United States in order to determine the exposure to fragrance ingredients. Each subject logged their product uses, time of day and body application sites in an online diary for seven consecutive days. The survey data did not contain information on the amount of product used per occasion or body measurements, such as weight and skin surface area. Nevertheless, this was found from the literature where the likely amount of product used per occasion or body measurement could be probabilistically chosen from distributions of data based on subject demographics. The daily aggregate applied consumer product exposure was estimated based on each subject’s frequency of product use, and Monte Carlo simulations of their likely product amount per use and body measurements. Statistical analyses of the habits and practices and consumer product exposure are presented, which show the robustness of the data and the ability to estimate aggregate consumer product exposure. Consequently, the data and modelling methods presented show potential as a means of performing ingredient safety assessments for personal care and cosmetics products.

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Safford B., A.M.Api, C.Barratt, D.Comiskey, G.Ellis, E.J. Daly, C.McNamara, C.O’Mahony, S.Robison, B.Smith, S.Tozeri
Regulatory Toxicology and Pharmacology Volume 72, Issue 3, August 2015, Pages 673-682
01/08/2015

Use of an aggregate exposure model to estimate consumer exposure to fragrance ingredients in personal care and cosmetic products.

Background:
Ensuring the toxicological safety of fragrance ingredients used in personal care and cosmetic products is essential in product development and design, as well as in the regulatory compliance of the products. This requires an accurate estimation of consumer exposure which, in turn, requires an understanding of consumer habits and use of products. Where ingredients are used in multiple product types, it is important to take account of aggregate exposure in consumers using these products. This publication investigates the use of a newly developed probabilistic model, the Creme RIFM model, to estimate aggregate exposure to fragrance ingredients using the example of 2-phenylethanol (PEA). The output shown demonstrates the utility of the model in determining systemic and dermal exposure to fragrances from individual products, and aggregate exposure. The model provides valuable information not only for risk assessment, but also for risk management. It should be noted that data on the concentrations of PEA in products used in this article were obtained from limited sources and not the standard, industry wide surveys typically employed by the fragrance industry and are thus presented here to illustrate the output and utility of the newly developed model. They should not be considered an accurate representation of actual exposure to PEA.
Methods:

Determination of aggregate exposure to a number of fragrance ingredients was conducted using a model developed by Creme Global in conjunction with RIFM (described here as the Creme RIFM model). Full details of the model are given in a concurrent publication (Comiskey et al., 2015).

The model uses probabilistic (Monte Carlo) simulation to allow sampling from distributions of data sets providing a more realistic estimate of aggregate exposure to individuals across a population. The Creme RIFM

Results:

The results for both applied product exposure and fragrance ingredient exposure are reported below. It should be noted that the applied product amount refers to the amount of product that is retained on the skin after application, taking into account the product retention factors. This product retention factor also helps define exposure to the individual fragrance ingredients.

The applied product and fragrance ingredient exposures are presented in the form of box-and-whisker plots which shows

Conclusions:
The dietary feedback system was used to deliver personalized dietary advice within a multi-country study. Overall, there was good agreement between the manual and automated feedback systems, giving promise to the use of automated systems for personalizing dietary advice.

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Hall B, Steiling W, Safford B, Coroama M, Tozer S, Firmani C, McNamara C, Gibney M.
Food Chem Toxicol. 2011 Feb;49(2):408-22. doi: 10.1016/j.fct.2010.11.016. Epub 2010 Nov 18.
18/11/2010

European consumer exposure to cosmetic products, a framework for conducting population exposure assessments Part 2.

Access to reliable exposure data is essential for the evaluation of the toxicological safety of ingredients in cosmetic products. This study complements the data set obtained previously (Part 1) and published in 2007 by the European cosmetic industry acting within COLIPA. It provides, in distribution form, exposure data on daily quantities of five cosmetic product types: hair styling, hand cream, liquid foundation, mouthwash and shower gel. In total 80,000 households and 14,413 individual consumers in five European countries provided information using their own products. The raw data were analysed using Monte Carlo simulation and a European Statistical Population Model of exposure was constructed. A significant finding was an inverse correlation between the frequency of product use and the quantity used per application recorded for mouthwash and shower gel. The combined results of Part 1 (7 product types) and Part 2 (5 products) reported here, bring up to date and largely confirm the current exposure parameters concerning some 95% of the estimated daily exposure to cosmetics use in the EU. The design of this study, with its relation to demographic and individual diversity, could serve as a model for studies of populations’ exposure to other consumer products.

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McNamara C, Rohan D, Golden D, Gibney M, Hall B, Tozer S, Safford B, Coroama M, Leneveu-Duchemin MC, Steiling W.
Food Chem Toxicol. 2007 Nov;45(11):2086-96. Epub 2007 Jul 7.
07/07/2007

Probabilistic modelling of European consumer exposure to cosmetic products.

In this study, we describe the statistical analysis of the usage profile of the European population to seven cosmetic products. The aim of the study was to construct a reliable model of exposure of the European population from use of the selected products: body lotion, shampoo, deodorant spray, deodorant non-spray, facial moisturiser, lipstick and toothpaste. The first step in this process was to gather reliable data on consumer usage patterns of the products. These data were sourced from a combination of market information databases and a controlled product use study by the trade association Colipa. The market information study contained a large number of subjects, in total 44,100 households and 18,057 habitual users (males and females) of the studied products, in five European countries. The data sets were then combined to generate a realistic distribution of frequency of use of each product, combined with distribution of the amount of product used at each occasion using the CREMe software. A Monte Carlo method was used to combine the data sets. This resulted in a new model of European exposure to cosmetic products being constructed.

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Hall B, Tozer S, Safford B, Coroama M, Steiling W, Leneveu-Duchemin MC, McNamara C, Gibney M.
Food Chem Toxicol. 2007 Nov;45(11):2097-108. Epub 2007 Jun 16.
16/06/2007

European consumer exposure to cosmetic products, a framework for conducting population exposure assessments.

Access to reliable exposure data is essential to evaluate the toxicological safety of ingredients in cosmetic products. This study was carried out by European cosmetic manufacturers acting within the trade association Colipa, with the aim to construct a probabilistic European population model of exposure. The study updates, in distribution form, the current exposure data on daily quantities of six cosmetic products. Data were collected using a combination of market information databases and a controlled product use study. In total 44,100 households and 18,057 individual consumers in five European countries provided data using their own products. All product use occasions were recorded, including those outside of home. The raw data were analysed using Monte Carlo simulation and a European Statistical Population Model of exposure was constructed. A significant finding was an inverse correlation between frequency of product use and quantity used per application for body lotion, facial moisturiser, toothpaste and shampoo. Thus it is not appropriate to calculate daily exposure to these products by multiplying the maximum frequency value by the maximum quantity per event value. The results largely confirm the exposure parameters currently used by the cosmetic industry. Design of this study could serve as a model for future assessments of population exposure to chemicals in products other than cosmetics.

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Tozer S, Kelly S, O’Mahony C, Daly EJ, Nash JF.
Food Chem Toxicol. 2015 Sep;83:103-10. doi: 10.1016/j.fct.2015.06.005. Epub 2015 Jun 16
16/06/2015

Aggregate exposure modelling of zinc pyrithione in rinse-off personal cleansing products using a person-orientated approach with market share refinement.

Realistic estimates of chemical aggregate exposure are needed to ensure consumer safety. As exposure estimates are a critical part of the equation used to calculate acceptable “safe levels” and conduct quantitative risk assessments, methods are needed to produce realistic exposure estimations. To this end, a probabilistic aggregate exposure model was developed to estimate consumer exposure from several rinse off personal cleansing products containing the anti-dandruff preservative zinc pyrithione. The model incorporates large habits and practices surveys, containing data on frequency of use, amount applied, co-use along with market share, and combines these data at the level of the individual based on subject demographics to better estimate exposure. The daily-applied exposure (i.e., amount applied to the skin) was 3.79 mg/kg/day for the 95th percentile consumer. The estimated internal dose for the 95th percentile exposure ranged from 0.01-1.29 μg/kg/day after accounting for retention following rinsing and dermal penetration of ZnPt. This probabilistic aggregate exposure model can be used in the human safety assessment of ingredients in multiple rinse-off technologies (e.g., shampoo, bar soap, body wash, and liquid hand soap). In addition, this model may be used in other situations where refined exposure assessment is required to support a chemical risk assessment.

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Tozer S, & Cian O’Mahony, Jen Hannah, John O’Brien, Seamus Kelly, Kirstin Kosemund-Meynen, Camilla Alexander-White
Food and Chemical Toxicology, Volume 131, September 2019, 110549
31/05/2019

Aggregate exposures to existing and novel fragrances in consumer products

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Comiskey Damien & Cian O’Mahony, E.J. Daly, Cronan McNamara
Toxicology Letters, Volume 229, Supplement, 10 September 2014, Page S111
10/09/2014

Combining databases to estimate population exposure to cosmetics and personal care products

Elsevier Toxicology Letters Creme Global Exposure to cosmetic products in Europe

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Tozer Sarah, J F Nash, and E.J. Daly
International Society for Environmental Epidemiology (ISEE) Annual Meeting, Abstract Number:4967, September 2013
01/09/2013

Probabilistic Aggregate Exposure Modelling for a Broad Spectrum Antimicrobial in Personal Cleansing Products

Background:

Realistic estimates of chemical aggregate exposure are needed to ensure consumer safety and satisfy the requirements of regulators. In most cases, aggregate exposure is estimated simply by adding deterministic exposures from all product types containing the chemical. However, this summation will result in an unrealistically-conservative estimate since individuals vary in their patterns of product use, and it is very unlikely that consumers use high levels of all products at the same time. As aggregate exposure estimates could be used to calculate acceptable “safe levels” and conduct risk assessments for chemicals, methods are needed to produce realistic exposure estimations.

Methods:

A probabilistic aggregate exposure model was developed to estimate consumer exposure in Europe and North America to a hypothetical broad spectrum biocide, from a range of rinse off personal cleansing products. It incorporates large habits and practices surveys, from industry/cosmetic trade associations, containing data on frequency of use, amount, co-use along with market share, and combines these data at the level of the individual based on subject demographics (gender, age, ethnicity) to realistically calculate exposure. Results: When the antimicrobial was assumed present in five rinse off products (Shampoo: 2% and other products: 0.5%), the average daily applied exposure (amount applied to the skin) was estimated at 1.65 mg/kg/day for the average person and 3.79 mg/kg/day for the 95th percentile consumer. This probabilistic modelling offers significant exposure refinement versus deterministic aggregate summation methods.

Conclusions:

This probabilistic aggregate exposure model provides robust data that can be used in the human safety assessment of multiple rinse-off technologies (e.g., shampoo, bar soap, body wash, liquid hand soap) containing the biocide. In addition, this model may be used in other situations where refined exposure assessment is required to support a chemical risk assessment.

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Tozer Sarah, Cian O’Mahony, Jay Nash, Seamus Kelly, E.J. Daly
Toxicology Letters, Volume 229, Supplement, 10 September 2014, Page S128
10/09/2014

Probabilistic aggregate exposure modelling to aluminium from the diet, cosmetics and medicines

Elsevier Toxicology Letters Creme Global Exposure to cosmetic products in Europe

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Aylward Lesa, Giulia Vilone, Christina Cowan-Ellsberry, Jon A. Arnot, John N. Westgate, Cian O’Mahony & Sean M. Hays
Journal of Exposure Science and Environmental Epidemiology 30 (Suppl 4)
05/12/2018

Exposure to selected preservatives in personal care products: case study comparison of exposure models and observational biomonitoring data

Exposure models provide critical information for risk assessment of personal care product ingredients, but there have been limited opportunities to compare exposure model predictions to observational exposure data. Urinary excretion data from a biomonitoring study in eight individuals were used to estimate minimum absorbed doses for triclosan and methyl-, ethyl-, and n-propyl- parabens (TCS, MP, EP, PP). Three screening exposure models (European Commission Scientific Commission on Consumer Safety [SCCS] algorithms, ConsExpo in deterministic mode, and RAIDAR-ICE) and two higher-tier probabilistic models (SHEDS-HT, and Creme Care & Cosmetics) were used to model participant exposures. Average urinary excretion rates of TCS, MP, EP, and PP for participants using products with those ingredients were 16.9, 3.32, 1.9, and 0.91 μg/kg-d, respectively. The SCCS default aggregate and RAIDAR-ICE screening models generally resulted in the highest predictions compared to other models. Approximately 60–90% of the model predictions for most of the models were within a factor of 10 of the observed exposures; ~30–40% of the predictions were within a factor of 3. Estimated exposures from urinary data tended to fall in the upper range of predictions from the probabilistic models. This analysis indicates that currently available exposure models provide estimates that are generally realistic. Uncertainties in preservative product concentrations and dermal absorption parameters as well as degree of metabolism following dermal absorption influence interpretation of the modeled vs. measured exposures. Use of multiple models may help characterize potential exposures more fully than reliance on a single model.

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Cronan McNamara, Sandrine Pigat
Present Knowledge in Food Safety A Risk-Based Approach Through The Food Chain 2023, Pages 633-642
13/10/2022

Exposure assessment: real-world examples of exposure models in action from simple deterministic to probabilistic aggregate and cumulative models

This chapter outlines probabilistic methods for assessing population dietary exposure. It discusses and makes recommendations on how to move from deterministic screening-type calculations to higher-tier, more refined calculations using probabilistic methods. The question of how to deal with variability and uncertainty in the exposure scenario input variables is covered. Probabilistic methods are more technically demanding but can overcome some of the challenges of aggregate and cumulative exposure assessment, whilst dealing effectively with variability and uncertainty. This results in a more refined and scientific approach to exposure. This chapter explains why it is important to document all model assumptions and qualitatively describe the potential effect of uncertainties. The evaluation of high-end exposures against toxicological endpoints is also briefly discussed. The type of data required for setting up the assessment and how to deal with data gaps are outlined and real-life case studies are included illustrating recommended approaches.

publication-Present Knowledge in Food Safety A Risk-Based Approach Through the Food Chain

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Hall Barbara, Sarah Tozer, Bob Safford, Manuela Coroama, Winfried Steiling, Marie-Cristine Leneveu-Duchemin, Cronan McNamara, Michael Gibney
Toxicology Letters, Volume 172, Supplement, 7 October 2007, Page S12
05/09/2007

Exposure to cosmetic products in Europe

A framework for conducting population exposure assessments

Access to reliable exposure data is essential to evaluate the toxicological safety of ingredients in cosmetic products. This study was carried out by European cosmetic manufacturers acting within the trade association Colipa, with the aim to construct a probabilistic European population model of exposure. The study updates, in distribution form, the current exposure data on daily quantities of six cosmetic products. Data were collected using a combination of market information databases and a controlled product use study. In total 44,100 households and 18,057 individual consumers in five European countries provided data using their own products. All product use occasions were recorded, including those outside of home. The raw data were analysed using Monte Carlo simulation and a European Statistical Population Model of exposure was constructed. A significant finding was an inverse correlation between frequency of product use and quantity used per application for body lotion, facial moisturiser, toothpaste and shampoo. Thus it is not appropriate to calculate daily exposure to these products by multiplying the maximum frequency value by the maximum quantity per event value. The results largely confirm the exposure parameters currently used by the cosmetic industry. Design of this study could serve as a model for future assessments of population exposure to chemicals in products other than cosmetics.

Elsevier Toxicology Letters Creme Global Exposure to cosmetic products in Europe

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