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Novel and Integrated Approaches to modelling aggregate exposures to - - PowerPoint PPT Presentation

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Novel and Integrated Approaches to modelling aggregate exposures to chemicals across different conditions of use and routes of exposure TERA Workshop: Beyond Science and Decision Making, Feb 19 2020 Dr. Clare Thorp, SVP North America Creme

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Novel and Integrated Approaches to modelling aggregate exposures to chemicals across different conditions of use and routes of exposure TERA Workshop: Beyond Science and Decision Making, Feb 19 2020

  • Dr. Clare Thorp, SVP North America

Creme Global clare.thorp@cremeglobal.com

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About Us

We are a Scientific Modelling, Data Analytics and Computing Company.

Our Mission

To enable better decision-making in a complex world.

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Services Food Cosmetics & Fragrances Chemical Associations Gov & Academia

Some of our clients

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Data Science Challenges

Foresight

Developing Predictive Models

Insight

Analysing and Visualising the Data

Understanding

Structuring, Validating and Sharing

Gathering Data

Collect the Data

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Novel and Integrated Approaches to modelling aggregate exposures to chemicals across different conditions of use and routes of exposure

Some of The Challenges:

  • 1. Data, or lack thereof
  • 2. Data, confidentiality
  • 3. Data, from multiple sources

CASE STUDY: RIFM

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Case Study Creme RIFM Model

A tool to estimate aggregate exposure from consumer product ingredients.

  • Cosmetics, personal care products, air care

products and household cleaning products.

  • United States and Europe populations.
  • Systemic, Dermal, Inhalation, Ingestion.
  • Probabilistic model based on real world data.
  • Flexible and customizable.
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Exp F A C R P BW or SA Frequency Amount Consumed Concentration Retention Factor Penetration Factor Anthropometric Data = x x x x

What Are the Data needs?

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Deterministic Method

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Percentile Exposure

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The Solution Aggregate exposure based on actual product consumption surveys and distributions of data provided is more realistic.

E.g. Amount of Toothpaste consumed

2g vs.

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Exp F A C R P B W Kantar Worldpanel = x x x x

Frequency of Use

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Kantar - Online Consumption Diaries

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Exp F A C R P B W Kantar Worldpanel Research Literature = x x x x

Amounts Used

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Amounts Used Europe → COLIPA (Hall et al., 2007; 2011) → Ficheux et al., 2016 USA → CTFA (Loretz et al., 2005; 2006; 2008) Hydroalcoholics → Tozer et al., 2004

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Exp F A C R P B W Kantar Worldpanel Research Literature Manufacturers = x x x x

Concentration of the fragrance chemical in the final product

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Fragrance Concentration

Fragrance Manufacturers Consumer Product Companies

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Two-level Concentrations

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Exp F A C R P B W Kantar Worldpanel Research Literature Manufacturers Research Literature = x x x x

Retention Factor

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Retention Factors (Examples)

Dermal Ingestion Inhalation Body Lotion 1 Shampoo 0.01 DeoSpray 0.235 0.0127 Toothpaste 0.1 0.05 Eau de Toilette 0.8 0.00363

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Exp F A C R P B W Kantar Worldpanel Research Literature Manufacturers X % = x x x x Research Literature

Penetration Factor

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Exp F A C R P B W Kantar Worldpanel Research Literature Manufacturers Research Literature 100% Population Surveys = x x x x

Anthropometric Data

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Height and Weight Data US 2009-2014 NHANES Survey Body weight and height data for 14,000 US Subjects EU France INCA2 Poland Kilmek-Piotrowska et al., 2015 Others NHANES data scaled based on EU country average weights and heights

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Surface Area Calculations Du Bois Formula SA = a x Wb x Hc Head, trunk, arms, hands, legs and feet.

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Exp F A C R P B W Kantar Worldpanel Research Literature Manufacturers Research Literature 100% Population Surveys = x x x x

Multiple sources of data Multiple conditions of use Multiple routes of exposure

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Exp F A C R P B W Frequency Amount Consumed Concentration Retention Factor Penetration Factor Anthropometric Data = x x x x

How does the data get pulled together?

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Frequency Amount Consumed Concentration Retention Factor Penetration Factor Anthropometric Data People

The problem is that the data comes from different people….

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Monte Carlo Simulation Example - Triangular Distribution Lower limit: 1g Upper limit: 8g Mode: 3g

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Monte Carlo Simulation 10 Subjects

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Monte Carlo Simulation 1000 Subjects

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Population Exposure Modelling

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Population Exposure Modelling

Age: 18-25

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Individual Exposure

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Individual Exposure

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Individual Exposure

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Individual Exposure

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Individual Exposure

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Individual Exposure

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Individual Exposure

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Individual Exposure

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Population Exposure

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Software

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How is the exposure model used?

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Many ways to consider exposure People: Everyone or Consumers only Time: Chronic or Acute Route: Dermal, Inhalation, Ingestion, or Systemic Product: Aftershave, Bar soap, Shampoo, etc. Grouping: Product, Category, or All Products Site: Palms, Wrists, Arms, Back, Stomach, etc. Statistic: Minimum, Median, Mean, P90, P95, etc.

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Publications

Comiskey et al. (2015). Novel database for exposure to fragrance ingredients in cosmetics and personal care products. Regul Toxicol Pharmacol. 72(3):660-72. doi: 10.1016/j.yrtph.2015.05.012 Safford et al. (2015). Use of an aggregate exposure model to estimate consumer exposure to fragrance ingredients in personal care and cosmetic products Regul Toxicol Pharmacol 72(3):673-682. doi: 10.1016/j.yrtph.2015.05.017 Safford et al. (2017). Application of the expanded Creme RIFM consumer exposure model to fragrance ingredients in cosmetic, personal care and air care products Regul Toxicol Pharmacol. 86:148-156. doi: 10.1016/j.yrtph.2017.02.021 Comiskey et al. (2017). Integrating habits and practices data for soaps, cosmetics and air care products into an existing aggregate exposure model. Regul Toxicol Pharmacol. 88:144-156. doi: 10.1016/j.yrtph.2017.05.017

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Thank You.

Creme Global 4th Floor, The Design Tower, Trinity Technology & Enterprise Campus, Grand Canal Quay, Dublin 2, Ireland, D02 P956 +353 (1) 677 0071 info@cremeglobal.com www.cremeglobal.com

clare.thorp@cremeglobal.com

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Capabilities Exposure Assessments Optimisation Assessments Highly configurable Highly customisable Data exploration