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Chris Bartlett

OpenTox Virtual Conference 2021 Session 10

An Approach to Data Mining Environmental Data for Personal Care Products  

Chris Bartlett1, Lisa Hoffman2, Ramez Labib2 

1 – Equilibrium Consulting  

2 – Avon Products 

Regulators, companies, and consumers have an increased focus on the environmental impact of personal care products. To develop environmentally sustainable personal care products, it is important to develop a chemical management strategy that can assess ingredients in order to assign an environmental impact score to the finished formulation. A challenge in conducting environmental risk assessments for personal care product ingredients is finding empirical data for persistence,  biodegradation, and aquatic toxicity to evaluate. For most organic chemicals, they will have empirical test data submitted for REACH registration or have well-characterized physical properties that would allow for modelling of environmental data endpoints in tools such as EPISUITE. While many chemicals submitted for REACH registration will have data, several chemical classes such as polymers and inorganics may be exempt from those data requirements. Those chemicals will not only lack empirical data but models such as EPISUITE are not optimized for those chemical classes. Therefore, when assessing these chemical classes you need to either develop a strategy to assess their component parts,  such as the metals in organics, or monomers in polymers, or have an approach for how to score the chemical class as a whole. In this presentation, we will discuss the optimal resources for empirical data,  available in silico tools, and strategies for identifying environmental data on different classes of personal care product ingredients.