A combined quantitative property-property relationship (QPPR) for estimating packaging-food and solid material-water partition coefficients of organic compounds
2019
Huang, Lei | Jolliet, Olivier
The packaging-food partition coefficient (Kₚf) is a key parameter to estimate the chemical migration from packaging to food and resulting ingestion exposures. As a particular case of Kₚf, the solid material-water partition coefficient (Kₘw) is also important in relating the material to the water phase-based skin permeation coefficient to further assess dermal contact exposure to chemicals in solid consumer products. Existing correlations to estimate Kₚf or Kₘw are applicable for a limited number of chemical-food-packaging or chemical-material combinations without considering the temperature effect. The present study develops a combined quantitative property-property relationship (QPPR) to predict Kₚf and Kₘw with a wide applicability. We compiled a dataset of 1846 measured Kₚf or Kₘw for 232 chemicals in 19 consolidated material types. A regression model predicts Kₚf or Kₘw as a function of chemical's Kₒw, food or water's ethanol equivalency, temperature and material type, which shows good fitting performance with R²ₐdⱼ of 0.93, and has been verified by internal and external validations to be robust, stable and has good predicting ability (R²ₑₓₜ > 0.80). A generic QPPR is also developed to predict Kₚf or Kₘw from chemical's Kₒw, food or water's ethanol equivalency, and temperature only (R²ₐdⱼ = 0.90), without the need to assign a specific material type. These QPPRs provide a comprehensive correlation method to estimate Kₚf for diverse chemical-food-packaging combinations or to estimate Kₘw for materials other than food packaging, which will facilitate high-throughput assessments of consumer exposures to chemicals in food packaging and in other solid materials such as building materials, furniture and toys.
Afficher plus [+] Moins [-]Mots clés AGROVOC
Informations bibliographiques
Cette notice bibliographique a été fournie par National Agricultural Library
Découvrez la collection de ce fournisseur de données dans AGRIS