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.
Keywords: Consumer products; Food packaging; Multiple-linear regression; Organic chemicals; Partition.
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