Modeling bioaccumulation in humans using poly-parameter linear free energy relationships (PPLFERS).

Area of Science:

• Environmental Chemistry
• Toxicology
• Computational Modeling

Background:

• Chemical partitioning coefficients are crucial for bioaccumulation models.
• Single-parameter linear free energy relationships (spLFERs) may inaccurately predict partitioning for polar chemicals.
• Existing models often rely on apolar chemical data.

Purpose of the Study:

• To present a poly-parameter linear free energy relationship (ppLFER) based model for organic chemical bioaccumulation in humans.
• To compare the predictive performance of a ppLFER model against a traditional spLFER model.
• To assess the accuracy of these models for both hydrophobic and hydrophilic chemicals.

Main Methods:

• Developed a human bioaccumulation model using ppLFERs to describe air-body partitioning.
• Calculated an air-body partition coefficient as a weighted average of organ-specific ppLFER partition coefficients.
• Compared the ppLFER model predictions with an spLFER model that treats the body as lipid and water mixtures.

Main Results:

• Both models showed good agreement for hydrophobic chemicals (log K(OW)>4, log K(OA)>8), with an average difference of 15%.
• The ppLFER model predicted ~90% lower body burdens for hydrophilic chemicals (log K(OW)<0).
• This discrepancy was primarily attributed to lower predicted sorption capacities in muscle and adipose tissues for hydrophilic chemicals by the ppLFER model.

Conclusions:

• The ppLFER model demonstrated significantly lower predictions for hydrophilic chemical bioaccumulation in humans.
• Uncertainties in predicting hydrophilic chemical sorption in muscle and adipose tissues were similar between ppLFER and spLFER models.
• The implementation of ppLFERs in this specific human bioaccumulation model offered limited practical benefit over spLFERs for hydrophilic compounds.