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Updated: Jun 5, 2025

Mass Spectrometry and Luminogenic-based Approaches to Characterize Phase I Metabolic Competency of In Vitro Cell Cultures
Published on: March 28, 2017
In Vitro Hepatic Metabolism Input Parameters Support Toxicokinetic Simulations for the Formation of Methoxy Propionic
Sophie Werner1,2,3, Lucie Hegg3,4, Nancy B Hopf3,4
1School of Life Sciences, University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland.
Abstract:
Propylene glycol ethers (PGEs) are organic solvents commonly found as technical grade on the commercial market, as mixtures of secondary (α-isomer) and primary (β-isomer, generally < 5%) alcohols. After handling products containing PGEs, they readily enter the human body where they are metabolized. The minor β-isomer is oxidized by alcohol dehydrogenase (ADH) followed by aldehyde dehydrogenase (ALDH) to a potentially harmful metabolite. Although the enzymatic rate is needed to estimate both parent and metabolite internal exposures, kinetic data for many PGEs are still scarce. Therefore, we generated in vitro hepatic intrinsic clearance data for propylene glycol methyl ether β-isomer (β-PGME) and its metabolite methoxy propionic acid (2-MPA) and integrated these data into an in silico toxicokinetic (TK) model. Hepatic clearance values for the model were generated using an established in vitro 3D culture of the human HepaRG cell line and human S9 liver fraction. Our results showed the presence of ADH and ALDH and consequently, the formation of 2-MPA in the 3D HepaRG and S9 fraction, which was slow to medium. We integrated the hepatic clearance values into the TK model to predict urinary 2-MPA concentrations. The simulated urinary 2-MPA concentrations fitted well (within twofold error from observed experimental data) for both liver systems, showing that they were both able to reliably predict the hepatic clearance of β-PGME. Although S9 is suitable for short-term studies, 3D cell culture models maintain metabolic competence over days and weeks. This opens the opportunity for long-term metabolism studies applying the 3D HepaRG model alone or in multi-organ systems.
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