The Use of Molecular Descriptors To Model Pharmaceutical Uptake by a Fish Primary Gill Cell Culture Epithelium

• Published in: Environmental science & technology 2019-02, Vol.53 (3), p.1576-1584
• Main Authors: Chang, Elisabeth D, Hogstrand, Christer, Miller, Thomas H, Owen, Stewart F, Bury, Nic R
• Format: Article
• Language: English
• Subjects: Acetazolamide; Animals; Bioavailability; Biological Transport; Biota; Biotechnology; Carbamazepine; Cell culture; Diclofenac; Drugs; Empirical analysis; Epithelium; Fishes; Fresh Water; Gemfibrozil; Gills; Ibuprofen; Ketoprofen; Lipophilic; Mathematical models; Molecular structure; Molecular weight; Pharmaceutical Preparations; Pharmaceuticals; Physicochemical properties; Principal components analysis; Properties (attributes); Propranolol; Quantitative Structure-Activity Relationship; Regression analysis; Risk assessment; Speciation; Warfarin
• ISSN: 0013-936X; 1520-5851
• DOI: 10.1021/acs.est.8b04394

Modeling approaches such as quantitative structure–activity relationships (QSARs) use molecular descriptors to predict the bioavailable properties of a compound in biota. However, these models have mainly been derived based on empirical data for lipophilic neutral compounds and may not predict the uptake of ionizable compounds. The majority of pharmaceuticals are ionizable, and freshwaters can have a range of pH values that affect speciation. In this study, we assessed the uptake of 10 pharmaceuticals (acetazolamide, beclomethasone, carbamazepine, diclofenac, gemfibrozil, ibuprofen, ketoprofen, norethindrone, propranolol, and warfarin) with differing modes of action and physicochemical properties (pK a, log S, log D, log K ow, molecular weight (MW), and polar surface area (PSA)) by an in vitro primary fish gill cell culture system (FIGCS) for 24 h in artificial freshwater. Principal component analysis (PCA) and partial least-squares (PLS) regression was used to determine the molecular descriptors that influence the uptake rates. Ionizable drugs were taken up by FIGCS; a strong positive correlation was observed between log S and the uptake rate, and a negative correlation was observed between pK a, log D, and MW and the uptake rate. This approach shows that models can be derived on the basis of the physicochemical properties of pharmaceuticals and the use of an in vitro gill system to predict the uptake of other compounds. There is a need for a robust and validated model for gill uptake that could be used in a tiered risk assessment to prioritize compounds for experimental testing.