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Deciphering and Predicting the Drug-Bile-Mucus Interplay

ORCID
0000-0001-7519-6122
Affiliation
Institute for Pharmacy and Food Chemistry, University of Wuerzburg, Am Hubland, 97074 Wuerzburg, Germany
Scheller, Lena;
ORCID
0000-0003-4624-8020
Affiliation
Institute for Pharmacy and Food Chemistry, University of Wuerzburg, Am Hubland, 97074 Wuerzburg, Germany
Hanio, Simon;
ORCID
0000-0003-4042-6762
Affiliation
Division of Pharmaceutical Biosciences, Drug Research Program, Faculty of Pharmacy, University of Helsinki, 00014 Helsinki, Finland
Kehrein, Josef;
ORCID
0000-0002-7549-7627
Affiliation
Institute for Pharmacy and Food Chemistry, University of Wuerzburg, Am Hubland, 97074 Wuerzburg, Germany
Meinel, Lorenz

Bile colloids and mucus influence the intestinal absorption of orally administered drugs, but this cannot not yet be predicted well.
Bile primarily consists of bile acids, such as Taurocholate, and Lecithin. Taurocholate and Lecithin readily form mixed micelles, within drugs are solubilized and shuttled from the intestinal lumen through the mucus layer to the epithelial surfaces. The mucus layer is formed by the negatively charged glycoprotein Mucin II (MUC2) which consequently plays an important role in its natural barrier function. Numerous studies detail the interaction of molecules with mucus or bile but surprisingly little is known about the interaction of the three components and how knowledge of their interplay could serve as foundation to predict biopharmaceutical characteristics for drug substances.
To confirm interaction of drugs with mucus and bile, 1H DOSY NMR and permeation experiments were performed. They demonstrated changes in diffusion kinetics of bile interacting and non-interacting compounds within mucus.
19F-NMR and flux studies using mucus and commercial intestinal porcine MUC2 demonstrated MUC2s capability to depict drug-mucus interaction.
Subsequently, 131 drugs were categorized as MUC2 and bile interacting or non-interacting based on 1H NMR signal pattern changes using intestinal porcine MUC2 and simulating intestinal fluids. Their MUC2 interaction profile was further evaluated by HPLC employing a MUC2 based stationary phase.
Signal pattern changes were extracted using indirect hard modelling and further correlated with quantitative structure-property relationship (QSPR) models yielding good predictive performance based on a clustering approach. These findings could potentially facilitate pre-screening processes of new drugs substances for their mucus and bile interacting profile and further leverage their rational formulation outcomes.

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