Predicting Oral Absorption of fenofibrate in Lipid-Based Drug Delivery Systems by Combining In Vitro Lipolysis with the Mucus-PVPA Permeability Model

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The aim of this work was to develop a new in vitro lipolysis-permeation model to predict the in vivo absorption of fenofibrate in self-nanoemulsifying drug delivery systems (SNEDDSs). More specifically, the in vitro intestinal lipolysis model was combined with the mucus-PVPA (Phospholipid Vesicle-based Permeation Assay) in vitro permeability model. Biosimilar mucus (BM) was added to the surface of the PVPA barriers to closer simulate the intestinal mucosa. SNEDDSs for which pharmacokinetic data after oral dosing to rats was available in the literature were prepared, and the ability of the SNEDDSs to maintain fenofibrate solubilized during in vitro lipolysis was determined, followed by the assessment of drug permeation across the mucus-PVPA barriers. The amount of drug solubilized over time during in vitro lipolysis did not correlate with the AUC (area under the curve) of the plasma drug concentration curve. However, the AUC of the drug permeated after in vitro lipolysis displayed a good correlation with the in vivo AUC (R-2 > 0.9). Thus, it was concluded that the in vitro lipolysisemucus-PVPA permeation model, simulating the physiological digestion and absorption processes, was able to predict in vivo absorption data, exhibiting great potential for further prediction of in vivo performance of SNEDDSs. (C) 2020 American Pharmacists Association (R). Published by Elsevier Inc. All rights reserved.

Original languageEnglish
JournalJournal of Pharmaceutical Sciences
Issue number1
Pages (from-to)208-216
Number of pages9
Publication statusPublished - 2021

    Research areas

  • Gastrointestinal tract, In vitro/in vivo (IVIVC) correlation, In vitro model, Lipid-based formulation, Oral drug delivery, Permeability, Poorly water-soluble drug, Precipitation, Self-emulsifying, VESICLE-BASED BARRIER, WATER-SOLUBLE DRUGS, PERMEATION ASSAY, VIVO PERFORMANCE, FORMULATIONS, TRANSPORT, EFFICIENT

ID: 256271372