Translating in vitro buccal permeation to in vivo and whole‑body exposure using in silico cell‑based and physiologically-based pharmacokinetic modelling

There is increasing interest in the delivery of chemicals to or through the oral buccal mucosa to avoid first-pass metabolism by the liver or the use of needles, which are associated with oral or parenteral administration. Moreover, buccal mucosa is several times more permeable than skin, making it an attractive route for controlled drug delivery via mucoadhesive films, tablets, and patches. Developing in silico models to predict rates of chemical permeation would greatly expediate experimental discovery to clinical use. However, predicting chemical permeation through the buccal mucosa is challenging due to limited availability of ex vivo human tissue for experimentation. Previously, we used tissue engineered buccal mucosa to parameterise an in silico model of buccal chemical permeation using partial differential equations, fitted to in vitro generated chemical permeation data of chemicals with known physiochemical properties. Here, we describe a new approach to predict in vivo permeation from in vitro data. The importance of the permeability barrier is included explicitly in the in silico models by parameterising from in vitro permeation experiments on buccal epithelium with fully formed or deficient permeability barriers. In vivo predictions are made by mapping mechanistic parameters, fitted to in vitro data, to in vivo cell geometry including cell layer thicknesses, cell-sizes and extracellular space. The predictions are tied to a physiologically-based pharmacokinetic model for whole-body chemical distribution that is validated against in vivo data. This combined in vitro-in silico approach has the potential to reduce animal experimentation and improve in vivo predictions for human buccal mucosa.