An advanced in silico model of the oral mucosa reveals the impact of extracellular spaces on chemical permeation

[Display omitted] •Developments in drug delivery have prompted interest in chemical permeation via the oral mucosa.•Improvements to in silico modelling could aid research in this area.•In vitro data with mechanistic and finite element modelling drive a new in silico platform.•This in silico approach predicts chemical permeation of oral mucosa. Accurately predicting the permeation of chemicals through human epithelial tissues is crucial for pharmaceutical therapeutic design and toxicology. Current mathematical models of multi-layered stratified squamous epithelium such as those in the oral cavity use simplistic ‘bricks and mortar’ geometries that do not fully account for the complex cellular architecture that may affect chemical permeation in these tissues. Here we aimed to develop a new, advanced mechanistic mathematical model of the human epithelium that more accurately represents chemical tissue permeation. Using measurements of cell size and tortuosity from micrograph images of both human oral (buccal) and tissue-engineered buccal mucosa along with mechanistic mathematical modelling, we show that the convoluted geometry of the extracellular spaces within the epithelium significantly impacts chemical permeation. We next developed an advanced histologically and physiologically-relevant in silico model of buccal mucosal chemical permeation using partial differential equations, fitted to chemical permeation from in vitro assay data derived from tissue-engineered buccal mucosal models and chemicals with known physiochemical properties. Our novel in silico model can predict epithelial permeation kinetics for chemicals with different physicochemical properties in the absence or presence of permeability enhancers. This in vitro − in silico approach constitutes a step-change in the modelling of chemical tissue permeation and has the potential to expedite pharmaceutical innovation by improved and more rapid screening of chemical entities whilst reducing the need for in vivo animal experiments.