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

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.

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Publication Details

Journal
International Journal of Pharmaceutics
Published
2024-10-14
DOI
https://doi.org/10.1016/j.ijpharm.2024.124827
Citations
4
Primary Topic
Analytical Chemistry and Chromatography
Type
article
Field-Weighted Citation Impact
0.96

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article

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

Amy L. Harding, Helen Colley, S. David Webb, Rachel N. Bearon et al.
4 citations
International Journal of Pharmaceutics
Analytical Chemistry and Chromatography
0.96
article

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

Amy L. Harding, Helen Colley, S. David Webb, Rachel N. Bearon, Craig Murdoch, Joseph Leedale, Sean M. Edwards
article en
4 citations

Abstract

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.

International Journal of PharmaceuticsVol. 666
University of Liverpool (GB), Syngenta (United Kingdom) (GB), Syngenta (Switzerland) (CH), University of Sheffield (GB)
National Centre for the Replacement, Refinement and Reduction of Animals in Research, Sheffield Teaching Hospitals NHS Foundation Trust
Openalex Percentile: Top 27%
Analytical Chemistry and Chromatography
0.96
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