Defining drug delivery into and across the oral mucosa using a tissue engineering and mathematical modelling approach

Most drugs are delivered either orally in tablet form or by injection. However, these routes have a number of drawbacks such as drug degradation by xenobiotic enzymes in the liver or patient discomfort and needle anxiety, which has led to the search for different modes of treatment. Drug delivery into or through the highly permeable oral mucosa using mucoadhesive pastels, films or patches offers pain-free, self-administration of drugs and is therefore an attractive alternative. These devices could also be used to treat several oral diseases such as recurrent ulcers, autoimmune conditions like oral lichen planus or candidiasis (thrush) that affect a surprisingly large proportion of the population. These oral diseases are often very painful, make chewing and swallowing difficult and can significantly impair quality of life.

The increased interest in mucoadhesive drug delivery systems in recent years has led to additional use of animal experiments to test different formulations or drug delivery devices. Optimising oral mucosal-mediated drug delivery is extremely important. We believe that the best and most efficient way to do this is to use mathematical models parameterised by data from in vitro tissue engineered oral mucosal drug delivery experiments to predict the optimal drug concentration, duration of delivery device contact and other variables that can then be further tested in the laboratory. Adoption of this methodology would lead to a marked decrease in the numbers of animals used for these studies. Unfortunately, at present, mathematical models representing the oral mucosa for this purpose have not yet been developed. Our overall aim is to readdress this omission by using biological data obtained from in vitro studies to create an in silico oral mucosal model that can be used to predict oral mucosal drug delivery outcomes for a variety of drugs, expediating their transition to clinical use.

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Project grant

Status

Pending start

Institution

University of Sheffield

Grant reference number

NC/W001160/1

Award date

Sep 2021 - Dec 2023

Grant amount

£430,354