Defining drug delivery into and across the oral mucosa using a tissue engineering and mathematical modelling approach
Lead Research Organisation:
University of Sheffield
Department Name: Clinical Dentistry
Abstract
Most drugs are delivered either in tablet form or by injection. However, these routes have a number of drawbacks such as drug degradation before reaching the bloodstream or patient discomfort and needle anxiety, which has led to the search for different modes of treatment. Drug delivery into or through the oral mucosa (the tissue that lines the inside of the mouth) using adhesive devices such as 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, painful lesions and fungal infections (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.
Although drug-containing devices have been developed for the skin (e.g., nicotine patch), this tissue is highly impermeable and so delivering drugs into or through it and into the bloodstream is difficult and inefficient. However, the oral mucosa is vastly more permeable than skin making it an ideal target for drug delivery either directly to the oral tissue or into the circulation, depending on the type of drug delivered. At present there are very few drugs that are delivered via the oral mucosa but advancement in the way in which oral drug delivery devices are manufactured has created new interest in this area, in particular for needle-free drug delivery.
Optimising oral mucosal drug delivery is extremely important. The best and most efficient way to do this is to use mathematical and computational models. Mathematical models are exceptionally useful tools for studying biological systems and are being increasingly used in medical research. By writing down the underlying physical and biochemical processes of a biological system in the form of mathematical equations, one can quickly and efficiently simulate these biological processes on a computer. These mathematical models can then be used to test many different theories, make predictions and trial numerous experimental scenarios virtually by computer simulation. Importantly, the net effect of their use is to reduce the number of animal experiments needed in drug development research. A good mathematical model of drug delivery can forecast how to best optimise treatment by determining such factors as: how long the drug will stay in the mucosal tissue or how quickly it will enter the bloodstream, how often to take the drug, the ideal chemical properties of the drug and the differences between drug delivery to healthy and diseased human tissue.
Unfortunately, at present, mathematical models representing the oral mucosa for this purpose have not yet been developed. Our aim is to readdress this by using biological data obtained from human tissue to create a virtual oral mucosal model that can then be used to predict drug delivery outcomes for a variety of different drugs. It is envisaged that this will dramatically increase the number of drugs that will be available for injection-free mucosal delivery.
Although drug-containing devices have been developed for the skin (e.g., nicotine patch), this tissue is highly impermeable and so delivering drugs into or through it and into the bloodstream is difficult and inefficient. However, the oral mucosa is vastly more permeable than skin making it an ideal target for drug delivery either directly to the oral tissue or into the circulation, depending on the type of drug delivered. At present there are very few drugs that are delivered via the oral mucosa but advancement in the way in which oral drug delivery devices are manufactured has created new interest in this area, in particular for needle-free drug delivery.
Optimising oral mucosal drug delivery is extremely important. The best and most efficient way to do this is to use mathematical and computational models. Mathematical models are exceptionally useful tools for studying biological systems and are being increasingly used in medical research. By writing down the underlying physical and biochemical processes of a biological system in the form of mathematical equations, one can quickly and efficiently simulate these biological processes on a computer. These mathematical models can then be used to test many different theories, make predictions and trial numerous experimental scenarios virtually by computer simulation. Importantly, the net effect of their use is to reduce the number of animal experiments needed in drug development research. A good mathematical model of drug delivery can forecast how to best optimise treatment by determining such factors as: how long the drug will stay in the mucosal tissue or how quickly it will enter the bloodstream, how often to take the drug, the ideal chemical properties of the drug and the differences between drug delivery to healthy and diseased human tissue.
Unfortunately, at present, mathematical models representing the oral mucosa for this purpose have not yet been developed. Our aim is to readdress this by using biological data obtained from human tissue to create a virtual oral mucosal model that can then be used to predict drug delivery outcomes for a variety of different drugs. It is envisaged that this will dramatically increase the number of drugs that will be available for injection-free mucosal delivery.
Technical Summary
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.
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.
