Testing drugs with the help of mathematical modelling

Lead Research Organisation: University of Glasgow
Department Name: School of Engineering


An important question that needs to be answered is: are there ways in which new drugs can be developed more time and cost efficiently while limiting the use of animals for testing?
Before a new drug can be authorised for human usage, it needs to pass a series of screening tests. These take years to complete and by the time the final screening processes are reached, millions of pounds have already been spent in the development of the new drug. Often the early screening techniques which are used are far from realistic which is why many drugs pass these early tests, however most will fail in the final stages. This is a problem that must be solved as the pharmaceutical companies involved in the development of drugs are losing a lot of time and money, and animals are being used unnecessarily in the final stages of testing.

In the early stages, testing usually consists of exposing cells or tissues to compounds in an in-vitro environment. Traditionally this involved a single layer of cells at the bottom of a petri dish filled with some fluid containing the compound. However, it is increasingly being recognised that more physiologically relevant in-vitro models are required [1]. There has therefore been a move to 2D and 3D systems which include multiple layers of cells; clusters of cells; cells contained within matrices and scaffolds and different combinations of these linked together using advanced cell culture apparatus. The inclusion of flow is becoming common in commercially available bioreactor systems [1,2]. Whilst these advances have provided enormous opportunity to fine-tune drug testing systems, to date this has not been achieved. An important question arises: what are the optimal experimental conditions which best mimic reality? Of course this will depend on the system at hand, however mathematical modelling can provide insights which can help to answer this important question.

This project will mathematically model in-vitro drug testing systems. These models will be used to define an optimal set of experimental conditions that will give rise to the most clinically-relevant results.

i. Review the literature and identify a subset of systems where new mathematical modelling approaches are needed most
ii. Develop mathematical models of fluid flow and nutrient/drug transport through 3D configurations of cells under controlled conditions
iii. Validate the models against experimental data from the literature and/or from interaction with collaborators
iv. Develop mathematical models of the effect of the environment on the behaviour and health of the cells/tissue
v. Use the mathematical models to provide guidance on the optimal experimental set-up for drug toxicity testing in the areas identified.

Mathematical modelling can be used to identify the optimal conditions for testing drugs as it offers a framework which helps us understand how drugs and nutrients permeate through cells and clusters of cells (spheroids) [3]; the exposure and release of biomarkers; the effect of changes to the spatial arrangement and density of cells; the effect of flow and the exchange of nutrients and compounds within the media [1,2]. This will allow more realistic testing systems to be developed which will be more indicative of the outcome of the clinical in vivo tests.

The models that will be developed in this project will be new and will be driven by the goal of developing systems which will identify drugs doomed to failure earlier. Regular conversations with relevant experimentalists and companies (e.g. Kirkstall Ltd) will be held to ensure the research remains relevant and well-informed. The models to be developed have the potential to lead to new design tools and to enable the rational design of new and more realistic drug testing systems.
Alignment with EPSRC Strategies and Research Areas
This research sits broadly within the he

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/N509668/1 01/10/2016 30/09/2021
1804827 Studentship EP/N509668/1 01/10/2016 31/03/2020 Lauren Hyndman