Animal testing is one of the most contentious issues in today’s chemical industry. Both sides of the fight, whether strongly against, or of the view that it is the better of two evils, agree that the moral choice is a difficult one. It is obvious that the perfect solution would be to develop a way of testing a drug’s safety and effectiveness without using animals.
Every new chemical developed today is extensively tested before it’s even allowed to be tested on humans never mind being released for public use. Standard protocols typically require around 4 years of testing which costs between £3-4 million and uses over 4000 animals. Despite this, all these resources don’t necessarily mean that there is zero risk of the chemical having adverse effects when taken by humans.
This wasteful nature of the chemical testing industry has recently become under focus prompting The National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs) to joint fund an almost £750k grant into finding innovative ways to increase the efficiency of the protocols. And strangely, it isn’t new biology or chemistry techniques that are being investigated, but mathematical ones.
A York-based, interdisciplinary team, lead by mathematician Dr Jon Pitchford, was one of only four research projects to be awarded a portion of this grant to investigate how mathematical techniques might be used to streamline the testing practices. Together with Dr James Cussens in Computer Science, Jon and his team plan to use a mathematical technique known as Bayesian Networks to exploit existing data.
This involves analysing the results of previous tests in order to better predict how chemicals will react in the future. They hope that by analysing the results they should be able to actually quantify the value of each stage of the standard protocol and so identify which are the key studies necessary to evaluate a chemical and which are dispensable. They will also analyse what levels of imprecision can be tolerated in the results so they may be able to reduce the numbers of animals tested on by obtaining sufficient precision with a smaller sample size. They hope it may even be possible to replace animal testing all together in some cases where it can be proved that this stage doesn’t lower the risk associated with a particular chemical.
Pitchford explains how this project is a perfect example of “how maths is a universal language and that problems can be solved by borrowing ideas and inspiration from diverse sources. This toxicology work is based on work I’ve done on how fish swim, how little old ladies break their bones, and how plants fight for nutrients in the soil. And it’s very “interdisciplinary”, something which we do well at York.”