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Thu 22nd June
Firm to reduce animal testing
A YORK company specialising in software for medical science has developed a system which it claims will reduce the need for laboratory testing on animals.

Working with scientists at the University of York, SimOmics has created an online data sharing system which will allow chemical formulations to be shared between companies, eliminating the need for many tests on animals.

SimOmics, a spin-out company which includes scientists from the University’s electronic engineering, environment, mathematics, and computer science departments, developed the system for the agricultural chemical production industry.

To ensure human safety, agricultural chemical formulations, such as pesticides, are tested on animals for acute oral, skin and eye irritation classification.

For confidentiality reasons, the chemical formulations are not shared between companies, which mean that other interested companies maybe testing the same formulas, requiring yet more animal experimentation.

Professor Jon Timmis, head of the University’s Department of Electronic Engineering and chief executive of SimOmics, said: “It is crucial that agricultural chemical products are tested before they are used in the environment.

“Small animals, such as rats and rabbits, are currently used to test chemical formulations, but there is now a growing commitment across the industry to reduce the number of animals used in testing and eventually replace them altogether.

“We estimate that the new system we are working on could reduce the need for tests on more than 1,000 animals a year.” 

The SimOmics team has been awarded £100,000 from the National Centre for the Replacement, Refinement and Reduction of Animals in Research (NC3Rs), to develop a system that will pool existing animal data together with non-animal data and mathematical models to determine acute oral, skin and eye irritation classifications while maintaining confidentiality of agrochemical company formulations.

Supported by the NC3Rs, and agrochemical companies Syngenta, and Dow Agrochemical scientists, the project will aim to deliver a new system to confidently classify mixtures of chemicals based on existing data.

This will then present the user with options to locate results without having to conduct any further testing on animals. York mathematicians and computer scientist will produce algorithms that allow the new tool to make predictions based on testing data already available.

Mr Timmis added: “We have seen much industry support for this already, so we are looking forward to launching the system within the next 12 months.”

For more information, please visit the York Press website

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