AstraZeneca and research partners drive wider application of machine learning to better understand the impact of chemicals on the environment

    AstraZeneca and research partners have published Environmental Science and Technology paper explaining how machine learning can be used to better understand the impact of chemicals on the environment

     Environmental Protection is a key sustainability priority at AstraZeneca with the aim to reduce environmental impacts on human health and the natural world

   Research team now call for greater collaboration and more training for scientists in this field to learn these new skills to better meet the future challenges of scientific discovery
 

Today, together with researchers at Kings College London, the Universities of Northumbria and Suffolk, and the Francis Crick Institute, AstraZeneca published a paper in Environmental Science and Technology calling for the wider application of machine learning in environmental toxicology research, to reduce the burden on animal testing and better meet the future challenges of scientific discovery.

Environmental Protection, together with Access to Healthcare and Ethics and Transparency, is a key priority of the approach to sustainability at AstraZeneca. Our scientific approach to environmental sustainability reduces our environmental impact by protecting our air, land and water, reducing our dependence on natural resources and ensuring the environmental safety of our products.

This publication is the result of an ongoing collaboration between AstraZeneca and academic partners, who have been working together to see how machine learning can help us to better understand the impact of chemicals on the environment.

Pollution from contaminants continues to be a cause for concern, not only on the environment but also for public health. To understand the effects of this pollution, the research team wanted to look specifically at how chemicals can accumulate in fish and invertebrates. Until now, the only viable way to really understand the impact was to study live animals. While this method remains the norm – and while governments still require these tests before chemicals can be sold – the group of scientists have now shown that there are alternative approaches.

In the Environmental Science and Technology paper, the research team calls for these methods to be applied to a much wider range of environmental toxicology data and have published a call to action to the international community to follow their lead. The team are asking for greater collaboration and more training for scientists in this field to learn these new skills. They also calling on governments and regulators to rise to the challenge and embrace machine learning.

Dr Stewart Owen, Principal Scientist, AstraZeneca commented: “Machine learning is increasingly being used to innovate and solve complex problems across all industries, from financial services to healthcare. However, we need to accelerate our understanding and application of these tools to better understand and respond to the environmental challenges we face as a society. In doing so, we can begin to push the boundaries of science today, to support us in meeting the greatest challenges of tomorrow more effectively.”

The collaboration is funded by the Biotechnology and Biological Sciences Research Council (BBSRC) and AstraZeneca through a project called “iNVERTOX: Rapid intelligent in silico prediction of sub-lethal ecotoxicological effects in invertebrates following pharmaceutical exposure” (Ref BB/P005187/1). By harnessing emerging technologies and artificial intelligence, the team were recently able to use computers to analyse data and provide useful insights that can potentially reduce the burden of animal testing in research. To learn more about this work click here.