Artificial intelligence (AI) could transform the pharmaceuticals industry and help develop new treatments for the likes of Alzheimer’s, rheumatoid arthritis and cancer, with research showing that technology could both speed up drug discovery and improve success rates.

Carried out by analytics firm GlobalData, the recent study found that AI was at the top of the list of technologies expected to have the biggest impact over the next 12 months, the Guardian reports.

The biggest drugmakers in the world – including AstraZeneca, GSK, Sanofi, Pfizer, Johnson & Johnson and Myers Squibb – are all now investing in AI, whether that’s through acquiring technologies or through collaborations.

And figures from US research firm Trinity Life Sciences show that around 90 per cent of big pharmaceutical firms started AI projects in 2020. 

GSK and AstraZeneca – the two biggest drugmakers in the UK – committed to a five-year partnership with Cambridge University to set up the Cambridge Centre for AI in Medicine, with the aim being to develop technologies to improve personalised medicine, improve clinical trials and aid drug discovery.

As explained by the news source, AI uses automated algorithms (the instructions that computers follow) to carry out tasks previously done by humans, going through large datasets to detect hidden patterns, as well as performing tasks in a matter of seconds, which would usually take months.

Karen Taylor, director of the Centre for Health Solutions at accounting and consultancy group Deloitte, said: “Drug discovery is being transformed through the use of AI, which is reducing the time it takes to mine the vast amounts of scientific data to enable a better understanding of disease mechanisms and identify new potential drug candidates. Traditional drug discovery has been very fragmentary, very hit and miss.”

Machine learning is also being used to help find new uses for existing drugs, with a recent article in Engineering & Technology magazine covering new research being done at Ohio State University to help find candidates for drug repurposing, as well as predicting the effects medications could have on certain outcomes.

The project involves using machine learning techniques to analyse datasets from millions of people, focusing on repurposing medication originally intended to prevent heart failure and stroke to treat coronary artery disease.

This represents the first time that this method has been used to mimic clinical trials, potentially allowing researchers to identify many more drugs that could be used for more than their current purpose.

Drug repositioning can make cost-effective treatments more available to patients with various different illnesses, including cancer. Developing and bringing new drugs to market is both costly and time-consuming, but repurposing existing licenced non-cancer drugs could potentially provide safe and less expensive treatments.

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