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According to a researcher from the University of Leeds, a robot-controlled laboratory where decisions are made by artificial intelligence (AI) has the potential to change the way new drugs are discovered.

Dr Richard Bourne, the engineer leading a project to develop a prototype 'lab-bot', said AI has the potential to reduce the time it takes to identify and synthesise molecules for new medicines.

The process of identifying and synthesising such molecules can take years as scientists refine the shape and property of target molecules. And in some cases, chemists have to test a million molecules before finding the most appropriate one for a certain type of medicine.

Dr Bourne, who is also an associate professor at the university's School of Chemical and Process Engineering, said the initial aim of the 'lab-bot' project is to find medicinally-active chemicals that can be used to treat conditions such as arthritis and cancer.

“This technology has the potential to fundamentally change the way drugs are discovered,” said Bourne. “Discovery chemists are involved in a ceaseless challenge to synthesise new drug molecules to the point where they can be successfully tested for medical activity.”

“But the process of reaching that point can be very slow, and that has consequences for people who are waiting for new drugs that could help alleviate painful and chronic conditions.

“If the process is rushed, then the new treatments may not be developed and new types of molecules will not be evaluated.”

Modern drug discovery often involves synthesising compounds that can act on the disease on a molecular level, one of which could be blocking proteins that are harmful to the human body.

To overcome this long process, Bourne and his colleagues, working in a suite of laboratories, are optimising the drug discovery process by bringing together machine learning and automation.

The team have also incorporated a method known as continuous flow chemistry, in which a robot-controlled system can autonomously change the parameters of a reaction until the optimal or best results are achieved.

In flow chemistry, reactions take place in narrow pipes rather than a traditional laboratory flask or reactor. In the system at Leeds, the reaction is contained in pipes that are smaller than a millimetre in diameter – making it possible to have greater control of the reactants.

Meanwhile, an AI system continuously monitors the outcome of the reactions, compares the results from other experiments held in an online database and then alters the parameters – such as temperature or pressure – until the optimal result is achieved.

“Our research at Leeds is about finding a balanced approach, so new molecules are found that are safe and reliable but are discovered in a timely manner,” Bourne added. “We believe by harnessing artificial intelligence we can achieve that accelerated approach.”

Dr Bourne has recently been awarded one of three Senior Research Fellowships by the Royal Academy of Engineering to further the investigation.

The award also complements a £3.5m grant made by the Engineering and Physical Sciences Research Council to Bourne and his academic partners to further ideas around “cognitive chemical manufacturing”.

Professor Karen Holford, chair of the Academy’s Research Committee, said: “I am delighted to welcome these leading researchers to join us.

“Working closely with their industrial partners, each awardee will establish a world-leading research group in their field of engineering that will ultimately help to generate real economic benefits.”

In September, experts at Heriot-Watt University, Edinburgh, claimed that the high-resolution capabilities of a new generation of medical imaging technologies could greatly enhance the ability to diagnose and treat a range of cancers.

In August, the Government announced that it had invested £250m for the creation of a National Artificial Intelligence Lab that will help the NHS more effectively treat conditions such as cancer, dementia and heart disease.

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