- Title: How AI robots are hunting for new drugs
- Date: 10th August 2017
- Summary: SHEFFIELD, ENGLAND, UK (FILE - JUNE 2017) (REUTERS) VARIOUS OF RESEARCHERS AT THE SHEFFIELD INSTITUTE FOR TRANSLATIONAL NEUROSCIENCE, SITRAN
- Embargoed: 24th August 2017 13:26
- Keywords: AI artificial intelligence Benevolent AI pharmaceuticals IBM
- Location: LONDON & SHEFFIELD, ENGLAND, UK/ZURICH, SWITZERLAND
- City: LONDON & SHEFFIELD, ENGLAND, UK/ZURICH, SWITZERLAND
- Country: Various
- Topics: Life Sciences,Science
- Reuters ID: LVA0056TKQ3IZ
- Aspect Ratio: 16:9
- Story Text: Artificial intelligence (AI) robots are turbo-charging the race to find new drugs for conditions like nerve disorder ALS or motor neurone disease.
The robots - complex software run through powerful computers - work as tireless and unbiased super-researchers. They analyse huge chemical, biological and medical databases, alongside reams of scientific papers, far quicker than humanly possible, throwing up new biological targets and potential drugs.
If the research goes on to deliver new medicines, it would mark a notable victory for AI in drug discovery, bolstering the prospects of a growing batch of start-up companies focused on the technology.
BenevolentAI is one of a handful of British "unicorns" - a start-up private company with a market value above $1 billion, in this case $1.7 billion - which is rapidly expanding operations at its offices in central London.
Jackie Hunter, CEO of BenevolentAI's bioscience industries department, BenevolentBio, says the company's technology will help drug companies' process huge amounts of data already available.
"(It) allows us to ingest vast quantities of publicly available literature, databases that we pay to access like patent databases and then we can use our technology first of all to be able to recognize the individual entities in that data - drugs, targets, genes, proteins - and then we can use the natural language processing to be able to recognise relationships between those entities and use artificial intelligence to refine that and create an extremely large knowledge graph that contains over a billion known relationships," she told Reuters, adding: " From that we can make inferences about what relationships shouldn't be known but are not yet discovered."
She says AI robots won't replace scientists and clinicians, but they should save time and money by finding drug leads several times faster than conventional processes.
"What we're trying to do here is to democratise the drug discovery process, put the tools in the hands of the drug discovers and help them use their insight, give them more information to apply their expert knowledge and you come up with new relationships and targets," she explained.
One candidate proposed by AI machines recently produced promising results in preventing the death of motor neurone cells and delaying disease onset in preclinical tests in Sheffield.
There are only two drugs approved by the U.S. Food and Drug Administration to slow the progression of ALS (amyotrophic lateral sclerosis), one available since 1995 and the other approved just this year. About 140,000 new cases are diagnosed a year globally and there is no cure for the disease, famously suffered by cosmologist Stephen Hawking.
Unlike humans, who may have pet theories, AI scans through data and generates hypotheses in an unbiased way.
Conventional drug discovery remains a hit-and-miss affair and Hunter believes the 50 percent failure rates seen for experimental compounds in mid- and late-stage clinical trials due to lack of efficacy is unsustainable, forcing a shift to AI.
A key test will come with a Phase IIb study by Benevolent to assess a previously unsuccessful compound from Johnson & Johnson in a new disease area - this time for treating Parkinson's disease patients with excessive daytime sleepiness.
Big pharmaceutical companies like GSK, Sanofi and Merck are now exploring the potential of AI through deals with start-ups.
They are treading cautiously, given the failure of "high throughput screening" in the early 2000s to improve efficiency by using robots to test millions of compounds. Yet AI's ability to learn on the job means things may be different this time.
Technology giants including Microsoft, IBM and Google's parent Alphabet are also setting up life sciences units to explore drug R&D.
For Benevolent's Hunter, today's attempts to find new drugs for ALS and other difficult diseases marks an important test-bed for the future of AI, which is already being deployed in other high-tech areas such as autonomous cars.
"The aim is to show that we can deliver in a very difficult and complex area. I believe if you can do it in drug discovery and development, you can show the power of AI anywhere."
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