Artificial intelligence may have been hyped – but when it comes to medicine, it already has a proven track record. So can machine learning rise to this challenge of finding a cure for this terrible disease? There is no shortage of companies trying to solve the dilemma.
It feels as if a superhuman effort is needed to help ease the global pandemic killing so many. Artificial intelligence may have been hyped – but when it comes to medicine, it already has a proven track record.
So can machine learning rise to this challenge of finding a cure for this terrible disease?
There is no shortage of companies trying to solve the dilemma.
Oxford-based Exscientia, the first to put an AI-discovered drug into human trial, is trawling through 15,000 drugs held by the Scripps research institute, in California.
And Healx, a Cambridge company set up by Viagra co-inventor Dr David Brown, has repurposed its AI system developed to find drugs for rare diseases.
The system is divided into three parts that:
- trawl through all the current literature relating to the disease
- study the DNA and structure of the virus
- consider the suitability of various drugs
Drug discovery has traditionally been slow.
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“I have been doing this for 45 years and I have got three drugs to market,” Dr Brown told BBC News.
But AI is proving much faster.
“It has taken several weeks to gather all the data we need and we have even got new information in the last few days, so we are now at a critical mass,” Dr Brown said.
“The algorithms ran over Easter and we will have output for the three methods in the next seven days.”
Healx hopes to turn that information into a list of drug candidates by May and is already in talks with labs to take those predictions into clinical trials.
For those working in the field of AI drug discovery, there are two options when it comes to coronavirus:
- find an entirely new drug but wait a couple of years for it to be approved as safe for use
- repurpose existing drugs
But, Dr Brown said, it was extremely unlikely one single drug would be the answer.
And for Healx, that means detailed analysis of the eight million possible pairs and 10.5 billion triple-drug combinations stemming from the 4,000 approved drugs on the market.
Prof Ara Darzi, director of the Institute of Global Health Innovation, at Imperial College, told BBC News: “AI remains one of our strongest paths to achieve a perceptible solution but there is a fundamental need for high quality, large and clean data sets.
“To date, much of this information has been siloed in individual companies such as big pharma or lost in the intellectual property and old lab space within universities.
“Now more than ever there, is a need to unify these disparate drug discovery data sources to allow AI researchers to apply their novel machine-learning techniques to generate new treatments for Covid-19 as soon as possible.”
In the US, a partnership between Northeastern University’s Barabasi Labs, Harvard Medical School, Stanford Network Science Institute and biotech start-up Schipher Medicine is also on the search for drugs that can quickly be repurposed as Covid-19 treatments.
Read more: www.bbc.com