Big pharma turns to artificial intelligence to speed drug discovery
Big pharma turns to artificial intelligence to speed drug
discovery, GSK signs deal
By Ben Hirschler July 1, 2017
LONDON (Reuters) - The world's leading drug companies are
turning to artificial intelligence to improve the hit-and-miss business of
finding new medicines, with GlaxoSmithKline unveiling a new $43 million deal in
the field on Sunday.
Other pharmaceutical giants including Merck & Co,
Johnson & Johnson and Sanofi are also exploring the potential of artificial
intelligence (AI) to help streamline the drug discovery process.
The aim is to harness modern supercomputers and machine
learning systems to predict how molecules will behave and how likely they are
to make a useful drug, thereby saving time and money on unnecessary tests.
AI systems already play a central role in other high-tech
areas such as the development of driverless cars and facial recognition
software.
"Many large pharma companies are starting to realise
the potential of this approach and how it can help improve efficiencies,"
said Andrew Hopkins, chief executive of privately owned Exscientia, which
announced the new tie-up with GSK.
Hopkins, who used to work at Pfizer, said Exscientia's AI
system could deliver drug candidates in roughly one-quarter of the time and at
one-quarter of the cost of traditional approaches.
The Scotland-based company, which also signed a deal with
Sanofi in May, is one of a growing number of start-ups on both sides of the
Atlantic that are applying AI to drug research. Others include U.S. firms Berg,
Numerate, twoXAR and Atomwise, as well as Britain's BenevolentAI.
"In pharma's eyes these companies are essentially
digital biotechs that they can strike partnerships with and which help feed the
pipeline," said Nooman Haque, head of life sciences at Silicon Valley Bank
in London.
"If this technology really proves itself, you may
start to see M&A with pharma, and closer integration of these AI engines
into pharma R&D."
STILL TO BE PROVEN
It is not the first time drugmakers have turned to
high-tech solutions to boost R&D productivity.
The introduction of "high throughput
screening", using robots to rapidly test millions of compounds, generated
mountains of leads in the early 2000s but notably failed to solve
inefficiencies in the research process.
When it comes to AI, big pharma is treading cautiously,
in the knowledge that the technology has yet to demonstrate it can successfully
bring a new molecule from computer screen to lab to clinic and finally to
market.
"It's still to be proven, but we definitely think we
should do the experiment," said John Baldoni, GSK's head of platform
technology and science.
Baldoni is also ramping up in-house AI investment at the
drugmaker by hiring some unexpected staff with appropriate computing and data
handling experience - including astrophysicists.
His goal is to reduce the time it takes from identifying
a target for disease intervention to finding a molecule that acts against it
from an average 5.5 years today to just one year in future.
"That is a stretch. But as we've learnt more about
what modern supercomputers can do, we've gained more confidence," Baldoni
told Reuters. "We have an obligation to reduce the cost of drugs and
reduce the time it takes to get medicines to patients."
Earlier this year GSK also entered a collaboration with
the U.S. Department of Energy and National Cancer Institute to accelerate
pre-clinical drug development through use of advanced computational
technologies.
The new deal with Exscientia will allow GSK to search for
drug candidates for up to 10 disease-related targets. GSK will provide research
funding and make payments of 33 million pounds ($43 million), if pre-clinical
milestones are met.
(Reporting by Ben Hirschler; Editing by Adrian
Croft/Keith Weir)
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