The Potential for AI in Life Sciences
AI and machine learning promise to transform life sciences.
How companies might prepare for a smarter future.
By Siniša Belina, Amplexor Life Sciences
From accelerating scientific breakthroughs and spotting previously elusive patterns in unwieldy global data masses, to enabling reater drug personalization, the scope
for artificial intelligence in life sciences seems
And, as other industries are experiencing, the
technology already is tangible and something they
must start planning for.
Intelligent internet and content searches that
adapt to user preferences, automated personal
assistants like Alexa and Siri, and customer care
channels such as web chat, already are exploiting
AI in everyday situations.
Via machine learning, a subset of AI, algorithms
don’t just make clever connections and spot trends
in masses of data. They also become increasingly
refined and efficient at this over time, responding
to the conditions they are exposed to and the
results they find, all of which adds to the speed of
Automation is a big attraction of the AI
proposition. If machines can get to grips with
routine knowledge work, and do it more rapidly
than humans ever could, it makes sense to pass
along the load, freeing up experts for value-added
work—as long as humans continue to perform
quality checks on what AI systems are doing.
In frontline healthcare, smart systems already
are making headway in patient diagnostics. Just
recently, U.K. researchers in Oxford announced
the availability of AI technology that can diagnose
heart disease and lung cancer at a much earlier
stage from analysis of patient scans.
Meanwhile, connected devices are being used
increasingly to feed patients’ data to those