The Eminent Imminent.
Artificial Intelligence and
Supercomputers
The Next Colossi in Pharmaceuticals
-Anand Theertan, Student @ VIT
“The
pharmaceutical industry is pretty unusual. 95 per cent of what it does fails.
For an evidence-based industry, we don’t actually use a lot of it.” says Jackie
Hunter, joint director at bioinformatics start-up Benevolent AI.
Ok,
let’s rundown the facts and face the conundrum.
One.
Every 30 seconds, a scientific paper is published.
Two.
Over 10,000 a day are added towards just the medical
portion of pharmaceutical research.
Three.
Because of this ungodly number, the amount of research
that becomes ‘usable’ is only a small portion of this.
Four.
How
can you turn such a disadvantage into a table-turning, game-changing asset?
Answer?
A.I
BenevolentAI
wants to solve this by developing a tool that combs through all this data to
provide researchers and scientists with up to-date information. This leads to a
much faster rate of drug discovery, which in turn leads to a better healthcare
system for all. This firm uses their “proprietary” artificial intelligence to mine and
analyse biomedical information, from clinical trial data to academic papers.
The
reality in today’s pharmaceutical world is that in 21-st century-esque dynamic
ever-growing bulging world, big pharmaceutical giants are out for blood.
These
giants actively seek geographies for the so-called “windows”, which literally
mean a rich, fat profitable venture. Their cut-throat competition requires no
stone, in fact, not even a tiny pebble of a profitable window to left unturned.
Profit windows must be opened consistently in a profitably and logistical-sound
manner.
Benevolent
AI aims to use the predictive power of its AI algorithm to design new
molecules, extracting new hypothesis based on a knowledge graph composed of
over a billion complex dynamic relationships between genes, targets, diseases,
proteins and drugs.
They
also aim to factor in the (1) economic status of target patients, (2)
epidemiological spread of the said disease and (3) clinical trial data for a
particular drug, which is crucial for big pharmaceutical giants like Pfizer
because they would need to accentuate profits steadily.
“The
way any industry is set up is very traditional. Drug discovery hasn’t really
changed much,” Jackie summarises. “If we can show that our approach works in a
really difficult, complex dynamic sector like the pharmaceutical industry and
human biomedicine, then the potential in other less complex industries, like
agro-tech and veterinary medicine, is much greater. Any research intensive
industry could benefit from this technology.”
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