Heavy regulation has led to a
conservatism reflected in the
industry’s belated adoption of new
technologies and a reluctance to
experiment with new business
models or approaches.
During last decade, as blockbuster
drug patents expire and as governments clamp down on pricing, life
sciences companies face unprecedented pressure to reduce costs
and improve productivity, making
technologies like artificial intelligence ever more necessary for
success. Add to this the shift from
small molecule drugs to specialty,
oncology, and orphan therapies
aimed at smaller populations.
Traditional mass-marketing will
just not work in that environment—targeted, more personalized outreach is required.
ARNO SOSNA: There is significant potential for life sciences to
leverage AI and drive greater effectiveness in commercializing new
drugs and treatments. Life sciences
is especially poised to derive value
from AI because of the significant
volume of data companies store
and process—perhaps more than
any other industry because of the
stringent regulations to document
everything. All of this data will
be foundational to running advanced statistics and analytics. So
organizations are in a tremendous
position to use AI for predictive
analytics and more data-driven
decision-making across their commercial efforts. AI will enable the
industry to automate commercial
processes to improve efficiency in
bringing products to market and
keep pace with the investments
they are making in drug development.
CHRISTOPHER BOONE: The
potential for AI to transform the
healthcare industry may be more
“Machine learning is
gaining broader traction in commercial operations, transforming
the way the industry
collects, synthesizes,
and uses data.”
In 2016, a stunning $8 to $12 billion was invested in artificial intelligence (AI), or machine learning,
according to a report by McKinsey.
The report also stated that healthcare is one of three industries
seeing the greatest profit margin
increases as a result of AI adoption, while Reuters reported that
“the world’s drug companies are
turning to artificial intelligence to
improve the hit-and-miss business
of finding new medicines.”
There are 9,500 drugs now in
Phase One through Phase Three
clinical trial development. This is
a pretty remarkable number, but
what’s more impressive is that it’s
growing at a rapid pace, about
20% over the last five years: three-quarters of what’s in the pipelines
are considered potential to be first-in-class, and that is often where
you see some of the step changes
in bringing new, novel drugs and
therapies to the marketplace. AI
will help us get there even faster.
Early business uses of AI have
proven successful in drug discovery, particularly in predicting molecule-target bonding,
identifying new biomarkers, and
uncovering new drug indications.
Now machine learning is gaining
broader traction in commercial
operations, too, transforming the
way the industry collects, synthesizes, and uses data.
New industry standards and de-
velopment frameworks are making
it easier and faster for software
developers to build solutions for
machine learning. As well, ad-
vanced computing hardware such
as graphic processing units (GPUs)
and chipsets are processing vast
amounts of data faster than ever
before—so much so that they are
being characterized as bionic.
Actionable insights help brand
managers, field reps, and medical
science liaisons improve decision-making and take smarter actions
to personalize their engagement
with healthcare professionals and,
ultimately, achieve greater commercial success.
It brings data together that we
have on the commercial side—
field data, digital data, patient data,
claims data—unifying it to make
sense and derive insights. But insights are only valuable if you can
connect them with action.
How do you take the mass amount
of resources that you have and
apply them in a smarter way? How
do you shift those resources up
and down and turn up the volume
and target different sets of customers and change your messaging
and do that on a dime? It’s about
being more dynamic in your commercial model.
Here’s a deeper dive into how that
will happen, with the assistance of
AI.
Why is healthcare one of the top
industries seeing the greatest
profit in artificial intelligence?
DAVID EHRLICH: The life sciences industry is a natural hot zone
for the application of analytics and
artificial intelligence. It’s got an
abundance of available data and
complex business challenges, such
as discovery of new compounds
amongst millions of possibilities
and a disconnected buying process
that lacks typical pricing signals.
