“An Open Approach to Big Data” – Driving Transformative Change in the Pharmaceuticals Sector

Big pharma has long focused on the lucrative
business of drug development, supported by armies of sales people deployed to
persuade physicians to choose its medicines. But emerging digital technologies
are reshaping the landscape. A new generation of companies is using big data,
sensors and artificial intelligence to provide precise real-time monitoring of
patients, especially those suffering from conditions such as diabetes and
chronic obstructive pulmonary disease, which are imposing a daunting burden on
overstretched health budgets.

As a result of the products and services these
companies are developing, a patient’s primary point of contact with the health
system can now be a remote monitoring centre,
or disembodied voice on the telephone, instead of a doctor’s office.

The Asia-Pacific region is set
to lead the way in the Internet of Things (IoT) market: According to research firm IDC, out of an estimated 29.5 billion
devices connected globally by 2020, 8.6 billion will be found in this part of
the world, with healthcare being one of the leading industries in the booming
IoT market.

Against the backdrop of housing over half of the world’s population,
Asia’s drug industry is estimated to be worth US$168 billion and growing at a
rate of over 12 percent per annum[1].
As Asian countries develop economically, their healthcare expenditure is also
increasing exponentially. The region’s growing middle class and an ageing population have increased the market
demand for non-essential and therapeutic treatments.

As healthcare providers look
to overhaul outdated models to cater to an increasingly connected society, ageing population and growing incidence of
chronic diseases, we are seeing major initiatives that leverage technology to
improve healthcare delivery and R&D in the region. Ng Teng Fong General
Hospital has high standards of data use for seamless and effective quality care
for its patients. Tan Tock Seng Hospital pharmacy’s robotic dispenser
efficiently prepares personalized and accurate medication.

However, although R&D expenditure has grown astronomically over the
years, the amount of new medicines
produced has not increased significantly along with it[2].

The big
players in the healthcare sector are focused on finding new wonder drugs to
take to market that ultimately revolutionise
the marketplace but it’s no easy task, of
course. To get a new drug to market,
companies have to demonstrate that it is incrementally better than what came
before. That is one of the guiding principles of the medical industry – and
pharmaceuticals companies across the world are running clinical trials every day
that are designed to prove it but how can
the industry verify that these are all being carried out on a level playing
field, that the parameters being used are standard and that the tests that are
run are fair and equable?

Ultimately,
the argument goes it’s about openness and transparency, publishing all the data
of successful and failed trials to enable better, more informed choices to be
made. Transparency is also a key element of what big data is all about. Whatever
the rights and wrongs of the political debate, big data technologies do have the
potential to deliver this kind of openness by laying the foundations for analysing complete data sets. This gives users
a comprehensive picture of the data and accurate
insight into what that is telling them. That’s critically important.

However, the insight that a comprehensive
analysis of an organisation’s big data
sets delivers extends beyond the issue of new drug development. This kind of
analysis can also help pharmaceuticals companies achieve greater success with
drug repurposing. By analysing data sets,
from compound structures to protein interactions, organisations can gain insight into which diseases are most likely
to be successfully treated with specific drugs, even where those conditions
differ from those for which the drug was originally assigned or intended.
Viagra, which was originally developed for high blood pressure, is perhaps the
most compelling example of a successfully repurposed drug.

This is a
hugely important area for pharmaceuticals organisations
as the ability make proactive use of research that might otherwise remain
unused can be key not only in enhancing the productivity of the organisation and its operational efficiency but
also in potentially improving public health.
Even where drug research has failed in addressing the challenge it was
originally targeted at and remains at a largely nascent stage, big data can
help it see the light of day, analyse it
and potentially find another clinical application for it that the original
scientists failed to uncover at the time.

This year has
highlighted to many of us the dangers of taking a small sample of data and
extrapolating definitive results from it. The pollsters got both the EU
Referendum and US Election results badly wrong, after all. The reason for that
was largely that the set of inputs they
used to predict the results were too narrowly focused and the model they built
from those inputs was therefore inaccurate.