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International Clinical Trials
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The pharmaceutical industry is facing a number of challenges today. At
every turn, there is demand for greater efficiency and innovation. The
traditional pressures of emerging markets, diminishing pipelines and
patent cliffs are considered normal nowadays, and are no longer treated
with the same level of concern. The focus now is to develop a biological
portfolio pipeline and an efficient strategy that can compete in the
face of generics, consumerisation, industry standardisation and
compliance pressures.
In the early 2000s, pharma companies
collaborated with external vendors and reaped the benefits of cost
rationalisation. Today, partially fuelled by the commercial pressures
created by the global recession of recent years, the industry is
focusing more on innovation across the value chain as well as at an
operational level.
The need for innovation is leading businesses
to leverage the data they hold and have access to, and this applies
across the board. Coupled with the recognition that health trusts and
patients are now the central cog in the pharma wheel – a place
traditionally held by products – the impetus is now to differentiate
through data.
Here to Stay
The pharma and life
sciences sector today is inundated with information, and firms are now
looking for ways to use analytics so they can ensure that they are able
to transform this data into valuable insights.
The data
generated could be internal or from other external sources, such as
public databases, market research companies or other payers and
providers. But it is not just traditional forms of data usually
associated with the pharma industry. The greater emphasis that is being
placed on the end user – the patient – means that more and more pharma
businesses are turning to data not previously used in drug development;
namely, the huge amounts of information made available through social
media.
Online social networks, as well as electronic medical
records, offer up a huge repository of real world patient data that can
then be analysed alongside traditional pharma data. With the right
input, analytics are able to provide valuable information for improving
and customising drug development and services, identifying undiagnosed
patients, predicting hospital readmissions and other medical
forecasting.
It also offers the ability to home in on health
outcomes and comparative effectiveness – referral patterns, drug
switches, off-label use, as well as disease trends and locations can be
understood better through the efficient harnessing of data from social
media. In fact, Gartner has predicted that by 2017, data discovery tools
will incorporate smart data discovery capabilities that will enhance
sophisticated interactive analysis and business insights (1).
The
bottom line for pharma companies to understand is that big data is here
to stay, and the generation of data-driven insights has moved from
being viewed as a competitive advantage to being the lifeline of the
industry.
Consumerisation and Personalisation
As
well as an explosion of data, the impact of consumerisation and
personalisation is being felt across a number of industries today – most
notably in retail, where stores are competing for the attention of
consumers. The same scenario cannot be seen in the pharma industry;
however, the growing trend of consumerisation is a force that requires
organisations to wake up and focus on the individual user of the drug or
service, not just the generalised audience as was the case previously.
To
succeed in this new consumer-orientated world, pharma and life sciences
companies must identify consumer segments critical to their product
offerings, and leverage big data analytics across all areas of the value
and development chain – two of the most common are currently within the
manufacture and supply of products, and in the development of products.
Big Data for Development
There is a growing
pressure on the pharma industry to provide better drugs more efficiently
and at a lower price. It is therefore fortunate that big data analysis
can go some way towards enabling this.
With big data analysis at
a clinical R&D level, a whole range of possibilities are opened up.
For example, predictive modelling becomes much more sophisticated and
extensive with big data analytics, and it can also reduce drug
development times as it helps to identify new potential candidate
molecules with a higher probability of success.
Similarly, by
leveraging social media and patient data, suitable individuals to enrol
in clinical trials can be identified more easily, and the selection
process can be more detailed as more factors can be taken into account –
thereby enabling trials that are smaller, shorter and less expensive,
but more effective.
Manufacturing and Supply Chain
Another
area that pharma companies are focusing on is the manufacturing and
supply chain. Compliance has emerged as one of the biggest concerns in
pharmaceutical manufacturing. In an industry with significant challenges
already, governmentimposed regulation presents more hoops to jump
through.
To handle compliance effectively, a two-pronged
approach is required that, among other aspects, utilises smarter data
analytics. But where does this information to be analysed come from? The
answer is: across the manufacturing and supply chain within the
organisation.
Manufacturing operations generate a massive amount
of information and similarly, with the application of the Internet of
Things and installation of sensors, the supply chain can also produce a
great deal of data. The information generated can then be analysed and
used in two ways. Firstly, it can be aggregated with data from across
other areas of the organisation to produce evidence that demonstrates
compliance to rules and regulations. Secondly, it can actually be fed
back in to the business to add value. For example, insights drawn from
the data can improve factory yield, reduce the rate of returns, compress
cycle times and lower the costs of machinery diagnosis and repair.
Listen to your Customer
There
is no dearth of data in the pharma and life sciences industry, but it
is how that information is used that is the issue. Companies must create
a more patient-centric industry that listens to and provides the drugs
that individuals need and can fit in with their lifestyle. By
transforming data into valuable insights across the entire pharma
business, organisations can begin to progress down this road.
Reference
1. Visit: www.gartner.com/newsroom/id/2970917
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