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Real-World Evidence in the Cloud: How
Technology is Revealing the Big Picture in Pharma
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Typically companies struggle to properly gauge the level
of storage and compute power they will need, either
over or under buying equipment, which is exacerbated
by the potentially long procurement cycles required
to acquire this infrastructure. Particularly as new and
unpredictable types of data may be collected in the
future to support RWE programs, companies may
find the questions they can ask of the data limited
by the constraints of their legacy data centers.
The impact of the shortcomings of this approach
has grown in step with the availability of data and
need to effectively analyze and use it across the
product lifecycle. Some companies are analyzing
the genomes of patients and their tumors to inform
steps as far back in the life cycle as target discovery.
Others are mining data on drug prescriptions and
EMRs to show the potential availability of patient
populations that may be qualified to participate in
clinical trials in different regions. However, without
the capacity to effectively store, analyze, and share
large-scale and disparate datasets, the value of this
data cannot be realized.
Wi t h e v e r y t h i n g f r o m t a r g e t d i s c o v e r y t o
reimbursement now reliant on vast amounts of real-
world data, leading companies are concluding that
inefficient and ineffective approaches to RWE are
no longer viable.
"We required a scalable platform that would provide
us with cutting-edge analytics and enable us to work
with large volumes of real world evidence that are
distributed globally across disparate sources," Patrick
Loerch, Celgene Senior Director Data Science, said.
Celgene, like many other companies, looked to the
AWS Cloud and AWS Technolog y Competenc y
Partners, to alleviate the challenges associated
with large-scale data storage, analytics, and secure
organizational data sharing.
HOW DATA LAKES ON THE AWS
CLOUD ENABLE EFFECTIVE RWE
Companies are responding to the emerging RWE
environment by replacing si lo e d, on-premis es
data repositories with cloud-based data lakes that
pool and catalog all of their information assets as
centralized repositories.
Instead of ever y department storing real-world
data on their own isolated systems, companies such
as Celgene are having newly in-licensed data flow
into an AWS Cloud data lake. By leveraging the
market tested analytics capabilities provided by
Deloitte ConvergeHEALTH Miner, teams working
across the product lifecycle are equipped to access,
analyze, and visualize the assets to support their
specific needs.
Feeding data f rom many s ources into a sing le,
c e nt r a l i z e d r e p o s i t o r y c r e at e s c o nt i nu o u s l y -
growing, multi-petabyte data lakes. The need to
store large, growing amounts of real-world data
makes the dynamic scalability and low cost of cloud
storage critical to the viability of the concept of
centralized data lakes. Working with AWS cloud
also enables companies to leverage the provider's
previous work on the structure, metadata system,
governance and security of data lakes. This work
coupled with Deloitte ConvergeHEALTH software,
