Solving the problems of unstructured data and high R&D costs in the pharma industry through the use of Cloud computing and Analytics

1. Solving the problem of disjointed
information and high R&D costs
Nihar Routray
BLP022

2. The Challenge
Need for a practical solution to tackle the twin problems of disjointed information and
extremely high R&D costs for a multi-national and multi-brand company.
 R & D in a pharmaceutical company is a very complex process requiring considerable
amount of time and a diverse set of stand-alone systems and specialized computer
applications. The requirement of resources for these applications has become so high
now that the company cannot afford the considerable costs of building, implementing
and supporting these infrastructures.
 Pharmaceutical companies
generally face the problem of
having complex silos of
information built around their
brands. Along with that large
amount of information is being
created everyday by numerous
systems and applications in all
kinds of formats which pose a
serious challenge to manage,
monitor and retrieve required
information at times of need.
 Being a large multi-national,
though the company employs advanced communication systems but still a significant
disconnect is observed between the various enterprise teams as they are dispersed
across different global locations.
 Pharma companies also need to maintain their legacy systems containing critical data as
the FDA requires data related to a drug to be maintained for a minimum period of 2
years after it was last sold. Due to this the legacy systems cannot be completely done
away with and integrating them will run into huge costs.
Assumption:
Have considered a pharmaceutical company which is spread across different geographies across
the world and has multiple brands in its drug portfolio

3. Current Situation
Currently, the company is just throwing in more resources, people, computational and storage
capabilities at the problem. However, this approach cannot be continued with and is
economically unviable in today’s world of cut-throat competition and economic climate.
Now let us understand the R&D process and how IT has been supporting it.
DISCOVERY
Pre Discovery
Aim: Understand the disease and choose target molecule
Process: Scientists from government, industry and academic institutes create
knowledge base using various computational tools and insights
Discovery
Aim: Find Lead compound
3-6 Years
Process: High Throughput screening via robotics and computational power, De
Novo creation, Genetic engineering
Pre-Clinical
Aim: Determine drug is safe for testing in human beings
Process: Extensive in vitro and in vivo tests and recording of test data
DEVELOPMENT
IND
Aim: Obtain approval from FDA for clinical trials in human beings
Process: Review by FDA and IRB
6-7 Years
Clinical Trials
Aim: Trials in human being to check drug efficacy, dosage and safety
Process: Drug tested on human beings in 3 phases moving from smaller to
larger patient groups. Trial data recorded on paper or through LIMS
Review
Aim: Review by FDA for drug approval and manufacturing
Process: FDA reviews the NDA which can be more than 100000 pages
1-2 Years
Manufacturing
Aim: Large scale manufacturing of drug
Process: Scaling up facility and large scale production following GMP
Ongoing Studies
Aim: Monitor drug in market
Process: Monitor the drug in market and report adverse events to FDA
Estimates
Cost: Upto 1 Billion
Duration: 10-15 years

4. All the steps mentioned above include a huge number of activities and consume a lot of time to
get completed. A variety of dedicated systems are employed at each stage to support processes
and record and manage the data being generated.
As we saw in the process flow, a new drug development costs around $1 billion and takes a
minimum of 10 years to complete. Also, a large number of potential drug research projects are
shelved at some point during the drug development process owing to adverse effects or limited
efficacy. According to Industry records, only 1 out of 1,000 potential compounds get approved
finally and are sold in the market.
The company is currently getting inundated with complicated and resource intensive
applications which are churning out huge amount of data. So, the company is hard pressed to
do more with less while increasing flexibility and responsiveness to meet the business needs.
The IT budgets of Pharma companies are nearly consuming 15% of the total R&D expenditures
and about 8% of the total headcount of the organization. This high level of resource
consumption while maybe essential but does move the organization away from its core mission
of drug discovery and development.
So it becomes highly imperative for the company to find ways to reduce R&D costs while at the
same time increasing productivity through better data management and retrieval.
Approach Highlights
Happiest Minds proposes a two pronged approach of embedding analytics into its daily
operations while leveraging the cloud to counter the problems of disjointed information and
high R&D costs. This approach would be carefully implemented along with an information
agenda as it would provide a high level roadmap aligning the business needs with the analytic
insight and the cloud platform to the underlying technology and processes.
The company will be provided with an access to a low-cost shared cloud computing
environment with an array of hardware, software and technical resources which would help
reduce the various costs. Our cloud platforms will help you integrate your entire business
services and include high levels of shared data management and advanced features to help you
adopt new business models which would clearly differentiate your organization from the rest in

5. the industry. These cloud platforms are also encompassed in a layer of security framework
which would take care of all the perceived risks. There would be further reduction in costs as all
the heavy functions such as computing power and storage will be leveraged in the cloud.
Proportion of Life Sciences R&D Informatics budget devoted to Cloud computing in 3 years:
Source: Insight Pharma Reports
The augmented analytics capabilities provide end users access to near real-time information
facilitating collaboration and preserving transparency. The differentiated analytics advantage
provided by Happiest Minds will help the company achieve value creation quite early in an
organization’s progression to sophistication by leveraging structured and unstructured data
from within and outside the organization.
Source: Analytics: The New Path to Value, a joint MIT Sloan Management Review and IBM Institute for Business Value study.
Copyright © Massachusetts Institute of Technology 2010.

6. Why Happiest Minds
Companies are seizing this opportunity provided by Happiest Minds to use advanced
information analytics and cloud computing for business advantage in their respective industry
sectors. These business leaders are not depending anymore only on intuition but are combining
the new analytics techniques with the expertise from Happiest Minds to make decisions in a
completely different way.
Creating disruptions through technology as well as through the next generation skilled worker