Like every other industry things are changing very fast in the pharma sector. With only 20 years of drug patent window, there is very little time for organizations to earn ROI. There is a clear ask for innovative technology solutions to speed up the process of ensuring profits.

The process of drug development is lengthy and complex combined with several processes, applications and approvals. Unquantified and unstructured data is produced from multiple systems in various forms. Advances in storage, network and computing technologies have enabled pharma companies to overcome this problem and economically and efficiently harness this Big Data and turn it into a potent source of business strength. Big Data is enabling joint analyses of clinical and pre-clinical data from disparate sources and also lends transparency to translational research to achieve personalized Medicine.

Pharma companies are now being under pressure to adopt groundbreaking drug technologies and enterprise-wide M&A to diversify the product portfolio to maintain revenue streams. Conclusions drawn from typical clinical trials are now not adequate enough for drug value assessment and decision making. There is, therefore, a need for data-driven insights with real-world clinical evidence. Translational research along with comparative effectiveness is becoming imperative to understand a drug’s impact in real life.

Implementation of Big Data infrastructure enables faster data processing, which, in-turn, allows organizations to support scientific analytics and derive more focused business outcomes for next-gen research. Big Data architecture includes a radical integrated repository, along with scalable collaborative interfaces and advanced analytics with flexible deployment options. It is predicted that the market for Big Data technology and services will reach $16.9 billion in 2015, up from $3.2 billion in 2010, an annual growth rate of 40 percent. Owing to this growth the pharma industry is becoming more patient centric and realizing value of patient outcomes, improved safety and efficacy, connected research and care through better data insights.

The figure below highlights the multiple advantages of implementing Big Data in pharma R&D.

With "data-to-insights" cycle coming into play, pharma companies can emphasize more on a stack of tools such as Hadoop, NoSQL Databases, MapReduce, In-memory Analytics, Enhanced Cloud Computing and Storage.

Transformation by use of data across Clinical continuum demand novel data exchange models for futuristic clinical outcome, coordinated research and care.

In the essence, better data handling, easy-to-learn/use modeling tools, and an array of analysis algorithms will help organizations build a framework to extract useful features from large datasets to further understand business insights and decrease time to information which will be the key to maximizing ROI.

Big data enabled consolidation and collaboration among different internal and external healthcare stakeholders will benefit pharma companies by breaking the silos that separate internal functions and enhance integrated, consistent research and care management. This will, in-turn, help the sponsors improve the quality and efficiency of Research & Healthcare delivery ultimately business outcomes.

Dr. Sarika Vanarse- Principal Consultant, Pharma R&D, Industry Solutions Group, Wipro Limited

Dr. Sarika Vanarse is a Principal consultant with Wipro's Pharma R&D, Industry Solutions Group. She deals mainly with innovative R&D solutions development. Dr. Vanarse holds a post-graduate degree in Medicine and has more than 11 years of Life Sciences IT consulting experience with Tier 1 organizations. She is currently leading several pharma R&D initiatives for large pharma companies. Her expertise includes R&D strategy and innovation, pharma R&D intellectual property rights, R&D process optimization consulting, clinical informatics and analytics, and data integration.