Where Science Meets Data Science

 Big Data drives the life sciences industry forward, optimizing nearly every dimension of the business. Just consider the megatrends reshaping the life sciences competitive landscape:

Pharmaceuticals
  • Research and development organizations are challenged to keep the pipeline full as profitable drugs face competition from generic versions and pricing pressures.
  • With new drug development costs reaching $1 billion or more, the stakes are incredibly high. The data-related challenges are just as great – with tens of billions of records and data volumes measured in petabytes as dynamic biotechs and global pharmaceuticals seek new compounds and correlations between genes and diseases.
  • Clinical trials must be streamlined to focus on specific populations and enable the “fast failures” that often lead to long-term success. It’s all about bringing safe, effective treatments to market quickly using the latest techniques, including genomics, proteomics and bioinformatics.
  • Complex sales and marketing programs are increasingly data-driven, with new requirements to engage and influence prescribers, payers and patients using integrated marketing and real-world evidence.
  • Precision pharmaceutical manufacturing processes and global supply chains require full visibility, two-way batch traceability, robust supplier management and other advanced capabilities – all of which start with integration of various data sets and sources.
  • More active regulatory oversight means risk management, pharmacovigilance and clinical affairs teams must monitor drugs more closely than ever before. Increasingly, social media is critical for capturing real-world evidence and picking up signals relative to adverse events or even positive side effects that can lead to new indications.

Big Data in Action in the Life Sciences Industry

Leaders in life sciences are embracing advanced analytics and comprehensive Big Data strategies to make big gains. 

  • Focused Sales and Marketing for the Pharmaceutical Industry: As it lost market share, a top-three pharma sought to identify prescribers who were writing fewer prescriptions. With enhanced analytics toolsets, the company analyzed more than one billion records from IMS monthly feeds to rapidly identify and proactively address brand switching and optimize the sales process and promotions.
  • Insights for Pharmaceutical Safety and Innovation: To prove the continued safety and efficacy of a major drug, a top-five pharma needed better insight into drug combinations and usage. A better environment enabled faster loading and analysis of 900 million prescription records and 15 million patient records. Now, clinical and business analysts can conduct rapid and iterative drug interaction analysis – including competitor drugs – to uncover previously unknown safety issues and repurposing opportunities.
  • Expanded Safety Analysis for Life Sciences: A top-five global life sciences company significantly improved safety analysis of conditions by more than 1,000% per pass of electronic medical records data and improved conversions from sample data to the full data set from three hours to two minutes.

American Cancer Society

Fighting Cancer:

American Cancer Society doesn’t want to just battle cancer. It wants to eliminate cancer.

Pharmacology

First Steps to Succeeding Faster with Big Data

So how can life sciences harness the power of Big Data and focus their investments on high-impact returns? The key components: 

  • Create the Right Big Data Strategy: effective strategies start with understanding how Big Data and advanced analytics can provide an advantage in key functions – from R&D to marketing to the supply chain.
  • Learn How Big Data Works: diverse data sets, from real-world evidence and social media to prescription records and claims data, must be integrated in well integrated data and analytics ecosystem.
  • The Future of Big Data: given their scientific expertise, life sciences leaders are helping to define the possible with Big Data, while recognizing that it’s a long game.

 The bottom line: for pharmas, biotechs and other life sciences firms, the ability to handle Big Data is a difference maker – both on the bottom line and for the billions of people who rely on their products.