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European Pharmaceutical Contractor

Big Data Meets Big Pharma

Every day, the world generates 2.5 exabytes of data – this is 2,500,000 terabytes. Data is not growing: it is exploding. The exponential growth is so big that 90% of the data stored today has been created in the last two years alone. According to Google’s Eric Schmidt, “There were five exabytes of information created between the dawn of civilization through 2003. That much information is now created every two days”.

While the term is over-used and its definition is nebulous at best, big data can be defined as extremely large datasets that may be analysed computationally to reveal patterns, trends and associations, especially those relating to human behaviour. Back in 2001, industry analyst Doug Laney of Gartner articulated the definition of big data as comprising of the three ‘Vs’: volume, velocity and variety. Many factors contribute to the increase in data volume, including transaction-based data stored through the years and unstructured data streaming in the form of social media.

In the past, the precipitous rise in data volume was a critical storage issue. But, with decreasing storage costs and disruptive technologies like cloud/ grid computing environments offered from companies such as Amazon and Google, the ability to now manage large data volumes is becoming more tenable. Data today comes in all types of formats: structured, numeric, text, email, video, audio and financial. The variety of data formats and the unprecedented speed and velocity in which data is being streamed is a challenge for most organisations, demanding that new requirements be instilled so that informed decisions can be made in a timely manner. The companies that manage, merge and govern the complexities of big data will be best positioned to create new realities.

An Asset, Not a Burden

Big data has moved beyond the hype. The data landscape in the life sciences sector is changing rapidly; advancing technologies, pre-competitive data sharing and the huge growth of structured and unstructured data volumes available to organisations are driving big data breakthroughs.

Life sciences companies are looking for new ways to leverage big data and turn it into actionable insights. Current challenges, such as the patent cliff, combined with shrinking pipelines illustrate the excessive pressure pharmaceutical firms are under to adopt groundbreaking drug technologies and enterprise-wide mergers and acquisitions (M&A) to diversify product portfolios, as well as maintain revenue streams. Conclusions drawn from typical clinical trials are no longer adequate enough for drug value assessment. There is a need to adjoin data-driven insights with translational research, as comparative effectiveness is becoming imperative to understand a drug’s impact on the market. Pharma companies must now leverage big data and turn it into a potent source of business strength.

Big data has application opportunities across all value chains of the life sciences and pharma industries. Adoption of big data in sales and marketing is gradually gaining power, primarily due to the function of interfacing through the web to listen to ‘patient voices’. This also has competitive implications in the form of market access, personalised medicine, compliance, safety monitoring and post-marketing clinical trials. Big data has enormous potential in R&D because of its intrinsic ability to process data from multiple sources, such as millions of documents, protocols, study records, images and applications, thus providing a unified view of the drug lifecycle.

Cloud computing, genomic sequencing and big data are inexorably linked. Cloud vendors like Amazon Web Services (AWS) and Google Genomics are leading players in the market, and their remote computing platforms are being used to store genomics data. AWS is hosting the Multiple Myeloma Research Foundation’s project to collect complete genome sequences and other data from 1,000 patients to identify new drug targets. Meanwhile, Google Genomics won a project from the Autism Speaks foundation to collect and analyse the genomes of 10,000 affected children and their parents for clues to the genetic basis of autism. Another customer is Tute Genomics, which has a database of 8.5 billion human DNA variants that can be searched for how frequently any given variant appears, what traits that variant is associated with, and how patients with a certain variant respond to particular drugs.


One of the industry’s largest drug makers, Pfizer, made a splash in 2011 when it announced its strategy as a data company to forge a partnership with Medco Health Solutions, to integrate genomic and phenotypic data to understand the biology of disease and identify patients likely to benefit from new drugs. The approach could make it possible to precisely select disease targets and improve the safety and efficacy of medical treatments targeted at sub-groups of patients with similar genetic profiles.

In the same year, Pfizer conducted the first-ever randomised virtual clinical trial under an investigational new drug application that manages study participation through the use of mobile and web-based technologies, allowing patients to participate regardless of their proximity to clinical sites. Pfizer was one of the first of the Big Pharma family to publicly announce a general framework designed to harness big data. Since then, other pharma and life sciences companies have followed suit:

WuXi and DNAnexus

China’s largest CRO, WuXi PharmaTech, teamed up with DNAnexus to offer cloud-based genomic services leveraging WuXi NextCODE’s genome analytic technology and DNAnexus’ cloud-based platform to facilitate pharmaceutical R&D. The strategic alliance will connect NextCODE’s sequence data analysis suite and open access drug discovery services, through a single, global, Health Insurance Portability and Accountability Act: a compliant cloud platform that will expand clinical research with collaborators and datasets, and accelerate the delivery of DNAbased diagnostics. For the first time, users will be able to use their genomic data seamlessly in tandem with the open access portal for diagnostic test validation or FDA submission services that the software now offers the global pharma and medical device industries. The database model and clinical research interfaces directly on the DNAnexus cloud; users can store and interpret their sequence data and collaborate with colleagues around the world through a single platform. WuXi has made several investments within the genomics space over the past year – including the purchase of a HiSeq X Ten sequencing system from Illumina and the acquisition of NextCODE for $65 million – and has invested $15 million into the deal with DNAnexus. The WuXi Genome Center is the subsidiary that will drive the company’s genomic strategy, offering complete solutions for drug development from preclinical to clinical trial stages, along with a full range of CRO services.

Novartis and 2net Platform
Qualcomm Life, a subsidiary of Qualcomm, was selected by Novartis as a global digital health collaborator for its Trials of the Future programme. Qualcomm Life’s 2net Platform will serve as a global connectivity suite for collecting and aggregating medical device data during clinical trials to improve the convenience and speed of capturing study participant data and test results, to ultimately gain more trial efficiencies and connect patient experiences.

The Trials of the Future initiative combines the 2net Platform with smartphone and mobile technologies to automate the collection of vital patient biometric data at patients’ homes during clinical trials, transmitting data securely to study coordinators. Novartis has stated that the company intends to use more mobile technology in its clinical trials to aid the marketing of future products.

The partners will also band together to start an investment firm. Qualcomm Ventures and Novartis will invest $100 million in technologies, products and services that ‘go beyond the pill’ to benefit physicians and patients. It is anticipated that these investments will be mainly focused on digital medicine: Qualcomm Ventures’ portfolio investments include startups such as Fitbit, Telcare, and AirStrip, whereas Novartis struck a deal in 2010 with Proteus Digital Health and, earlier this year, with Google for a glucose-sensing contact lens technology.

Roche and Genomic Management Solution

Roche acquired informatics company Bina Technologies and its proprietary Genomic Management Solution (Bina-GMS). GMS is a software system expected to dramatically improve the speed and cost of genomic analyses. Bina’s platform was selected by the US Department of Veterans Affairs (VA) to provide whole genome/exome and single-nucleotide polymorphism microarray data analysis as part of the Million Veteran Program. It is the VA’s aim to enrol one million US veterans to target the genetic underpinnings of combat-related illnesses, such as posttraumatic stress disorder. Bina-GMS will be integrated into Roche’s diagnostic sequencing unit as the company continues to develop new algorithms that link next-generation sequencing (NGS) data to disease-relevant genetic markers.

Moving forward, Roche will be able to support similar big data population studies, as well as grow its personalised medicine offerings. The Bina purchase is one of several deals Roche has struck in the NGS space, including Ariosa Diagnostics, AbVitro, Genia, Pacific BioSciences and Foundation Medicine.

Medidata and Vivofit
Medidata and Garmin teamed up to track patient activity in early clinical trials. Garmin will integrate its Vivofit wristband activity tracker with Medidata’s clinical cloud. The idea is to use the mHealth device to enhance patient engagement, data quality and operational efficiencies in a couple of early-stage clinical trials that Medidata is conducting, to better understand the relationship between data and treatment endpoints. Patients will be able to access more information about their health status via their smartphones. Over the longer-term, devices like the Vivofit could potentially reduce clinical visits and provide physicians with more robust data for diagnoses.

AstraZeneca and Labguru
AstraZeneca (AZ) adopted BioData’s Labguru platform, a web-based lab management system for the global administration of biological reagents used in preclinical research. AZ will deploy Labguru across multiple sites in North America and Europe, replacing and consolidating several legacy systems spanning across a number of scientific business units. The system tracks projects, protocols, biological collections and inventory, and is designed to streamline operations, monitor costs and enhance collaboration between researchers inside AZ and in academic labs across the world. Labguru’s comprehensive procurement capabilities include a product catalogue of over 800,000 items from major vendors including PeproTech and Sigma-Aldrich.

GlaxoSmithKline and Apple ResearchKit

Apple’s ResearchKit is an open-source software framework allowing medical researchers to gather data easily, and efficiently, by utilising apps on an iPhone. ResearchKit has gained major support from some of the world’s largest pharma companies, such as GlaxoSmithKline and Purdue Pharma. Both firms plan to use Apple’s ResearchKit in clinical trials.

The platform is designed to enable sponsors running clinical trials to design apps that keep tabs on patient-reported outcomes, measure vital signs and use the iPhone’s many sensors to harvest clinical information. A typical clinical study might include thousands of participants; ResearchKit can easily surpass that number and even reach hundreds of thousands of subjects – over 11,000 volunteers signed up for ResearchKit within a day of the app being made available.

The success of this platform is mainly the result of Apple’s brand recognition and its reputation for being a privacy-first company: Apple does not sell data to third parties, unlike Facebook or Google, in order to drive advertising revenues – an important sticking point in the healthcare community.

Big Data: Big Opportunity

As data analytics and cloud computing continue to grow, big data will offer more lucrative opportunities for life sciences companies, not just large technology firms. According to a recent press release from tech analyst firm 451 Research Group (formerly Yankee Group), the total data market – consisting of platforms, management, analytics and mining – is expected to nearly double in size, from $60 billion in 2014 to $115 billion by 2019: a growth rate faster than the entire information and communications technology market (1).

Like every nascent technology, big data adoption will entail some challenges. However, the first step to successful adoption in the life sciences sector is to have open communication and establish value-added partnerships that maximise the ‘other return on investment’ – return on information, that is.


1. 451 Research Group, 451 Research predicts total data market to hit $115 billion by 2019, 28 May 2015. Visit: Marketing/press_releases/5.28.15_ Total_Data_PR_Final.pdf

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Adam Dion is Senior Industry Analyst at GlobalData. He writes competitive intelligence on the CRO/CMO, pharma and biotechnology sectors capturing industry trends, M&A activity, investment flow, operations strategy and financial benchmarking. Adam’s analysis is regularly mentioned in top press outlets, including The Wall Street Journal, The Financial Times, CenterWatch, FierceBiotech and Outsourcing Pharma. Prior to joining GlobalData, Adam was an analyst with Technology Business Research, a leading technology market research and consulting firm. He earned his BS in Neuroscience from Merrimack College and MS in Marketing from the University of New Haven.
Adam Dion
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