28 - 30 November, 2017 | Brussels

Media Center


Best in Class Case Study with Allan Jordan

Allan Jordan strongly believes that while big data is important and can change pharma, it should not just be gathered without reason. There needs to be a purpose, and purpose is the main thing driving his latest project. 

The project in question is focused on exploiting genome sequencing efforts to discover new targets for cancer treatment. A huge opportunity for positive change. Download the Case Study to find out more. 

Does Big Data in Pharma = Big Money?

As of now, big data is not used as often and as well as it should be in the Pharmaceutical Industry.   Slowly the Industry is adopting data and analytics to improve itself.

Data usage could lead to accelerated drug discovery, better help patients and predict emergency rush hours.  To keep reading, download the PDF file. 

How to Create a Competitive Advantage with Big Data Analytics in Pharma

Nigel Hughes, Director Integrative Healthcare Informatics, Janssen R&D, takes a closer look at how access to external data is critical in today’s world and the ways data accessibility can provide pharmaceutical companies with a competitive advantage.

With large scale initiatives coming into practice, such as the European Medical Information Framework (EMIF), Hughes shares his top tips for implementing a project like this. Read this interview to find out the key opportunities and threats of utilising real world data and how the rise of personalised/ precision medicine will impact the use of data.

6 Ways Pharmaceutical Companies are Using Big Data to Drive Innovation & Value

Pharmaceutical companies have always relied on empirical data in order to identify patterns, test theories and understand the efficacy of treatments. Big data is just another evolution in a trend that has been continuing for hundreds of years: that of human beings having ever greater access to information and data. But to really garner the benefits requires a different way of looking at data. Here are 6 ways that pharmaceutical companies can use Big Data and analytics to generate business value and drive innovation.


Big Data for Product Development

Big data is turning up everywhere. In this Process Perspectives podcast, Kaare Buch Petersen, Information Architect in Global IT at Christen Hansen, a Denmark-based supplier of bioscience products to food and health industries, talks about how his company has been using big data in the development of their new products.


Get Beyond The Silo With Big Data Analytics

In this infographic experts provide insight on how pharma firms can capitalise on cracking open their data silos. 

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“It is a good time to be a data scientist in the pharmaceutical industry”

We caught up with Nigel Hughes, Scientific Director at Janssen, to explore the role of data analytics in the pharmaceutical industry, the challenges for those already working in data teams and the future of predictive analytics.


Top 5 tips to incorporate data visualisation into a successful business strategy

The biggest challenge life science companies now face is to learn how to use data, source of an enormous amount of information, and step out of the silos. Ahead of the third annual Data Analytics for Pharma Development, PharmaIQ had an exclusive interview Marie Montoya, CEO and Founder or M Montoya Consultancy, to understand how data visualisation, once incorporated into a business strategy, can help life science companies turn their business around into a cost efficient model. 

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Big Data in Life Sciences - Beyond the Buzz

Big data has moved beyond the big hype. The data landscape in life sciences is changing rapidly, advancing technologies, pre-competitive data sharing and huge growth of structured and unstructured data volumes available to organisations are driving big data breakthroughs. Life science companies are looking for new ways to leverage big data and turn it into actionable insights. This new infographic looks at the trends driving change in the data landscape in life sciences and the guiding principles that can help organisations.


The Power of Big Data Anaytics in Pharma [Infographic]

In this infographic experts provide insight on the opportunities that exist in big data analytics for Pharma and how pharma firms can capitalise on cracking open their data silos.


Big Data: The Secret Ingredient to a Successful Life Sciences Formula

In this interview, Dimitris Agrafiotis, the Vice President & Chief Data Officer at Covance, discusses the five steps of the clinical trial process and details the ways in which Big Data is involved every step of the way. How has Big Data changed the game for you – given you new capabilities and platforms and the ability to analyze large data sets? There is a lot of hype behind Big Data and I think it’s very important to dissolve some of this hype. For example, modern relational database technologies handle massive amounts of data absolutely brilliantly and this will be very important in Covance’s clinical data warehousing efforts. I saw the evolution in the life science business. I saw the volume of data increase, the diversity of data increase and the complexity of data increase. But at the same time, conventional technologies advanced at almost an equal pace. So today’s relational databases are not exactly your grandmother’s relational databases.

Drowning in Data, but Starving for Knowledge? How to Define Big Data for Healthcare

Thomas R. Ortiz, is the Chief Medical Officer at Reliance Medical Group, LLC and operates the Primary Care Medical Practices in five counties within New Jersey. In this interview, Ortiz says his business would do better with more organised data streams, which would improve overall outcomes and costs. Find out how his organisation tackles the many challenges of big data within healthcare.

Creating An Efficiency Value of $1 Million With Data Analytics

Big Data in healthcare delivery is really an illusion, according to Daniel Morreale, the Vice President and Chief Information Officer at Kingsbrook Jewish Medical Center.

Other than large, academic medical centers, or medical giants such as Quest or Kaiser Permanente, a majority of big hospitals are doing very little with their big data for a variety of reasons; not the least of which is a drought of data scientists to drill down and dissect the data.

Kingsbrook discovered big data could lead to success when they started to dig into the reason for delays and broken appointments in its radiology center. Thanks to analytics, they were able to reduce their broken appointments by 25% and create an efficiency value of a little bit more than $1 million.