Big data - the huge volume of digital data generated worldwide - continues to grow exponentially, opening up new opportunities and creating new challenges for the healthcare, pharmaceutical and biotech industries.
As society adapts to new activities and technologies that generate ever-greater quantities of data relevant to pharma, it is fast becoming a marketing tool that cannot be overlooked. Exactly how best to use big data has yet to be established, but recent research indicates its potential worth in market research, product pricing, patient support and education, and more. The very scale of big data and the difficulty of working with it pose difficult questions about data capture standards and the protection of privacy while accessing invaluable information. Who, for example, provides the expertise?
This comprehensive study will prove an essential companion for anyone hoping to understand big data and its role in pharma marketing.
For this essential report, FirstWord consulted experts on the analysis and application of big data such as Duncan Ross, Director of Data Science at Teradata, a company that works in data management, data gathering and data analysis, for their views, which inform a document that guides the reader through every facet of a complex and ever-expanding subject.
The report opens with a broad definition of big data and goes on to examine the subject in great detail, from looking at its sources to explaining how it is being used as a marketing tool.
Sections on usage in other industries and on the issues and challenges it raises will ensure the reader is fully briefed on big data and how to work with it.
Key Report Features
A background to big data
A summary of big data sources for pharma and biotech
Uses for big data in pharma and biotech marketing
Lessons from other industries
Challenges facing those wanting to use big data
Predictions for the future of big data in pharma and biotech
Learn from experts in the industry
Know what to expect (and what not to expect) from big data in marketing
Recognise the key issues in the use of big data
Know why big data is important
Understand how big data can tailor marketing
Be able to get the best from big data
Know the weaknesses in text analytics in social media
Key Questions Answered
Why should I take an interest in big data?
Can I use social media findings in marketing?
Should I perform data analysis in-house or use third party suppliers?
Why is patient support and education important?
Who Should Read This Report
Marketing directors at pharmaceutical and biotech companies
Marketing directors at social media companies
Business development teams at data analytics companies
Heads of IT at pharmaceutical and biotech companies
Expert Views Include:
Nic Brereton, Founder and director at BresMed Health
Chris Winchester, deputy managing director at Oxford PharmaGenesis
Dennis Urbaniak, VP, US Diabetes at Sanofi US
Destry Sulkes, executive vice president and co-founder of Medivo
Mark Divers, head of the Karolinska Institutet biobank
Michael Doyle, director of marketing at Accelrys
Joel Dudley, assistant professor of genetics and genomic sciences and director of biomedical informatics at Mount Sinai School of Medicine
Duncan Ross, director of data science at Teradata
Jan-Eric Litton, professor, department of medical epidemiology and biostatistics, Karolinska Institutet
Jonathan Peachey, head of consulting, Kinapse
Andy Black, co-founder and chief executive officer, Kinapse
Ryan Peeler, director at Lnx Research
Dream Samir, managing director at Merck Serono
"Big data isn't just about the amount of data, it's about having the means to analyse the data, and gain knowledge and insights from the whole dataset, not just a bit at a time. It's also about combining multiple data sources and learning from the relationships across these." Joel Dudley, assistant professor of genetics and genomic sciences and director of biomedical informatics at Mount Sinai School of Medicine
"Big data’s real sweet spot is around innovation, and innovation always has an element of risk associated with it. Failing fast is important – you want to identify the approaches that are heading towards value and very quickly discard the ones that aren't.” Duncan Ross, Director of Data Science at Teradata
"There are lots of software developers and engineers who were not working in the healthcare arena but love working with data to find new solutions, and they and their platforms can easily be transferred over into our industry." Dennis Urbaniak, VP, US Diabetes at Sanofi US
"There is potential for companies to be able to differentiate themselves and their products through big information." Jonathan Peachey, head of consulting, Kinapse
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