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Big Data Series, Part II – The Future of Human Society

Experts are only now beginning to realise the importance of Big Data. This relatively new phenomenon is providing vast amounts of information, helping us shape the future of human society.

After analyzing how the healthcare sector will be influenced by the rise of this technology in the 1st part of our Big Data Series, it’s time to take a look at how Big Data can deal with larger scenarios affecting humankind.

Dealing with Pandemics

Global and regional pandemics and epidemics are obviously among the most serious events that can occur within any society. While these have been contained pretty well over the last few years, it is also true that big data can play a major role in assisting in the fight against the spread of diseases. Examples in Africa have already shown that mobile phone location data can be highly effective in tracking population movements, helping emergency relief organisations and governments anticipate how a disease is likely to spread.

 

Big Data and Mobile Mapping

Mobile phone data from West Africa is being used to map population movements and predict how the Ebola virus might spread (source: BCC)

“Until now they had to rely on anecdotal information, on-the-ground surveys, police and hospital reports.” – Nuria Oliver, a scientific director at mobile phone company Telefonica, extract from  the BBC article ‘Ebola: can big data analytics help contain its spread

 

Big data is also playing a major role in cancer research. Flatiron Health has developed a service called the OncologyCloud, based on the idea that 96% of potentially available data on patients with cancer is not yet analysed. The aim of this initiative is to make such information available to clinicians, and thus jump start a revolution in the treatment of cancer. Changing the way life science companies use real-world data will much likely accelerate research, generate evidence and get a step closer to outsmarting deadly diseases.

Pharma Tweaks

Big data could also play a major role in the pharmaceutical industry, with several of the biggest drug manufacturers already investing in the technology. For example, GlaxoSmithKline employs online technology and a data algorithm developed by F1’s elite McLaren Applied Technologies team to minimise the risk of leakage from its best-selling Ventolin (salbutamol) bronchodilator drug.

“Using multiple sensors and hundreds of thousands of readings, the potential for leakage is coming down to close to zero.” – Brian Neill, diagnostics director in GSK’s programme and risk management division, extract from the FT article: Big data promise exponential change in healthcare

 

Analysis in this sphere is already beginning to influence the sales and marketing of pharmaceuticals significantly. Applications in this area are actually quite vast, with the ability of big data to help fine-tune research and clinical trials, providing measurement capability for doctors, insurers and regulators, thus providing massive potential.

Genome Data

One of the most obvious sources of big data is the human genome itself, and techniques related to data analysis in this thriving technology promise to enable genome data to be stored and analysed with much greater sophistication.

BC Platforms, a Swiss-Finnish company that manages clinical and genomic data with its own analytics platforms for academics, healthcare providers and life science companies, has entered into agreements with the likes of Microsoft Azure and Codigo46 of Mexico to create the largest biobank in Latin America. Human genome data from over one-million people on the continent will be acquired over the next three years, in what is undoubtedly a massive project.

“Microsoft has built a scalable cloud-based service that enables us to easily and reliably process large volumes of genomic data, and we are leveraging this in our partnership with Codigo46.” – Tero Silvola, CEO BC Platforms, extract from the Microsoft article: Codigo, BC Platforms, Microsoft partner to build commercial repository of Latin America genotype data

 

Actually understanding this data is undoubtedly challenging, but already gene sequencing experts state that this field is rapidly evolving due to big data, and is even becoming primarily information-driven. What is emerging is an entire subfield of artificial intelligence, which will enable experts in this area to detect and understand hidden patterns in monumentally large datasets, improving our understanding of the very building blocks of life.

As more big data is collected, it seems increasingly clear that the potential of this new phenomenon is only just beginning to be explored.