Whitepaper: Big Data in pharmaceuticals – big opportunities or big challenges or both?

Big data covers every facet of our working life. Every aspect of pharmaceutical research and development involves the generation of huge quantities of data, with the expectation that we can turn this information rapidly into useful knowledge, which in turn can be used to make ‘data-driven’ decisions to better understand and control processes…

This derived knowledge can also be used to reduce costs, improve efficiencies, reduce development times and facilitate rapid post-approval changes. It needs to be understood that in addition to having multiple data-users within an organisation, these individuals/ groups, will have different objectives, i.e. trending, change control, decision making, etc.

In addition, with increased complexity of molecules and processes, there is an increased likelihood of generating larger volumes of supporting data. Biologicals and particularly biosimilars are good examples of this latter scenario. Thus for example, the ability to evaluate and trend significant volumes of analytical data generated from orthogonal methodologies, which often generate conflicting data, as part of a comparability exercise for biologicals/biosimilars will continue to be challenging.

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