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article imageWhy big data analytics are proving essential for pharma

By Tim Sandle     Aug 4, 2020 in Business
Big data has the potential to become translated into 'big business' for pharmaceutical firms, despite the slow growth with analysis of large volumes of data using artificial intelligence solutions.
Pharmaceutical companies are starting to use voluminous data to do everything from interpreting clinical findings to measuring the effectiveness of drugs based on real-world health outcomes.
One reason why there is a great deal of interest in big data analytics in the pharmaceutical field is captured by Alex Zhavoronkov (writing in Forbes). The commentator explains that the pharmaceutical sector is probably the only area of business where, to get the product from idea to market, the company will need to spend about a decade and several billion dollars to advance a product (in this case a medicine) to the final phase. At any point up to final registration of the drug, there is about 90 percent chance of failure.
It is for this combination of time, money and low probability of success that pharmaceutical companies are seeking to balance their risks with a wider use of artificial intelligence and big data analytics. There is also the likelihood that the use of these approaches will accelerate given the future availability of lower cost AI-applications that can be used in combination with faster hardware. in turn, these technologies will boost progress with the digitalization of pharmaceutical Research and Development data. , There are clear limits to the insights that such large data sets, on their own, can provide based on the complexity of the information and the time required; hence the fact that AI and big data analytics need to go hand-in-hand.
As well as AI, the rapid integration of cloud computing platforms has eased the processing of big data analytics and consequently the demand for big data services has risen.
The above benefits are outlined in a paper that was undertaken an analysis of annual company reports, investor relations information, patent applications, and scientific publications drawn from 21 pharmaceutical companies (across 2014 to 2019). This led the authors to assess the industry ‘early mature’ phase of using AI in R&D. Despite the earlier stage of development, the signal is that it is worthwhile for drug development firms to invest in order to become a ‘digital pharma player’.
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