Pharmaceutical sector is one of the strongest industry sectors across the globe. The arena is known for the big revenues it churns every year. The complex nature of its operations and the huge amount of data created on the course of development of its products is not known by many people.
The pharmaceutical industry
Just to have an idea of the extremely large amount of data that this industry sector has to deal with, it will be appropriate to know that only one out of every 10,000 discovered compounds becomes an approved drug for sale. Further, only three out of every 20 approved drugs bring in enough revenue to cover developmental costs. And finally only one out of every three approved drugs can create enough income to cover the development costs of prior failures.
Apart from that, it takes a period of around 7-10 years and an average cost of $500 million to develop each new drug. All this very clearly establishes what a mountainous size of molecular and clinical data gets stored in proprietary networks of pharmacy industries.
Still, till recent times pharma companies didn’t seem interested about going for analyzing their data and exploring the possibilities it might offer. The primary reason behind it was elucidated by Scott Evangelista, principal at Deloitte Consulting who in his study ‘The Case for Advanced Analytics’ said that the more profitable these enterprises are, the less they look for the pennies and the minor tweaks and twists that would boost efficiency and return on investment.
But now, things are changing for the good, and pharmaceutical companies are adopting data visualization and analytics, and have begun realizing the benefits of doing the same in their operations.
Adoption of data visualization
Increasing adoption of data visualization and analytics in the pharma sector has witnessed a surge in their collaboration with both internal players and the outside world. To gain a competitive edge, increase their expertise and enlarge their ever-growing databanks, pharmaceutical sectors are now working with external partners and academic collaborators.
Pharma companies have now turned more open towards partnering. With various research organizations and data management companies and exchanging their data with them for better visualization and analytics. Further, they have also begun partnering with academic collaborators across the globe. A pharma company named Eli Lilly launched Phenotypic Drug Discovery Initiative with an aim to get a first look at compounds being developed outside of the company. Under the initiative, external researchers submit their compounds for screening and the company uses its proprietary tools and data to identify whether any of them have the potential to become drugs.
Additionally, data visualization and analytics has also helped the pharma companies in interacting with their customers, health professionals and insurance companies. With the help of sentimental analysis through various social media networks, pharma companies are now personally reaching out to their customers and physicians. Insights gained from these efforts can then be used to shape strategy throughout the pipeline progression. Also, some pharmaceutical enterprises are now creating proprietary data networks where payers and providers can share, analyze and respond to outcomes and claims data; which in turn helps these companies to enlarge their databanks far beyond clinical trials.
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