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How is Business Intelligence helping the Pharma Industry to Achieve Efficiencies and Halt Costs?

We have long been in an age where there is too much information for one single person to analyze. What we now call “data analytics”- consisting of greater volumes of data, smarter analytics, and more advanced technologies- has been an indispensable tool for businesses to make informed decisions in the modern world.

The pharmaceutical industry is a highly regulated one with new drug approvals requiring years of R & D, testing, and refining. The life sciences industry is one of the most data-centric organizations and it generates large quantities of data in the form of images, video, audio, and documents. The data for a single drug can run into petabytes and constantly increase with every new data set that is generated. A recent study by Aberdeen Group indicated that the life sciences industry is moving to a “Big Data-driven business” with new drug approvals requiring years of R&D and testing.

Data analytics in the Drug discovery process:

The drug discovery process is a long and expensive process. The process involves screening for chemicals that might be used to treat a disease using a broad variety of assays. In 1938, Sandoz Labs in Switzerland was the first company to produce synthetic vitamin C, but the process was not cost-efficient. In the 1990s, new technology allowed the company to optimize its process and lower the cost by 30%. The company held tie-ups with research organizations to use its technology to develop drugs for HIV, cancer, diabetes, and other diseases. But the tie-ups didn’t work out. In 2000, the company conducted a study to find out why the tie-ups did not work out. The study revealed that the drug research organizations were not looking at the data in the right way. The study prompted Sandoz to develop a new data analysis software, called Sandoz Insight, to help organizations make better decisions. The software helped Sandoz increase its sales by 50% and helped it win new business.

BI & Data analytics in clinical trials and precision medicine:

Business intelligence is a key part of the next generation of healthcare delivery and research, as it helps to reduce costs, time, and inefficiencies. The data-driven research and development (R&D) of precision medicine is a key example of how business intelligence can be used to improve the healthcare industry. Precision medicine is a new approach to disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle. It’s based on the understanding that most health issues are caused by a complex interaction between genetic, environmental, and behavioral factors, and that a one-size-fits-all approach to healthcare simply doesn’t work well.

Data analytics in Research and development:

Clinical trials are the costliest step in pharmaceutical research and development (R&D). Over 70% of developmental costs are due to clinical trials, which are also the slowest step in R&D. In fact, it takes about 12 years for a drug to get from the initial discovery to the market. This is a long time when you consider that many new drugs fail in clinical trials, and those that pass cost a lot of money to develop. It’s no surprise that pharmaceutical companies are looking for ways to improve their R&D efficiency and lower their developmental costs.

Conclusion: Business intelligence is playing a key role in helping the pharmaceutical industry to achieve efficiencies and halt costs to keep the industry moving forward. The pharmaceutical industry is a key supplier of consumer products and services globally. In 2014, the pharmaceutical industry contributed more than US$1.1 trillion to the global economy.

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