Business intelligence in pharma: a use case
Business intelligence in pharma: a use case
Date:
The business intelligence (BI) solutions provider SAS was asked to help the pharmaceutical company AstraZeneca make the manufacturing process of its Turbuhaler product cost-effective and with lower variations. The challenge ahead of the company was that building a solution with enough capacity to handle all of the production-related data that was stored in so many unique systems.

“AstraZeneca asked SAS to produce a prototype of a business intelligence solution with the capacity to store, analyze and generate reports for a large number of different user groups,” SAS says in a note on its website. “The goal was to increase yield, improve quality, minimize variations and save time. Using SAS, AstraZeneca -- which operates 26 plants in 18 countries -- achieved quality-assured, cost-efficient Turbuhaler production by automating its vast data management and analytics efforts.”

Requirements

Eva Nossborn, Process Engineer at AstraZeneca explains that the company had very strict requirements for the SAS solution.

“Pure production data combined with supportive data sources, e.g., planning systems and quality systems, generate tables with enormous amounts of data,” Nossborn says. “There are approximately 1,000 parameters in the system. The daily rate for an individual table was recently about 170 million rows, and the amount grows by 1.5 million rows every week."

 What was provided

According to SAS, the most time-consuming part of the project was building a system to collect all of the data in one database and ensuring that everything met the high standards demanded within the pharmaceutical industry.

“Between 50 and 100 employees create or receive the reports from the system,” SAS said. “The primary users are the process engineers, who are responsible for following up on daily production. They receive prepared reports and are also able to develop their own special reports. Other users include operators, statisticians, analysts and those responsible for quality assurance, as well as other managers within the company."

Time saved was the main advantage that the SAS solution provided. However, this was only a part of the initial motive behind building the system. Streamlining production with a comprehensive plan was important too.

"We work continuously to increase productivity," says Henrik Åkerblom, a process engineer and one of those responsible for the implementation of the SAS solution. "This applies to increased utilization level during production and increasing the yield and quality of the products. Using SAS, we have been able to minimize the variations in the production process and expand the contents of the analyses performed."

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