Pharmaceuticals

When Takeda wanted to produce more efficiently, they leveraged Minitab’s predictive analytics to increase yield from cell cultures used during the production process.

The regulatory authorities worldwide, largely driven by the Federal Drugs Administration in the U.S and its European counterpart, are making increasing demands in the interest of patient safety.

Pharmaceutical companies and organizations in the health sector are to apply more complete and complex techniques mainly for process validation but also for the monitoring and the evaluation of the performance of production processes (traditionally called SPC – Statistical Process Control).

There will also be greater demands of the use of statistical procedures for method or measurement validation, notably to check for measurement imprecision and bias. To meet these demands, it is good practice to follow these three 'critical checks.’

When manufacturer Shire Pharmaceuticals identified undesirable impurities in rare disease treatments, investigations began. What was guilty, the measurement system or the process? Without understanding the cause, the impurities risked problems with the release of the product not being compliant or affecting patient safety.

This pharmaceuticals track provides the foundation for effectively applying statistical tools to the different stages of the FDA Process Validation Guideline. Learn how to use data analysis techniques to understand product variation and defects, determine shelf life, assess if a process is capable of meeting specifications, and monitor the stability of a validated process.

Process validation is vital to the success of manufacturing pharmaceutical drugs, vaccines, test kits, and a variety of other biological products for people and animals. The FDA recommends three stages for process validation. Minitab can help you analyze your data with the statistical techniques typically conducted within each stage of process validation.