Solutions to Deliver Better, Safer Pharmaceutical Solutions that Help Save Lives
- Deliver Safer, More Affordable Therapeutics
- Boost Drug Production
- Critical Checks to Ensure Process Performance
- Identify Root Cause of Impurities
- Training: Statistical Tools for Pharma
- Passing FDA Process Validation
Our Pharmaceutical Manufacturing Solutions
We know your ultimate goal is to improve the quality and consistency of your manufacturing operations and increase production yields, while bringing the safest products to market. Minitab understands that patients around the world are counting on you to save their lives or those of their loved ones. By operating more efficiently, you can keep costs down and deliver more affordable therapeutics to the people who need them. That’s why every single healthcare company in the Fortune 500 leverages Minitab solutions.
We can help you prevent downtime, increase production yields, and reduce defects to eliminate costs and achieve your goals. We also understand the important safety measures you take before bringing your solutions to market. Use the power of machine learning to predict changes to your process or fluctuations in demand to eliminate problems before they occur.
Deliver Safer, More Affordable Therapeutics
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.
We know every pharmaceutical compound, chemical, or biologic needs to be high-quality and consistent. From development to approval, the pharmaceutical manufacturing process must be carefully planned, accurately measured, and closely monitored. And the data must be analyzed so you can have the utmost confidence in your results.
Only Minitab enables you to address all these challenges in one market-leading ecosystem. Our proven solutions give you the power to collect your data automatically, or allow operators to manually enter data so you can monitor your processes in real-time. Instant alarms can alert you to defects as they occur—and that means you can act without sacrificing a single lot in! Our manufacturing operations solutions analyze your findings to make improvements and leverage the power of prediction to catch problems in your manufacturing process or machinery before they occur.
“(I use Minitab) for day-to-day data analysis. (Any person) who does not have a statistical background can easily use this software for data analysis purposes like simple mean, median, mode, standard deviation to complex analysis like anova, t-test, the correlation coefficient, and principal component analysis.”
Chief Scientific Officer