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Eston Martz

FDA Compliance

Does Every Good Analytical Chemist Need to Be a Statistician?

Tools that make analysis easier

Published: Tuesday, October 27, 2015 - 09:48

I read trade publications that cover everything from banking to biotech, looking for interesting perspectives on data analysis and statistics, especially where they pertain to quality improvement.

Recently I read a great blog post by Tony Taylor, an analytical chemist with a background in pharmaceuticals. In it, he discusses the implications of the FDA's updated guidance for industry analytical procedures and methods validation. His audience comprises analytical chemists and pharmaceutical researchers, people who are technologically savvy and adept at solving problems. The kind of people you’d imagine are very capable and eager to collect some data and figure out what they mean.

Or maybe not.

What Taylor’s post makes clear is that even a highly educated, scientifically inclined audience like this doesn’t necessarily appreciate the value of statistical analysis—or at least, doesn’t really enjoy actually doing it.

Taylor acknowledges an issue that Minitab has focused on from its earliest days: When it comes to analyzing data and using statistics, some people seem to get it right away, and others don’t. Some people enjoy it, and many others find it tedious or even painful.

Those who fall into that second category—even highly educated analytical chemists—tend to try to avoid statistics, even though there are many tools available to help them get the benefits of analyzing their data more easily and quickly. The problem is that trying to avoid statistics and data in today’s world is like an ostrich burying its head in the sand so it won’t see a threat.

Taylor points out that new FDA guidelines make this particularly true in the pharmaceutical realm, where “the use of statistics will only be increasing in the future.”

So does this mean every analytical chemist needs to be a statistician? No. But Taylor makes a strong case that good analytical chemists at least need to appreciate and be prepared to apply statistical methods in their work—and that’s excellent advice for people in most professions.

Tools that make statistics and data analysis easier

Minitab has always sought to help more people understand and apply statistics, so it’s extremely gratifying that Taylor gives us a shout-out by name: “If one wishes to utilize some of the most useful aspects of statistical experimental design and optimization, then one would need to use a simple statistical tool such as Minitab... This program is very easy to use, and with only a rudimentary understanding of the principles, can help us to improve our analytical practice enormously.”

Now that’s music to our ears! Our goal has always been to make Minitab easy to use, and by adding features like the Assistant to guide you through statistical analysis and help you interpret the results correctly, we are striving to open the world of data analysis to as many people as possible.


Click here for larger image.

Taylor goes on to call out Minitab’s design of experiment (DOE) capabilities, which certainly have great application in chemistry and pharmaceutical research. He notes that with Minitab...it is very straightforward to plan, implement, and analyze fractional factorial designs, which allow us to investigate the dominant variables within a method and help to control them more effectively. We can use the same methods for identifying interactions between variables in our methods and control or eliminate them. It is very easy to plan a fractional factorial design such as the Plackett-Burman, in order to significantly reduce the number of experiments required to validate an analytical method for robustness. We can also use full factorial methods to optimize an analytical method in significantly fewer experiments using the tools available within Minitab.”

Though Taylor doesn’t mention it specifically, one of my favorite additions to Minitab 17 is the DOE Assistant. Designed experiments are extremely powerful, but there is a perception that they are difficult to set up and analyze. The Assistant will actually guide you through the process of designing and analyzing both screening and optimization experiments, and even puts your results into straightforward language that’s easy to understand and share with others, regardless of their level of expertise.


A DOE optimization report created with the Assistant in Minitab 17. Click here for larger image.

Resources for using statistics in pharmaceuticals

If you’re just getting started with statistics or Minitab, check out our e-learning course, Quality Trainer. You can also download Minitab Statistical Software and try it free for 30 days.

We've also developed an instructor-led training program that can help you use statistical methods to validate a pharmaceutical process for each stage of the FDA Process Validation Guideline.

If you’re using Minitab Statistical Software, we offer resources to help with your validation, including Minitab’s software validation kit here. This kit was created to help you understand how we validate Minitab for market readiness. And you can find additional information about validating Minitab relative to the FDA guideline CFR Title 21 Part 11 here.

Finally, Minitab's statistical consultants—highly respected statisticians with experience in pharmaceuticals, medical devices, and many other industries—can help you overcome even the toughest data analysis challenges.

Whatever industry you’re in, wherever you are on the continuum of statistical experience and expertise, we encourage you to get the maximum benefit from the data you’re collecting and analyzing, and we’d love to help.

Discuss

About The Author

Eston Martz’s picture

Eston Martz

For Eston Martz, analyzing data is an extremely powerful tool that helps us understand the world—which is why statistics is central to quality improvement methods such as lean and Six Sigma. While working as a writer, Martz began to appreciate the beauty in a robust, thorough analysis and wanted to learn more. To the astonishment of his friends, he started a master’s degree in applied statistics. Since joining Minitab, Martz has learned that a lot of people feel the same way about statistics as he used to. That’s why he writes for Minitab’s blog: “I’ve overcome the fear of statistics and acquired a real passion for it,” says Martz. “And if I can learn to understand and apply statistics, so can you.”

Comments

Statistics a buzzword

I believe you will find this symptom in every industry. In the auto industry, I feel we should be pioneers of analytical techniques, but I am one of two engineers at my company that realize the deep importance of DOE and Anova in industrial applications. Does every chemist, social statistician, or engineer need to be a good statistician? No, I don't think so, but do they need the philosophical desire to use statistics in conjunction with improvement and management systems? Yes. I think Minitab does most of the heavy plugging and chugging for you these days, but the philosophical foundation of statistics as a powerful process control tool is as lost as a buzzword.

I have a theory that buzzwords (statistics included) lose their meaning the further into an organization they travel. The first person to use them is knowlegdeable, but as they travel through diffferent ears and brains (similar to the Kindergarten telephone game), it loses its meaning to the recipient on the other end.

I apologize for the pessimism on your post. On the flip side, you are in a perfect position to bring your peers to your level and bring your company to a new level, just like my team mate and I are perpetually optimistic that we can change our surroundings by being perpetually optimistic about the power of engineering methodology.