Bringing data together in one place for positive outcomes
The solution for Owen, in his consulting work for real pharmaceutical clients through Insight By Design and with his students at De Montfort, is JMP software. JMP has become integral to the QbD program, where it’s used to organize research data and to document and access the data students generate as part of assignments in experimental design. And Schlindwein agrees: “The use of JMP® enables us to teach students how to organize research data, apply visualization and perform data analysis. Data management and data integrity are key within product development and manufacture.”
Owen is especially excited about the Projects capability in JMP 14. Projects allows users to divide their desktops into zones for files, folders and virtual folders. Users can add reports, data tables, scripts, journals and even files in formats other than JMP. After they perform an analysis, the files appear in tabs. They can display multiple reports or graphs and run scripts from the Project. And importantly, the reports and graphs remain linked to the data table.
“It’s all interactive, so I can compare what happened in one table with another table,” Owen explains. “If I have different models, I can quickly tab through them. If I want to access an associated report, I can pull that up.
“A problem endemic to both academia and industry is having your data scattered all over the place,” he continues. “But with JMP, you can very quickly bring it all together.”
In addition, as users create models or data visualizations, they can save the script of the data table to a journal. “Now you have a means of re-creating that analysis exactly in the future,” Owen says. “And because the data can be arranged in tabs, you can see this sequential buildup of knowledge. Or you can create a dashboard view and present the same data in different ways, depending on the story you need to tell.”
Most importantly, JMP enables the management of contextual data – an increasingly valuable consideration. “People move from company to company more than they used to,” Owen points out. “And every time someone leaves a company, knowledge gets lost.”
By way of illustration, Owen offers a real-world example of the value of capturing institutional knowledge. In pharmaceutical manufacturing, pills sometimes stick to the mold they’re formed in, slowing production. “Historically you would fly in your experts for troubleshooting,” Owen says. “But now you have a useful way to store and access that data-driven knowledge so that you can retrieve and apply it quickly.”
Such historical and contextual data is key to QbD. “Quality by Design involves risk assessments,” Owen says. “You need to know the frequency, the severity and your ability to detect a potential problem.” In the past, stakeholders would ask experts what they remembered from past experience. “Today they ask, ‘What data do you have to support this?’”
Trustworthy data is equally important for regulatory compliance. “Regulators will come in and ask, ‘How do you control this? How can you ensure the safety of patients?’“ Owen explains. “Now you have a mechanism to say, ‘Here are the potential risks, and these are the control strategies, and here’s the data to support it.’”
But the greatest value for Owen is that JMP combines so many capabilities in a single tool. “Some programs might do experimental design well, but that’s all they do,” Owen says. “JMP has the table manipulation, it has the modeling, it has the visualization. It has all these things. You can actually use one package to do everything and organize the output.”