Thursday, October 2, 2014

Analytics for Modern Bioprocess Development

Today, we feature an article from our partners at BioProcess International Magazine. This is an excerpt from the article Analytics for Modern Bioprocess Development.

Like most other industries growing within the rapidly changing information era, the bioindustry is generating more data than it ever has before. But meaningful information — that which can be linked to process knowledge and, ultimately, process control — is useful only with a robust and efficient data acquisition system. As Gernot John (director of marketing and innovation at PreSens) observes, the underlying factors supporting improved data acquisition in the industry include an increased interest in switching from offline to online measurements, scalability (miniaturization) of analytical instrumentation, and the ongoing change from analog to digital signal transmission.

“Determining the type of process data you need to evaluate — whether it’s quality data, discrete, or online measurements, and/or batch-record data — begins by asking ‘What are we trying to achieve?’” notes Justin Neway, PhD (general manager, operations intelligence and senior fellow, Accelerys Science Council, at Accelrys). He identifies at least four drivers in the need for process informatics. The first is a need to reduce process variability by improving process understanding (which is the touchstone of PAT and QbD), implementing robust design processes, and using online instrumentation. “When QbD came out, it started to sound a bit more pragmatic than PAT. Then the industry started to see the connection between it and PAT, and the industry began actually producing useful outcomes. Now, with the aim of process robustness, it becomes much more business oriented,” says Neway. He points out that a robust process reduces business risk by decreasing supply chain risk. It also can improve profitability and decrease patient safety issues and risks of 483s and FDA warning letters.

Another driver for process informatics is the need for transparency in outsourcing relationships. “That’s not just about cost. It’s about companies specializing in their core area,” says Neway. Much of the renewed emphasis on contract relationships stems from a 2013 FDA draft guidance on quality agreements (2) “The phrase I love in that document is that the FDA considers contractors ‘an extension of the manufacturer’s own facility’” says Neway. With that statement, the agency solidifies the union between sponsor company and contract organization — they are one in the same.

A third driver is the bioindustry’s need for collaboration. Certainly that applies to the partnership between a sponsor company and a contractor, but it holds true for internal collaborations as well. Those types of collaborations can be tough for two reasons, says Neway. “First: You need process development (where the process is designed and scaled up) to collaborate with quality (which takes the responsibility for minimizing risks to patients) and manufacturing (where the process is operated repeatedly at commercial scale and needs support from those who designed it). Second: You need to have those collaborations on a global scale. Email is not enough — you need an environment where people can dive in and work on the same data regardless of time zone, department, even what company logo they’re working under. That is one of the big drivers for process informatics”

The last is the bioindustry’s need for knowledge capture, transfer, and management. Experienced professionals are retiring from the industry, taking with them the process knowledge and expertise that much new hires still needs to embody. “That means knowledge needs to transfer from more-experienced people to less-experienced people as efficiently as possible,” says Neway. This last point is especially important for connecting the operations data and measurements data between, for example, quality laboratories working with laboratory information system (LIMS) and process batch-scale operations working with batch record systems and data historians. People tend to act in silos. “Their LIMS system is organized to identify and manage samples, test protocols, operators, standards, and provide reports of all the results of all the samples. It was not built with an organization that reflects the production process.”

You can find out more about topics like this and meet and network with other professionals in the bioprocessing field at this year's BioProcess International Conference and Exhibition.  As a reader of this blog, when you register to join us October 20-23 in Boston, you are eligible to receive 20% off the standard rate when you mention code BPI14BLOG.

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