Process Development The Ultimate Tip for a Scale-up that is Guaranteed to Succeed

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When it comes to originator companies and drug development, there is a lot of money at stake. Faster development and faster time-to-market means more time to benefit from patent protection — that’s the motto. Here we examine why so much depends on a systematic approach and the role of the scale-up.

Some process engineers might cringe a little when they hear the buzzword “scale-up,” even if they have not yet had much experience with it. On the list of top flops, the scale-up of pharmaceutical processes ranks very high. Stories about failed approaches that cost companies a great deal of money and might have even cost project managers their jobs probably make their rounds in every pharmaceutical company. If something goes wrong during a scale-up, problems arise in process control, which are almost always at the expense of product quality. It is not without reason that there is ample literature dedicated to this topic, and every mechanical engineer attaches great importance to the statement that their machines are scale-up capable.

Norbert Pöllinger, a pharmacist by training and head of Glatt Pharmaceutical Service for over 20 years, could tell many a story about failed scale-ups. However, he has even more to say about successful scale-ups, and of course he would much prefer to talk about that. “There’s no need to be afraid of scaling up,” is Pöllinger’s philosophy, which has been cemented by many years of practical experience. Pharmaceutical Services has been involved in the development and production of solid pharmaceutical dosage forms for clinical trials and market supply to external customers for several years. And of course, this also includes seamless scale-ups from the laboratory to production scale.

Trial and Error — a Practice Best Avoided in Process Development

The trial and error approach that some companies take with new drugs when they want to move quickly from the lab to production does not help achieve the goal, says Pöllinger. In his experience, most errors occur because companies neglect the risk-based approach when scaling up and skimp on the number of lab tests. Anyone who subscribes to the motto “no risk, no fun” would be better off letting off a little steam at the gym instead. In this case, diligence and a great deal of brain power are of the essence. The more preparation that goes into formulation development in the laboratory, the safer and smoother the transition to market supply will be.

The concept behind this is called Quality by Design (QbD) and has actually been around for quite a while. The U.S. FDA has been promoting this approach for almost 20 years and has dedicated no less than four guidance documents to the topic of scaling up, which regulate how drug manufacturers should ramp up production of a drug once it has been approved. The final FDA guidance from 2014 specifically encourages drug manufacturers to use a risk-based approach when evaluating equipment changes during the scale-up and post-approval change (SUPAC) process.

Only Those who Understand their Processes can Produce Quality

It is all the more surprising that only part of the pharmaceutical industry follows this recommendation while others neglect the systematic approach based on sound science and quality risk management. “QbD emphasizes product, process understanding and process control,” Pöllinger points out. For good reason, Pharmaceutical Services therefore favors the FDA’s approach and is in agreement with its key customers, the manufacturers of originator drugs.

“We put a lot of hard work into formulation development in the lab,” says Pöllinger, who also has an example ready to illustrate this approach. For the process development of a blockbuster drug with tight time constraints, for example, the Glatt pharmaceutical team carried out 26 small-scale trials on a four-kilogram scale before scaling up to 80 kilograms. Eight tests were run here. Three attempts were enough for the 300 kilogram batch, and only two were needed for the final scale-up to 600 kilograms.

The tests were flanked by the design of experiments (DoE), in which the critical product and process parameters were worked through. In addition, the influence of the active ingredient quality was investigated using several active ingredient batches. Pöllinger is a huge fan of the statistical design of experiments, because the method demands a structured approach and an examination of which process parameters are important and/or critical. “Development is about considering what difficulties can exist and what must be done to avoid them,” he explains.

Design of Experiments — Invest Time here, and Reap the Rewards Later

Many companies skirt around DoE, he says, running one or two small-scale experiments and then going straight to full-scale — at proportions that make it difficult and extremely expensive to correct mistakes. Another advantage of implementing QbD is that once regulators have validated and signed off on the process, the company can play with the parameters within the design space and does not have to report every single change to regulators again.

According to the pharmaceutical expert, any company that wants to get to market quickly and that strives for a secure market supply, the approach described is the preferable one. And this will be rewarded with faster time-to-market, robust processes and fewer faulty batches. As a result, any discomfort that some might feel when they hear the words “scale-up” should be a thing of the past.

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