The vision of Life Science Leader is to be an essential business tool for life science executives. Our content is designed to not only inform readers of best practices, but motivate them to implement those best practices in their own businesses.
Issue link: https://lifescienceleadermag.epubxp.com/i/161331
Pharma Manufacturing LSL: WHAT ARE SOME OF THE CHALLENGES TO IMPLEMENTING CM GIVEN THE ABSENCE OF FDA REGULATORY GUIDANCE? KN: There are two issues. One is how big is a lot size, and how do you define that with CM. I think there is some good guidance that has been developed here. The other issue involves the use of online analytics to monitor and control your process. These are not the traditional, single-loop feedback control systems (i.e. controlling temperature or pressure on a reactor). They require much higher-level control strategies, and understanding those is a challenge. These provide more data than that of a batch environment (i.e. doing military-standard sampling and testing for release). When you gather more data, you are going to see more variability than when working with a smaller sample size. Now, the variability was always there; you just weren't picking it up in the sampling technique you were using. That has been somewhat of a challenge — to talk about how you manage this much larger data set, and what is acceptable in terms of adequately controlling your process. This is a learning process for both the manufacturers and the regulators. We have found the FDA to be relatively open and cooperative to the manufacturing approaches we want to take at Pfizer. Some of the new approaches should improve overall robustness of manufacturing processes over time. In many cases, multiproduct CM platforms will make it easier to respond to surges in demand, allowing companies to better manage drug shortage situations. I think one of the best ways to go about implementing CM processes is to develop the analytics in line with the application. Once we get to the point where we are satisfied with a control strategy, it's really good to be open and suggest it to the regulators as part of the data exchange around the technology. Engage the regulatory agencies as early as you are comfortable, sharing with them where you are going. You need to suggest and propose the appropriate control strategy around that technology to the regulators, because you are the experts. LSL: WHAT ARE SOME OF THE IMPORTANT CONSIDERATIONS FOR CREATING CONTROL STRATEGIES FOR HYBRID MANUFACTURING? KN: Quite often, a lot of the data you've been capturing all along for other reasons can really be helpful in monitoring the health of your total manufacturing process. That's where you start to get into some of the more subtle and less obvious relationships that can give you information on your process. This is a big challenge, because you have so much information now that you've got to be careful in terms of how you use it versus what is actually needed specifically for process control. Take tablet coating, for example. Occasionally, we would have 48 LifeScienceLeader.com September 2013 coatings that were uneven, which might result in having to reprocess or reject a batch that wasn't cosmetically acceptable, even though the active and the tablet were fine. For years we have been striving to get better control of the inherent challenges with tablet coating. To that end, we placed some better technology to monitor temperature in the tablet coater. We found that we were collecting a lot of other data, like motor speed on the drum of the coater, flow rate of the coating solution going in, air flow rate and temperature, as well as the routine types of monitoring metrics. We then conducted a fairly sophisticated analysis that provided a "fingerprint" of the tablet-coating process. This allowed us to watch for trends and anticipate flaws before they showed up in the physical product. LSL: WHAT ARE SOME OF THE METRICS EMPLOYED TO DETERMINE HYBRID MANUFACTURING AS BEING EFFECTIVE? KN: You can evaluate those traditional measures — quality, yield, productivity, labor costs, etc. — as a straight comparison. Certainly, we do see improvements in those unit operations that can benefit significantly from CM. From an expense perspective or in an ongoing cost per unit, you'll typically see a lower cost for continuous than you would for batch. But if you've got a batch facility that is largely depreciated, and you've got to build a new CM facility, you need to compare capital and operating costs in your analysis. The other thing we noticed is that the processing costs are typically incremental. You need high volume so that you're multiplying by a big number of units to realize value. This is something to pay close attention to as a product approaches the end of its life cycle. Generic incursion can drop volumes, substantially reducing the total benefit. LSL: ANY PLEASANT SURPRISES FROM IMPLEMENTATION OF CM PROCESSES? KN: Yes, we have seen some examples. I can't go into detail on the products, but they were typically in situations where you could actually do something a different way with continuous than you could with batch. I'll use an example of a chemical process step where you have an exothermic reaction that you couldn't do in batch because it was unsafe to have that much material in a reactor generating that much heat. Because you couldn't control it safely, you had to use different chemistry. In a flow reactor, because you're dealing with microscopic amounts of the material, even though the heat is generated, you can remove it much more effectively. Because you are using a small amount of material, there's not as much of a risk. We've had a couple of cases that have produced substantial ROI compared to a batch process.