Chemineer
 Portable mixer performs continuous and batch applications


 Chemineer’s high-performance portable DT mixer is appropriate for liquid–liquid, liquid–solid, and gas–liquid continuous or batch applications. The mixer can handle a volume of 10,000 L and viscosities as large as 2000 cp. Employees can use one mixer for several vessels because the mixer can be removed easily from the process. The mixer also can be removed for cleaning. Alternatively, the mixer’s drive can be removed while its wetted parts remain with the vessel for easy transport.

The DT mixer incorporates premium-efficiency motors and a heavy-duty gearbox designed to handle the high shaft-bending loads encountered in agitator service. The bearings and gears are sized to bear these loads without requiring additional support outside of the gearbox. Designed for agitator service, the machine’s mechanical seals provide high runout capability, are pressure-balanced for good wear characteristics, and made of FDA-approved materials. The cartridge design of the seal makes replacement quick and safe and helps improve performance.

IDS  
 Compact camera provides high resolution


The UI-5480CP Gigabit Ethernet camera from IDS provides 5-megapixel resolution and is much smaller than most competing cameras. Power-over-Ethernet (PoE) technology lets users connect the camera with a single network cable to a PoE-compatible computer, and the camera’s compact size makes it easy for users to attach it to existing machines.

The camera’s high resolution allows for a large field of view and allows it to capture multiple product labels (e.g., on syringes) at one time. The camera includes a software development kit that allows users to access all of the camera’s functions (e.g., to enable autoexposure, capture an image, or change the frame rate). The software also allows the camera to interface with third-party software, such as that from Cognex. A viewer allows users to set and save camera parameters, capture and adjust video, zoom in or out, adjust color, and save images. The camera is compatible with Linux and Windows systems.

Articles

PharmTech's monthly newsletter, Equipment and Processing Report, reviews the Editor's Picks for the August 2011 edition from Chemineer and IDS.

August 2011 Editor's Picks: Products from Chemineer and IDS

Q: Our facility manufactures several products, and, from time to time, we must process ingredients that we haven’t encountered before through wet granulation. We try to use previous experience to develop the optimal granulation process for each new ingredient, but we sometimes get it wrong. Many times, we’ve taken materials from the granulator only to find that they exhibit poor flow and insufficient density. How can we easily determine the end point of a given granulation process?

A: One solution is to track wet granulation using a powder rheometer. Powder rheometers characterize samples by measuring them in motion. Basic flow energy (BFE), a dynamic powder parameter, can be a sensitive marker of the transition point from wet mass to granules and a precise tool for detecting when granules have attained their optimal properties.

BFE is the energy required to induce a specific flow pattern in a conditioned powder bed. One can measure BFE with a powder rheometer easily using wet samples taken directly from the granulator. Pause the granulation, extract a representative sample for measurement directly into the flow vessel of the powder rheometer, and continue processing if necessary. 

To ensure a homogenous, representative sample, avoid the areas around the spray nozzle and walls, where material tends to be less uniform. Use large sample sizes for large granulates to ensure representative sampling of the batch. Automated measurement protocols can make the measurement fast and highly reproducible. The axial and rotational forces acting on a helical blade as it rotates through the sample are precisely measured to quantify the resistance of the bed (through BFE), which is governed by the properties of the wet granulate.

As water content increases, BFE climbs slowly, and it rises sharply at concentrations coincident with the end point. Physical examination of the samples suggests that this sharp rise corresponds with the transition from wet mass to granules. 

Because BFE is independent of scale, it is of great value when switching from laboratory to pilot to commercial scale. Processing to an endpoint defined in this way gives the operator scope to vary conditions in response to changing feed, scale, or equipment. The approach also is consistent with quality by design. 

—Tim Freeman, director of operations for Freeman Technology

If you have a problem with your equipment or process, an industry expert may have the solution. Please send your question to 

 and we may be able to provide an answer in a future issue. All questions will remain anonymous.

Troubleshooting

We try to use previous experience to develop the optimal granulation process for each new ingredient, but we sometimes get it wrong. Many times, we?ve taken materials from the granulator only to find that they exhibit poor flow and insufficient density. How can we easily determine the end point of a given granulation process?

Finding the End of the Granulation Process

The global economy is still constraining drugmakers’ budgets, and most manufacturers are urgently looking for ways to reduce waste and cut expenses. Several years ago, many pharmaceutical firms were talking about Six Sigma, an industry-neutral organizational change-management strategy that uses statistical tools to improve manufacturing processes. The goal of this strategy is to reduce variation to the point where a process yields fewer than 3.4 defects for every million products. Achieving such a consistent level of quality control could greatly reduce waste and save money for the pharmaceutical industry. But why has talk about Six Sigma died down at a time when it could be of great benefit?

The strategy has generated a backlash, says Jim Catania, managing consultant at Tunnell Consulting. Top managers in the drug industry have noticed news stories about companies, including Home Depot, trying and failing to realize the performance and cost improvements they expected from Six Sigma. Some practitioners who have encountered difficulties have blamed their failures on flaws in the Six Sigma method itself, and these remarks may have created an impression that the strategy doesn’t work. 

But declaring that Six Sigma doesn’t work is akin to declaring that calculus or chemistry doesn’t work, says Catania. Failures generally result from poor leadership and execution. Companies need bright people and intelligent application to use the strategy successfully. Unless a firm clearly understands its current baseline performance, its goals for future improvement, and its strategy for achieving these goals, its Six Sigma program will not be optimized, says Catania. 

Six Sigma is most appropriate for supplies or processes over which a company has tight control, and it might not be suitable for every aspect of pharmaceutical manufacturing, says Chris Moreton, vice-president of pharmaceutical sciences at Finnbrit Consulting and a member of 

’s Editorial Advisory Board. For example, a raw material’s median particle size can vary by as much as ±20%, partly because the industry does not have sufficient understanding or control of some common unit processes (e.g., milling) that determine physical properties. This amount of variability is “not good enough for Six Sigma unless you’ve got a tremendously robust process,” says Moreton.

Imposing the Six Sigma strategy on established formulations and products is not straightforward, and may not work. A better approach is to begin with a quality-by-design (QbD) program for a new product that is targeted to Six Sigma. A drugmaker must understand and be able to control its design space to achieve Six Sigma, says Moreton. QbD, “the ultimate control strategy,” is the basis for Six Sigma, and personnel can monitor the process and maintain control using process analytical technologies, he adds.

Training employees in the statistical tools that make up Six Sigma is only one small facet in implementing the method, as some companies have learned. “We have seen people train black belts without really focusing them” and embedding them in the process, says Catania. When black belts “drop in like Special Forces and try to effect change remotely,” they will not be effective, he adds. 

Instead, the Six Sigma strategy must become part of day-to-day operations for a company to attain all of its benefits. “We’ve embedded it into our workforce and how we handle projects, whether it’s a new customer coming in, process improvement on the line, or even investigations in what we’re doing,” says David Pittman, director of technical operations, inspection, packaging, and warehouse for OsoBio. 

By providing a framework for organizational change management, the Six Sigma strategy “creates the discipline and path to ensure that changes are data driven, that the stakeholders are enrolled, that the implementation has a baseline measurement, and that improvement is real and sustainable,” says Catania. When the methodology is “applied with rigor and discipline, it absolutely works.” Pharmaceutical heavyweights such as Johnson and Johnson, Merck, and Genentech all have active Six Sigma initiatives, notes Catania. The current economy might provide a further reason for more companies to embrace this strategy for process improvement. 

Production Lines

Achieving a consistent level of quality control could greatly reduce waste and save money for the pharmaceutical industry. But why has talk about Six Sigma died down at a time when it could be of great benefit?

Is Six Sigma Still Relevant for Drugmakers?

Healthcare legislation is spurring important changes in today’s economy, including an increased demand for follow-on biologics. These products have properties and benefits similar to those of their patented large-molecule counterparts. Manufacturers of follow-on biologics have a new opportunity to earn profits by reproducing biologics for known markets with high demand. Original patent holders, meanwhile, hope to be the best producer of a given product in the business and to hold on to valuable market share in the face of shrinking profit margins.

For both types of manufacturers, process understanding will be more crucial than ever because it will help them compete and seize new opportunities by ensuring predictable product outcomes. Using information technology (IT) tools to enhance process understanding helps reduce variability that can affect speed to market. IT tools can maximize profits by reducing waste and increasing yields. They also can reduce manufacturing risks related to process variability and provide a higher assurance of safety for consumers.

An IT tool, such as a process-intelligence platform, helps to identify and manage risks and puts the focus on quality, thus helping to achieve the abovementioned business benefits for original drugmakers and follow-on manufacturers. For example, easy access to data early during process development can help personnel build a process model to control process variability during scale-up and manufacturing, thus reducing the risks of extended startup times and lost batches. 

Process and quality data management is essential and only possible if the right tools are in place to enable collaborative data analysis across manufacturing and quality teams, which might span locations around the globe. When all manufacturing sites can view the data from multiple sites and systems on a common platform, teams can compare and contrast results and share information that helps ensure consistent quality. Reducing technology-transfer risks and enabling comparisons of critical process parameters (CPPs) and critical quality attributes (CQAs) across process-development teams and contract manufacturing organizations takes quality and process understanding to the appropriate level. 

Data gathered from the process-design stage and throughout the manufacturing processes can improve understanding of a product and its manufacturing process. A process-intelligence software platform can aggregate, contextualize, and analyze data on demand to make process characterization easier and less error-prone. The platform also can improve process predictability and safety for both original drugs and biosimilars. 

For example, a producer of follow-on biologics might use a process-intelligence platform in the following ways to improve manufacturing processes:

To ensure that CQAs are identified and controlled within the design space as part of a quality-by-design program. This task requires effective collaboration between process-development, manufacturing, and quality-assurance teams that are often spread across several time zones, organizations, or corporations. The process understanding needed to define and obtain regulatory approval for a design space that enables the desired quality outcomes should be developed, implemented, and supported jointly. By better identifying the relationships between CPPs and CQAs that provide effective process control and continuous quality verification, process variability can be significantly reduced, and thus the excess of raw-material and finished-product inventory can be reduced. 

To monitor manufacturing processes at contract manufacturing sites or at a company’s own sites to compare outcomes and determine sources of process variability. An IT tool, such as a process-intelligence platform, provides self-service access to data from multiple sources (e.g., paper records and various manufacturing and quality systems), reduces inefficiencies, and minimizes variability and risks. 

Biopharmaceutical manufacturers have always realized business benefits from improved process understanding, but now more than ever, manufacturers need IT tools to reduce and control variability and improve yields. The business pressure for makers of follow-on biologics and original biopharmaceuticals to reduce margins requires both kinds of companies to reduce process variability to improve bottom-line results.
 
 

Justin O. Neway, PhD, is executive vice-president, chief science officer, and cofounder of Aegis Analytical, 1380 Forest Park Circle, Suite 200, Lafayette, CO 80026, tel. 303.625.2100, 

In the Mixer

Using information technology tools to enhance process understanding helps reduce variability that can affect speed to market.

Equipment and Processing Report-08-17-2011

August 2011 Editor's Picks: Products from Chemineer and IDS

Finding the End of the Granulation Process

Is Six Sigma Still Relevant for Drugmakers?

Biosimilars Increase the Need for IT to Reduce Variability