Process Analytical Technology and Process Control in Solid-Dosage Manufacturing

Fotosearch/Eriko Koga/Comstock/Getty Images; Dan WardSince FDA issued its report, Pharmaceutical Current Good Manufacturing Practices (CGMPs) for the 21st Century—A Risk-Based Approach (1), and its guidance on process analytical technology (PAT) (2) in 2004, academia and industry have been making strides in integrating quality-by-design (QbD) principles and PAT into solid-dosage manufacturing processes.

PAT and QbD principles both emphasize the need for process and material understanding as a basis for effective control of the process. “This emphasis has stimulated the industry to focus on how to get the information it really needs, which is leading to a productive re-examination of the existing analytical toolkit and an embracing of newer technologies that deliver the goods,” says Tim Freeman, managing director for Freeman Technology. Progress has also been made in integrating PAT into continuous manufacturing of finished-drug products, with the eventual goals of closed-loop control and real-time product release.

PAT

Online PAT is successfully being used to optimize individual unit operations in solid-dosage manufacturing by monitoring on-line critical quality attributes (CQAs). Data from PAT give manufacturers better understanding and can be used to control the unit operation. Moisture content, for example, is used to determine the endpoint of a drying cycle. In tableting, the most common online measurements are near infrared (NIR) spectroscopy, which measures moisture content and blend uniformity, and laser-diffraction particle sizing.

Bulk-powder characterization techniques, which are performed at-line or in the laboratory, also fulfill the purpose of PAT by providing crucial information in a timely manner. “Precisely quantifying the flow behavior of powders, either as raw materials or as a blend, and other characteristics such as the ease with which a powder entrains and releases air, supports the development of more efficient processes,” explains Freeman. Flow-property measurements are increasingly being recognized as a desirable online measurement, but this technology is not yet available.

Continuous solid-dosage manufacturing

PAT can be used in continuous solid-dosage manufacturing, in which individual batch-processing units are connected in one process train. Advantages of continuous manufacturing include a smaller equipment footprint, production volume flexibility, and higher production efficiency, in addition to the potential for improved quality and process stability as a result of employing PAT. Continuous processing also allows more efficient process development. Because parameter-change effects can be measured in nearly real-time using a continuous setup, dozens of conditions can be tested in hours rather than days or weeks, notes Douglas Hausner, associate director for industrial relations and business development at the Engineering Research Center for Structured Organic Particulate Systems (C-SOPS), which is based at Rutgers, the State University of New Jersey. In most cases, the same equipment used in the development stage can be used in production, which eliminates the need for scale-up.

Although most solid-dosage processes today operate as a series of independent unit operations, pilot programs for continuous processing have made progress, and commercial implementation could occur within the coming year. The design of a continuous direct-compaction line built at C-SOPS, for example, was recently used to construct a commercial line at Janssen, which will be filed for FDA approval.

GEA Pharma System’s ConsiGma continuous manufacturing platform is an example of a commercially available continuous-manufacturing system. It can incorporate several different continuous technologies for the production of solid-dosage forms, such as wet granulation, dry granulation, and direct compression. The ConsiGma wet-granulation line consists of a blender, twin-screw granulator, fluid-bed dryer, granule conditioning unit, rotary tablet press, and continuous coater. This new generation of continuous manufacturing technology minimizes start-up and shut-down material losses because steady state can be reached quickly, notes Kris Schoeters, product manager for continuous processing at GEA Pharma Systems. PAT plays a crucial role in the GEA system. In the granulator, online optical systems are used to measure CQAs. Moisture content and blend uniformity are measured using NIR. Particle size is measured using an online laser-diffraction system, and tablet-content uniformity is measured using Fourier Transform (FT)-NIR transmission spectroscopy. Measurement data feeds into a process-control system to reach the goal of closed-loop control.

Sampling challenges

Incorporating PAT into a continuous process for solid-dosage drug production has not been a simple task, however. One challenge has been retrofitting the equipment to enable collection of the correct data from PAT devices. Some measurements (e.g., flow, pressure, and temperature) are readily available from inline sensors. Other measurements, such as online NIR spectrometry, are more complex and have required creativity in the physical interface with processing equipment. Enabling the sensor to collect good data, for example, has often required that probes and windows be retrospectively engineered into the processing equipment.

“NIR is a reflectance measurement that measures whatever is sampled by the probe. If a sample is stuck to the probe lens, it will be measured repeatedly,” notes Hausner. The C-SOPS line incorporates a window for the NIR measurement in the transfer pipe directly above the tablet press to measure blend content as close as possible to the tablet press. C-SOPS researchers investigated several different designs of modifying the pipe leading into the tablet press. The researchers concluded that plug-flow without turbulence was crucial to minimizing noise and allowing the analysis to run quickly.

Figure 1: An in-process optical probe enables process analytical technology (Lighthouse Probe, GEA Pharma Systems).GEA Pharma’s self-cleaning Lighthouse Probe, developed with J&M Analytik, was designed as a solution to the problem of sample adhering to the lens (see Figure 1). The viewing windows can be cleaned during the process, and a self-calibration feature indicates if a window is contaminated.

Work at Pfizer included developing solutions for sampling, such as screw transfer devices that enable sampling points to be inserted in flowing powders and developing heated probes to avoid material sticking, notes Steve Hammond, senior director and team leader of Pfizer’s Process Analytical Sciences Group. Pfizer also conducted experiments to determine reflective properties of powders, depth of penetration, and return of radiation in loose and compressed powders. Other aspects of sampling, such as mass of material contributing to a measurement, integration times for scanning, and the effect of reference scanning had to be extensively studied and understood, adds Hammond.

Integrating PAT and process control

The next step after integrating PAT into the continuous process as a monitoring tool is to incorporate the data from PAT into process control. In a feed-forward/feed-backward or closed-loop control system, critical process parameters (CPPs) are dynamically adapted and fed to the controller to keep the process within specification. In today’s batch processes, unit operations are operated as “islands of automation,” but the goal of continuous processing is to control multiple, single units as one unit by using an overarching process-control system.

Closed-loop control has been used successfully for many years in other process industries. “The frightening part for the pharmaceutical industry is moving from manual control with people making decisions to advanced process control, in which process data and modeling software automatically control the process,” comments Jonathon Thompson, senior manager of Compliance Services Consulting at Invensys. “PAT can give you a lot of data, which you need to turn into information about the process and whether it is within the CQA parameters,” he explains. “Process-modeling software compares real-time data to an ideal or ‘golden’ batch profile, identifies what parameters need to be changed to meet the ideal, and feeds this back into the control system.”

Researchers have been addressing several issues while integrating process control. One issue is that although some process equipment (e.g., newer feeders) is typically already instrumented for control, other equipment may require retrofitting. The tubular blender used at C-SOPS, for example, had a simple motor with a tachometer to control the speed, and C-SOPS engineers added instrumentation to allow more sophisticated control of the blender speed.Integration of instrument software with plant equipment is a challenge. Some installations that require simple endpoint or on/off control could use simple, analog 4–20 mA connections, says Hammond, but the most valuable applications generally require more sophisticated control that involves developing either direct communication with the manufacturing equipment’s control systems or communication with plant supervisory control and data acquisition (SCADA) systems.

“Ten years ago these communication links were custom developed for each piece of equipment. In recent years the development of “open architecture” software has simplified this aspect of instrument integration,” explains Hammond. Open-architecture software (e.g., OPC) uses open standards that enable connectivity. This software meets the need for communication protocols to enable analytical instruments to communicate with control systems, says Hammond, who notes that, after working with instrument vendors and control-system companies over the past five years, most of Pfizer’s vendors’ instruments now communicate via OPC.

Another challenge has been ensuring that data from PAT flows into the process-control system quickly enough to enable meaningful control of process fluctuations to keep CQAs within specification. “If the measurement takes longer than the residence time of the material—for example, 30–45 seconds of residence time in the blender—then the measurement can not be used for process control,” explains Hausner. He says that available NIR instruments are adequate for some applications, but faster analysis may be needed for other applications, such as smaller doses or lower percentages of API, which would necessitate more scans to obtain a measurement. C-SOPS continues to investigate solutions for NIR measurement in its production-scale Continuous Pharmaceutical Advanced Manufacturing Laboratory (CpAML). Analysis costs are part of the equation, notes Hausner. For example, a current CpAML project is comparing the use of one, fast (i.e., expensive) spectrometer with an array of slower but more economical spectrometers. An alternative method is inferential sensing, in which offline laboratory data is used with known correlations to give the control system the data it needs, adds Thompson.

Tracking material flow through the system is a crucial aspect of process control. A SCADA system tracks the location of a “product plug” as it moves through the process and adds this context to the PAT data in the process-control modeling software, explains Ivo Backx, manager of business and project development for the pharmaceutical industry at Siemens Industry Automation Division. “In tablet production, for example, multiple variables control the CQAs and you need to know what these attributes are and the correlation between them at specific points in the process,” says Backx. “For example, you need to know that the material in the tablet press now had a certain content uniformity at the blender.” Material tracking through the system is linked to requirements for traceability, notes Backx.

Figure 2: A continuous, high-shear granulation and drying systemin operation at the GEA test center (ConsiGma, GEA Pharma Systems).Traceability is simple in a batch system because it is assumed that all the product from one batch is the same. “For a continuous operation, traceability becomes much more important because not all the product is submitted to the same process at the same time. Using a first-in/first-out (FIFO) principle is, therefore, very important,” says Schoeters, who notes that GEA has adapted the unit operations of mixing, granulation, drying, compression, and coating in such a way that the product is traceable throughout the production line and back-mixing is limited as much as possible. The ConsiGma system, such as the line shown in Figure 2, continuously monitors CPPs to keep them in control and maintain product quality. This includes measurements using PAT (e.g., particle size, moisture, uniformity), but primarily involves monitoring of and control-feedback loops on machine parameters. Torque of the granulator screws, for example, is continuously monitored, and a deviation from the set value triggers actions and alarms.

Other challenges

High equipment costs and restrictions on capital spending are currently barriers to implementing PAT and continuous processing technologies. In addition, revised European regulatory guidance requires refiling of NIR instruments after calibration updates (3). “This new guidance on NIR is very restrictive. It does not allow for changes in raw materials, instrument maintenance, and all the routine occurrences that require calibration maintenance,” notes Hammond.

Real-time release

Although real-time release (RTR) is a goal for industry and for regulators, only a few companies have achieved it as a commercial reality. In RTR, product quality assurance is based on online analysis, and the product is released as it is produced rather than a batch being held while waiting for quality-control testing. RTR could be implemented for batch processing, in that a batch could be released if there were no deviations throughout the batch. In continuous processing, product could be released continually given no deviations. Theoretically, online measurement would identify out-of-specification product and allow it to be segregated or even identify a change in CQAs before the product goes out of specification (4).

A new program, Accelerating Innovative Research (AIR), builds on the C-SOPS infrastructure at Rutgers and is focused on working with existing PAT as well as partnering with companies to move RTR testing technology forward. The program will involve working with large pharmaceutical companies to run specific formulations as case studies in an effort to build up a toolbox of knowledge on how spectroscopic data can be used for RTR testing.

Implementing closed-loop control is a step towards RTR. “Intelligent processes that are proactively controlled to ensure the expected outcome are inherently capable of supporting a RTR strategy. Regulators have always stated that tight control of the unit operations leading up to final product is the best way to ensure quality of the product and enable a RTR filing,” says Hammond, who notes that Pfizer’s Chantix RTR application is now filed in all major markets and most of the rest of world. “The value of RTR has been reduction in laboratory testing. The focus in the future will be on enabling a modern supply chain, with flexible response to a pull from the market, and maintaining lower inventory.”

Many in industry and academia say that continuous manufacturing using online PAT with closed-loop process control and real-time release represent the future of solid-dosage manufacturing. These concepts are part of a “seismic shift in culture change within the pharmaceutical industry, which continues to put the spotlight on manufacturing in a way that has been absent in the past,” concludes Freeman.

References>

1. FDA, Pharmaceutical cGMPs for the 21st Century—Risk-Based Approach: Final Report (Rockville, MD, 2004).

2. FDA, Guidance for Industry: PAT—A Framework for Innovative Pharmaceutical Development, Manufacturing and Quality Assurance (Rockville, MD, 2004).

3. EMA, EMEA/CHMP/CVMP/QWP/17760/2009 Rev2, “Guideline on the use of Near Infrared Spectroscopy (NIRS) by the pharmaceutical industry and the data requirements for new submissions and variations, draft” (London, 2012), www.ema.europa.eu/docs/en_GB/document_library/Scientific_guideline/2012/02/WC500122769.pdf, accessed March 4, 2013.

4. K. Schoeters, Pharm.Tech. Eur. 23 (2) 20-21 (2011).

FIGURES ARE COURTESY OF GEA PHARMA SYSTEMS