New FDA Initiative Invites Advanced Controls
Officials from the U.S. FDA publicly asked technology experts in other industries to find performance-enhancing technologies that could help pharmaceutical manufacturers cut costs, improve product quality or speed to market, during the November 2004 annual meeting of the International Society of Pharmaceutical Engineers.
Officials from the U.S. FDA publicly asked technology experts in other industries to find performance-enhancing technologies that could help pharmaceutical manufacturers cut costs, improve product quality or speed to market, during the November 2004 annual meeting of the International Society of Pharmaceutical Engineers. This announcement was made as part of the FDA's recent Process Analytical Technologies (PAT) initiative, which encourages manufacturers to adapt advanced process improvement technologies.
The FDA issued its PAT guidelines in a document entitled, "Guidance for Industry PAT—A Framework for Innovative Pharmaceutical, Development, Manufacturing and Quality Assurance." The basic premise of the framework is to encourage innovation and the use of new technologies in the industry. PAT is defined by the FDA as "a system for designing, analyzing, and controlling manufacturing through timely measurements of critical quality and performance attributes of raw and in-process materials and processes with the goal of ensuring final product quality."
To provide these measures, the FDA has increased emphasis on advanced control, on-line analysis and sensing, and other advanced simulation and analysis software. These technologies will provide a basis for identifying and understanding relationships and interactions with process variables and for developing effective risk mitigation strategies.
Prior to PAT, manufacturers were hesitant to utilize newer technologies or utilize unproven industry technologies because of the regulatory uncertainty involved with changing their processes. Now, however, the FDA is encouraging use of new technologies for improving efficiencies in the manufacturing process, pledging that regulators will "rise to the challenge of utilizing new cutting edge technologies and scientific data."
In keeping with FDA philosophy that PAT is not a single sensor or analytical technology but a complete regulated solution, a comprehensive methodology should be applied to any new technologies considered for use, beginning with an audit and ROI analysis and extending through implementation and monitoring.
One example of an advanced analytical technology that is migrating from other industrial applications to pharmaceuticals is nuclear magnetic resonance (NMR). Most notable in medical diagnostics in the form of MRI scanning, NMR has been used to analyze chemical substances in petroleum refining, and is now being considered for a variety of pharmaceutical applications, including clean in place, check weighing, and other applications.
The more precisely a manufacturer can characterize and control the production process at various stages of production, the greater its ability to use advanced technology to optimize that production. NMR technology reads magnetic properties of atomic nuclei. When the nuclei are placed in a strong magnetic field, the nuclei change orientation in measurable ways, and in doing so reveal a wealth of information about composition and chemical structure of the sampled compound.
Additional mathematical and statistical analysis of the samples can create a highly accurate model of the compound's composition. Because it is based on statistical inference rather than direct observation, this measurement would have been difficult, if not impossible, to validate previously. The new PAT initiative enables integration of technologies that use on-line scientific data to better analyze and provide automatic feedback to the process.
Thermal effusivity sensing is another example of an advanced analytical technique now being considered for pharmaceutical applications. A new sensor from Mathis Instruments, for example, precisely measures the moisture endpoint in a fluidized bed dryer while minimizing the characterization time, compared to competing methods. Statistical process models reduce product characterization times from weeks to hours, especially valuable for production applications involving frequent product switchover or multiple products.
NMR and thermal effusivity sensing are but two examples of technologies that should flourish under the FDA's new guideline. The door is now open for model-based predictive control, simulation, and numerous other technologies that have been linked to tremendous productivity gains in other industries, but not yet applied in the pharmaceutical industry. Determining the right PAT device or technology for each company requires a comprehensive audit of current procedures and ROI analysis that extends through implementation and monitoring (see "PAT methodology" graphic).
Different on-line analytical technologies must be considered on an individual application basis and deployed considering process and control experiences, analysis of expected performance improvements, ROI, and a carefully designed risk assessment. As FDA officials point out: PAT should not be construed as a single type of analytical technology or a sensor, but as a complete regulated solution. Above all, the most important goal of PAT should be to design and develop the best application available using the best technology for delivering the highest quality products.
Janice T. Abel is director of pharmaceutical industry marketing for Invensys Process Systems; Victor Lough is the program manager for Invensys Applied Services, Europe, Middle East and Africa.
PAT guideline benefits
Following are examples of efficiency gains the U.S. FDA hopes to help companies achieve via the Process Analytical Technologies initiative:
Reduce production cycle times;
Prevent rejects, scrap, and re-work;
Increase automation to improve operator safety and reduce human errors;
Improve energy, material, and equipment use;
Improve process analysis and controls;
Enable real-time release;
Improve process time delays caused by quality control delays or laboratory analysis;
Improve product quality and consistency; and
Facilitate processing to improve efficiency and manage variability.
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