

Oct 02, 2009
Volume 33, Issue 10

In August 2002, the US Food and Drug Administration issued a pronouncement on pharmaceutical manufacturing called Pharmaceutical CGMPs for the 21st Century: A Risk-Based Approach (1). The initiative encouraged the pharmaceutical industry to adopt concepts related to modern quality techniques and state-of-the art processing and paved the way for new thinking about pharmaceutical manufacturing. Current good manufacturing practice (CGMP) guidelines from the late 1980s focused on stasis of conditions based on documented evidence from a small number of validated batches, followed by rigid adherence to standard operating procedures developed for these batches. The modern guidelines are much more dynamic, focusing on a deep understanding of scientific and mechanistic principles associated with the process in order to yield instantaneous and continuous control that can effect change in real time. This represents a paradigm shift from laboratory-centric assurances of quality to one driven by engineering principles.

Two concepts related to risk-based manufacturing are quality by design (QbD) and process analytical technology (PAT). QbD is the more far-reaching term because it involves aspects from development through manufacturing. PAT focuses on manufacturing and relates the mechanistic and scientific interactions inherent to formulation and processing. A necessary connection point for deep process knowledge is the analytical means to establish relationships among the factors of interest. Primary laboratory methods of analysis need well-qualified individuals and substantial time. However, innovations to spectral processing through chemometric models make techniques such as near- infrared (NIR) spectroscopy particularly useful as an alternative. Spectroscopic methods glean information about the interactions between electromagnetic radiation and matter. NIR spectroscopy is grouped within vibrational spectroscopy because it is used for detecting vibrational modes that are associated with functional groups in chemical compounds. Once this technique has been calibrated versus a primary method, the resulting procedure is fast, nondestructive, requires no sample preparation, and is conducive to study in real time. An additional benefit is that the analysis can be automated within standard operating procedures. This makes spectral acquisition and processing covert to the user and merely requires the user to initiate the process with a GO button and await results.

The case for continuous processing in modern pharmaceutical manufacturing

Continuous operations are amenable to process development and real-time adjustment brought about by PAT and lead to continuous improvement. The large established base of batch unit operations associated with solid oral dosage processing may also be studied to elucidate deeper understanding. However, there is a major difference in potential outcomes between batch and continuous processes. Once the batch operation is closed and processing begins, one's ability to correct a quality problem for local (within a mixer or blender for example) or global (to a process before or after the mixer) issues is limited. One may assess content uniformity of the batch in real time, but if uniformity is suspect, the entire batch is at risk. For example, a lubricating step for a direct compression formulation in a bin blender can be studied and modeled to establish appropriate rotation speeds and mixing times to achieve uniformity and minimize particle degradation. However, moving the batch to the tablet press may lead to segregation, which disrupts tablet content uniformity and risks introducing inconsistencies in compression and ejection forces. A batch containing 1000 kg or more of drug product may be at risk. By contrast, a low-throughput continuous-mixing process feeding a subsequent process (continuous rates from 5 kg/h to 100 kg/r or more are feasible) may be monitored constantly at several points. If physical characteristics are trending poorly at the tablet press, adjustments, within the established design space of a well-characterized process, may be made in real time. For example, the rotational speed of the mixer may be increased or decreased to alter the lubricant coating functionality and the at-risk portion of the product run is eliminated or at worse, minimized to the hold-up volume of the mixer.

Continuous processing is characterized by vibrancy, and one can use both feed forward and feed back information that allows interaction among several processes in a global manner. Stryczek et al. (2) provide insight on how the global control potential in continuous operation may be used to influence disparate points in the manufacturing scheme. The study was a retrospective collection of aggregate data related to a solid oral dosage manufacturing process and implicated raw material characteristics, external ambient conditions, and granulating process conditions as influences on dissolution rates. Controlling the granulation process and the other unit operations associated with the process would be a monumental task at the step-by-step batch level involving several manufacturing days with potentially different ambient conditions. Controlling a low-throughput continuous process in a one-day process scheme is much more reasonable because one only needs to consider a single day of ambient conditions.

Continuous processing is adaptable and fits well into the life-cycle approach seen in the 2008 FDA draft guidance on process validation (3). The approach emphasizes the interaction among design, qualification, and verification with the need for continual improvement throughout the product life cycle. The result is a desired state that relies on intimate understanding of critical parameters related to process, product, and quality. Allied with this concept is the potential breadth and depth of the operating space. It is beneficial for a sponsor to include the widest possible range of defined attributes in their application to FDA. Judicious experimental design, factorial sequences, and rapid nondestructive analysis, by NIR spectroscopy for example, make it quite feasible to study many raw material sources as well as wide operating space for equipment variables such as impeller speed, vessel rotation rate, chopper speed, spray rates, and drying temperatures.

Continuous processing is well-suited to process automation schemes. The International Society of Automation (ISA), through their S95 Standards, characterizes levels for integrating control systems with business enterprise systems (4). This is reconstituted in the PAT framework as four increasingly interconnected layers of control and process understanding. At Layer 1, there is some communication of univariate and multivariate process information. Layer 3 is much more elegant and links several analytical devices under common software platforms that are commercially available from several vendors. This seamless interchange can be used to control several aspects within a continuous process. The highest layer encompasses logistics and planning that is well suited to a continuous process where raw-material identification at the receiving area may be matched to final content uniformity assessment, which then triggers automatic reordering of materials when the uniformity is confirmed.