LAUSR

It has been 15 years since the FDA issued its pharmaceutical CGMPs for the 21st-century report laying out its quality by design (QbD) and process analytical technologies (PAT) initiative (1). QbD tenets emphasize the need to understand, predict, monitor, and control the interplay of critical material attributes (CMA) and critical process parameters (CPP) on critical quality product attributes (CQPA) (2,3). Over the last 15 years, significant progress has been made in developing PAT and subsequent analysis of data generated from these techniques. The United States Pharmacopeia has recently issued a Chemometrics chapter that discusses the application of qualitative and quantitative techniques and the interpretation of multivariate data (4). PAT is an important QbD tool. Raman spectroscopy has emerged as a fast, effective, and versatile PAT real-time analyzer. A review of Raman spectroscopy as a PAT tool for real-time monitoring of pharmaceutical secondary manufacturing processes is provided (5). While the emphasis of the review presents applications of Raman spectroscopy for monitoring secondary manufacturing of solids, the article also provides examples of analytical process control of upstream active pharmaceutical ingredient (API) synthesis and crystallization and biotechnology applications such as enzymatic hydrolysis and protein production. Over the last decade or so, numerous analytical technologies have been used to assess blend uniformity and mixing dynamics. Spectroscopic, velocimetric, tomographic, and acoustic emission mixing assessment techniques are reviewed (6). Use of imaging techniques as PAT tools has been steadily increasing as the accuracy, precision, speed, and robustness of these analyzers has improved, and they have become commercially available. An in-line vision imaging system is described that provides real-time mini-tab film-coat thickness estimates during fluid-bed coating (7). Pharmaceutical applications of hot melt extrusion (HME) have been reported since the 1970s. HME has found particular promise as a scalable continuous manufacturing process to improve the solubility and bioavailability of many recent breakthrough APIs. A technical note demonstrating the application of FT-NIR analysis to provide real-time monitoring of a HME product exemplifies the utility of PAT in continuous processing (8). Data analysis methodologies are another important QbD tool. The increased array of real-time process analyzers used to monitor any given process or material generates very large and complex data sets. Thus, the intricacies of such complex data treatment requires sophisticated data management strategies. A timely review demonstrates the challenges presented by the current state of pharmaceutical material characterization methods and the incorporation of multivariate analysis to enhance the understanding of pharmaceutical materials (9). Data fusion is a relatively new and powerful data analysis technique. Some of the first pharmaceutical applications were reported in early 2000. Data fusion is a methodology that combines multiple data sources to obtain a more informed, accurate, consistent, robust, and sophisticated understanding. For the first time, critical process parameters and near-infrared (NIR) spectroscopy data are employed to predict final product dissolution that could be used for realtime release testing (10). Data fusion of 5 critical process parameters and 4 principal component analysis NIR scores were used to develop a predictive partial least squares regression model. The data fusion method incorporates the NIR chemical (coating concentration; water concentration) and physical (coat thickness) properties with the processing Guest Editors: William C. Stagner and Rahul V. Haware