An Evaluation of Wet Granulation Process Selection for API Prone to Polymorphic Form Conversion in the Presence of Moisture and Heat.

PURPOSE: Wet granulation (WG) is one of the most versatile processes to improve blend properties for processing. However, due to its need for moisture and heat, it is often considered not amenable to active pharmaceutical ingredients (APIs) prone to forming hydrates. Despite this claim, little literature exists evaluating the extent to which polymorphic form conversions occur for such API when processed with WG. This work sets out to explore two common WG methods, high-shear (HSG) and fluid-bed (FBG), and two drying processes, tray-drying (TD) and fluid-bed drying (FBD), and evaluate the risk they pose to hydrate form conversion. METHODS: The progression of anhydrous to hydrate form conversion of two model compounds with vastly different solubilities, fexofenadine hydrochloride and carbamazepine, was monitored throughout the various processes using powder X-ray diffraction. The resultant granules were characterized using thermogravimetric analysis, differential scanning calorimetry, BET adsorption, and sieve analysis. RESULTS: FBG and FBD processing resulted in the preservation of the original form of both APIs, while HSG+TD resulted in the complete conversion of the API. The FBD of fexofenadine and carbamazepine granules prepared with HSG resulted in partial and complete re-conversion back to the original anhydrous forms, respectively. CONCLUSION: The drying process is a critical factor in anhydrous form conservation. FBG and FBD yielded better preservation of the initial anhydrous forms. HSG could be an acceptable granulation method for API susceptible to hydrate formation if the API solubility is low. Selecting an FBG+FBD process minimizes API hydrate formation and preserves the original anhydrous form.

Particle Property Characterization and Data Curation for Effective Powder Property Modeling in the Pharmaceutical Industry.

Computational modeling, machine learning, and statistical data analysis are increasingly utilized to mitigate chemistry, manufacturing, and control failures related to particle properties in solid dosage form manufacture. Advances in particle characterization techniques and computational approaches provide unprecedented opportunities to explore relationships between particle morphology and drug product manufacturability. Achieving this, however, has numerous challenges such as producing and appropriately curating robust particle size and shape data. Addressing these challenges requires a harmonized strategy from material sampling practices, characterization technique selection, and data curation to provide data sets which are informative on material properties. Herein, common sources of error in particle characterization and data compression are reviewed, and a proposal for providing robust particle morphology (size and shape) data to support modeling efforts, approaches for data curation, and the outlook for modeling particle properties are discussed.