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Demonstrate the use of a knowledge management and data curation (KProMS) system to support a collaborative research project involving the generation of extensive critical product quality data and the investigation of alternative statistical sampling/analysis strategies for product release. A suite of workflows was developed for the analytical testing and calibration activities associated with the required USP dissolution, HPLC, weight, hardness, and physical dimension measurements. The workflow library also includes the computational steps in the relevant Bayesian and frequentist statistical analyses. The necessary interfaces enabling the transfer of raw data from the instrument output files into KProMS were also implemented. By virtue of a HUB-based implementation of KProMS, all of the details of both laboratory and statistical procedures as well as the resulting data and analysis are web-accessible to all authorized participants. The system enabled data generation, sharing and harvesting over the web, and seamless integration of activities between groups located in three different locations. KProMS can be effectively used in routine management of the dosage form quality data in pharmaceutical operations. This would allow industrial laboratories to seamlessly generate data and populate the knowledgebase to track the analysis for product release and for correlation to process control charting.

This work is an extension of the earlier work from this laboratory aimed at identifying raw material properties critical to the modeling of granule and ribbon properties as part of the optimization of roller (RC) compaction processes. The utility of roll gap (RG) and near-infrared (NIR) signal, specifically, the spectral slope, as process critical control parameters (PCCPs) was also evaluated. Raw material tabletability, particle size, size distribution span, and tapped density were found to be most important factors for building robust predictive models. RG and NIR spectral slope in combination with RC operating parameters yielded models with good predictability for RC responses. Our results support the suitability of RG and NIR spectral slope as PCCPs in roller compaction, specifically, through ribbon density monitoring.

Developing pharmaceutical product formulation in a timely manner and ensuring quality is a complex process that requires a systematic, science-based approach. Information from various categories, including properties of the drug substance and excipients, interactions between materials, unit operations, and equipment is gathered. Knowledge in different forms, including heuristics, decision trees, correlations, and first-principle models is applied. Decisions regarding processing routes, choice of excipients, and equipment sizing are made based on this information and knowledge. In this work, we report on the development of a software infrastructure to assist formulation scientists in managing the information, capturing the knowledge, and providing intelligent decision support for pharmaceutical product formulation.

What is the role of standardized methods for determining the impact of material properties in pharmaceutical formulation and process development? In this Perspective article, we identify material properties that are potentially important in solid dosage form design, and we review approaches linking these properties to product specifications in dry granulation process development. We also assess the potential benefits that could be obtained by standardizing the methods for determining the impact of material properties of commonly used excipients and propose a program of research to achieve the desired goal of an efficient, science-based approach for incorporating material properties in solid dosage form design.