(665e) A Workflow-Based Framework for Managing Product Analytical Data and Statistical Results for Lot Release

Authors: 
Joglekar, G., Purdue University
DeLaurentis, P., Purdue University
Mockus, L., Purdue University
Reklaitis, G. V., Purdue University
The workflow based framework for knowledge management (KProMS) was used to support an FDA collaborative research project involving the generation of extensive critical product quality data and investigation of alternative statistical sampling/analysis strategies for lot release. The suite of comprehensive workflows include 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. Both categories of workflows were developed in consultation with subject matter experts. The experimental workflows provided the framework for systematic recording of all experimental data, including calibration runs, replicates, and so forth, while the computational workflows document the statistical procedures, the results of statistical analysis, the decision criteria as well as the decision outcomes. The necessary interfaces enabling the transfer of raw data from the instrument output files directly into the KProMS system 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 in the study, with varying levels of read-write privileges. Although the workflows were implemented to meet the needs of the specific collaborative research project, suitable modifications of the workflows and the KProMS system 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.

Related references

Icten, E, G. Joglekar, C. Wallace, K. Loehr, J. Sacksteder, A. Girdhar, Z.K. Nagy, and G.V. Reklaitis, “A Knowledge Provenance Management System for a Dropwise Additive Manufacturing System for Pharmaceutical Products”, I&EC Research 55 (36), 9676–9686, (2016)

Joglekar, G., A. Giridhar and G.V. Reklaitis, “A workflow modeling system for capturing data provenance”, Comput. & Chem Engr, 67, 148-158 (2014)

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