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theses

As the pharmaceutical industry seeks more efficient methods for the production of higher value therapeutics, the associated data analysis, data visualization, and predictive modeling require dependable data origination, management, transfer, and integration. As a result, the management and integration of data in a consistent, organized, reliable manner is a big challenge for the pharmaceutical industry. The S88 recipe model, an international standard for describing standard batch processes, has been adapted in this study to deliver a well-defined data structure that will improve the data communication inside the system architecture for continuous processing. This work has been divided into two parts due to differing requirements between laboratory-based analytical measurements and the pilot-plant continuous pharmaceutical process. In the laboratory platform, recipes have been developed for a sub-set of material property tests that for instance, could be performed on the analytical instrument (e.g. FT4 for flow). Drupal, an open source content management system, is implemented on an Amazon web service for data transfer between the analytical devices eventually a data management platform. A recipe module for Drupal is developed for recipe management, in which users could create, import, and modify recipes. Scientists can access recipes through Drupal’s web page interface and perform experiments following standard recipe steps. Research data can be recorded by manual input or automatically parsing data files on the backend of the server. This system works like a recipe based electronic laboratory notebook. In the continuous manufacturing pilot plant, process data is generated by unit operation equipment and integrated process analytical technology (PAT) instruments 1. A process control system (e.g. DeltaV (Emerson)) collects the data from equipment and a PAT data management tool (e.g. synTQ (Optimal Industrial Automation)). The PAT data management collects data from an inline/online measurement system 2. The recipe for the whole continuous process is implemented in DeltaV. Data in DeltaV is collected according to the recipe and is transferred to a data storage hub (PI system (OSI Soft)) in the same structure. The Event Frame feature from PI system allows the possibility to create an individual recipe based on continuous data feeding. From PI system, the data is sent to online data storage box and cloud system. From the box/cloud, the data can be access at different physical company sites, can be analyzed and applied for various applications. This study is the first attempt to apply ISA-88, a batch control standard, to continuous pharmaceutical manufacturing. All the detailed information of the lab-based experiment and process manufacturing, including equipment, samples and parameters are documented in the recipe. Recipes containing data can be exported from this system to be shared and transferred. After detaching the data from recipes, a reliable and consistent data source is provided for data visualization and process modeling. Another feature is the two-dimensional barcode labels that are used in this strategy. Every ingredient and equipment of the analytical experiment or manufacturing process will have a unique barcode, which can be used to identify the item and trace all the information related. This enforces material traceability, which is an essential requirement in the overall Quality by Design (QbD) initiative.

ETD_7702

M.S.

Includes bibliographical references

by Huiyi Cao

doi:10.7282/T3RF5X9H

ETD graduate

The author owns the copyright to this work.