LAPSE:2018.0343
Published Article
LAPSE:2018.0343
A Systematic Framework for Data Management and Integration in a Continuous Pharmaceutical Manufacturing Processing Line
Huiyi Cao, Srinivas Mushnoori, Barry Higgins, Chandrasekhar Kollipara, Adam Fermier, Douglas Hausner, Shantenu Jha, Ravendra Singh, Marianthi Ierapetritou, Rohit Ramachandran
July 31, 2018
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, and reliable manner is a big challenge for the pharmaceutical industry. In this work, an ontological information infrastructure is developed to integrate data within manufacturing plants and analytical laboratories. The ANSI/ISA-88.01 batch control standard 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. All the detailed information of the lab-based experiment and process manufacturing, including equipment, samples and parameters, are documented in the recipe. This recipe model is implemented into a process control system (PCS), data historian, as well as Electronic Laboratory Notebook (ELN) system. Data existing in the recipe can be eventually exported from this system to cloud storage, which could provide a reliable and consistent data source for data visualization, data analysis, or process modeling.
Keywords
continuous pharmaceutical manufacturing, data management, ISA-88, OSI Process Information (PI), recipe
Suggested Citation
Cao H, Mushnoori S, Higgins B, Kollipara C, Fermier A, Hausner D, Jha S, Singh R, Ierapetritou M, Ramachandran R. A Systematic Framework for Data Management and Integration in a Continuous Pharmaceutical Manufacturing Processing Line. (2018). LAPSE:2018.0343
Author Affiliations
Cao H: Department of Chemical and Biochemical Engineering, Engineering Research Center for Structured Organic Particulate Systems (C-SOPS), Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
Mushnoori S: Department of Electrical & Computer Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
Higgins B: Johnson & Johnson, Co., Cork, Ireland
Kollipara C: Janssen Research & Development, Spring House, PA 19002, USA
Fermier A: Janssen Research & Development, Spring House, PA 19002, USA
Hausner D: Department of Chemical and Biochemical Engineering, Engineering Research Center for Structured Organic Particulate Systems (C-SOPS), Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
Jha S: Department of Electrical & Computer Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
Singh R: Department of Chemical and Biochemical Engineering, Engineering Research Center for Structured Organic Particulate Systems (C-SOPS), Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
Ierapetritou M: Department of Chemical and Biochemical Engineering, Engineering Research Center for Structured Organic Particulate Systems (C-SOPS), Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
Ramachandran R: Department of Chemical and Biochemical Engineering, Engineering Research Center for Structured Organic Particulate Systems (C-SOPS), Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
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Journal Name
Processes
Volume
6
Issue
5
Article Number
E53
Year
2018
Publication Date
2018-05-10
Published Version
ISSN
2227-9717
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PII: pr6050053, Publication Type: Journal Article
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LAPSE:2018.0343
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doi:10.3390/pr6050053
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Jul 31, 2018
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