Difference between revisions of "Journal:A systematic framework for data management and integration in a continuous pharmaceutical manufacturing processing line"
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|title_full = A systematic framework for data management and integration in a continuous pharmaceutical manufacturing processing line | |title_full = A systematic framework for data management and integration in a continuous pharmaceutical manufacturing processing line | ||
|journal = ''Process'' | |journal = ''Process'' | ||
|authors = Cao, Huiyi; Mushnoori, Srinivas; Higgins, Barry; Kollipara, Chandrasekhar; Fernier, Adam; Hausner, Douglas; Jha, Shantenu; Singh, Ravendra; Ierapetritou, Marianthi; Ramachandran, Rohit | |authors = Cao, Huiyi; Mushnoori, Srinivas; Higgins, Barry; Kollipara, Chandrasekhar; Fernier, Adam;<br />Hausner, Douglas; Jha, Shantenu; Singh, Ravendra; Ierapetritou, Marianthi; Ramachandran, Rohit | ||
|affiliations = Rutgers University, Johnson & Johnson, Janssen Research & Development | |affiliations = Rutgers University, Johnson & Johnson, Janssen Research & Development | ||
|contact = Email: rohit dot r at rutgers dot edu; Tel.: +1-848-445-6278 | |contact = Email: rohit dot r at rutgers dot edu; Tel.: +1-848-445-6278 | ||
| Line 24: | Line 24: | ||
| text = This article should not be considered complete until this message box has been removed. This is a work in progress. | | text = This article should not be considered complete until this message box has been removed. This is a work in progress. | ||
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==Abstract== | |||
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 [[Laboratory|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, and [[electronic laboratory notebook]] (ELN). 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''': data management, continuous pharmaceutical manufacturing, ISA-88, recipe, OSI Process Information (PI) | |||
==Introduction== | |||
For decades, the pharmaceutical industry has been dominated by a batch-based manufacturing process. This traditional method can lead to increased inefficiency and delay in time-to-market of product, as well as the possibility of errors and defects. Continuous manufacturing in contrast, is a newer technology in pharmaceutical manufacturing that can enable faster, cleaner, and more economical production. The U.S. [[Food and Drug Administration]] (FDA) has recognized the advancement of this manufacturing mode and has been encouraging its development as part of the FDA's "quality by design" (QbD) paradigm.<ref name="LeeModern15">{{cite journal |title=Modernizing Pharmaceutical Manufacturing: from Batch to Continuous Production |journal=Journal of Pharmaceutical Innovation |author=Lee, S.L.; O'Connor, T.F.; Yang, X. et al. |volume=10 |issue=3 |pages=191–99 |year=2015 |doi=10.1007/s12247-015-9215-8}}</ref> The application of process analytical technology (PAT) and control systems is a very useful effort to gain improved science-based process understanding.<ref name="FDAGuidance04">{{cite web |url=https://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/ucm070305.pdf |format=PDF |title=Guidance for Industry PAT—A Framework for Innovative Pharmaceutical Development, Manufacturing, and Quality Assurance |publisher=U.S. Food and Drug Administration |date=September 2004 |accessdate=15 May 2018}}</ref> One of the advantages of the continuous pharmaceutical manufacturing process is that it provides the ability to monitor and rectify data/product in real time. Therefore, it has been considered a data rich manufacturing process. However, in the face of the enormous amount of data generated from a continuous process, a sophisticated data management system is required for the integration of analytical tools to the control systems, as well as the off-line measurement systems. | |||
==References== | ==References== | ||
Revision as of 17:42, 15 May 2018
| Full article title | A systematic framework for data management and integration in a continuous pharmaceutical manufacturing processing line |
|---|---|
| Journal | Process |
| Author(s) |
Cao, Huiyi; Mushnoori, Srinivas; Higgins, Barry; Kollipara, Chandrasekhar; Fernier, Adam; Hausner, Douglas; Jha, Shantenu; Singh, Ravendra; Ierapetritou, Marianthi; Ramachandran, Rohit |
| Author affiliation(s) | Rutgers University, Johnson & Johnson, Janssen Research & Development |
| Primary contact | Email: rohit dot r at rutgers dot edu; Tel.: +1-848-445-6278 |
| Year published | 2018 |
| Volume and issue | 6(5) |
| Page(s) | 53 |
| DOI | 10.3390/pr6050053 |
| ISSN | 2227-9717 |
| Distribution license | Creative Commons Attribution 4.0 International |
| Website | http://www.mdpi.com/2227-9717/6/5/53/htm |
| Download | http://www.mdpi.com/2227-9717/6/5/53/pdf (PDF) |
 |
This article should not be considered complete until this message box has been removed. This is a work in progress. |
Abstract
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, and electronic laboratory notebook (ELN). 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: data management, continuous pharmaceutical manufacturing, ISA-88, recipe, OSI Process Information (PI)
Introduction
For decades, the pharmaceutical industry has been dominated by a batch-based manufacturing process. This traditional method can lead to increased inefficiency and delay in time-to-market of product, as well as the possibility of errors and defects. Continuous manufacturing in contrast, is a newer technology in pharmaceutical manufacturing that can enable faster, cleaner, and more economical production. The U.S. Food and Drug Administration (FDA) has recognized the advancement of this manufacturing mode and has been encouraging its development as part of the FDA's "quality by design" (QbD) paradigm.[1] The application of process analytical technology (PAT) and control systems is a very useful effort to gain improved science-based process understanding.[2] One of the advantages of the continuous pharmaceutical manufacturing process is that it provides the ability to monitor and rectify data/product in real time. Therefore, it has been considered a data rich manufacturing process. However, in the face of the enormous amount of data generated from a continuous process, a sophisticated data management system is required for the integration of analytical tools to the control systems, as well as the off-line measurement systems.
References
- ↑ Lee, S.L.; O'Connor, T.F.; Yang, X. et al. (2015). "Modernizing Pharmaceutical Manufacturing: from Batch to Continuous Production". Journal of Pharmaceutical Innovation 10 (3): 191–99. doi:10.1007/s12247-015-9215-8.
- ↑ "Guidance for Industry PAT—A Framework for Innovative Pharmaceutical Development, Manufacturing, and Quality Assurance" (PDF). U.S. Food and Drug Administration. September 2004. https://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/ucm070305.pdf. Retrieved 15 May 2018.
Notes
This presentation is faithful to the original, with only a few minor changes to presentation, including with grammar and punctuation. In some cases important information was missing from the references, and that information was added.
