Automated Data Review in Secondary Pharmaceutical Manufacturing by Pattern Recognition Techniques
| Autor: | Simeone Zomer, Chrismono Himawan, Natascia Meneghetti, Pierantonio Facco, Fabrizio Bezzo, Massimiliano Barolo |
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| Rok vydání: | 2016 |
| Předmět: |
Engineering
business.industry Process analytical technology Pattern recognition 02 engineering and technology 021001 nanoscience & nanotechnology 030226 pharmacology & pharmacy QbD process analytical technology Quality by Design Automated data pharmaceutical manufacturing Chemical Engineering (all) 03 medical and health sciences 0302 clinical medicine Computer-integrated manufacturing Pattern recognition (psychology) Pharmaceutical manufacturing Manufacturing operations Artificial intelligence 0210 nano-technology business Pharmaceutical industry |
| DOI: | 10.1016/b978-0-444-63428-3.50138-7 |
| Popis: | A methodology is proposed to support the periodic review of manufacturing data in the pharmaceutical industry. Pattern recognition techniques are employed to isolate and analyze operation-relevant data segments to the purpose of automatically extracting the information embedded in large databases of secondary manufacturing systems. The results achieved by testing the proposed methodology on two six-month datasets of a commercial-scale drying unit demonstrate the potential of this approach, which can be easily extended to other manufacturing operations. |
| Databáze: | OpenAIRE |
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