Using data science to find predictors of adverse regulatory inspections : enhancing quality risk management in the pharmaceutical industry
submitted by Steffen Eich (from Germany)
| Alternative title: | Using data science to enhance quality risk management in the pharmaceutical industry |
|---|---|
| Year of publication: |
2021
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| Authors: | Eich, Steffen |
| Publisher: |
St. Gallen |
| Subject: | Pharmazeutische Industrie | Data Science | Qualitätsmanagement | Pharmaceutical Industry | Regulatorische Inspektionsergebnisse | regulatory inspection outcomes | total quality management | operational excellence | Operative Exzellenz | machine learning | Maschinelles Lernen | FDA Food and Drug Administration | data analytics | Datenanalyse | Pharmaindustrie | Pharmaceutical industry | Quality management | Künstliche Intelligenz | Artificial intelligence | Arzneimittel | Pharmaceuticals | Regulierung | Regulation | Arzneimittelrecht | Pharmaceutical law | Risikomanagement | Risk management | Arzneimittelmarkt | Pharmaceutical market | Qualitätssicherung | Datenverarbeitung |
| Extent: | 1 Online-Ressource (circa 234 Seiten) Illustrationen |
|---|---|
| Type of publication: | Book / Working Paper |
| Type of publication (narrower categories): | Hochschulschrift ; Graue Literatur ; Non-commercial literature |
| Language: | English |
| Thesis: | Dissertation, University of St.Gallen, 2021 |
| Notes: | Im Buchhandel erschienen unter dem Titel Using data science to enhance quality risk management in the pharmaceutical industry Zusammenfassung in deutscher und englischer Sprache |
| Classification: | Pharmazeutische Technologie |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10013348655