Smart Pharmaceutical Manufacturing: Ensuring End-to-End Traceability and Data Integrity in Medicine Production

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Details zur Publikation

Autorenliste: Leal F, Chis AE, Caton S, González–Vélez H, García–Gómez JM
Jahr der Veröffentlichung: 2021
Zeitschrift: Big Data Research (2214-5796)
Bandnummer: 24
Erste Seite: 1
Letzte Seite: 12
Seitenumfang: 12
ISSN: 2214-5796
Sprachen: Englisch-Vereinigtes Königreich (EN-GB)


Beschreibung

Production lines in pharmaceutical manufacturing generate numerous heterogeneous data sets from various embedded systems which control the multiple processes of medicine production. Such data sets should arguably ensure end-to-end traceability and data integrity in order to release a medicine batch, which is uniquely identified and tracked by its batch number/code. Consequently, auditable computerised systems are crucial on pharmaceutical production lines, since the industry is becoming increasingly regulated for product quality and patient health purposes. This paper describes the EU- funded SPuMoNI project, which aims to ensure the quality of large amounts of data produced by computerised production systems in representative pharmaceutical environments. Our initial results include significant progress in: (i) end-to-end verification taking advantage of blockchain properties and smart contracts to ensure data authenticity, transparency, and immutability; (ii) data quality assessment models to identify data behavioural patterns that can violate industry practices and/or international regulations; and (iii) intelligent agents to collect and manipulate data as well as perform smart decisions. By analysing multiple sensors in medicine production lines, manufacturing work centres, and quality control laboratories, our approach has been initially evaluated using representative industry- grade pharmaceutical manufacturing data sets generated at an IT environment with regulated processes inspected by regulatory and government agencies.


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Zuletzt aktualisiert 2021-08-04 um 10:46