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

dc.contributor.authorChis, Adriana E.
dc.contributor.authorCaton, Simon
dc.contributor.authorGonzález–Vélez, Horacio
dc.contributor.authorGarcía–Gómez, Juan M.
dc.contributor.authorLeal, Fátima
dc.date.accessioned2021-01-25T17:35:57Z
dc.date.available2021-01-25T17:35:57Z
dc.date.issued2021
dc.description.abstractProduction 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.pt_PT
dc.identifier.citationLeal, F., Chis, A. E., Caton, S., González–Vélez, H., García–Gómez, J. M., et al. (2021). Smart Pharmaceutical Manufacturing: Ensuring End-to-End Traceability and Data Integrity in Medicine Production. Big Data Research, 24, 1-12. DOI: https://doi.org/10.1016/j.bdr.2020.100172. Disponível no Repositório UPT, http://hdl.handle.net/11328/3347pt_PT
dc.identifier.issn2214-5796
dc.identifier.urihttp://hdl.handle.net/11328/3347
dc.language.isoengpt_PT
dc.publisherElsevierpt_PT
dc.rightsopen accesspt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectALCOApt_PT
dc.subjectBlockchainpt_PT
dc.subjectData anayticspt_PT
dc.subjectData qualitypt_PT
dc.subjectIntelligent agentspt_PT
dc.subjectSmart contractspt_PT
dc.titleSmart Pharmaceutical Manufacturing: Ensuring End-to-End Traceability and Data Integrity in Medicine Productionpt_PT
dc.typejournal articlept_PT
degois.publication.firstPage1pt_PT
degois.publication.lastPage12pt_PT
degois.publication.titleBig Data Researchpt_PT
degois.publication.volume24pt_PT
dspace.entity.typePublicationen
person.affiliation.nameREMIT – Research on Economics, Management and Information Technologies
person.familyNameLeal
person.givenNameFátima
person.identifier.ciencia-id2211-3EC7-B4B6
person.identifier.orcid0000-0003-4418-2590
person.identifier.ridY-3460-2019
person.identifier.scopus-author-id57190765181
relation.isAuthorOfPublication8066078f-1e30-4b0a-aa84-3b6a2af4185c
relation.isAuthorOfPublication.latestForDiscovery8066078f-1e30-4b0a-aa84-3b6a2af4185c

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