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

Detalhes bibliográficos
Autor(a) principal: Leal, Fátima
Data de Publicação: 2021
Outros Autores: Chis, Adriana E., Caton, Simon, González–Vélez, Horacio, García–Gómez, Juan M.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/11328/3347
Resumo: 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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spelling Smart Pharmaceutical Manufacturing: Ensuring End-to-End Traceability and Data Integrity in Medicine ProductionALCOABlockchainData anayticsData qualityIntelligent agentsSmart contractsProduction 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.Elsevier2021-01-25T17:35:57Z2021-01-252021-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfLeal, 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/11328/3347http://hdl.handle.net/11328/3347Leal, 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/11328/3347http://hdl.handle.net/11328/3347eng2214-5796http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessLeal, FátimaChis, Adriana E.Caton, SimonGonzález–Vélez, HoracioGarcía–Gómez, Juan M.reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-16T02:09:12Zoai:repositorio.upt.pt:11328/3347Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:40:21.790734Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Smart Pharmaceutical Manufacturing: Ensuring End-to-End Traceability and Data Integrity in Medicine Production
title Smart Pharmaceutical Manufacturing: Ensuring End-to-End Traceability and Data Integrity in Medicine Production
spellingShingle Smart Pharmaceutical Manufacturing: Ensuring End-to-End Traceability and Data Integrity in Medicine Production
Leal, Fátima
ALCOA
Blockchain
Data anaytics
Data quality
Intelligent agents
Smart contracts
title_short Smart Pharmaceutical Manufacturing: Ensuring End-to-End Traceability and Data Integrity in Medicine Production
title_full Smart Pharmaceutical Manufacturing: Ensuring End-to-End Traceability and Data Integrity in Medicine Production
title_fullStr Smart Pharmaceutical Manufacturing: Ensuring End-to-End Traceability and Data Integrity in Medicine Production
title_full_unstemmed Smart Pharmaceutical Manufacturing: Ensuring End-to-End Traceability and Data Integrity in Medicine Production
title_sort Smart Pharmaceutical Manufacturing: Ensuring End-to-End Traceability and Data Integrity in Medicine Production
author Leal, Fátima
author_facet Leal, Fátima
Chis, Adriana E.
Caton, Simon
González–Vélez, Horacio
García–Gómez, Juan M.
author_role author
author2 Chis, Adriana E.
Caton, Simon
González–Vélez, Horacio
García–Gómez, Juan M.
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Leal, Fátima
Chis, Adriana E.
Caton, Simon
González–Vélez, Horacio
García–Gómez, Juan M.
dc.subject.por.fl_str_mv ALCOA
Blockchain
Data anaytics
Data quality
Intelligent agents
Smart contracts
topic ALCOA
Blockchain
Data anaytics
Data quality
Intelligent agents
Smart contracts
description 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.
publishDate 2021
dc.date.none.fl_str_mv 2021-01-25T17:35:57Z
2021-01-25
2021-01-01T00:00:00Z
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format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv Leal, 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/11328/3347
http://hdl.handle.net/11328/3347
Leal, 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/11328/3347
http://hdl.handle.net/11328/3347
identifier_str_mv Leal, 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/11328/3347
url http://hdl.handle.net/11328/3347
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2214-5796
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dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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