Durá, Marta, Sánchez-García, Angel, Sáez, Carlos, Leal, Fátima, Chis, Adriana E., González-Vélez, Horacio and García-Gómez, Juan M. (2022) Towards a Computational Approach for the Assessment of Compliance of ALCOA+ Principles in Pharma Industry. In: Challenges of Trustable AI and Added-Value on Health. Studies in Health Technology and Informatics, 294 . IOS Press, pp. 755-759. ISBN 978-1-64368-285-3
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Abstract
The pharmaceutical industry is a data-intensive environment and a heavily-regulated sector, where exhaustive audits and inspections are performed to ensure the safety of drugs. In this context, processing and evaluating the data generated in the manufacturing lines is a relevant challenge since it requires compliance with pharma regulations. This work combines data integrity metrics and blockchain technology to evaluate the compliance-degree of ALCOA+ principles among different levels of drug manufacturing data. We propose the DIALCOA tool, a software to assess the compliance-degree for each ALCOA+ principle, based on the assessment of data from manufacturing batch reports and its different levels of information.
Item Type: | Book Section |
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Uncontrolled Keywords: | ALCOA+ compliance; Data integrity; pharma manufacturing industry |
Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science R Medicine > RS Pharmacy and materia medica H Social Sciences > HD Industries. Land use. Labor > Specific Industries > Manufacturing Industry |
Divisions: | School of Computing > Staff Research and Publications |
Depositing User: | Clara Chan |
Date Deposited: | 01 Jun 2022 10:14 |
Last Modified: | 27 Jun 2022 15:53 |
URI: | https://norma.ncirl.ie/id/eprint/5608 |
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