Blockchain for Data Originality in Pharma Manufacturing

Durá, Marta, Leal, Fátima, Sánchez-García, Ángel, Sáez, Carlos, García-Gómez, Juan M., Chis, Adriana E. and González-Vélez, Horacio (2023) Blockchain for Data Originality in Pharma Manufacturing. Journal of Pharmaceutical Innovation. ISSN 1939-8042

Preview

PDF Download (3MB) | Preview

Abstract

Purpose: This paper analyses the feasibility of tracking data originality for pharmaceutical manufacturing in a tamper-proof manner using a geographically distributed system. The main research question is whether it is possible to ensure the traceability of drug manufacturing through the use of smart contracts and a private blockchain network.

Methods: This work employs a private Ethereum network with a proof-of-authority consensus algorithm to allow participating nodes to commit the medicament manufacturing originality as transactions in blocks. We use smart contracts to assess the “Original” principle of the ALCOA+ data integrity principles for full sensor-enabled production lines within pharmaceutical manufacturing plants. We have evaluated our data originality assessment approach employing a temporal series of 1300 reports generated based on real datasets from pharma production lines. Out of these reports, 300 reports have been randomly tampered with to make them “unoriginal” (i.e., falsified).

Results: Evaluation consistently shows that the proposed approach systematically detects all the manufacturing records whether original or not, together with any source of falsification. By randomly injecting four common data falsification types, their approach effectively detects tampering and ensures the authenticity of the data originality acquired by sensors within manufacturing lines.

Conclusion: The approach of using a private blockchain network with a proof-of-authority consensus algorithm and smart contracts is a feasible method to track data originality for pharmaceutical manufacturing in a tamper-proof manner. In addition, this approach effectively detects tampering and ensures the authenticity of the data originality acquired by sensors within manufacturing lines.

Item Type:	Article
Additional Information:	This article is licensed under a Creative Commons Attribution 4.0 International License, which "permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made."
Uncontrolled Keywords:	Blockchain; Production line; ALCOA; Ethereum; Data integrity; Data quality
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 > HM Sociology > Information Science > Communication > Medical Informatics
Divisions:	School of Computing > Staff Research and Publications
Depositing User:	Tamara Malone
Date Deposited:	11 Jul 2023 10:36
Last Modified:	11 Jul 2023 10:36
URI:	https://norma.ncirl.ie/id/eprint/6767

Actions (login required)

View Item