How innovative technologies shape the future of pharmaceutical supply chains

IF 6.7 1区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Computers & Industrial Engineering Pub Date : 2024-11-23 DOI:10.1016/j.cie.2024.110745
Hajer Nabli , Abir Ghannem , Raoudha Ben Djemaa , Layth Sliman
{"title":"How innovative technologies shape the future of pharmaceutical supply chains","authors":"Hajer Nabli ,&nbsp;Abir Ghannem ,&nbsp;Raoudha Ben Djemaa ,&nbsp;Layth Sliman","doi":"10.1016/j.cie.2024.110745","DOIUrl":null,"url":null,"abstract":"<div><div>In the intricate tapestry of the pharmaceutical industry, the supply chain serves as the backbone, orchestrating the production, distribution, and delivery of life-saving medications. This network faces numerous challenges, including supply chain disruptions, counterfeit products, drug shortages, regulatory complexities, and so on. To address these issues, this study employed a multi-faceted methodology integrating blockchain, the Internet of Things (IoT), and artificial intelligence (AI) to enhance supply chain management. This article first provides an overview of the current pharmaceutical supply chain and its challenges. It then examines emerging technologies, compares these technologies to traditional practices based on criteria such as efficiency, accuracy, cost-effectiveness, traceability, and scalability, and concludes by discussing the adoption of these technologies in the pharmaceutical supply chain. Key findings reveal that blockchain provides immutable records and enhances traceability, IoT enables real-time monitoring and improved inventory management, and AI supports demand forecasting and anomaly detection. These advancements collectively enhance supply chain operations, offering superior efficiency and accuracy, reduced operational costs, improved traceability, and greater scalability. The study highlights that the adoption of these technologies represents a promising path towards achieving greater operational excellence and integrity in pharmaceutical supply chain operations.</div></div>","PeriodicalId":55220,"journal":{"name":"Computers & Industrial Engineering","volume":"199 ","pages":"Article 110745"},"PeriodicalIF":6.7000,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Industrial Engineering","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0360835224008672","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

Abstract

In the intricate tapestry of the pharmaceutical industry, the supply chain serves as the backbone, orchestrating the production, distribution, and delivery of life-saving medications. This network faces numerous challenges, including supply chain disruptions, counterfeit products, drug shortages, regulatory complexities, and so on. To address these issues, this study employed a multi-faceted methodology integrating blockchain, the Internet of Things (IoT), and artificial intelligence (AI) to enhance supply chain management. This article first provides an overview of the current pharmaceutical supply chain and its challenges. It then examines emerging technologies, compares these technologies to traditional practices based on criteria such as efficiency, accuracy, cost-effectiveness, traceability, and scalability, and concludes by discussing the adoption of these technologies in the pharmaceutical supply chain. Key findings reveal that blockchain provides immutable records and enhances traceability, IoT enables real-time monitoring and improved inventory management, and AI supports demand forecasting and anomaly detection. These advancements collectively enhance supply chain operations, offering superior efficiency and accuracy, reduced operational costs, improved traceability, and greater scalability. The study highlights that the adoption of these technologies represents a promising path towards achieving greater operational excellence and integrity in pharmaceutical supply chain operations.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
创新技术如何塑造医药供应链的未来
在错综复杂的制药业中,供应链是骨干力量,协调着救命药物的生产、分销和交付。这一网络面临着众多挑战,包括供应链中断、假冒产品、药品短缺、监管复杂等。为解决这些问题,本研究采用了一种整合区块链、物联网(IoT)和人工智能(AI)的多元方法来加强供应链管理。本文首先概述了当前的医药供应链及其面临的挑战。然后,文章研究了新兴技术,并根据效率、准确性、成本效益、可追溯性和可扩展性等标准将这些技术与传统做法进行了比较,最后讨论了在医药供应链中采用这些技术的问题。主要研究结果表明,区块链可提供不可篡改的记录并提高可追溯性,物联网可实现实时监控并改善库存管理,人工智能可支持需求预测和异常检测。这些先进技术共同加强了供应链的运营,提供了更高的效率和准确性,降低了运营成本,提高了可追溯性和可扩展性。该研究强调,采用这些技术是实现制药供应链运营更卓越、更完整的一条大有可为的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Computers & Industrial Engineering
Computers & Industrial Engineering 工程技术-工程:工业
CiteScore
12.70
自引率
12.70%
发文量
794
审稿时长
10.6 months
期刊介绍: Computers & Industrial Engineering (CAIE) is dedicated to researchers, educators, and practitioners in industrial engineering and related fields. Pioneering the integration of computers in research, education, and practice, industrial engineering has evolved to make computers and electronic communication integral to its domain. CAIE publishes original contributions focusing on the development of novel computerized methodologies to address industrial engineering problems. It also highlights the applications of these methodologies to issues within the broader industrial engineering and associated communities. The journal actively encourages submissions that push the boundaries of fundamental theories and concepts in industrial engineering techniques.
期刊最新文献
Distributed UAV swarms for 3D urban area coverage with incomplete information using event-triggered hierarchical reinforcement learning On prediction of future failure times based on bathtub-shaped type-II censoring samples Bayesian analysis of multi-fidelity modeling in the stochastic simulations How innovative technologies shape the future of pharmaceutical supply chains A varied-width path planning method for multiple AUV formation
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1