Strengthening the Drug Supply Chain Management in a tertiary care hospital in Sri Lanka

This paper provides a detailed overview of the block chain technology and how it can be used to build a foolproof system in eliminating counterfeit products in pharmaceutical industries. From the last decade, pharmaceutical companies are facing difficulties in tracking their products during the supply chain process, allowing the counterfeiters to add their fake medicines into the market. Counterfeit drugs are analysed as a very big challenge for the pharmaceutical industry worldwide. As indicated by the statistics, yearly business loss of around $200 billion is reported by US pharmaceutical companies due to these counterfeit drugs. These drugs may not help the patients to recover the disease but have many other dangerous side effects. According to the World Health Organization (WHO) survey report, in under-developed countries every 10th drug use by the consumers is counterfeit and has low quality. Hence, a system that can trace and track drug delivery at every phase is needed to solve the counterfeiting problem. The block chain has the full potential to handle and track the supply chain process very efficiently. In this paper, we have proposed and implemented a block chain based drug supply chain management. Our proposed system block chain-based drug supply chain management for consumers. In this drug supply chain management the system is deployed using Hyper ledger fabrics which is capable of continuously monitor and track the drug delivery process in the smart pharmaceutical industry. Finally, we also perform several tests to check the efficiency and usability of our proposed system.

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A Blockchain and Machine Learning-Based Drug Supply Chain Management and Recommendation System for Smart Pharmaceutical Industry

Electronics ◽

10.3390/electronics9050852 ◽

2020 ◽

Vol 9 (5) ◽

pp. 852 ◽

Cited By ~ 2

Author(s):

Khizar Abbas ◽

Muhammad Afaq ◽

Talha Ahmed Khan ◽

Wang-Cheol Song

Keyword(s):

Machine Learning ◽

Supply Chain ◽

Supply Chain Management ◽

Pharmaceutical Industry ◽

Recommendation System ◽

Chain Process ◽

Drug Supply ◽

Counterfeit Drugs ◽

Chain Management ◽

Drug Supply Chain

From the last decade, pharmaceutical companies are facing difficulties in tracking their products during the supply chain process, allowing the counterfeiters to add their fake medicines into the market. Counterfeit drugs are analyzed as a very big challenge for the pharmaceutical industry worldwide. As indicated by the statistics, yearly business loss of around $200 billion is reported by US pharmaceutical companies due to these counterfeit drugs. These drugs may not help the patients to recover the disease but have many other dangerous side effects. According to the World Health Organization (WHO) survey report, in under-developed countries every 10th drug use by the consumers is counterfeit and has low quality. Hence, a system that can trace and track drug delivery at every phase is needed to solve the counterfeiting problem. The blockchain has the full potential to handle and track the supply chain process very efficiently. In this paper, we have proposed and implemented a novel blockchain and machine learning-based drug supply chain management and recommendation system (DSCMR). Our proposed system consists of two main modules: blockchain-based drug supply chain management and machine learning-based drug recommendation system for consumers. In the first module, the drug supply chain management system is deployed using Hyperledger fabrics which is capable of continuously monitor and track the drug delivery process in the smart pharmaceutical industry. On the other hand, the N-gram, LightGBM models are used in the machine learning module to recommend the top-rated or best medicines to the customers of the pharmaceutical industry. These models have trained on well known publicly available drug reviews dataset provided by the UCI: an open-source machine learning repository. Moreover, the machine learning module is integrated with this blockchain system with the help of the REST API. Finally, we also perform several tests to check the efficiency and usability of our proposed system.

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