Using LLMs to Accelerate the Development of Blockchain-Based Solutions: A Case Study on Controlled Medication Management

Abstract

Blockchain technology is revolutionizing industries that demand transparency, compliance, and accountability. However, developing blockchain solutions remains a complex and time-consuming process that requires extensive expertise in domain requirements, design, and implementation. The integration of Large Language Models (LLMs) into the blockchain development process can offer a novel approach that addresses the challenges of designing, implementing, and evaluating blockchain-based solutions. In this paper, we analyze the traditional phases involved in the development of blockchain solutions and demonstrate how LLMs can enhance and accelerate each development phase. As a case study, we apply our LLM-assisted approach to the development phases involved in devising a blockchain-based solution for the management and administration of controlled medications in the healthcare industry. We utilize a customized version of ChatGPT to automate and accelerate the generation of requirements, sequence diagrams, smart contract code, unit tests, and cost and security analyses, with each phase building on the output of the previous one. We test and validate the LLM-assisted approach and compare it to a manually developed approach. The results reveal significant acceleration and efficiency gains across all phases involved in the development of blockchain solutions.

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