Regulatory Affairs Chatbot: Revolutionizing Compliance Through AI Integration

Abstract

Background: Regulatory requirements are becoming more complex and stringent due to recent developments in global standards. Most of the time, pharmaceutical companies opt for traditional and lengthy methods, however, these methods are not efficient. As a result, they need to find more effective and innovative solutions in order to expedite the regulatory requirements process. Objectives: Here, we have integrated Artificial Intelligence (AI) powered chatbots into regulatory affairs as a potential solution. This paper focuses on the designing and staged assessment of a regulatory requirements AI-based chatbot employing a Retrieval-Augmented Generation (RAG) technique for upgrading the accuracy and trustworthiness of the regulatory requirements. Materials and Methods: The system proposed is creating an AI chatbot with the help of Lang Chain, Open AI’s GPT-3.5 model, and FAISS (Facebook AI Similarity Search), which is capable of reading regulatory documents and answering compliance queries. Results: The tests were mock-run with the help of representative USFDA documents and domain-specific queries to demonstrate that our chatbot achieves up to 87% accuracy and lowers the average response time by 45% as compared to the manual process. Conclusion: Such integration can not only simplify the processes, but also enhance the efficiency and provide support to comply with mandatory requirements in the pharmaceutical industry. AI chatbots optimize the regulatory work, thus facilitating the adoption process that is facing a delay due to data security and compliance issues.