REVOLUTIONIZING DRUG DELIVERY INNOVATION: LEVERAGING AI-DRIVEN CHATBOTS FOR ENHANCED EFFICIENCY

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Abstract

This study aims to delineate the pivotal role of ChatGPT, an Artificial intelligence-driven (AI) language model, in revolutionizing drug delivery research within the pharmaceutical sciences domain. The investigation adopted a structured approach involving systematic literature exploration across databases such as PubMed, ScienceDirect, IEEE Xplore, and Google Scholar. A selection criterion emphasizing peer-reviewed articles, conference proceedings, patents, and seminal texts highlights the integration of AI-driven chatbots, specifically ChatGPT, into various facets of drug delivery research and development. ChatGPT exhibits multifaceted contributions to drug delivery innovation, streamlining drug formulation optimization, predictive modeling, regulatory compliance, and fostering patient-centric approaches. Real-world case studies have underscored its efficacy in expediting drug development timelines and enhancing research efficiency. This paper delves into the diverse applications of ChatGPT, showcasing its potential across drug delivery systems. It elucidates its capabilities in accelerating research phases, facilitating formulation development, predictive modeling for efficacy and safety, and simplifying regulatory compliance. This discussion outlines the transformative impact of ChatGPT in reshaping drug delivery methodologies. In conclusion, ChatGPT, an AI-driven chatbot, has emerged as a transformative tool in pharmaceutical research. Their integration expedites drug development pipelines, ensures effective drug delivery solutions, and augments healthcare advancements. Embracing AI tools such as ChatGPT has become pivotal in evolving drug delivery methodologies for global patient welfare.

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APA

Malkawi, R. (2024, March 1). REVOLUTIONIZING DRUG DELIVERY INNOVATION: LEVERAGING AI-DRIVEN CHATBOTS FOR ENHANCED EFFICIENCY. International Journal of Applied Pharmaceutics. Innovare Academics Sciences Pvt. Ltd. https://doi.org/10.22159/ijap.2024v16i2.50182

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