  In this study, we introduce PharmacyGPT, a novel framework to assess the
capabilities of large language models (LLMs) such as ChatGPT and GPT-4 in
emulating the role of clinical pharmacists. Our methodology encompasses the
utilization of LLMs to generate comprehensible patient clusters, formulate
medication plans, and forecast patient outcomes. We conduct our investigation
using real data acquired from the intensive care unit (ICU) at the University
of North Carolina Chapel Hill (UNC) Hospital. Our analysis offers valuable
insights into the potential applications and limitations of LLMs in the field
of clinical pharmacy, with implications for both patient care and the
development of future AI-driven healthcare solutions. By evaluating the
performance of PharmacyGPT, we aim to contribute to the ongoing discourse
surrounding the integration of artificial intelligence in healthcare settings,
ultimately promoting the responsible and efficacious use of such technologies.
