Abstract
Personalized medicine is a novel frontier in health care that is based on each person’s unique genetic makeup. It represents an exciting opportunity to improve the future of individualized health care for all individuals. Pharmacogenomics, as the main part of personalized medicine, aims to optimize and create a more targeted treatment approach based on genetic variations in drug response. It is predicted that future treatments will be algorithm-based instead of evidence-based that will consider a patient’s genetic, transcriptomic, proteomic, epigenetic, and lifestyle factors resulting in individualized medication. A generative pretrained transformer (GPT) is an artificial intelligence (AI) tool that generates language resembling human-like writing enabling users to engage in a manner that is practically identical to speaking with a human being. GPT’s predictive algorithms can respond to questions that have never been addressed. Chat Generative Pretrained Transformer (ChatGPT) is an AI chatbot’s advanced with conversational capabilities. In the present study, questions were asked from ChatGPT about the future of personalized medicine and pharmacogenomics. ChatGPT predicted both to be a promising approach with a bright future that holds great promises in improving patient outcomes and transforming the field of medicine. But it still has several limitations that need to be solved.
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GP participated in the supervision of the study design and validation. NS participated in the visualization and investigation. BS participated in the reviewing and editing the manuscript. BL provided insightful comments. NK contributed in ChatGPT search and English revision. MH conceptualized and wrote the first draft of the manuscript.
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Patrinos, G.P., Sarhangi, N., Sarrami, B. et al. Using ChatGPT to predict the future of personalized medicine. Pharmacogenomics J 23, 178–184 (2023). https://doi.org/10.1038/s41397-023-00316-9
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DOI: https://doi.org/10.1038/s41397-023-00316-9