The prescription is a critical bridge between medical diagnosis and therapeutic intervention, embodying a complex decision that balances medical evidence, clinical experience, and individual patient needs. However, the prescribing process faces significant challenges from rising drug costs and the existence of therapeutically similar but economically diverse drug options, creating an urgent need for prescription optimization that maintains therapeutic efficacy while reducing financial burden. While artificial intelligence (AI) agents have demonstrated transformative potential in automating complex tasks across scientific and medical domains, their application has not yet adequately addressed the critical dimension of economic impact within healthcare. To bridge this gap, we develop EcoRxAgent, an AI agent designed to generate economically substitutable prescriptions. This agent operates through a sequential pipeline that retrieves candidate drugs, generates candidate prescription sets, rigorously checks their safety, conducts a cost-effectiveness analysis, and ultimately outputs all economically substitutable prescriptions (i.e. safety-checked prescriptions with lower total cost). Our experimental results on two independent cohorts (total n = 1559) prescriptions show that the agent can automatically generate prescriptions that are therapeutically non-inferior to physicians’ original prescriptions while achieving a significant reduction ratio in overall medication costs ranging from 14.40% to 40.14%. This study demonstrates the substantial potential of AI agents in creating tangible economic benefits within the healthcare domain.
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Cheng Li
Peiyuan Lai
Na Zhang
npj Digital Medicine
Sun Yat-sen University
Sun Yat-sen Memorial Hospital
Guangdong Provincial Center for Disease Control and Prevention
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Li et al. (Wed,) studied this question.
www.synapsesocial.com/papers/69d8955f6c1944d70ce06525 — DOI: https://doi.org/10.1038/s41746-026-02612-7