This paper is in the following e-collection/theme issue:

Applications of AI (290) Chatbots and Conversational Agents (744) Clinical Information and Decision Making (1929) Information Retrieval (350) Generative Language Models Including ChatGPT (714) Pharmacology and Pharmaceutics (112)

Published on in Vol 4 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/79751, first published .
Effectiveness of ChatGPT, Google Gemini, and Microsoft Copilot in Answering Thai Drug Information Queries: Cross-Sectional Study

Effectiveness of ChatGPT, Google Gemini, and Microsoft Copilot in Answering Thai Drug Information Queries: Cross-Sectional Study

Effectiveness of ChatGPT, Google Gemini, and Microsoft Copilot in Answering Thai Drug Information Queries: Cross-Sectional Study

Authors of this article:

Suphannika Pornwattanakavee1 Author Orcid Image ;   Nattawut Leelakanok1 Author Orcid Image ;   Teerarat Todsarot1 Author Orcid Image ;   Gabrielle Angele Tatta Guinto1 Author Orcid Image ;   Ratchanon Takun1 Author Orcid Image ;   Assadawut Sumativit1 Author Orcid Image ;   Marisa Senngam1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Suphannika Pornwattanakavee   1 , PharmD ;   Nattawut Leelakanok   1 , BScPharm, MScPharm, PhD ;   Teerarat Todsarot   1 , PharmD ;   Gabrielle Angele Tatta Guinto   1 ;   Ratchanon Takun   1 ;   Assadawut Sumativit   1 ;   Marisa Senngam   1 , PharmD, BCP

1 Division of Clinical Pharmacy, Faculty of Pharmaceutical Sciences, Burapha University, Chonburi, Thailand

Corresponding Author:

  • Marisa Senngam, PharmD, BCP
  • Division of Clinical Pharmacy
  • Faculty of Pharmaceutical Sciences
  • Burapha University
  • 169 Long-Haad Bangsaen Road
  • Saensook, Mueang
  • Chonburi 20131
  • Thailand
  • Phone: 66 38390401
  • Fax: 66 38390400
  • Email: marisa@go.buu.ac.th