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<p>Large language models (LLMs) show promise for improving clinical trials in wealthy countries but remain underexplored in low- and middle-income countries (LMICs), where healthcare infrastructure is weaker and resources limited. This article explores opportunities for LLM integration and addresses ethical challenges in LMIC clinical trials through a review of recent literature (2024–2025) on LLMs in healthcare and clinical research, examining adaptation potential for LMICs using thematic analysis to identify ethical issues specific to LMIC contexts, including data control, fairness, and sustainability. LLMs can accelerate protocol development, improve multilingual patient recruitment, streamline regulatory processes, and address data gaps through synthetic records; however, implementation raises concerns about data privacy, community representation, AI transparency, and technological dependence on foreign platforms. While LLMs can enhance clinical trial efficiency and inclusivity in LMICs, successful integration requires locally-adapted models, community-centered ethical oversight, and regional partnerships, with thoughtful implementation potentially democratizing healthcare innovation benefits across Global South populations.</p>

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Large language models for clinical trials in the Global South: opportunities and ethical challenges

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月21日

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  • Hafiz Ahmed

摘要

Large language models (LLMs) show promise for improving clinical trials in wealthy countries but remain underexplored in low- and middle-income countries (LMICs), where healthcare infrastructure is weaker and resources limited. This article explores opportunities for LLM integration and addresses ethical challenges in LMIC clinical trials through a review of recent literature (2024–2025) on LLMs in healthcare and clinical research, examining adaptation potential for LMICs using thematic analysis to identify ethical issues specific to LMIC contexts, including data control, fairness, and sustainability. LLMs can accelerate protocol development, improve multilingual patient recruitment, streamline regulatory processes, and address data gaps through synthetic records; however, implementation raises concerns about data privacy, community representation, AI transparency, and technological dependence on foreign platforms. While LLMs can enhance clinical trial efficiency and inclusivity in LMICs, successful integration requires locally-adapted models, community-centered ethical oversight, and regional partnerships, with thoughtful implementation potentially democratizing healthcare innovation benefits across Global South populations.