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Recommending Clinical Trials for Online Patient Cases using Artificial Intelligence.

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Summary

TrialGPT, an AI framework, enhances clinical trial recruitment by matching online patient cases to studies, improving patient access to novel treatments. This AI-driven approach significantly outperforms traditional methods.

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Area of Science:

  • Medical Informatics
  • Clinical Trial Management
  • Artificial Intelligence in Healthcare

Background:

  • Clinical trial recruitment faces significant hurdles, including limited patient awareness and complex eligibility criteria.
  • The proliferation of online platforms (social media, health communities, PubMed) offers novel, untapped sources for identifying potential clinical trial participants.
  • Traditional recruitment methods often fail to leverage these diverse, non-traditional data sources effectively.

Purpose of the Study:

  • To evaluate the efficacy of TrialGPT, a large language model-based framework, in matching online patient cases to suitable clinical trials.
  • To compare the performance of TrialGPT against conventional keyword-based search methods for clinical trial recruitment.
  • To assess the potential of utilizing non-traditional patient case sources for clinical trial participant identification.

Main Methods:

  • Collected 50 online patient cases from medical case reports and social media platforms.
  • Employed the TrialGPT framework, utilizing a large language model, to match these patient cases with relevant clinical trials.
  • Compared the matching performance of TrialGPT against traditional keyword-based search strategies.

Main Results:

  • TrialGPT demonstrated a 46% superior performance compared to traditional keyword-based searches in matching patients to clinical trials.
  • On average, patients identified through TrialGPT were eligible for 7 out of the top 10 recommended clinical trials.
  • Positive feedback was received from both case authors and clinical trial organizers upon outreach, indicating feasibility and acceptance.

Conclusions:

  • TrialGPT effectively leverages non-traditional online patient data to enhance clinical trial recruitment.
  • The AI-driven approach significantly improves patient eligibility and access to clinical trials for specialized care.
  • This framework presents a promising strategy for expanding patient access to innovative treatments through novel recruitment pathways.