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<h1 class="forstaffpages" style="opacity: 1;">TrialGPT</h1>
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<h2 class="forstaffpages" style="opacity: 1;">An AI Powered Tool for Matching Patients to Clinical Trials</h2>
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</div>
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<div class="row">
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<div class="slide-image"><img src="/research/trialgpt/static/main/img/ai_and_machine_learning_featured_article.jpg" alt="Regents Award"></div>
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<div class="slide-text">
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<h3>Our TrialGPT Paper is Highlighted by Nature Communications</h3>
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<p>Nature Communications chose to feature our article in their dedicated Editors'
|
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Highlights of recent published research on "AI and machine learning".</p>
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<a href="https://www.nature.com/collections/ceiajcdbeb" class="blue-cta" target="_blank">Read More</a>
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<div class="slide-image"><img src="/research/trialgpt/static/main/img/nih-trialgpt-news-release-202411-2.jpg" alt="Regents Award"></div>
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<div class="slide-text">
|
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<h3>NIH-developed AI Algorithm Matches Potential Volunteers to Clinical Trials</h3>
|
||
<p>Researchers from the National Institutes of Health (NIH) have developed an AI algorithm to speed up
|
||
matching potential volunteers to relevant clinical research trials.</p>
|
||
<a href="https://www.nih.gov/news-events/news-releases/nih-developed-ai-algorithm-matches-potential-volunteers-clinical-trials" class="blue-cta" target="_blank">Read More</a>
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<div class="mySlides">
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<div class="slide-image"><img src="/research/trialgpt/static/main/img/nlm-regents-award-2024.jpg" alt="Regents Award"></div>
|
||
<div class="slide-text">
|
||
<h3>Dr. Zhiyong Lu Received 2024 NLM Regents Award</h3>
|
||
<p>Dr. Zhiyong Lu was honored at the 2024 NLM Regents meeting for his leadership in developing TrialGPT.</p>
|
||
</div>
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</div>
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</div>
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<div class="mySlides">
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<div class="row">
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<div class="slide-image"><img src="/research/trialgpt/static/main/img/framework_thumbnail.jpg" alt="Innovation Awards"></div>
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<div class="slide-text">
|
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<h3>TrialGPT 2.0 Selected for NIH Director's Challenge Innovation Awards</h3>
|
||
<p>We have developed a proof-of-concept system named TrialGPT
|
||
that utilizes LLMs to efficiently match patients with suitable clinical trials.</p>
|
||
<a href="https://oir.nih.gov/sourcebook/awards-fellowships-grant-opportunities/directors-challenge-innovation-award-program/2024-directors-challenge-awards#2024-directors-lu" class="blue-cta" target="_blank">Read More</a>
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<div class="slide-text">
|
||
<h3>TrialGPT Featured in the Cover Page of AUANews</h3>
|
||
<p>TrialGPT shows significant potential to efficiently and effectively match patients to clinical trials,
|
||
standing at the forefront of a new era in clinical trial matching.</p>
|
||
<a href="https://auanews.net/issues/articles/2024/march-2024/artificial-intelligence-connecting-patients-to-clinical-trials-with-artificial-intelligence" class="blue-cta" target="_blank">Read More</a>
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<div style="text-align:center">
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<div class="home-highlights">
|
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<h2>Highlights</h2>
|
||
<ul>
|
||
<li>An end-to-end framework for zero-shot patient-to-trial matching with LLM</li>
|
||
<li>Comprises three modules: TrialGPT-Retrieval, TrialGPT-Matching, and TrialGPT-Ranking</li>
|
||
<li>Achieves an accuracy of 87.3% with faithful explanations, close to the expert performance</li>
|
||
<li>Reduces the screening time by 42.6% in patient recruitment</li>
|
||
</ul>
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<p class="text-white">
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<a href="/research/trialgpt/about/" class="text-white">
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<em>Learn more</em>
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<img src="/research/trialgpt/static/main/img/trialgpt-home-highlights.png" alt="Highlights">
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<div class="flex-item-video">
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<iframe aria-labelledby="focusVideo2" src="https://www.youtube.com/embed/Sys9Ki6t4DQ" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen="" id="YTVideo_1" data-gtm-yt-inspected-41="true" data-gtm-yt-inspected-45="true" title="TrialGPT Video"></iframe>
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</section>
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<section class="usa-section citation-section">
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<div class="citation-block">
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<h2>Cite TrialGPT</h2>
|
||
<div class="publication">
|
||
<a href="https://www.nature.com/articles/s41467-024-53081-z" target="_blank" rel="noreferrer">
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<div>
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||
<div class="publication-journal">Nature Communications</div>
|
||
<div class="publication-year">2024</div>
|
||
<div class="publication-title">Matching Patients to Clinical Trials with Large Language Models</div>
|
||
<div class="publication-authors">Qiao Jin, Zifeng Wang, Charalampos S. Floudas, Fangyuan Chen,
|
||
Changlin Gong, Dara Bracken-Clarke, Elisabetta Xue, Yifan Yang, Jimeng Sun, Zhiyong Lu
|
||
</div>
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</div>
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</a>
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</div>
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<!-- <div class="publication">
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<div class="publication-journal">Nature Communications</div>
|
||
<div class="publication-year">2024</div>
|
||
<div class="publication-title">Matching Patients to Clinical Trials with Large Language Models</div>
|
||
<div class="publication-authors">Qiao Jin, Zifeng Wang, Charalampos S. Floudas, Fangyuan Chen,
|
||
Changlin Gong, Dara Bracken-Clarke, Elisabetta Xue, Yifan Yang, Jimeng Sun, Zhiyong Lu
|
||
</div>
|
||
</div>
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</a>
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<h2>Contacts</h2>
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<ul class="flex-container homepage-focus-areas-list">
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<li class="list-item">
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<a href="mailto:qiao.jin@nih.gov">
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<img src="/research/trialgpt/static/main/img/qiaojin.jpg" alt="Qiao Jin">
|
||
</a>
|
||
<p><a href="mailto:qiao.jin@nih.gov">Qiao Jin, MD</a>
|
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