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Matching patients to clinical trials with large language models

214
Citations
November 18, 2024
Published Date

Research Abstract & Technology Focus

AbstractPatient recruitment is challenging for clinical trials. We introduce TrialGPT, an end-to-end framework for zero-shot patient-to-trial matching with large language models. TrialGPT comprises three modules: it first performs large-scale filtering to retrieve candidate trials (TrialGPT-Retrieval); then predicts criterion-level patient eligibility (TrialGPT-Matching); and finally generates trial-level scores (TrialGPT-Ranking). We evaluate TrialGPT on three cohorts of 183 synthetic patients with over 75,000 trial annotations. TrialGPT-Retrieval can recall over 90% of relevant trials using less than 6% of the initial collection. Manual evaluations on 1015 patient-criterion pairs show that TrialGPT-Matching achieves an accuracy of 87.3% with faithful explanations, close to the expert performance. The TrialGPT-Ranking scores are highly correlated with human judgments and outperform the best-competing models by 43.8% in ranking and excluding trials. Furthermore, our user study reveals that TrialGPT can reduce the screening time by 42.6% in patient recruitment. Overall, these results have demonstrated promising opportunities for patient-to-trial matching with TrialGPT.
matching patients clinical trials large language
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Matching patients to clinical trials with large language models

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What is the core focus of the research titled 'Matching patients to clinical trials with large language models'?

This literature focuses on: AbstractPatient recruitment is challenging for clinical trials. We introduce TrialGPT, an end-to-end framework for zero-shot patient-to-trial matching with large language models. TrialGPT comprises three modules: it first performs large-scale filt...

Are there open-source GitHub repositories related to Matching patients to clinical trials with large language models?

Yes, open-source projects like VoltAgent/awesome-design-md (A collection of DESIGN.md files inspired by popular brand design systems. Drop one into your project and let coding agents generate a matching UI.) are actively building upon these concepts.

Which startups are commercializing the technology behind Matching patients to clinical trials with large language models?

Products like Clera are bringing this to market. Their focus is: An AI agent matching candidates to the right roles..

What other academic literature is closely related to 'Matching patients to clinical trials with large language models'?

Yes, highly correlated activity was mapped. An entry titled 'Matching patients to clinical trials with large language models' discusses this: AbstractPatient recruitment is challenging for clinical trials. We introduce TrialGPT, an end-to-end framework for zero-shot patient-to-trial match...

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