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. 2023 Dec;16(12):2417-2420.
doi: 10.1111/cts.13648. Epub 2023 Oct 12.

Applying Natural Language Processing to ClinicalTrials.gov: mRNA cancer vaccine case study

Bianca Vora  1 , Denison Kuruvilla  1 , Chloe Kim  2 , Michael Wu  2 , Colby S Shemesh  1 , Gillie A Roth  3
Affiliations

Applying Natural Language Processing to ClinicalTrials.gov: mRNA cancer vaccine case study

Bianca Vora et al. Clin Transl Sci. 2023 Dec.

Abstract

Recently, biotechnology and pharmaceutical industries have made strides to adopt and implement Natural Language Processing (NLP) to address challenges faced when extracting and synthesizing high volumes of information found in unstructured and semistructured text. Here we present, and provide a summary of the findings from, a use case where NLP and text mining methodologies were used to extract clinical trial data from ClinicalTrials.gov for mRNA cancer vaccines.

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Conflict of interest statement

All authors are employees and stockholders of Roche/Genentech, Inc.

Figures

FIGURE 1
FIGURE 1
Natural Language Processing (NLP) Framework for mining data from ClinicalTrials.gov. Twenty‐seven unique clinical trials were extracted and included in the final analysis.
See this image and copyright information in PMC

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