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

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 provi...

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Bibliographic Details
Published in:Clinical and Translational Science
Main Authors: Bianca Vora, Denison Kuruvilla, Chloe Kim, Michael Wu, Colby S. Shemesh, Gillie A. Roth
Format: Article
Language:English
Published: Wiley 2023-12-01
Online Access:https://doi.org/10.1111/cts.13648
Description
Summary: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.
ISSN:1752-8054
1752-8062

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