An exploration into CTEPH medications: Combining natural language processing, embedding learning, in vitro models, and real-world evidence for drug repurposing.

ABSTRACT:

Background

In the modern era, the growth of scientific literature presents a daunting challenge for researchers to keep informed of advancements across multiple disciplines.

Objective

We apply natural language processing (NLP) and embedding learning concepts to design PubDigest, a tool that combs PubMed literature, aiming to pinpoint potential drugs that could be repurposed.

Methods

Using NLP, especially term associations through word embeddings, we explored unrecognized relationships between drugs and diseases. To illustrate the utility of PubDigest, we focused on chronic thromboembolic pulmonary hypertension (CTEPH), a rare disease with an overall limited number of scientific publications.

Results

Our literature analysis identified key clinical features linke

SUBMITTER: Steiert D 

PROVIDER: S-EPMC11478854 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature