PretoxTM: a text mining system for extracting treatment-related findings from preclinical toxicology reports

PretoxTM: a text mining system for extracting treatment-related findings from preclinical toxicology reports

Abstract Over the last few decades the pharmaceutical industry has generated a vast corpus of knowledge on the safety and efficacy of drugs. Much of this information is contained in toxicology reports, which summarise the results of animal studies designed to analyse the effects of the tested compou...

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Main Authors: Javier Corvi, Nicolás Díaz-Roussel, José M. Fernández, Francesco Ronzano, Emilio Centeno, Pablo Accuosto, Celine Ibrahim, Shoji Asakura, Frank Bringezu, Mirjam Fröhlicher, Annika Kreuchwig, Yoko Nogami, Jeong Rih, Raul Rodriguez-Esteban, Nicolas Sajot, Joerg Wichard, Heng-Yi Michael Wu, Philip Drew, Thomas Steger-Hartmann, Alfonso Valencia, Laura I. Furlong, Salvador Capella-Gutierrez
Format: Article
Language:English
Published: BMC 2025-02-01
Series:Journal of Cheminformatics
Subjects:
Natural language processing
Text mining
Toxicology
Adverse effect
Preclinical
Animal model
Online Access:https://doi.org/10.1186/s13321-024-00925-x
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https://doi.org/10.1186/s13321-024-00925-x

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