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Automated identification of molecular effects of drugs (AIMED).

Authors :
Fathiamini S
Johnson AM
Zeng J
Araya A
Holla V
Bailey AM
Litzenburger BC
Sanchez NS
Khotskaya Y
Xu H
Meric-Bernstam F
Bernstam EV
Cohen T
Source :
Journal of the American Medical Informatics Association : JAMIA [J Am Med Inform Assoc] 2016 Jul; Vol. 23 (4), pp. 758-65. Date of Electronic Publication: 2016 Apr 23.
Publication Year :
2016

Abstract

Introduction: Genomic profiling information is frequently available to oncologists, enabling targeted cancer therapy. Because clinically relevant information is rapidly emerging in the literature and elsewhere, there is a need for informatics technologies to support targeted therapies. To this end, we have developed a system for Automated Identification of Molecular Effects of Drugs, to help biomedical scientists curate this literature to facilitate decision support.<br />Objectives: To create an automated system to identify assertions in the literature concerning drugs targeting genes with therapeutic implications and characterize the challenges inherent in automating this process in rapidly evolving domains.<br />Methods: We used subject-predicate-object triples (semantic predications) and co-occurrence relations generated by applying the SemRep Natural Language Processing system to MEDLINE abstracts and ClinicalTrials.gov descriptions. We applied customized semantic queries to find drugs targeting genes of interest. The results were manually reviewed by a team of experts.<br />Results: Compared to a manually curated set of relationships, recall, precision, and F2 were 0.39, 0.21, and 0.33, respectively, which represents a 3- to 4-fold improvement over a publically available set of predications (SemMedDB) alone. Upon review of ostensibly false positive results, 26% were considered relevant additions to the reference set, and an additional 61% were considered to be relevant for review. Adding co-occurrence data improved results for drugs in early development, but not their better-established counterparts.<br />Conclusions: Precision medicine poses unique challenges for biomedical informatics systems that help domain experts find answers to their research questions. Further research is required to improve the performance of such systems, particularly for drugs in development.<br /> (© The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Details

Language :
English
ISSN :
1527-974X
Volume :
23
Issue :
4
Database :
MEDLINE
Journal :
Journal of the American Medical Informatics Association : JAMIA
Publication Type :
Academic Journal
Accession number :
27107438
Full Text :
https://doi.org/10.1093/jamia/ocw030