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Publication
Extraction of Pharmacokinetic Evidence of Drug-drug Interactions from the Literature
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| artigo principal | 1.74 MB | Adobe PDF |
Advisor(s)
Abstract(s)
Drug-drug interaction (DDI) is a major cause of morbidity and mortality and a
subject of intense scientific interest. Biomedical literature mining can aid
DDI research by extracting evidence for large numbers of potential interactions
from published literature and clinical databases. Though DDI is investigated in
domains ranging in scale from intracellular biochemistry to human populations,
literature mining has not been used to extract specific types of experimental
evidence, which are reported differently for distinct experimental goals. We
focus on pharmacokinetic evidence for DDI, essential for identifying causal
mechanisms of putative interactions and as input for further pharmacological
and pharmaco-epidemiology investigations. We used manually curated corpora of
PubMed abstracts and annotated sentences to evaluate the efficacy of literature
mining on two tasks: first, identifying PubMed abstracts containing
pharmacokinetic evidence of DDIs; second, extracting sentences containing such
evidence from abstracts. We implemented a text mining pipeline and evaluated it
using several linear classifiers and a variety of feature transforms. The most
important textual features in the abstract and sentence classification tasks
were analyzed. We also investigated the performance benefits of using features
derived from PubMed metadata fields, various publicly available named entity
recognizers, and pharmacokinetic dictionaries. Several classifiers performed
very well in distinguishing relevant and irrelevant abstracts (reaching
F1~=0.93, MCC~=0.74, iAUC~=0.99) and sentences (F1~=0.76, MCC~=0.65,
iAUC~=0.83). We found that word bigram features were important for achieving
optimal classifier performance and that features derived from Medical Subject
Headings (MeSH) terms significantly improved abstract classification. ...
Description
Keywords
Statistics - Machine Learning Computer Science - Information Retrieval Quantitative Biology - Quantitative Methods
Citation
Kolchinsky A, Lourenço A, Wu H-Y, Li L, Rocha LM (2015) Extraction of Pharmacokinetic Evidence of Drug – Drug Interactions from the Literature. PLoS ONE 10(5): e0122199. doi:10.1371/ journal.pone.0122199
Publisher
PLOS