首页|Large-scale automatic extraction of side effects associated with targeted anticancer drugs from full-text oncological articles
Large-scale automatic extraction of side effects associated with targeted anticancer drugs from full-text oncological articles
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NSTL
Elsevier
Targeted anticancer drugs such as imatinib, trastuzumab and erlotinib dramatically improved treatment outcomes in cancer patients, however, these innovative agents are often associated with unexpected side effects. The pathophysiological mechanisms underlying these side effects are not well understood. The availability of a comprehensive knowledge base of side effects associated with targeted anticancer drugs has the potential to illuminate complex pathways underlying toxicities induced by these innovative drugs. While side effect association knowledge for targeted drugs exists in multiple heterogeneous data sources, published full-text oncological articles represent an important source of pivotal, investigational, and even failed trials in a variety of patient populations. In this study, we present an automatic process to extract targeted anticancer drug-associated side effects (drug-SE pairs) from a large number of high profile full-text oncological articles.
Text miningInformation extractionTargeted anticancer drugsDrug side effectsDrug discoveryDrug repositioningDrug toxicity prediction
Xu, Rong、Wang, QuanQiu
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Case Western Reserve Univ, Med Informat Program, Ctr Clin Invest, Cleveland, OH 44106 USA
NSTL
Elsevier
