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We describe our system for the DDIExtraction-2013 shared task of classifying Drug-Drug interactions (DDIs) given labeled drug mentions. The challenge called for a five-way classification of all drug pairs in each sentence: a drug pair is either non-interacting, or interacting as one of four types. Our approach begins with the use of a two-stage weighted SVM(More)
To protect the safety of patients, it is vital that researchers find methods for representing drug mechanism knowledge that support making clinically relevant drug-drug interaction (DDI) predictions. Our research aims to identify the challenges of representing and reasoning with drug mechanism knowledge and to evaluate potential informatics solutions to(More)
Members of the W3C Health Care and Life Sciences Interest Group (HCLS IG) have published a variety of genomic and drug-related datasets as Resource Description Framework (RDF) triples. This experience has helped the interest group define a general data workflow for mapping health care and life science (HCLS) data to RDF and linking it with other Linked Data(More)
Whether seizures in the developing brain cause long-term changes in the mature brain has been debated. We tested the hypothesis that a model of early-life seizures, induced by systemic injection of a GABA(B) receptor antagonist CGP56999A in immature rats, decreased GABA(B) receptor-mediated inhibitory postsynaptic currents (IPSCs) in the hippocampus of(More)
The entire drug safety enterprise has a need to search, retrieve, evaluate, and synthesize scientific evidence more efficiently. This discovery and synthesis process would be greatly accelerated through access to a common framework that brings all relevant information sources together within a standardized structure. This presents an opportunity to(More)
We present a new evidence taxonomy that, when combined with a set of inclusion criteria, enable drug experts to specify what their confidence in a drug mechanism assertion would be if it were supported by a specific set of evidence. We discuss our experience applying the taxonomy to representing drug-mechanism evidence for 16 active pharmaceutical(More)
Out-of-date or incomplete drug product labeling information may increase the risk of otherwise preventable adverse drug events. In recognition of these concerns, the United States Federal Drug Administration (FDA) requires drug product labels to include specific information. Unfortunately, several studies have found that drug product labeling fails to keep(More)
We describe a novel experiment that we conducted with the Drug Interaction Knowledge-base (DIKB) to determine which combinations of evidence enable a rule-based theory of metabolic drug-drug interactions to make the most optimal set of predictions. The focus of the experiment was a group of 16 drugs including six members of the HMG-CoA-reductase inhibitor(More)
BACKGROUND Every year, hundreds of thousands of patients experience treatment failure or adverse drug reactions (ADRs), many of which could be prevented by pharmacogenomic testing. However, the primary knowledge needed for clinical pharmacogenomics is currently dispersed over disparate data structures and captured in unstructured or semi-structured(More)
Inadequate representation of evidence and knowledge about potential drug-drug interactions is a major factor underlying disagreements among sources of drug information that are used by clinicians. In this paper we describe the initial steps toward developing a foundational domain representation that allows tracing the evidence underlying potential drug-drug(More)