AIMC Topic: Drug Interactions

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Drug-drug Interaction Discovery Using Abstraction Networks for "National Drug File - Reference Terminology" Chemical Ingredients.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The National Drug File - Reference Terminology (NDF-RT) is a large and complex drug terminology. NDF-RT provides important information about clinical drugs, e.g., their chemical ingredients, mechanisms of action, dosage form and physiological effects...

Text mining for pharmacovigilance: Using machine learning for drug name recognition and drug-drug interaction extraction and classification.

Journal of biomedical informatics
Pharmacovigilance (PV) is defined by the World Health Organization as the science and activities related to the detection, assessment, understanding and prevention of adverse effects or any other drug-related problem. An essential aspect in PV is to ...

Connecting proteins with drug-like compounds: Open source drug discovery workflows with BindingDB and KNIME.

Database : the journal of biological databases and curation
Today's large, public databases of protein-small molecule interaction data are creating important new opportunities for data mining and integration. At the same time, new graphical user interface-based workflow tools offer facile alternatives to cust...

Learning the Structure of Biomedical Relationships from Unstructured Text.

PLoS computational biology
The published biomedical research literature encompasses most of our understanding of how drugs interact with gene products to produce physiological responses (phenotypes). Unfortunately, this information is distributed throughout the unstructured te...

Gene Ontology and KEGG Pathway Enrichment Analysis of a Drug Target-Based Classification System.

PloS one
Drug-target interaction (DTI) is a key aspect in pharmaceutical research. With the ever-increasing new drug data resources, computational approaches have emerged as powerful and labor-saving tools in predicting new DTIs. However, so far, most of thes...

Toward a complete dataset of drug-drug interaction information from publicly available sources.

Journal of biomedical informatics
Although potential drug-drug interactions (PDDIs) are a significant source of preventable drug-related harm, there is currently no single complete source of PDDI information. In the current study, all publically available sources of PDDI information ...

Extracting drug-drug interactions from literature using a rich feature-based linear kernel approach.

Journal of biomedical informatics
Identifying unknown drug interactions is of great benefit in the early detection of adverse drug reactions. Despite existence of several resources for drug-drug interaction (DDI) information, the wealth of such information is buried in a body of unst...

Functional evaluation of out-of-the-box text-mining tools for data-mining tasks.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The trade-off between the speed and simplicity of dictionary-based term recognition and the richer linguistic information provided by more advanced natural language processing (NLP) is an area of active discussion in clinical informatics. ...

Modeling analgesic drug interactions using support vector regression: a new approach to isobolographic analysis.

Journal of pharmacological and toxicological methods
BACKGROUND: Modeling drug interactions is important for illustrating combined drug actions and for predicting the pharmacological and/or toxicological effects that can be obtained using combined drug therapy.

Taco-DDI: accurate prediction of drug-drug interaction events using graph transformer-based architecture and dynamic co-attention matrices.

Neural networks : the official journal of the International Neural Network Society
Drug-drug interactions (DDIs) are critical in pharmaceutical research, as adverse interactions can pose significant risks for patient treatment plans. Accurate prediction of DDI events risk levels can provide valuable guidance for designing safer and...