%0 Journal Article
%T A useful tool for drug interaction evaluation: The University of Washington Metabolism and Transport Drug Interaction Database
%A Houda Hachad
%A Isabelle Ragueneau-Majlessi
%A Ren¨¦ H Levy
%J Human Genomics
%D 2010
%I BioMed Central
%R 10.1186/1479-7364-5-1-61
%X Adverse drug reactions (ADRs) remain one of the leading causes of morbidity and mortality in healthcare. In January 2000 the Institute of Medicine reported that between 44,000 and 98,000 deaths occur annually from medical errors in American hospitals [1]. Of this total, an estimated 7,000 deaths occur due to ADRs. It is estimated that drug-drug interactions (DDIs) represent 3-5 per cent of all in-hospital medication errors and that they are also an important cause of patient visits to emergency departments [2] Among the factors that contribute to the occurrence of a DDI are patient age, number and type of concomitant medications and disease stage. In recent years, while healthcare providers have been offered access to and have benefitted from numerous drug information tools that have provided them with guidance on how drugs can be co-administered, researchers within the drug development community have had access to a more limited portfolio of data repositories. These scientists need to browse the vast literature for primary scientific data (ie datasets on metabolic isozymes, transporters, substrates, inducers, and inhibitors) that will provide them with context for their research findings and help with their drug interaction programme.The University of Washington's Metabolism and Transport Drug Interaction Database (DIDB; http://www.druginteractioninfo.org webcite) was initially designed with extensive input from scientists from pharmaceutical companies and was tailored to their various needs. Later, the tool capabilities were expanded and its use was extended to other groups (Table 1).The database contains in vitro and in vivo kinetics information for drug-metabolising enzymes and transporters, pharmacokinetics parameters/pharma-codynamic measures and side effects reported in clinical drug interaction studies. Each dataset integrates both the experimental design and the primary results. The database can be searched not only by main concepts in the field of drug int
%K drug-drug interactions
%K database
%K metabolism
%K transporters
%K cytochrome P450 enzymes
%U http://www.humgenomics.com/content/5/1/61