Using genomics to help predict drug interactions.
This article proposes using genomic information to help tailor the output of a drug interaction program for a patient. This paper focuses on a particular CYP450 enzyme to illustrate adding genomic information to an existing drug interaction database. The data are formatted as an Extensible Markup Language (XML) document. The additional interaction information based on genomics for a patient is added to an XML document using XML tags. The suggestion is to combine specifics about a patient's genome with genomic information in the drug interactions database to increase the accuracy and details of a drug interaction program.
Gardner
Donald
D
The Rockefeller University, Box 74 (Rizack Lab), 1230 York Avenue, New York, NY 10021, USA. gardner@rockefeller.edu
D001189:Aryl Hydrocarbon Hydroxylases / Q000235:genetics; D065731:Cytochrome P-450 CYP2C19; D003628:Database Management Systems; D016208:Databases, Factual; D020000:Decision Support Systems, Clinical; D004347:Drug Interactions / Q000235:genetics*; D004360:Drug Therapy, Computer-Assisted / Q000379:methods*; D020869:Gene Expression Profiling / Q000379:methods; D020022:Genetic Predisposition to Disease / Q000235:genetics; D005820:Genetic Testing / Q000379:methods*; D023281:Genomics / Q000379:methods; D006801:Humans; D019146:Hypermedia; D016247:Information Storage and Retrieval; D019300:Medical Errors / Q000517:prevention & control*; D016347:Medical Records Systems, Computerized; D006899:Mixed Function Oxygenases / Q000235:genetics; D011381:Programming Languages; D012042:Registries
D006899:Mixed Function Oxygenases; D001189:Aryl Hydrocarbon Hydroxylases; C045793:CYP2C19 protein, human; D065731:Cytochrome P-450 CYP2C19