|
KMID : 0365220120490020071
|
|
Korean Journal of Public Health
2012 Volume.49 No. 2 p.71 ~ p.77
|
|
|
Overview of the Prediction of New Indication from Large-Scale Pharmacological Datausing Computational Modeland ItsRationality
|
|
Lee Young-Mee
Son Hyeon-Seok
|
|
|
Abstract
|
|
|
|
Off-label use is the novel utilization of drugs for indications other than what the clinical trial set out to prove; these new indications are often discovered in post-marketing clinical trials or as side effects. Proving the new use, however, warrants large investments in terms of effort, time, and capital. Moreover, limitation on clinical trials proves to be a hindrance in proving the efficacy at all. Because it is time consuming and capital-intensive to invent a new drug to treat certain conditions, pharmaceutical companies usually necessitate a suitable drug candidate based on its characteristics instead of testing completely new structures. It would greatly save resources and increase the success rate significantly for the pharmaceutical companies to systematically apply predicted indications obtained using bioinformatics to the primary selection process. This approach using bioinformatics can also be applied to off-label drugs when clinical trials cannot be carried out to serve as one of the supports for unlabeled use. New indications are currently actively being predicted in bioinformatics for the above reasons; the extent and the methods used for the predictions were observed. The research done through computerized algorithms that use existing database of biomedical information on these off-label uses as found on PubMed are studied and evaluated in terms of its methods and extent.
|
|
|
KEYWORD
|
|
|
bioinformatic drug, drug repositioning, prediction of new indication, off-label use
|
|
|
FullTexts / Linksout information
|
|
|
|
|
|
Listed journal information
|
|
|
|