Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Wertheim cung cấp cho các bạn kiến thức về ngành y đề tài:Predicting drug side-effects by chemical systems biology. | X Genome Biology Minireview Predicting drug side-effects by chemical systems biology Nicholas P Tatonetti Tianyun Liut and Russ B Altmanrt Addresses Training Program in Biomedical Informatics fDepartment of Bioengineering Stanford University iDepartment of Genetics Stanford University Stanford CA 94305 USA. Correspondence Russ B Altman. Email Abstract New approaches to predicting ligand similarity and protein interactions can explain unexpected observations of drug inefficacy or side-effects. Drug-related adverse events affect approximately 2 million patients in the United States each year resulting in about 100 000 deaths 1 . For example highly publicized cases of severe adverse reactions recently resulted in a US Food and Drug Administration advisory panel suggesting that the popular pain relievers Percocet and Vicodin be banned 2 . Some adverse events are predictable consequences of the known mechanism of a drug but others are not predicted and seem to result from off-target pathways. When developing novel chemical entities NCEs for a therapeutic application knowledge of binding partners and affected biological pathways is useful for predicting both efficacy and side-effects. Traditional drug design has relied heavily on the one drug-one target paradigm 3 but this may overlook system-wide effects that cause the drug to be unsuccessful. Adverse side-effects and lack of efficacy are the two most important reasons a drug will fail clinical trials each accounting for around 30 of failures 3 . The development of tools that can predict adverse events and system-wide effects might thus reduce the attrition rate. Such tools will most certainly include emerging information about protein-protein interactions signaling pathways and pathways of drug action and metabolism. A systems view of the body s responses to a drug threatens the simplicity of the one drug-one target paradigm but could provide a framework for considering all effects and not just
