Predictors for drug effects with brain disease: Shed new light from EEG parameters to brain connectomics
Predictors for drug effects with brain disease: Shed new light from EEG parameters to brain connectomics
复制标题
药物对脑部疾病影响的预测因素：从脑电图参数到脑连接组学提供新的线索
DOI：
10.1016/j.ejps.2017.04.019
复制
发表时间：
2017
影响因子：
4.6
通讯作者：
Xu Peng
中科院分区：
文献类型：
--
作者：
Tian Yin;Yang Li;Xu Wei;Zhang Huiling;Wang Zhongyan;Zhang Haiyong;Zheng Shuxing;Shi Yupan;Xu Peng
Though researchers spent a lot of effort to develop treatments for neuropsychiatric disorders, the poor translation of drug efficacy data from animals to human hampered the success of these therapeutic approaches in human. Pharmaceutical industry is challenged by low clinical success rates for new drug registration. To maximize the success in drug development, biomarkers are required to act as surrogate end points and predictors of drug effects. The pathology of brain disease could be in part due to synaptic dysfunction. Electroencephalogram (EEG), generating from the result of the postsynaptic potential discharge between cells, could be a potential measure to bridge the gaps between animal and human data. Here we discuss recent progress on using relevant EEG characteristics and brain connectomics as biomarkers to monitor drug effects and measure cognitive changes on animal models and human in real-time. It is expected that the novel approach, i.e. EEG connectomics, will offer a deeper understanding on the drug efficacy at a microcirculatory level, which will be useful to support the development of new treatments for neuropsychiatric disorders.
