Methods for Personalized Drug Effectiveness Prediction in Cancer Precision Medicine
WANG Hongqiang1, GU Kangshen2
1.Precision Medicine and Biomedical Bigdata Laboratory, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei 230031 2.Department of Tumor, The First Affiliated Hospital of Medical University of Anhui, Hefei 230031
Abstract How to efficiently predict individual drug effectiveness is a hot topic of cancer research. In this paper, the way to precisely estimate and predict the effectiveness of targeted-drugs of a specific patient is analyzed by reviewing and examining the basic theory and the development of targeted treatment of cancer. A paradigm of genetic testing, cancerization genetic testing mode, is proposed. Recently developed high-throughput sequencing technique is utilized and molecular pathology of individual patient based on artificial intelligence are systematically analyzed and precisely diagnosed in this mode. The conventional genetic testing paradigm only focuses on mutation detection using low-throughput sequencing technologies with one-sided and seriously biased diagnosis and the shortcoming is overcome by the cancerization testing model with over-simplicity for realizing the precision medicine. Furthermore the clinical practice of the proposed mode is discussed.
Fund:Supported by National Natural Science Foundation of China(No.61402010,61374181), Natural Science Foundation of Anhui Province(No.1408085MF133)
About author:: (WANG Hongqiang(Corresponding author), born in 1977, Ph.D., professor. His research interests include bioinformatics, preci-sion medicine and pattern recognition.)(GU Kangsheng, born in 1964, Ph.D., professor. His research interests include precision medicine, cancer treatment, and personalized medicine.)
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2017, Vol. 30 
