As the prevalence of data accumulation by electronic medical records and personal genomics, the expectation for research and appliance using these clinical big data is increasing. We review the following several reports by our research groups as example for these analyses. In Kyoto University Hospital, the basis for analyzing clinical data extracted from the electronic medical record system has been developed. It is possible to perform powerful analysis by combining electronic medical record data with our “Cyber Oncology” system, in which various data necessary for cancer related research is stored. We analyzed the fluctuation of neutrophil number of cancer patients undergoing chemotherapy by VAR model using the time-series laboratory data. The number of monocytes, which was only empirically known predictor, was shown to be a predictive factor for neutrophil number. In another study, we developed a prediction model for prognosis of cancer patients. Model construction using all combinations of three common laboratory tests resulted that a logistic regression model using serum albumin, lactate dehydrogenase, and neutrophil count can predict mortality within 90 days with high accuracy. The next generation sequencer and its research and clinical application have made great progress in recent years. The establishment of a national database of clinical genome information is being advanced in Japan. In the process of curating the genetic variants, molecular dynamics simulation attracts attention as an analytical method for examining their clinical significance and association with disease mechanisms. We analyzed the structural change of ALK gene by simulation and clarified the mechanism of drug resistance in I1171T mutant. In addition, we showed that brigatinib can bind effectively to EGFR triple mutant, which is refractory to every drug currently available. We further suggested the possibility of modification to the drug molecule structure with higher affinity. As described above, clinical real world data analysis can be a powerful tool in many situations such as mining clinical findings, elucidation of disease mechanisms, or drug discovery.
