When predicting the effects of medication for psychiatric diseases and their side effects based on genetic information, there are many things to consider besides just genetic information, including the index to be evaluated. We have shown before that it is important to simultaneously analyze both pharmacokinetic factors such as the blood concentration and pharmacodynamic factors such as the site of drug action, when searching for genetic information that can be used to predict the treatment effects of fluvoxamine for depression and its side effects. For example, we have shown that there exists a specific concentration that can be used to predict remission in the treatment of depression with fluvoxamine (Fukui et al, 2008); however, it is considered that without a sufficient examination of such factors besides genetic information, it is difficult to predict the effects using just genetic information. On the other hand, the situation is more complex with medication for schizophrenia. Although it appears that consensus has been obtained in that the goal of medication for depression is remission, the goal of medication for schizophrenia is not clear and it cannot be said that prediction studies on the effects have been sufficiently conducted using genetic information. Therefore, at our facility, focusing on metabolic anomalies due to antipsychotics, QT prolongation, and hyperprolactinemia, which have become issues in recent years, a prediction study on side effects was conducted. Because such side effects can be quantified, in comparison with the effects study, it is advantageously simple to examine the relationship with genetic information. However, in the course of this study, we discovered that there was a gender difference in terms of glycolipid metabolic anomalies, that antipsychotics particularly extended the QT interval during nighttime, and that prolactine following the administration of antipsychotics temporally increased before declining again a few weeks later. We believe that when examining the relationship between side effects and genetic information, the genetic information may not be sufficiently utilized unless the analysis is performed after obtaining a better understanding of the characteristics of such side effects.