In this study, utilizing the concepts of related work and considering practical aspects of the drug discovery process, we attempted to predict compound brain concentration-time profiles using a model that combines M&S and ML approaches. Regarding M&S, we built a hybrid model that links the plasma concentration-time profile to the brain compartment. The kinetic parameters for the ML component were predicted using random Forest (RF) models. We assumed two practical situations in which the compound plasma concentration-time profiles had already been obtained but without any information regarding the compounds' brain concentrations or the situation in which limited information is available (i.e., the brain concentration at one time point). Figure shows an example of the flow of early ADME screening for CNS drugs. In the early (i.e., hit to lead) stage before an in vivo brain PK study is conducted, a PK study of plasma is performed. Using promising compounds, an in vivo brain PK study is then performed with a limited number of sampling time points due to the high cost of such a study, accompanied by brain protein-binding assays. Consequently, we believe practical predictive models of brain concentration-time profiles for drug discovery should be built using in vivo brain data obtained under limited conditions. It should be noted that a full plasma PK study is performed before a brain PK study. The cassette dosing PK are frequently used; however, single dosing PK could replace in the later stage.