Consequently, in the practical drug discovery stage, DMPK (drug metabolism and pharmacokinetics) researchers usually investigate brain to plasma partition coefficients or unbound fraction of Kp,brain (Kp,uu,brain) in candidates. In order to obtain Kp,brain values, in vivo animal pharmacokinetic (PK) studies are performed in which the concentrations of compounds in plasma and brain are measured at one or a few time points; for Kp,uu,brain, the in vitro unbound fractions of compounds in plasma (fu,p) and brain (fu,br) are also needed . Although in vitro studies can be performed for thousands of compounds, in vivo studies in animals are not preferred from the viewpoint of animal welfare and cost. Based on these practical necessities, in silico methods for the prediction of Kp,brain or Kp,uu,brain with high accuracy have been published recently by many groups. For example, Kp,brain, a tissue partition coefficient, can be predicted using a tissue composition-based algorithm ; Kp,brain can be predicted as a target of objective variables in machine learning models ; Kp,uu, brain can be predicted as a target of objective variables in machine learning models ; and Kp,uu, brain can be calculated from predicted Kp,brain, fu,p, and fu,br values .