1. This study optimized the reported approach for the prediction of drug-drug interactions (DDIs) using hepatocytes suspended in serum (HHSS) and provided a practical usage of HHSS in the early and late phases of drug discovery. 2. First, the IC50 was determined using HHSS and evaluated as a qualitative index for DDI risks in the early phase. A retrospective study on clinical DDI cases revealed that inhibitors with IC50 < 100 μmol/L caused clinical DDIs while those with IC50 > 100 μmol/L showed weak or no potential for DDIs. Meanwhile, a pragmatic cutoff value could not be determined using previously reported Ki values of recombinant human cytochrome P450s. 3. Second, for a more substantial DDI risk assessment in the later phase, quantitative predictions of clinical DDI based on a static model were attempted by optimizing the most appropriate inhibitor concentration ([I]). The use of hepatic input plasma concentrations as a surrogate for [I] achieved the most successful predictions of the magnitude of increase in the AUC (within a 2-fold range of the observed values for 93.8% of inhibitors). 4. Through this study, we proposed the practical application of HHSS for an effective workflow to explore and profile candidates with less DDI liability.