For many orally administered basic drugs with pH-dependent solubility, concurrent administration with acid-reducing agents (ARAs) can significantly impair their absorption and exposure. In this study, pH-dependent drug-drug interaction (DDI) prediction methods, including in vitro dissolution-permeation chamber (IVDP) and physiologically based pharmacokinetic (PBPK) modeling, were evaluated for their ability to quantitatively predict the clinical DDI observations using 11 drugs with known clinical pH-dependent DDI data. The data generated by IVDP, which consists of a gastrointestinal compartment and a systemic compartment separated by a biomimic membrane, significantly correlated with the clinical DDI observations. The gastrointestinal compartment AUC ratio showed strong correlation with clinical AUC ratio (R=0.72 and P=0.0056), and systemic compartment AUC ratio showed strong correlation with clinical C ratio (R=0.91 and P=0.0003). PBPK models were also developed for the 11 test compounds. The simulations showed that the predictions from PBPK model with experimentally measured parameters significantly correlated with the clinical DDI observations. Future studies are needed to evaluate predictability of Z-factor-based PBPK models for pH-dependent DDI. Overall, these data suggested that the severity of pH-dependent DDI can be predicted by in vitro and in silico methods. Proper utilization of these methods before clinical DDI studies could allow adequate anticipation of pH-dependent DDI, which helps with minimizing pharmacokinetic variation in clinical studies and ensuring every patient with life-threatening diseases receives full benefit of the therapy.