The pharmaceutical sector is increasingly prioritizing the improvement of predictive modeling for human pharmacokinetics (PK) related to drug candidates, aiming to reduce costs and enhance efficiency in research and development. Most of these initiatives have focused on predicting drug absorption after oral administration, which is the preferred method for drug delivery. Despite significant progress in this field, accurately forecasting the fraction of the dose that is absorbed (Fa) continues to pose a considerable challenge. In recent years, multi-compartment and transit models have become increasingly popular because of their effectiveness. However, these models treat the stomach as a single compartment with a fixed pH, which can lead to inaccuracies in estimating the solubilization of basic drugs in the stomach under certain conditions, ultimately resulting in false results. To address the above challenge, a kinetic stomach pH calculator that converts a pH-time profile to a single pH input has been introduced, yet it remains inadequate for drugs with low base pKa values such as quazepam. This article explored the integration of pH-dependent solubility into the stomach compartment on the previously published kinetic model, demonstrating its potential to improve the predictive accuracy regarding the impact of food on quazepam. This innovative method has demonstrated greater effectiveness in assessing the impact of food on basic drugs with low pKa. It is suggested that this revised approach may prove advantageous for all models encountering similar difficulties.