Venetoclax is a pivotal BCL-2 inhibitor, yet its plasma pharmacokinetics (PK) often fail to predict clinical outcomes accurately. Since the pharmacological target is intracellular, plasma concentrations may not reflect actual exposure in Peripheral Blood Mononuclear Cells (PBMCs) or sequestration in erythrocytes (RBCs). We aimed to develop a multi-compartment PK model to quantify the distribution of Venetoclax and its two major metabolites across plasma, RBCs, and PBMCs. Peripheral blood from 15 patients undergoing Venetoclax therapy was collected and processed to separate Plasma, RBCs, and PBMCs. We developed a high-resolution analytical method using a Shimadzu Nexera X3 coupled to a Sciex ZenoTOF 7600 system for simultaneous quantification in all matrices. MATLAB was used to construct a compartmental PK model defining rate constants (kin, kout) for drug transfer between plasma and cellular compartments. The UPLC-QTOF method demonstrated high sensitivity, successfully detecting Venetoclax and metabolites even at low intracellular concentrations. Preliminary data indicate significant partitioning of the parent drug into cellular compartments, suggesting RBCs may act as a drug reservoir. The MATLAB model describes the dynamic equilibrium between plasma fraction and intracellular accumulation. Detailed kinetic parameters, including PBMC-to-plasma accumulation ratios and metabolite impact, will be presented. This study models Venetoclax kinetics simultaneously in plasma, RBCs, and target PBMCs within the same patient cohort. By shifting the focus from plasma TDM to intracellular pharmacokinetics, this approach offers a more precise tool for understanding drug resistance mechanisms and optimizing dosage in precision oncology.