Modeling and dose schedule design for cycle-specific chemotherapeutics

Model-based optimal control has been used to synthesize chemotherapy treatment schedules. Constraints on drug delivery or states are used to maintain drug administration within toxicity limits, and the objective function usually minimizes the tumor volume at a prespecified final time. These solutions predict a characteristic 3-phase treatment profile: maximum initial drug delivery; a non-dosing period; and the remainder of the drug delivered at the end of the treatment window. Ethically, however, a doctor cannot allow a tumor to grow untreated, thereby invalidating the controller formulation. Dose schedule development, therefore, requires an alternative formulation to obtain clinically relevant dosing schedules.;Dose schedule design for the therapeutic tamoxifen (TM) was investigated using nonlinear model predictive control (NMPC) and a tumor regression reference trajectory. Performance was dependent on accurate incorporation of the pharmacodynamic (PD) effect, and the desired trajectory was tracked. The techniques evaluated could be adapted to other therapeutics administered over regular intervals, though alterations to the objective function would be necessary for clinical implementation.;More detailed cell-level tumor growth models were investigated using population balance equations. Individual cell cycle states were included within the model, as were saturating growth rates representative of Gompertzian growth seen from solid tumors. Open-loop simulations involving two cycle specific therapeutics (S- and M-phase active) questioned the simultaneous administration of therapeutics which predicted the largest final tumor volumes. These results require additional investigation, as does the accuracy of the bilinear PD effect structure.;A physiologically-based pharmacokinetic (PBPK) model for systemic docetaxel (Doc) disposition in SCID mice was developed based on collected plasma, tumor, and tissue concentration data. This model was scaled to humans and compared against patient Doc plasma data from several clinical trials as well as Doc plasma predictions from other models in the literature. A low-order neutrophil model from the literature was tailored to patient neutrophil samples from the clinical study. The human-scaled PBPK Doc and neutrophil PD models were combined and used to evaluate Doc regimens from the literature. Finally, a NMPC was synthesized based on the PBPK and PD models and used to develop clinically-relevant dosing regimens under PD constraints.