Semimechanistic Bone Marrow Exhaustion Pharmacokinetic/Pharmacodynamic Model for Chemotherapy-Induced Cumulative Neutropenia

Abstract

Paclitaxel is a commonly used cytotoxic anticancer drug with potentially life-threatening toxicity at therapeutic doses and high interindividual pharmacokinetic variability. Thus, drug and effect monitoring is indicated to control dose-limiting neutropenia. Joerger et al. (2016) developed a dose individualization algorithm based on a pharmacokinetic (PK)/pharmacodynamic (PD) model describing paclitaxel and neutrophil concentrations. Furthermore, the algorithm was prospectively compared in a clinical trial against standard dosing (Central European Society for Anticancer Drug Research Study of Paclitaxel Therapeutic Drug Monitoring; 365 patients, 720 cycles) but did not substantially improve neutropenia. This might be caused by misspecifications in the PK/PD model underlying the algorithm, especially without consideration of the observed cumulative pattern of neutropenia or the platinum-based combination therapy, both impacting neutropenia. This work aimed to externally evaluate the original PK/PD model for potential misspecifications and to refine the PK/PD model while considering the cumulative neutropenia pattern and the combination therapy. An underprediction was observed for the PK (658 samples), the PK parameters, and these parameters were re-estimated using the original estimates as prior information. Neutrophil concentrations (3274 samples) were overpredicted by the PK/PD model, especially for later treatment cycles when the cumulative pattern aggravated neutropenia. Three different modeling approaches (two from the literature and one newly developed) were investigated. The newly developed model, which implemented the bone marrow hypothesis semiphysiologically, was superior. This model further included an additive effect for toxicity of carboplatin combination therapy. Overall, a physiologically plausible PK/PD model was developed that can be used for dose adaptation simulations and prospective studies to further improve paclitaxel/carboplatin combination therapy.

Pharmacokinetic–pharmacodynamic modelling of neutrophil response to G‐CSF in healthy subjects and patients with chemotherapy‐induced neutropenia

“…This was not unexpected because the effect of neutrophils on filgrastim or pegfilgrastim disposition was based on a drug receptor-binding model, and the turnover of targetcarrying neutrophils (piecemeal degranulation) and the chemotherapy and corticosteroid effects were represented by KPD-type models. For both filgrastim and pegfilgrastim, the value for k tr and estimates for k c , k int and K D , as well as the linear elimination components and distribution volumes, were consistent with estimates from previous G-CSF mimetics ANC dynamics modelling reports [8,[30][31][32]. After correction for bioavailability factors (0.65 vs. 1), the volume of distribution (V D /F) was higher (8.3 vs. 3.1 l), and the clearance slightly lower (0.57 vs. 0.83 l h -1 ) for pegfilgrastim compared with filgrastim.…”

“…For both filgrastim and pegfilgrastim, the value for k tr and estimates for k c , k int and K D , as well as the linear elimination components and distribution volumes, were consistent with estimates from previous G‐CSF mimetics ANC dynamics modelling reports . After correction for bioavailability factors (0.65 vs .…”

Bayesian Data Assimilation to Support Informed Decision Making in Individualized Chemotherapy

“…The first scenario served to demonstrate the limitations of MAP‐based estimations for the gold‐standard model, however, the model does not account for the observed cumulative neutropenia over multiple cycles. Therefore, we considered for dose adaptations a model accounting for bone marrow exhaustion over multiple cycles, see paragraph about the multiple cycle study paclitaxel. We exemplarily considered the dose selection for the third treatment cycle based on prior information and patient‐specific measurements during the first two cycles.…”

“…7,21 Because recursive data processing and decision-support gain in relevance for long-term monitoring, we performed a simulation study for multiple cycle therapy with paclitaxel using the NLME model in ref. 9. It describes the effect of the anticancer drug paclitaxel (200 mg/m 2 , 3-hour infusion) over six cycles of 3 weeks each, corresponding to treatment arm A of the CEPAC/TDM study.…”

“…7) using the gold‐standard model for neutropenia . Further, we compare the full Bayesian approaches regarding quality of uncertainty quantification and computational runtime for multiple cycle chemotherapy . Although MCMC, SIR, and PF all provide a reliable uncertainty quantification, the efficient data processing of the sequential approach will be clearly beneficial in a continuous monitoring context, where digital healthcare devices (e.g., wearables) allow patients to measure and report individual marker concentrations online.…”