Population Pharmacokinetic Modeling of Selinexor in Multiple Myeloma Patients with Chronic Kidney Disease, Including End-Stage Renal Disease.

다국어 초록 (Multilingual Abstract)

Population Pharmacokinetic Modeling of Selinexor in Multiple Myeloma Patients with Chronic Kidney Disease, Including End-Stage Renal Disease.

To optimize the dosing regimen of selinexor in renal impairment patients with multiple myeloma, we characterized its pharmacokinetic properties. We utilized a modeling and simulation (M&S) tool, especially for unexplored end-stage renal disease (ESRD) patients. Our findings provide insights into appropriate dose adjustments and strategies for managing selinexor treatment in patients with renal impairment, particularly those with ESRD, to ensure safety and efficacy. A prospective, investigator-initiated study was conducted to optimize selinexor dosing in relapsed or refractory multiple myeloma (RRMM) patients with renal impairment, including those with ESRD. Selinexor was co-administered with dexamethasone, and pharmacokinetic (PK) analysis was performed using nonlinear mixed-effects modeling (NONMEM) to evaluate covariates influencing PK parameters. Simulations were conducted to identify appropriate dosing for renal-impaired patients to achieve PK targets comparable to those in patients with normal renal function. A two-compartment model best described the data. Clearance and central and peripheral volume of distribution were allometrically scaled by total body weight. Total protein concentration significantly improved model prediction. (p-value <0.001) The simulation was performed using a standard regimen and compared by the Chronic Kidney Disease (CKD) stage. PK simulations indicated that the standard 80 mg selinexor regimen achieved pharmacokinetic exposure comparable to that observed in patients with normal renal function, suggesting that dose adjustment is unnecessary for patients with renal impairment. Lower doses (40 mg, 60 mg) were found to provide subtherapeutic exposure. The study found no significant correlation between selinexor exposure and renal function markers (serum creatinine, eGFR), with body weight and serum protein levels being the key predictors of drug clearance. Though renal impairment, including ESRD, did not directly affect exposure, comorbidities like proteinuria and weight fluctuations in CKD patients could influence drug levels. Taken together, this research highlights the importance of physiological factors, such as serum protein and body weight, influencing selinexor exposure in renal impairment patients.

목차 (Table of Contents)

• Abstract
• 1. Introduction
• 2. Materials and Methods
• 1) Patient population
• 2) Drug administration
• 3) Sampling time
• 4) Pharmacokinetic bioanalytical method
• 5) Modeling software
• 6) Population pharmacokinetic analysis
• 3. Results
• 1) Patient characteristics and observed data
• 2) Population pharmacokinetic analysis
• 3) Simulation-based optimization of dosing regimen
• 4) Unbound fraction of selinexor in CKD patients
• 4. Discussion
• 5. Conclusion
• 6. References
• Table Contents
• Table 1.
• Baseline characteristics of study patients
• Table 2.
• Final population pharmacokinetic model parameters
• Figure Contents
• Figure 1.
• The goodness-of-fit plot of the final pharmacokinetic model
• Figure 2.
• Visual predictive checks
• Figure 3.
• Comparison with FDA reported results
• Figure 4.
• Unbound fraction of selinexor
• Figure 5.
• Exposure of selinexor by renal function