Population pharmacokinetics of lenalidomide in patients with B‐cell malignancies

Hughes, Jim H.; Phelps, Mitch A.; Upton, Richard N.; Reuter, Stephanie E; Gao, Yue; Byrd, John C.; Grever, Michael R.; Hofmeister, Craig C.; Marcucci, Guido; Blum, William; Blum, Kristie A.; Foster, David J. R.

doi:10.1111/bcp.13873

Cited by 10 publications

(16 citation statements)

References 44 publications

(51 reference statements)

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“…The equations describing CL/F, Vc/F, Vp/F, and Q/F parameters for the i‐th individual are listed below:

\begin{matrix} true \\ left normalCL / F_{i} = 6.27 \times {(\frac{BWT}{70})}^{0.75} \\ left \times ((), 1 - 0.173 \cdot normalCY P_{moderate}) \\ left \times ((), 1 - 0.303 \cdot normalCY P_{strong}) \\ left \times {(\frac{WNCL}{71.23})}^{0.406} \times ((), 1 - 0.004 ((), normalBPBL - 38.20)) \end{matrix}

{normalV}_{normalc} / {normalF}_{i} = 3.32 \times {((), \frac{normalBWT}{70})}^{1}

{normalV}_{normalp} / {normalF}_{i} = 279.21 \times {((), \frac{normalBWT}{70})}^{1} \times (1 - 0.825 \cdot Solid)

Q / {normalF}_{i} = 1.29 \times {((), \frac{normalBWT}{70})}^{0.75} \times (1 - 0.653 \cdot Solid)

wherein BPBL is baseline percentage bone marrow blasts, BWT is baseline body weight, and WNCL is weight‐standardized CR CL . In line with other oral oncology drugs, the residual variability for both hematologic and solid tumor patients was around 60% to 70% despite inclusion of covariates …”

Section: Resultssupporting

confidence: 58%

“…In line with other oral oncology drugs, the residual variability for both hematologic and solid tumor patients was around 60% to 70% despite inclusion of covariates. [17][18][19][20][21] Prediction-based diagnostic plots showed good agreement between model predictions and observed concentrations (Figure 2, Supplemental Figure S2). The final model described the data without any obvious bias in residual error over time and concentration (Figure 2).…”

Section: Covariate Analyses and Final Modelmentioning

confidence: 99%

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Population Pharmacokinetics of Glasdegib in Patients With Advanced Hematologic Malignancies and Solid Tumors

Lin

Shaik

Martinelli

et al. 2019

The Journal of Clinical Pharma

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Glasdegib is an inhibitor of the Hedgehog pathway recently approved in the United States for the treatment of acute myeloid leukemia. A population pharmacokinetic analysis was conducted to characterize the kinetic behavior of glasdegib and its sources of variability (covariates) by utilizing data from 269 patients with cancer treated with oral glasdegib doses ranging from 5 to 640 mg/d. Nonlinear mixed-effects modeling was conducted using NONMEM (v.7.3) and Perl-speaks NONMEM (v.4.2.0). The estimated apparent total clearance, apparent central volume of distribution, and apparent peripheral volume of distribution were 6.27 L/h, 3.32 L, and 279.2 L, respectively. Age, sex, race, and hepatic function were not significant covariates on glasdegib pharmacokinetic parameters. Baseline body weight, percentage bone marrow blasts, creatinine clearance, and use of moderate or strong cytochrome P450 3A inhibitors were statistically significant covariates on apparent total clearance; however, the magnitude of the effects was not considered clinically meaningful.

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“…The equations describing CL/F, Vc/F, Vp/F, and Q/F parameters for the i‐th individual are listed below:

\begin{matrix} true \\ left normalCL / F_{i} = 6.27 \times {(\frac{BWT}{70})}^{0.75} \\ left \times ((), 1 - 0.173 \cdot normalCY P_{moderate}) \\ left \times ((), 1 - 0.303 \cdot normalCY P_{strong}) \\ left \times {(\frac{WNCL}{71.23})}^{0.406} \times ((), 1 - 0.004 ((), normalBPBL - 38.20)) \end{matrix}

{normalV}_{normalc} / {normalF}_{i} = 3.32 \times {((), \frac{normalBWT}{70})}^{1}

{normalV}_{normalp} / {normalF}_{i} = 279.21 \times {((), \frac{normalBWT}{70})}^{1} \times (1 - 0.825 \cdot Solid)

Q / {normalF}_{i} = 1.29 \times {((), \frac{normalBWT}{70})}^{0.75} \times (1 - 0.653 \cdot Solid)

Section: Resultssupporting

confidence: 58%

Section: Covariate Analyses and Final Modelmentioning

confidence: 99%

Population Pharmacokinetics of Glasdegib in Patients With Advanced Hematologic Malignancies and Solid Tumors

Lin

Shaik

Martinelli

et al. 2019

The Journal of Clinical Pharma

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“…The PPK parameters included the apparent clearance (CL/F), volume of distribution (V/F) and absorption rate constant Ka. Due to the limit of plasma concentration data collected in this study, the value of Ka could not be robustly estimated, and thus Ka was fixed at 6.55 h −1 based on existing lenalidomide PPK studies 23 – 25 .…”

Section: Resultsmentioning

confidence: 99%

“…Therefore, population pharmacokinetic (PPK) studies on lenalidomide are needed to identify factors contributing to interpatient PK differences, thus refining regimens to mitigate its adverse reactions. Yet hardly any of the current PPK studies has included as a covariate the genetic polymorphism of the ABCB1 gene 22 – 25 , we utilize a nonlinear mixed-effects model (NONMEM) to conduct a PPK study on lenalidomide in Chinese patients incorporating the genotypes of ABCB1 3435 C > T (rs1045642), ABCB1 1236 A > G (rs1128503) and ABCB1 2677 A > C/T (rs2032582) which have high variant frequencies in the Chinese population in the hope of optimizing the clinical application of lenalidomide 26 .…”

Section: Introductionmentioning

confidence: 99%

Population pharmacokinetics of lenalidomide in Chinese patients with influence of genetic polymorphisms of ABCB1

Liang,

Shi,

et al. 2024

Sci Rep

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Affected by differences in the pharmacokinetics (PK) of lenalidomide, the toxicity of lenalidomide varies among different patients, with serious toxicity leading to dose reduction or discontinuation. The differences in the PK of lenalidomide may be related to factors such as patients’ physiological characteristics, pathological characteristics and gene polymorphisms etc., which may also affect its toxicity. The aim of this study is to establish a population pharmacokinetic (PPK) model of lenalidomide and explore factors associated with the adverse events (AEs) of lenalidomide from a PK perspective. Blood samples were collected by opportunistic blood collection. Drug concentrations were determined by using HPLC/MS and genotype of ABCB1 3435 C > T (rs1045642), ABCB1 1236 A > G (rs1128503) and ABCB1 2677 A > C/T (rs2032582) was tested by the first-generation DNA sequencing technology. NONMEM software and SPSS 26.0 software were used respectively to establish PPK model of lenalidomide and explore the correlation between PK parameters and the incidence of serious AEs of lenalidomide. 51 patients were enrolled in the PPK study, and one-compartment model with first-order absorption and elimination agreed well with the observed data. The significant covariate affecting lenalidomide apparent volume of distribution (V/F) were the gene polymorphism of ABCB1 3435 C > T and diet. Safety studies could be conducted in 39 patients. The V/F value in patients suffering from serious AEs was significantly higher than that in others ( median = 67.04 L vs 37.17 L, P = 0.033). According to the covariates screened, the incidence of serious AEs was higher in patients with genotype CT or TT at ABCB1 3435 C > T locus than that in patients with genotype CC (P = 0.039). Additionally, V/F value was the highest in patients carrying genotype TT with postprandial medication, in whom the incidence of serious AEs was higher than others (P = 0.037). In conclusion, the genotype of ABCB1 3435 C > T locus and diet had pharmacokinetically relevant impact on lenalidomide, which may also be related to the incidence of serious AEs. Patients with gene variants of CT or TT at ABCB1 3435 C > T locus may be more susceptible to serious AEs, and monitoring of adverse reactions should be particularly strengthened in patients who carried genotype TT with postprandial medication.

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“…Population pharmacokinetic (PopPK) modelling enables parameter estimation and concentration time-course prediction for both the study population and individual subjects simultaneously [12]. Understanding the pharmacokinetics and pharmacodynamics of tramadol and ODT after an extended release oral dosing may aid appropriate use in older patients regarding appropriate drug selection and dosing [13].…”

Section: Introductionmentioning

confidence: 99%

Population Pharmacokinetic Model for Tramadol and O-desmethyltramadol in Older Patients

Al-Qurain

Upton

Tadros

et al. 2022

Eur J Drug Metab Pharmacokinet

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Background and ObjectivesTramadol is commonly prescribed to manage chronic pain in older patients. However, there is a gap in the literature describing the pharmacokinetic parameters for tramadol and its active metabolite (O-desmethyltramadol [ODT]) in this population. The objective of this study was to develop and evaluate a population pharmacokinetic model for tramadol and ODT in older patients. Methods Twenty-one patients who received an extended-release oral tramadol dose (25-100 mg) were recruited. Tramadol and ODT concentrations were determined using a validated liquid chromatography/tandem mass spectrometry method. A population pharmacokinetic model was developed using non-linear mixed-effects modelling. The performance of the model was assessed by visual predictive check. Results A two-compartment, first-order absorption model with linear elimination best described the tramadol concentration data. The absorption rate constant was 2.96/h (between-subject variability [BSV] 37.8%), apparent volume of distribution for the central compartment (V 1 /F) was 0.373 l (73.8%), apparent volume of distribution for the peripheral compartment (V 2 /F) was 0.379 l (97.4%), inter-compartmental clearance (Q) was 0.0426 l/h (2.19%) and apparent clearance (CL/F) was 0.00604 l/h (6.61%). The apparent rate of metabolism of tramadol to ODT (k t ) was 0.0492 l/h (78.5%) and apparent clearance for ODT (CL m ) was 0.143 l/h (21.6%). Identification of Seniors at Risk score (ISAR) and creatinine clearance (CrCL) were the only covariates included in the final model, where a higher value for the ISAR increased the maximum concentration (C max ) of tramadol and reduced the BSV in Q from 4.71 to 2.19%. A higher value of CrCL reduced tramadol C max and halflife (T 1/2 ) and reduced the BSV in V 2 /F (from 148 to 97.4%) and in CL/F (from 78.9 to 6.61%). Conclusion Exposure to tramadol increased with increased frailty and reduced CrCL. Prescribers should consider patients frailty status and CrCL to minimise the risk of tramadol toxicity in such cohort of patients.

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Population pharmacokinetics of lenalidomide in patients with B‐cell malignancies

Cited by 10 publications

References 44 publications

Population Pharmacokinetics of Glasdegib in Patients With Advanced Hematologic Malignancies and Solid Tumors

Population Pharmacokinetics of Glasdegib in Patients With Advanced Hematologic Malignancies and Solid Tumors

Population pharmacokinetics of lenalidomide in Chinese patients with influence of genetic polymorphisms of ABCB1

Population Pharmacokinetic Model for Tramadol and O-desmethyltramadol in Older Patients

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