A Time-Dependent Model Describes Methotrexate Elimination and Supports Dynamic Modification of MRP2/ABCC2 Activity

A new pharmacokinetic model of urinary methotrexate to assess adherence in rheumatoid arthritis

BACKGROUND AND OBJECTIVES

Methotrexate (MTX) is the first-line therapy for rheumatoid arthritis (RA). While therapeutic adherence is essential to successful management, no objective MTX assay is currently available. Using population pharmacokinetic modelling (PopPK), our objective was to describe the urinary MTX (MTXu) kinetics in treated patients and to evaluate its abilities to assess the MTX-adherence.

METHODS

The association between urinary methotrexate level and methotrexate administration was assessed using a generalized linear model. Then, a population pharmacokinetic model was developed based on data from 59 patients using with Monolix 2021. R2. Simulations were run to establish a reference kinetic profile and evaluate the proportion of samples predicted as true positives.

RESULTS

Compared to the control group, multivariate analysis showed that MTXu was independently associated with methotrexate administration (p < 0.0001) with a sensitivity and specificity greater than 99%. The final PopPK model selected was a two-compartment model with first-order absorption and elimination. Internal and external validation of the model met all predefined criteria. When using an analytical assay with a LOQ equal to 1 nM, the proportion of samples predicted as true positives is over 90%, as a function of MTX dose (7.5-25 mg/week) and post-administration sampling days (1-7 days).

CONCLUSION

We developed a pharmacokinetic model able to describe expected patterns of urinary methotrexate. This allowed us to propose a new objective test of MTX adherence, which could help in routine practice to differentiate patients who are truly unresponsive to methotrexate from those who are unresponsive because of non-adherence.

Population Pharmacokinetic Model of Methotrexate in Brazilian Pediatric Patients with Acute Lymphoblastic Leukemia

OBJECTIVES

Methotrexate (MTX) is subject to therapeutic drug monitoring because of its high pharmacokinetic variability and safety risk outside the therapeutic window. This study aimed to develop a population pharmacokinetic model (popPK) of MTX for Brazilian pediatric acute lymphoblastic leukemia (ALL) patients who attended the Hospital de Clínicas de Porto Alegre, Brazil.

METHODS

The model was developed using NONMEM 7.4 (Icon®), ADVAN3 TRANS4, and FOCE-I. To explain inter-individual variability, we evaluated covariates from demographic, biochemical, and genetic data (single nucleotide polymorphisms [SNPs] related to the transport and metabolism of drugs).

RESULTS

A two-compartment model was built using 483 data points from 45 patients (0.33-17.83 years of age) treated with MTX (0.25-5 g/m2) in different cycles. Serum creatinine (SCR), height (HT), blood urea nitrogen (BUN) and a low BMI stratification (according to the z-score defined by the World Health Organization [LowBMI]) were added as clearance covariates. The final model described MTX clearance as [Formula: see text]. In the two-compartment structural model, the central and peripheral compartment volumes were 26.8 L and 8.47 L, respectively, and the inter-compartmental clearance was 0.218 L/h. External validation of the model was performed through a visual predictive test and metrics using data from 15 other pediatric ALL patients.

CONCLUSION

The first popPK model of MTX was developed for Brazilian pediatric ALL patients, which showed that inter-individual variability was explained by renal function and factors related to body size.

A Hybrid Algorithm Combining Population Pharmacokinetic and Machine Learning for Isavuconazole Exposure Prediction

OBJECTIVES

Maximum a posteriori Bayesian estimation (MAP-BE) based on a limited sampling strategy and a population pharmacokinetic (POPPK) model is used to estimate individual pharmacokinetic parameters. Recently, we proposed a methodology that combined population pharmacokinetic and machine learning (ML) to decrease the bias and imprecision in individual iohexol clearance prediction. The aim of this study was to confirm the previous results by developing a hybrid algorithm combining POPPK, MAP-BE and ML that accurately predicts isavuconazole clearance.

METHODS

A total of 1727 isavuconazole rich PK profiles were simulated using a POPPK model from the literature, and MAP-BE was used to estimate the clearance based on: (i) the full PK profiles (refCL); and (ii) C24h only (C24h-CL). Xgboost was trained to correct the error between refCL and C24h-CL in the training dataset (75%). C24h-CL as well as ML-corrected C24h-CL were evaluated in a testing dataset (25%) and then in a set of PK profiles simulated using another published POPPK model.

RESULTS

A strong decrease in mean predictive error (MPE%), imprecision (RMSE%) and the number of profiles outside ± 20% MPE% (n-out20%) was observed with the hybrid algorithm (decreased in MPE% by 95.8% and 85.6%; RMSE% by 69.5% and 69.0%; n-out20% by 97.4% and 100% in the training and testing sets, respectively. In the external validation set, the hybrid algorithm decreased MPE% by 96%, RMSE% by 68% and n-out20% by 100%.

CONCLUSION

The hybrid model proposed significantly improved isavuconazole AUC estimation over MAP-BE based on the sole C24h and may improve dose adjustment.

Parametric and Nonparametric Population Pharmacokinetic Models to Assess Probability of Target Attainment of Imipenem Concentrations in Critically Ill Patients

Population pharmacokinetic modeling and simulation (M&S) are used to improve antibiotic dosing. Little is known about the differences in parametric and nonparametric M&S. Our objectives were to compare (1) the external validation of parametric and nonparametric models of imipenem in critically ill patients and (2) the probability of target attainment (PTA) calculations using simulations of both models. The M&S software used was NONMEM 7.2 (parametric) and Pmetrics 1.5.2 (nonparametric). The external predictive performance of both models was adequate for eGFRs ≥ 78 mL/min but insufficient for lower eGFRs, indicating that the models (developed using a population with eGFR ≥ 60 mL/min) could not be extrapolated to lower eGFRs. Simulations were performed for three dosing regimens and three eGFRs (90, 120, 150 mL/min). Fifty percent of the PTA results were similar for both models, while for the other 50% the nonparametric model resulted in lower MICs. This was explained by a higher estimated between-subject variability of the nonparametric model. Simulations indicated that 1000 mg q6h is suitable to reach MICs of 2 mg/L for eGFRs of 90-120 mL/min. For MICs of 4 mg/L and for higher eGFRs, dosing recommendations are missing due to largely different PTA values per model. The consequences of the different modeling approaches in clinical practice should be further investigated.

Evaluation of body-surface-area adjusted dosing of high-dose methotrexate by population pharmacokinetics in a large cohort of cancer patients

Background

The aim of this study was to identify sources of variability including patient gender and body surface area (BSA) in pharmacokinetic (PK) exposure for high-dose methotrexate (MTX) continuous infusion in a large cohort of patients with hematological and solid malignancies.

Methods

We conducted a retrospective PK analysis of MTX plasma concentration data from hematological/oncological patients treated at the University Hospital of Cologne between 2005 and 2018. Nonlinear mixed effects modeling was performed. Covariate data on patient demographics and clinical chemistry parameters was incorporated to assess relationships with PK parameters. Simulations were conducted to compare exposure and probability of target attainment (PTA) under BSA adjusted, flat and stratified dosing regimens.

Results

Plasma concentration over time data (2182 measurements) from therapeutic drug monitoring from 229 patients was available. PK of MTX were best described by a three-compartment model. Values for clearance (CL) of 4.33 [2.95–5.92] L h^− 1 and central volume of distribution of 4.29 [1.81–7.33] L were estimated. An inter-occasion variability of 23.1% (coefficient of variation) and an inter-individual variability of 29.7% were associated to CL, which was 16 [7–25] % lower in women. Serum creatinine, patient age, sex and BSA were significantly related to CL of MTX. Simulations suggested that differences in PTA between flat and BSA-based dosing were marginal, with stratified dosing performing best overall.

Conclusion

A dosing scheme with doses stratified across BSA quartiles is suggested to optimize target exposure attainment. Influence of patient sex on CL of MTX is present but small in magnitude.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08443-x.

Effect of Body Fat on Population Pharmacokinetics of High-Dose Methotrexate in Pediatric Patients With Acute Lymphoblastic Leukemia

Nearly all international regimens for pediatric acute lymphoblastic leukemia (ALL) incorporate intravenous "high-dose" methotrexate (HDMTX, ≥1 g/m² ) to penetrate the central nervous system. Dosing is routinely adjusted for body surface area (BSA), but limited data describe the pharmacokinetics of HDMTX, particularly in obese and/or large patients. To understand the impact of body size (BSA) and body fat percentage (BFP) on HDMTX pharmacokinetics, we performed a secondary analysis of 36 children and adolescents 10-21 years old treated for newly diagnosed ALL and who were enrolled in a prospective study examining body composition. All patients received 5 g/m² of HDMTX infused over 24 hours. Plasma methotrexate concentrations were measured at 24, 42, and 48 hours. At 48 hours, ≥0.4 μmol/L was defined as "delayed elimination," necessitating prolonged supportive care. BFP was measured using dual-energy x-ray absorptiometry. A nonparametric population pharmacokinetic model was constructed with subsequent simulations to explore effects of BSA and BFP extremes. Despite standard BSA-adjusted dosing, we found significant intrapatient variability in mean MTX concentration (38%; range, 1.2%-86%). BSA and BFP were not linearly associated with increased area under the curve (AUC, P = 0.74 and P = 0.12), but both larger size (BSA) and greater obesity (BFP) were associated with an approximately 2-fold higher risk for delayed elimination at 48 hours. HDMTX AUC was not associated with toxicity. MTX pharmacokinetics vary among and even within patients despite BSA-adjusted dosing. Obesity and large size are identified as new risk factors for delayed elimination, requiring further investigation.

Nonparametric Methods in Population Pharmacokinetics

Population pharmacokinetic (PK) modeling is a widely used approach to analyze PK data obtained from groups of individuals, in both industry and academic research. The approach can also be used to analyze pharmacodynamic (PD) data and pooled PK/PD data. There are 2 main families of population PK methods: parametric and nonparametric. The objectives of this article are to present an overview of nonparametric methods used in population pharmacokinetic modeling and to explain their specific characteristics to inform scientists and clinicians about their potential value for data analysis, simulation, dosage design, and therapeutic drug monitoring (TDM). Nonparametric methods have several interesting characteristics for population PK analysis, including computation of exact likelihoods, the ability to accommodate parameter probability distributions of any shape (eg, non-Gaussian), and to detect subpopulations and outliers. Nonparametric population methods are also highly relevant for model-based TDM and design of individualized drug dosage regimens. Several algorithms have been developed to estimate model parameter values within an individual and compute that individual's dosage to achieve target drug exposure with maximum precision and accuracy. Nonparametric modeling methods for both population and individual PK analysis are available under user-friendly packages.

Population Pharmacokinetics of Imipenem in Critically Ill Patients: A Parametric and Nonparametric Model Converge on CKD-EPI Estimated Glomerular Filtration Rate as an Impactful Covariate

BACKGROUND

Population pharmacokinetic (popPK) models for antibiotics are used to improve dosing strategies and individualize dosing by therapeutic drug monitoring. Little is known about the differences in results of parametric versus nonparametric popPK models and their potential consequences in clinical practice. We developed both parametric and nonparametric models of imipenem using data from critically ill patients and compared their results.

METHODS

Twenty-six critically ill patients treated with intravenous imipenem/cilastatin were included in this study. Median estimated glomerular filtration rate (eGFR) measured by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation was 116 mL/min/1.73 m2 (interquartile range 104-124) at inclusion. The usual dosing regimen was 500 mg/500 mg four times daily. On average, five imipenem levels per patient (138 levels in total) were drawn as peak, intermediate, and trough levels. Imipenem concentration-time profiles were analyzed using parametric (NONMEM 7.2) and nonparametric (Pmetrics 1.5.2) popPK software.

RESULTS

For both methods, data were best described by a model with two distribution compartments and the CKD-EPI eGFR equation unadjusted for body surface area as a covariate on the elimination rate constant (Ke). The parametric population parameter estimates were Ke 0.637 h-1 (between-subject variability [BSV]: 19.0% coefficient of variation [CV]) and central distribution volume (Vc) 29.6 L (without BSV). The nonparametric values were Ke 0.681 h-1 (34.0% CV) and Vc 31.1 L (42.6% CV).

CONCLUSIONS

Both models described imipenem popPK well; the parameter estimates were comparable and the included covariate was identical. However, estimated BSV was higher in the nonparametric model. This may have consequences for estimated exposure during dosing simulations and should be further investigated in simulation studies.

Validation of Pharmacological Protocols for Targeted Inhibition of Canalicular MRP2 Activity in Hepatocytes Using [99mTc]mebrofenin Imaging in Rats

The multidrug resistance-associated protein 2 (MRP2) mediates the biliary excretion of drugs and metabolites. [^99mTc]mebrofenin may be employed as a probe for hepatic MRP2 activity because its biliary excretion is predominantly mediated by this transporter. As the liver uptake of [^99mTc]mebrofenin depends on organic anion-transporting polypeptide (OATP) activity, a safe protocol for targeted inhibition of hepatic MRP2 is needed to study the intrinsic role of each transporter system. Diltiazem (DTZ) and cyclosporin A (CsA) were first confirmed to be potent MRP2 inhibitors in vitro. Dynamic acquisitions were performed in rats (n = 5-6 per group) to assess the kinetics of [^99mTc]mebrofenin in the liver, intestine and heart-blood pool after increasing doses of inhibitors. Their impact on hepatic blood flow was assessed using Doppler ultrasound (n = 4). DTZ (s.c., 10 mg/kg) and low-dose CsA (i.v., 0.01 mg/kg) selectively decreased the transfer of [^99mTc]mebrofenin from the liver to the bile (k₃). Higher doses of DTZ and CsA did not further decrease k₃ but dose-dependently decreased the uptake (k₁) and backflux (k₂) rate constants between blood and liver. High dose of DTZ (i.v., 3 mg/kg) but not CsA (i.v., 5 mg/kg) significantly decreased the blood flow in the portal vein and hepatic artery. Targeted pharmacological inhibition of hepatic MRP2 activity can be achieved in vivo without impacting OATP activity and liver blood flow. Clinical studies are warranted to validate [^99mTc]mebrofenin in combination with low-dose CsA as a novel substrate/inhibitor pair to untangle the role of OATP and MRP2 activity in liver diseases.

Pharmacokinetics and pharmacogenetics of high-dose methotrexate in Chinese adult patients with non-Hodgkin lymphoma: a population analysis

PURPOSE

High-dose methotrexate (HD-MTX) is widely used in the treatment of non-Hodgkin lymphoma (NHL), but the pharmacokinetic properties of HD-MTX in Chinese adult patients with NHL have not yet been established through an approach that integrates genetic covariates. The purposes of this study were to identify both physiological and pharmacogenomic covariates that can explain the inter- and intraindividual pharmacokinetic variability of MTX in Chinese adult patients with NHL and to explore a new sampling strategy for predicting delayed MTX elimination.

METHODS

A total of 852 MTX concentrations from 91 adult patients with NHL were analyzed using the nonlinear mixed-effects modeling method. FPGS, GGH, SLCO1B1, ABCB1 and MTHFR were genotyped using the Sequenom MassARRAY technology platform and were screened as covariates. The ability of different sampling strategies to predict the MTX concentration at 72 h was assessed through maximum a posteriori Bayesian forecasting using a validation dataset (18 patients).

RESULTS

A two-compartment model adequately described the data, and the estimated mean MTX clearance (CL) was 6.03 L/h (9%). Creatinine clearance (CrCL) was identified as a covariate for CL, whereas the intercompartmental clearance (Q) was significantly affected by the body surface area (BSA). However, none of the genotypes exerted a significant effect on the pharmacokinetic properties of MTX. The percentage of patients with concentrations below 0.2 µmol/L at 72 h decreased from 65.6 to 42.6% when the CrCL decreased from 90 to 60 ml/min/1.73 m² with a scheduled dosing of 3 g/m², and the same trend was observed with dose regimens of 1 g/m² and 2 g/m². Bayesian forecasting using the MTX concentrations at 24 and 42 h provided the best predictive performance for estimating the MTX concentration at 72 h after dosing.

CONCLUSIONS

The MTX population pharmacokinetic model developed in this study might provide useful information for establishing personalized therapy involving MTX for the treatment of adult patients with NHL.

The Pharmacogenetics of Immune-Modulating Therapy

Immunosuppressive drugs are a prerequisite in organ transplantation to prevent rejection and are also widely used in inflammatory diseases such as inflammatory bowel disease (IBD) or also in some hematologic malignancies-depending on the mode of action. For thiopurine analogs the polymorphic thiopurine S-methyltransferase (TPMT) was early detected to be associated with thiopurine-induced leukopenia; recent studies identified also NUDT15 to be related to this severe side effect. For drugs like methotrexate and mycophenolate mofetil a number of ADME genes like UDP-glucuronosyltransferases (UGTs) and ABC efflux transporters were investigated, however, with partly contradicting results. For calcineurin inhibitors like cyclosporine and in particular tacrolimus however, cytochrome P450 3A4 and 3A5 variants were found to significantly affect the pharmacokinetics. Genetic variants in genes encoding relevant pharmacodynamic proteins, however, lacked compelling evidence to affect the clinical outcome. This chapter reviews the current evidence on the association of pharmacogenetic traits to dose finding and clinical outcome of small-molecule immunosuppressants. Moreover this chapter critically summarizes suitability to apply pharmacogenetics in clinical practice in order to optimize immunosuppressant therapy.