MTXPK.org: A Clinical Decision Support Tool Evaluating High-Dose Methotrexate Pharmacokinetics to Inform Post-Infusion Care and Use of Glucarpidase

Understanding hemoglobin contribution to high-dose methotrexate disposition-population pharmacokinetics in pediatric patients with hematological malignancies

PURPOSE

The aim of the present study was to develop a population pharmacokinetic model for methotrexate (MTX) during high-dose treatment (HDMTX) in pediatric patients with acute lymphoblastic leukemia (ALL) and non-Hodgkin's lymphoma (NHL) and to describe the influence of variability factors.

METHODS

The study included 50 patients of both sexes (aged 1-18 years) who received 3 or 5 g/m2 of HDMTX. A nonlinear mixed effect modeling approach was applied for data analysis. Parameter estimation was performed by first-order conditional estimation method with interaction (FOCEI), whereas stepwise covariate modeling was used to assess variability factors.

RESULTS

The final model is a two-compartment model that incorporates the effect of body surface area and the influence of hemoglobin and serum creatinine on MTX clearance (CL). Population pharmacokinetic values for a typical subject were estimated at 5.75 L/h/m2 for clearance (CL), 21.3 L/m2 for volume of the central compartment (V1), 8.2 L/m2 for volume of the peripheral compartment (V2), and 0.087 L/h/m2 for intercompartmental clearance (Q). According to the final model, MTX CL decreases with increasing serum creatinine, whereas a positive effect was captured for hemoglobin. A difference of almost 32% in MTX CL was observed among patients' hemoglobin values reported in the study.

CONCLUSION

The developed population pharmacokinetic model can contribute to the therapy optimization during HDMTX in pediatric patients with ALL and NHL. In addition to renal function and body weight, it describes the influence of hemoglobin on CL, allowing better understanding of its contribution to the disposition of HDMTX.

Population pharmacokinetic analyses of methotrexate in pediatric patients: a systematic review

BACKGROUND AND OBJECTIVES

Methotrexate is widely utilized in the chemotherapy of malignant tumors and autoimmune diseases in the pediatric population, but dosing can be challenging. Several population pharmacokinetic models were developed to characterize factors influencing variability and improve individualization of dosing regimens. However, significant covariates included varied across studies. The primary objective of this review was to summarize and discuss population pharmacokinetic models of methotrexate and covariates that influence pharmacokinetic variability in pediatric patients.

METHODS

Systematic searches were conducted in the PubMed and EMBASE databases from inception to 7 July 2023. Reporting Quality was evaluated based on a checklist with 31 items. The characteristics of studies and information for model construction and validation were extracted, summarized, and discussed.

RESULTS

Eighteen studies (four prospective studies and fourteen retrospective studies with sample sizes of 14 to 772 patients and 2.7 to 93.1 samples per patient) were included in this study. Two-compartment models were the commonly used structural models for methotrexate, and the clearance range of methotrexate ranged from 2.32 to 19.03 L/h (median: 6.86 L/h). Body size and renal function were found to significantly affect the clearance of methotrexate for pediatric patients. There were limited reports on the role of other covariates, such as gene polymorphisms and co-medications, in the pharmacokinetic parameters of methotrexate pediatric patients. Internal and external evaluations were used to assess the performance of the population pharmacokinetic models.

CONCLUSION

A more rigorous external evaluation needs to be performed before routine clinical use to select the appropriate PopPK model. Further research is necessary to incorporate larger cohorts or pool analyses in specific susceptible pediatric populations to improve the understanding of predicted exposure profiles and covariate identification.

Access to Methotrexate Monitoring in Latin America: A Multicountry Survey of Supportive Care Capacity

High-dose methotrexate (HDMTX) is used to treat a broad spectrum of cancers. Methotrexate (MTX) monitoring and adequate supportive care are critical for safe drug administration; however, MTX level timing is not always possible in low- and middle-income countries. The aim of this study was to evaluate HDMTX supportive care capacity and MTX monitoring practices in Latin America (LATAM) to identify gaps and opportunities for improvement. A multicenter survey was conducted among LATAM pediatric oncologists. Twenty healthcare providers from 20 institutions answered the online questionnaire. HDMTX was used to treat acute lymphoblastic leukemia (ALL; 100%), non-Hodgkin lymphoma (84.2%), diffuse large B-cell lymphoma (47.4%), osteosarcoma (78.9%), and medulloblastoma (31.6%). Delays in starting HDMTX infusion were related to bed shortages (47.4%) and MTX shortages (21.1%). MTX monitoring was performed at an in-hospital laboratory in 52%, at an external/nearby laboratory in 31.6%, and was not available in 10.5%. Median interval between sampling and obtaining MTX levels was ≤ 2 h in 45% and ≥ 6 h in 30%, related to laboratory location. Sites without access to MTX monitoring reduced the MTX dose for patients with high-risk ALL or did not include MTX in the treatment of patients with osteosarcoma. Respondents reported that implementation of point-of-care testing of MTX levels is feasible. In LATAM, highly variable supportive care capacity may affect the safe administration of MTX doses. Improving accessibility of MTX monitoring and the speed of obtaining results should be prioritized to allow delivery of full doses of MTX required by the current protocols.

Factors influencing methotrexate pharmacokinetics highlight the need for individualized dose adjustment: a systematic review

PURPOSE

To develop a population pharmacokinetic (PPK) model for methotrexate (MTX) dosage for all ages, assess the association between concentration and clearance, and determine covariates affecting MTX disposition.

METHODS

We compared MTX PK profiles among neonates, children, and adults by performing a systematic literature search for published population MTX models and conducted a Monte Carlo-based meta-analysis. Subsequently, we evaluated study quality and covariates significantly affecting dosage regimens and compared LDMTX and HDMTX PK profiles.

RESULTS

Of the total 40 studies included, 34 were HDMTX, and six were LDMTX studies. For HDMTX, three studies involving neonates reported estimated apparent clearances (median, range) of 0.53 (0.27-0.77) L/kg/h; for 14 studies involving children, 0.23 (0.07-0.23) L/kg/h; and for 13 involving adults, 0.11 (0.03-0.22) L/kg/h. Neonates had a higher volume of distribution than children and adults. For LDMTX studies, apparent clearance was 0.085 (0.05-1.68) L/kg/h, and volume of distribution was 0.25 (0.018-0.47) L/kg, lower than those of HDMTX studies, with large between-subject variability. Bodyweight significantly influenced apparent clearance and volume of distribution, whereas renal function mainly influenced clearance. Mutations in certain genes reduced MTX clearance by 8-35.3%, whereas those in others increased it by 15-48%. Body surface area (BSA) significantly influenced apparent clearance with a median reduction of 51% when BSA increased in pediatric patients.

CONCLUSIONS

Methotrexate dosage regimens were primarily based on body surface area and renal function. Further studies are needed to evaluate MTX pharmacokinetics and pharmacodynamics in both children (especially infants) and adults.

A semimechanistic pharmacokinetic/pharmacodynamic model for alanine aminotransferase-based hepatotoxicity of methotrexate in paediatric patients with acute lymphoid leukaemia

AIMS

Methotrexate (MTX) is recognized for its potential to induce hepatotoxicity, commonly manifested by elevated alanine aminotransferase (ALT) levels. However, the quantitative relationship between the pharmacokinetics (PK) of MTX and ALT-based hepatotoxicity remains unclear. This study aimed to develop a semimechanistic PK/pharmacodynamic (PD) model to characterize the MTX-induced hepatotoxicity based on ALT in paediatric patients with acute lymphoid leukaemia.

METHODS

A retrospective study was conducted on paediatric patients who received high-dose (3-5 g/m2 ) MTX treatment. MTX concentrations were assessed at 24-h intervals until the concentration dropped below 0.1 μmol/L. ALT concentrations were measured both before and after MTX administration. A population PK model was initially developed, which was later connected to a semimechanistic hepatotoxicity model.

RESULTS

The PK model was developed using 354 MTX concentrations obtained from 51 patients, while the PD model was constructed using 379 ALT concentrations collected from 48 patients. The optimal PK model for MTX consisted of a 2-compartment structure, where body surface area served as a covariate for clearance and central volume of distribution. An indirect response model coupled to a liver injury signal transduction model was developed to describe the dynamics of ALT after MTX administration. The drug effect was adequately described by a linear model, exhibiting considerable interoccasion variability for each treatment session. No significant covariates were identified to have an impact on the PD parameters.

CONCLUSION

A semimechanistic model was developed to describe ALT-based hepatotoxicity of MTX, and it has the potential to serve as a valuable tool for characterizing drug-induced hepatotoxicity.

Tutorial on model selection and validation of model input into precision dosing software for model-informed precision dosing

There has been rising interest in using model-informed precision dosing to provide personalized medicine to patients at the bedside. This methodology utilizes population pharmacokinetic models, measured drug concentrations from individual patients, pharmacodynamic biomarkers, and Bayesian estimation to estimate pharmacokinetic parameters and predict concentration-time profiles in individual patients. Using these individualized parameter estimates and simulated drug exposure, dosing recommendations can be generated to maximize target attainment to improve beneficial effect and minimize toxicity. However, the accuracy of the output from this evaluation is highly dependent on the population pharmacokinetic model selected. This tutorial provides a comprehensive approach to evaluating, selecting, and validating a model for input and implementation into a model-informed precision dosing program. A step-by-step outline to validate successful implementation into a precision dosing tool is described using the clinical software platforms Edsim++ and MwPharm++ as examples.

Clinical decision support for chemotherapy-induced neutropenia using a hybrid pharmacodynamic/machine learning model

Consensus guidelines recommend use of granulocyte colony stimulating factor in patients deemed at risk of chemotherapy-induced neutropenia, however, these risk models are limited in the factors they consider and miss some cases of neutropenia. Clinical decision making could be supported using models that better tailor their predictions to the individual patient using the wealth of data available in electronic health records (EHRs). Here, we present a hybrid pharmacokinetic/pharmacodynamic (PKPD)/machine learning (ML) approach that uses predictions and individual Bayesian parameter estimates from a PKPD model to enrich an ML model built on her data. We demonstrate this approach using models developed on a large real-world data set of 9121 patients treated for lymphoma, breast, or thoracic cancer. We also investigate the benefits of augmenting the training data using synthetic data simulated with the PKPD model. We find that PKPD-enrichment of ML models improves prediction of grade 3-4 neutropenia, as measured by higher precision (61%) and recall (39%) compared to PKPD model predictions (47%, 33%) or base ML model predictions (51%, 31%). PKPD augmentation of ML models showed minor improvements in recall (44%) but not precision (56%), and data augmentation required careful tuning to control overfitting its predictions to the PKPD model. PKPD enrichment of ML shows promise for leveraging both the physiology-informed predictions of PKPD and the ability of ML to learn predictor-outcome relationships from large data sets to predict patient response to drugs in a clinical precision dosing context.

Clinical covariates that improve the description of high dose methotrexate pharmacokinetics in a diverse population to inform MTXPK.org

The MTXPK.org webtool was launched in December 2019 and was developed to facilitate model-informed supportive care and optimal use of glucarpidase following the administration of high-dose methotrexate (HDMTX). One limitation identified during the original development of the MTXPK.org tool was the perceived generalizability because the modeled population comprised solely of Nordic pediatric patients receiving 24-h infusions for the treatment of acute lymphoblastic leukemia. The goal of our study is to describe the pharmacokinetics of HDMTX from a diverse patient population (e.g., races, ethnicity, indications for methotrexate, and variable infusion durations) and identify meaningful factors that account for methotrexate variability and improve the model's performance. To do this, retrospectively analyzed pharmacokinetic and toxicity data from pediatric and adolescent young adult patients who were receiving HDMTX (>0.5 g/m2 ) for the treatment of a cancer diagnosis from three pediatric medical centers. We performed population pharmacokinetic modeling referencing the original MTXPK.org NONMEM model (includes body surface area and serum creatinine as covariates) on 1668 patients, 7506 administrations of HDMTX, and 30,250 concentrations. Our results support the parameterizations of short infusion duration (<8 h) and the presence of Down syndrome on methotrexate clearance, the parameterization of severe hypoalbuminemia (<2.5 g/dL) on the intercompartmental clearance (Q2 and Q3), and the parameterization of pleural effusion on the volume of distribution (V1 and V2). These novel parameterizations will increase the generalizability of the MTXPK.org model once they are added to the webtool.

Factors influencing delayed clearance of high dose methotrexate (HDMTX) in pediatric, adolescent, and young adult oncology patients

Purpose

To identify modifiable risk factors associated with prolonged clearance of methotrexate in pediatric, adolescent, and young adult (AYA) oncology patients receiving high dose methotrexate (HDMTX).

Design/Method

A single institution, retrospective chart review of patients receiving HDMTX between 2010-2017. Patients had a diagnosis of either leukemia or osteosarcoma. Data included demographics, concurrent intravenous (IV) medications, IV fluids (IVF) administered, urine output (UO), and rises in serum creatinine (RSC) reflective of renal toxicity (RT). Outcome measures included 1) delayed targeted MTX clearance (DC), 2) actual time to clearance (TTC) and 3) length of stay (LOS).

Results

Data from 447 HDMTX administrations were analyzed. The sample consisted of 241 (54%) osteosarcoma encounters, and 206 (46%) leukemia encounters, with an average patient age of 12.7 years. Multivariate analysis showed that DC was associated with the diagnosis of leukemia (OR 7.64, p <.0001), and less UO on day 1 (OR 0.76, p=0.005). Increased TTC was associated with increasing age (RR 1.02, p<0.0001), higher 24-hour MTX levels (RR 1.001, p=0.012) and 48-hour MTX levels (RR 1.02, p<0.0001), RT (RR 1.004, p<0.0001), use of IV lorazepam (RR 1.08, p=0.001) and IV metoclopramide (RR 1.08, p<0.001) both on day 3. Like TTC, LOS was affected by MTX levels at 24 (RR 1.001, p=0.025) and 48 hours (RR 1.03, p<0.0001), RT (RR 1.006, p<0.0001), total IV medications on day 3 (RR 1.042, p<0.0001), and the use of leucovorin on day 2 (RR 0.93, p=0.002).

Conclusion

Multiple modifiable risk factors were identified which can be leveraged to improve HDMTX clearance. Subsequent efforts will assess whether acting on such risk factors can improve MTX clearance and shorten LOS.

Glucarpidase (carboxypeptidase G2): Biotechnological production, clinical application as a methotrexate antidote, and placement in targeted cancer therapy

Patients receiving high-dose methotrexate (HDMTX) for malignancies are exposed to diverse complications, including nephrotoxicity, hepatotoxicity, mucositis, myelotoxicity, neurological symptoms, and death. Glucarpidase is a recombinant carboxypeptidase G2 (CPG2) that converts MTX into nontoxic metabolites. In this study, the role of vector type, gene optimization, orientation, and host on the expression of CPG2 is investigated. The effectiveness of various therapeutic regimens containing glucarpidase is classified and perspectives on the dose adjustment based on precision medicine are provided. Conjugation with cell-penetrating peptides, human serum albumin, and polymers such as PEG and dextran for delivery, higher stability, and production of the biobetter variants of CPG2 is highlighted. Conjugation of CPG2 to F(ab՜)2 or scFv antibody fragments against tumor-specific antigens and the corresponding prodrugs for tumor-targeted drug delivery using the antibody-directed enzyme prodrug therapy (ADEPT) is communicated. Trials to reduce the off-target effects and the possibility of repeated ADEPT cycles by adding pro-domains sensitive to tumor-overexpressed proteases, antiCPG2 antibodies, CPG2 mutants with immune-system-unrecognizable epitopes, and protective polymers are reported. Intracellular cpg2 gene expression by gene-directed enzyme prodrug therapy (GDEPT) and the concerns regarding the safety and transfection efficacy of the GDEPT vectors are described. A novel bifunctional platform using engineered CAR-T cell micropharmacies, known as Synthetic Enzyme-Armed KillER (SEAKER) cells, expressing CPG2 to activate prodrugs at the tumor niche is introduced. Taken together, integrated data in this review and recruiting combinatorial strategies in novel drug delivery systems define the future directions of ADEPT, GDEPT, and SEAKER cell therapy and the placement of CPG2 therein.

A pooled subgroup analysis of glucarpidase treatment in 86 pediatric, adolescent, and young adult patients receiving high-dose methotrexate therapy in open-label trials

BACKGROUND

Delayed methotrexate elimination can occur in patients undergoing high-dose methotrexate cancer treatment. Effectiveness of glucarpidase for rapidly reducing methotrexate concentrations was shown in compassionate-use trials in patients aged 0-84 years.

METHODS

We performed post hoc analyses of infants (≥28 days to <2 years), children (≥2 to <12 years), adolescents (≥12 to <15 years), and young adults (≥15 to <25 years) from four multicenter, open-label, single-arm, glucarpidase compassionate-use trials. Patients had toxic methotrexate levels due to delayed methotrexate elimination and/or renal dysfunction, and received glucarpidase (50 U/kg). The primary endpoint was clinically important reduction (CIR) in plasma methotrexate (methotrexate ≤1 μmol/L at all post-glucarpidase measurements) based on high-performance liquid chromatography.

RESULTS

Among 86 patients included in efficacy analyses, CIR was achieved by zero of one infant (0.0%), five of 16 children (31.3%), seven of 24 adolescents (29.2%), and 26/45 young adults (57.8%). Median methotrexate reduction was 98.7% or higher in each group 15 minutes post-glucarpidase. Patients with pre-glucarpidase methotrexate less than 50 μmol/L (35/42, 83.3%) were more likely to achieve CIR than those with methotrexate 50 μmol/L or higher (1/37, 2.7%). The most common treatment-related adverse event was paresthesia, occurring in three adolescents (4.5%) and six young adults (5.2%). No other treatment-related adverse event occurred in 5% or higher of any age group.

CONCLUSION

After accounting for pre-glucarpidase methotrexate levels, glucarpidase efficacy at inducing CIR in pediatric/young adult patients was consistent, with efficacy observed in the overall study population (i.e., patients aged 0-84), and no unexpected safety findings were observed. These findings demonstrate glucarpidase (50 U/kg) is an effective and well-tolerated dose for pediatric, adolescent, and young adult patients.

External evaluation and systematic review of population pharmacokinetic models for high-dose methotrexate in cancer patients

Several population pharmacokinetic (PPK) models have been established to optimize the therapeutic regimen and reduce the toxicity of high-dose methotrexate (HDMTX) in patients with cancer. However, their predictive performance when extrapolated to different clinical centers was unknown. In this study, we aimed to externally evaluate the predictive ability of HDMTX PPK models and determine the potential influencing factors. We searched the literature and determined the predictive performance of the selected models using methotrexate concentrations in 721 samples from 60 patients in the First Affiliated Hospital of the Navy Medical University. Prediction-based diagnostics and simulation-based normalized prediction distribution errors (NPDE) were used to evaluate the predictive performance of the models. The influence of prior information was also assessed using Bayesian forecasting, and the potential factors affecting model predictability were investigated. Thirty models extracted from published PPK studies were assessed. Prediction-based diagnostics showed that the number of compartments potentially influenced model transferability, and simulation-based NPDE indicated model misspecification. Bayesian forecasting significantly improved the predictive performance of the models. Various factors, including bioassays, covariates, and population diagnosis, influence model extrapolation. The published models were unsatisfactory for all prediction-based diagnostics, except for the 24 h methotrexate concentration monitoring and simulation-based diagnostics, making them inappropriate for direct extrapolation. Moreover, Bayesian forecasting combined therapeutic drug monitoring could improve the predictive performance of the models.

Target attainment and population pharmacokinetics of flucloxacillin in critically ill patients: a multicenter study

PURPOSE

Insufficient antimicrobial exposure has been associated with worse clinical outcomes. Reportedly, flucloxacillin target attainment in critically ill patients was heterogeneous considering the study population selection and reported target attainment percentages. Therefore, we assessed flucloxacillin population pharmacokinetics (PK) and target attainment in critically ill patients.

METHODS

This prospective, multicenter, observational study was conducted from May 2017 to October 2019 and included adult, critically ill patients administered flucloxacillin intravenously. Patients with renal replacement therapy or liver cirrhosis were excluded. We developed and qualified an integrated PK model for total and unbound serum flucloxacillin concentrations. Monte Carlo dosing simulations were performed to assess target attainment. The unbound target serum concentration was four times the minimum inhibitory concentration (MIC) for ≥ 50% of the dosing interval (ƒT_>4xMIC ≥ 50%).

RESULTS

We analyzed 163 blood samples from 31 patients. A one-compartment model with linear plasma protein binding was selected as most appropriate. Dosing simulations revealed 26% ƒT_>2 mg/L ≥ 50% following continuous infusion of 12 g flucloxacillin and 51% ƒT_>2 mg/L ≥ 50% for 24 g.

CONCLUSION

Based on our dosing simulations, standard flucloxacillin daily doses of up to 12 g may substantially enhance the risk of underdosing in critically ill patients. Prospective validation of these model predictions is needed.

Novel and replicated clinical and genetic risk factors for toxicity from high-dose methotrexate in pediatric acute lymphoblastic leukemia

STUDY OBJECTIVE

Methotrexate (MTX) is a key component of treatment for high-risk pediatric acute lymphoblastic leukemia (ALL) but may cause acute kidney injury and prolonged hospitalization due to delayed clearance. The purpose of this study is to identify clinical and genetic factors that may predict which children are at risk for creatinine increase and prolonged MTX clearance.

DESIGN

We conducted a single-center, retrospective cohort study of pediatric patients with ALL who received 4000-5000 mg/m2 of MTX. Measurements We performed germline genotyping to determine genetic ancestry and allele status for 49 single nucleotide polymorphisms (SNPs) identified from the literature as related to MTX disposition. Bayesian hierarchical ordinal regression models for creatinine increase and for prolonged MTX clearance were developed.

MAIN RESULTS

Hispanic ethnicity, body mass index (BMI) < 3%, BMI between 85%-95%, and Native American genetic ancestry were found to be associated with an increased risk for creatinine elevation. Older age, Black race, and use of the intensive monitoring protocol were associated with a decreased risk for creatinine elevation. Older age, B- compared to T-ALL, and the minor alleles of rs2838958/SLC19A1 and rs7317112/ABCC4 were associated with an increased risk for delayed clearance. Black race, MTX dose reduction, and the minor allele of rs2306283/SLCO1B1 were found to be associated with a decreased risk for delayed clearance.

CONCLUSIONS

These predictors of MTX toxicities may allow for more precise individualized toxicity risk prediction.

Insights from a pharmacometric analysis of HDMTX in adults with cancer: Clinically relevant covariates for application in precision dosing

AIMS

High-dose methotrexate (HDMTX) is an essential part of the treatment of several adult and paediatric malignancies. Despite meticulous supportive care during HDMTX administration, severe toxicities, including acute kidney injury (AKI), may occur contributing to patient morbidity. Population pharmacokinetics provide a powerful tool to predict time to clear HDMTX and adjust subsequent doses. We sought to develop and validate pharmacokinetic models for HDMTX in adults with diverse malignancies and to relate systemic exposure with the occurrence of severe toxicity.

METHODS

Anonymized, de-identified data were provided from 101 US oncology practices that participate in the Guardian Research Network, a non-profit clinical research consortium. Modelled variables included clinical, laboratory, demographic and pharmacological data. Population pharmacokinetic analysis was performed by means of nonlinear mixed effects modelling using MonolixSuite.

RESULTS

A total of 693 HDMTX courses from 243 adults were analysed, of which 62 courses (8.8%) were associated with stage 2/3 acute kidney injury (43 stage 2, 19 stage 3). A three-compartment model adequately fitted the data. Time-dependent serum creatinine, baseline serum albumin and allometrically scaled bodyweight were clinically significant covariates related to methotrexate clearance. External evaluation confirmed a satisfactory predictive performance of the model in adults receiving HDMTX. Dose-normalized methotrexate concentration at 24 and 48 hours correlated with AKI incidence.

CONCLUSION

We developed a population pharmacometric model that considers weight, albumin and time-dependent creatinine that can be used to guide supportive care in adult patients with delayed HDMTX elimination.

Prevalence and management of methotrexate-induced neurotoxicity in pediatric patients with osteosarcoma: a single-center experience

AIMS

To determine the incidence, clinical presentation, and outcome of methotrexate (MTX) associated neurotoxicity in pediatric patients treated for osteosarcoma, with the aim of identifying possible risk factors and suggesting recommended treatment for these sequelae.

MATERIALS AND METHODS

All medical files of patients treated for osteosarcoma in a single pediatric haemato-oncology center between November 2011 and August 2021 were retrospectively reviewed. All patients were treated according to the EURAMOS AOST0331 protocol, using cisplatin, doxorubicin, and high-dose MTX at a dose of 12 g/m² over 4 h.

RESULTS

Seventy-eight patients with osteosarcoma were identified (age range 5 to 23 years, 42 males). Seven patients (9%) sustained neurotoxicity following treatment with high-dose MTX. Manifestations of neurotoxicity included among others, generalized seizures, confusion, encephalopathy, dysarthria, and choreiform movements. All but one episode occurred following two sequential cycles of high-dose MTX. All 7 had subacute toxicity, 5-10 days following MTX administration, and 1 had both acute and subacute toxicity. Brain MRI was performed for all patients and demonstrated typical MRI changes attributed to MTX neurotoxicity in 4 of them. Two patients received aminophylline; one patient received dextromethorphan. Patients with normal MRI imaging resumed MTX therapy without any sequels. No risk factors were found for high-dose MTX-related toxicity occurrence.

CONCLUSIONS

The time of risk of neurotoxicity due to high-dose MTX treatment for osteosarcoma is days 5-10 following two sequential treatment cycles. These findings together with treatment options for these adverse effects should be detailed in the therapeutic protocol of MTX use among pediatric patients with osteosarcoma.

Pharmacokinetic Modeling of Hydrocortisone by Including Protein Binding to Corticosteroid-Binding Globulin

Background: Patients with adrenal insufficiency are treated with oral hydrocortisone (HC) to compensate for the loss of endogenous cortisol production. Intrinsic imperfections of cortisol replacement strategies in mimicking normal cortisol secretion are the underlying cause of the increased morbidity and mortality of patients suffering from secondary adrenal insufficiency (SAI). To improve oral hydrocortisone substitution therapy, a better understanding of its pharmacokinetics (PK) is necessary. The previous PK model did not include protein binding. It is known that protein binding can impact hydrocortisone pharmacokinetics. The aim of this study is to describe HC pharmacokinetics including the protein-binding state using Edsim++ (Mediware, Prague) pharmacokinetic modeling software, paving the way for an in-silico tool suitable for drug delivery design. Methods: A total of 46 patients with SAI participated in a randomized double-blind crossover study Patients randomly received a low dose of HC (0.2–0.3 mg/kg body weight/day) for 10 weeks, followed by a high dose (0.4–0.6 mg/kg body weight/day) for another 10 weeks, or vice versa. Plasma samples were obtained and analyzed for free and total hydrocortisone. Single compartment population pharmacokinetic analysis was performed using an extended Werumeus-Buning model built in Edsim++. This model includes a mathematical approach for estimating free cortisol by Nguyen et al., taking the protein binding of HC to albumin and hydrocortisone-binding globulin (CBG, transcortin) into consideration, as well as different states of CBG which affect binding kinetics to HC. The goodness of fit for observed versus predicted values was calculated. Results and conclusions: Nguyen’s formula for free cortisol estimation was successfully implemented in a pharmacokinetic model. The model shows high Spearman’s correlation for observed versus predicted hydrocortisone concentrations. Significantly higher correlations (Spearman’s r, 0.901 vs. 0.836) between total and free hydrocortisone AUC₂₄ (area-under the curve over 24 h) are found when comparing new and old models. This new model was used to simulate the plasma concentration–time behavior of a more suitable hydrocortisone formulation.

Population pharmacokinetics of methotrexate in pediatric patients with acute lymphoblastic leukemia and malignant lymphoma

1. This study aimed to identify physiological and pharmacogenomic covariates and develop a population pharmacokinetic model of high-dose methotrexate (HD-MTX) in Chinese pediatric patients with acute lymphoblastic leukemia (ALL) and malignant lymphoma.2. A total 731 MTX courses and 1658 MTX plasm concentration from 205 pediatric patients with ALL and malignant lymphoma were analyzing using a nonlinear mixed-effects model technique. 47 SNPs in 16 MTX-related gene were genotyped and screened as covariates. A PPK model was established to determine the influence of covariates such as body surface area (BSA), age, laboratory test value, and SNPs on the pharmacokinetic process of HD-MTX.3. Two-compartmental model with allometric scaling using BSA could nicely characterize the in vivo behavior of HD-MTX. After accounting for body size, rs17004785 and rs4148416 were the covariates that influence MTX clearance (CL). The PPK model obtained was: CL =9.33 * (BSA/1.73) ^0.75 * e^{0.13*rs17004785} * e^{0.39*rs4148416} * e^ηCL, Vc =24.98 * (BSA/1.73) * e^ηvc, Q = 0.18 * (BSA/1.73) ^0.75 * e^ηQ and Vp =4.70 * (BSA/1.73) * e^ηvp.4. The established model combined with Bayesian approach could estimate individual pharmacokinetic parameters and optimize personalized HD-MTX therapy for pediatric patients with ALL and malignant lymphoma.

Extracorporeal Treatment for Methotrexate Poisoning: Systematic Review and Recommendations from the EXTRIP Workgroup

Methotrexate is used in the treatment of many malignancies, rheumatological diseases, and inflammatory bowel disease. Toxicity from use is associated with severe morbidity and mortality. Rescue treatments include intravenous hydration, folinic acid, and, in some centers, glucarpidase. We conducted systematic reviews of the literature following published EXtracorporeal TReatments In Poisoning (EXTRIP) methods to determine the utility of extracorporeal treatments in the management of methotrexate toxicity. The quality of the evidence and the strength of recommendations (either "strong" or "weak/conditional") were graded according to the GRADE approach. A formal voting process using a modified Delphi method assessed the level of agreement between panelists on the final recommendations. A total of 92 articles met inclusion criteria. Toxicokinetic data were available on 90 patients (89 with impaired kidney function). Methotrexate was considered to be moderately dialyzable by intermittent hemodialysis. Data were available for clinical analysis on 109 patients (high-dose methotrexate [>0.5 g/m²]: 91 patients; low-dose [≤0.5 g/m²]: 18). Overall mortality in these publications was 19.5% and 26.7% in those with high-dose and low-dose methotrexate-related toxicity, respectively. Although one observational study reported lower mortality in patients treated with glucarpidase compared with those treated with hemodialysis, there were important limitations in the study. For patients with severe methotrexate toxicity receiving standard care, the EXTRIP workgroup: (1) suggested against extracorporeal treatments when glucarpidase is not administered; (2) recommended against extracorporeal treatments when glucarpidase is administered; and (3) recommended against extracorporeal treatments instead of administering glucarpidase. The quality of evidence for these recommendations was very low. Rationales for these recommendations included: (1) extracorporeal treatments mainly remove drugs in the intravascular compartment, whereas methotrexate rapidly distributes into cells; (2) extracorporeal treatments remove folinic acid; (3) in rare cases where fast removal of methotrexate is required, glucarpidase will outperform any extracorporeal treatment; and (4) extracorporeal treatments do not appear to reduce the incidence and magnitude of methotrexate toxicity.

Incidence and management of patients with methotrexate delayed elimination in the clinical practice: A Delphi study

INTRODUCTION

High-dose methotrexate (HDMTX) is administered for the treatment of some cancers. HDMTX is usually safe but may crystallize in renal tubules causing acute kidney injury (AKI). Consequently, MTX elimination is delayed, resulting in a severe and life-threatening condition. No studies have been published about the impact of MTX toxicity in Spain. This study aims to estimate the incidence and management of MTX delayed elimination and toxicity.

METHODS

A two-round Delphi study was performed to reach consensus between 10 medical experts on haemato-oncology and paediatric oncology with experience in the management of HDMTX treated patients from leading Spanish hospitals. An online questionnaire was developed based on national and international guidelines and previous evidence regarding HDMTX-related toxicity. Consensus was established at 80% agreement. Median and interquartile ranges were calculated, and incidence data were extrapolated to the Spanish general population.

RESULTS

Out of 1.475 patients estimated to receive HDMTX treatment annually in Spain, 27.5% present MTX delayed elimination and 11.6% develop HDMTX-induced AKI (35.4% with severe systemic toxicities (>grade 3) and 18.8% develop chronic renal disease). Mortality is estimated in 4.2%. Immuno-enzymatic assay is used in most of the hospitals (90%) for MTX serum level monitoring. All experts use increased supportive care and high leucovorin as first-line treatment. Available treatments in experts' hospitals in case toxicity persists are haemodialysis (90% of hospitals), glucarpidase (60%) and hemofiltration (50%). Most prevalent non-renal systemic toxicities are haematologic and mucositis (21-40% of patients). Patients with HDMTX-induced AKI require from intensive care (5% of patients), more than 3 sessions and 4 days of dialysis, and about 8.5 days of hospitalization (non-ICU patients) and 12 days in case of patients requiring ICU.

CONCLUSIONS

These results are the first evidence regarding HDMTX-induced AKI in Spain. Incidence and mortality results are in line with previous studies. Clinical management is based on preventive measures and the treatment depend on the availability in the hospital. The need for effective, safe and rapid treatment for the reduction of MTX toxic levels and the improvement of monitoring methods were noted by experts as urgent needs. Further observational studies to validate these results would be needed.

Urine volume to hydration volume ratio is associated with pharmacokinetics of high-dose methotrexate in patients with primary central nervous system lymphoma

High-dose methotrexate (HD-MTX)-based chemotherapy is the first-line treatment for primary central nervous system lymphoma (PCNSL), but is associated with severe adverse effects, including myelosuppression and renal impairment. MTX is primarily excreted by the kidneys. Renal function calculated using serum creatinine (Scr) derived from muscle may be overestimated in elderly PCNSL patients. Therefore, we aimed to construct a population pharmacokinetic model in PCNSL patients and explore the factors associated with MTX clearance. Sixteen PCNSL patients (median age, 66 years) treated with HD-MTX were included, and serum MTX concentrations were measured at 193 points in 49 courses. A population pharmacokinetic analysis was performed using NONMEM. A Monte Carlo simulation was conducted, in which serum MTX concentrations were stratified into three groups of creatine clearance (Ccr) (50, 75, and 100 ml/min) with three groups of the urine volume to hydration volume (UV/HV) ratio (<1, 1-2, and >2). The final model was constructed as follows: MTX clearance = 4.90·(Ccr/94.5)0.456 ·(UV/HV)0.458 . In the Monte Carlo simulation, serum MTX concentrations were below the standard values (10, 1, and 0.1 µM at 24, 48, and 72 h, respectively, after the start of the MTX administration) in most patients with UV/HV >2, even with Ccr of 50 ml/min. Conversely, half of the patients with UV/HV <1 and Ccr of 50 ml/min failed to achieve the standard values. The present results demonstrated that the UV/HV ratio was useful for describing the pharmacokinetics of MTX in PCNSL patients.

Creation of an inventory of quality markers used to evaluate pharmacokinetic literature: A systematic review

WHAT IS KNOWN AND OBJECTIVE

Robust critical appraisal tools for clinical pharmacokinetic studies are limited. Before development of such a tool is possible, quality markers (items deemed important for credibility of study results) must be identified. We aim to create an inventory of quality markers intended for the appraisal of clinical pharmacokinetic studies and to categorize identified markers into associated domains of study quality.

METHODS

Medline via ProQuest central (1946-Sep 2020, EMBASE (1974-Sep 2020), Cochrane database of systematic reviews, Google and Google Scholar were searched using the following search categories: pharmacokinetics, reporting guidelines and quality markers. Reference lists of the identified articles were searched manually. Any article (review, study or guideline) reporting quality markers related to the appraisal of pharmacokinetic literature was eligible for inclusion. Articles were further screened and limited to those reported in English on human subjects only. Cell-based and animal-based pharmacokinetic studies were excluded. Extracted data from included articles included identified or perceived markers of quality and baseline article data. Identified quality markers were then categorized according to manuscript reporting domains (abstract, introduction/background, methodology, results, discussion and conclusion).

RESULTS AND DISCUSSION

Of 789 studies identified, 17 articles were included for extraction of quality markers. A total of 35 quality markers were identified across eight categories. The most frequently reported quality markers were related to method (13/35) and result sections (6/35). Quality markers encompassed all aspects of study design and reporting and were both similar and different to established reporting checklists for clinical pharmacokinetic studies.

WHAT IS NEW AND CONCLUSION

The inventory of quality markers is now suitable to undergo further testing for inclusion in a tool designed for the appraisal of clinical pharmacokinetic studies.

A hybrid machine learning/pharmacokinetic approach outperforms maximum a posteriori Bayesian estimation by selectively flattening model priors

Model‐informed precision dosing (MIPD) approaches typically apply maximum a posteriori (MAP) Bayesian estimation to determine individual pharmacokinetic (PK) parameters with the goal of optimizing future dosing regimens. This process combines knowledge about the individual, in the form of drug levels or pharmacodynamic biomarkers, with prior knowledge of the drug PK in the general population. Use of “flattened priors” (FPs), in which the weight of the model priors is reduced relative to observations about the patient, has been previously proposed to estimate individual PK parameters in instances where the patient is poorly described by the PK model. However, little is known about the predictive performance of FPs and when to apply FPs in MIPD. Here, FP is evaluated in a data set of 4679 adult patients treated with vancomycin. Depending on the PK model, prediction error could be reduced by applying FPs in 42–55% of PK parameter estimations. Machine learning (ML) models could identify instances where FPs would outperform MAPs with a specificity of 81–86%, reducing overall root mean squared error (RMSE) of PK model predictions by 12–22% (0.5–1.2 mg/L) relative to MAP alone. The factors most indicative of the use of FPs were past prediction residuals and bias in past PK predictions. A more clinically practical minimal model was developed using only these two features, reducing RMSE by 5–18% (0.20–0.93 mg/L) relative to MAP. This hybrid ML/PK approach advances the precision dosing toolkit by leveraging the power of ML while maintaining the mechanistic insight and interpretability of PK models.

Population Pharmacokinetics of High-Dose Methotrexate in Chinese Pediatric Patients With Acute Lymphoblastic Leukemia

High-dose methotrexate (HD-MTX) is widely used in pediatric acute lymphoblastic leukemia (ALL) treatment regimens. In this study, we aimed to develop a population pharmacokinetic (PK) model of HD-MTX in Chinese pediatric patients with ALL for designing personalized dosage regimens. In total, 4,517 MTX serum concentration data for 311 pediatric patients with ALL, aged 0.75–15.2 years and under HD-MTX treatment, were retrospectively collected at a tertiary Children’s Hospital in China. The non-linear mixed-effect model was used to establish the population PK model, using NONMEM software. The potential covariate effects of age, body weight, and biochemical measurements (renal and liver function) on MTX PK disposition were investigated. The model was then evaluated using goodness-of-fit, visual predictive check. MTX PK disposition was described using a three-compartment model reasonable well. Body weight, implemented as a fixed allometric function on all clearance and volume of distribution parameters, showed a substantial improvement in model fit. The final population model demonstrated that the MTX clearance estimate in a typical child with body weight of 19 kg was 6.9 L/h and the central distribution of volume estimate was 20.7 L. The serum creatinine significantly affected the MTX clearance, with a 0.97% decrease in clearance per 1 μmol/L of serum creatinine. Other covariates (e.g., age, sex, bilirubin, albumin, aspartate transaminase, concomitant medication) did not significantly affect PK properties of MTX. The proposed population PK model could describe the MTX concentration data in Chinese pediatric patients with ALL. This population PK model combined with a maximum a posteriori Bayesian approach could be used to estimate individual PK parameters, and optimize personalized MTX therapy in target patients, thus aiming to reduce toxicity and improve treatment outcomes.

Systematic Review of Pharmacogenetic Factors That Influence High-Dose Methotrexate Pharmacokinetics in Pediatric Malignancies

Methotrexate (MTX) is a mainstay therapeutic agent administered at high doses for the treatment of pediatric and adult malignancies, such as acute lymphoblastic leukemia, osteosarcoma, and lymphoma. Despite the vast evidence for clinical efficacy, high-dose MTX displays significant inter-individual pharmacokinetic variability. Delayed MTX clearance can lead to prolonged, elevated exposure, causing increased risks for nephrotoxicity, mucositis, seizures, and neutropenia. Numerous pharmacogenetic studies have investigated the effects of several genes and polymorphisms on MTX clearance in an attempt to better understand the pharmacokinetic variability and improve patient outcomes. To date, several genes and polymorphisms that affect MTX clearance have been identified. However, evidence for select genes have conflicting results or lack the necessary replication and validation needed to confirm their effects on MTX clearance. Therefore, we performed a systematic review to identify and then summarize the pharmacogenetic factors that influence high-dose MTX pharmacokinetics in pediatric malignancies. Using the PRISMA guidelines, we analyzed 58 articles and 24 different genes that were associated with transporter pharmacology or the folate transport pathway. We conclude that there is only one gene that reliably demonstrates an effect on MTX pharmacokinetics: SLCO1B1.

Relationship Between the Free and Total Methotrexate Plasma Concentration in Children and Application to Predict the Toxicity of HD-MTX

High-dose methotrexate (HD-MTX) can be highly effective as well as extremely toxic. Many drug molecules can bind to plasma proteins to different extents in vivo, whereas only the free drug can reach the site of action to exert a pharmacological effect and cause toxicity. However, free MTX concentrations in plasma have not been reported. Traditional analyses of free drugs are both cumbersome and inaccurate. We collected 92 plasma samples from 52 children diagnosed with ALL or NHL or other lymphomas that were treated with HD-MTX. The hollow fiber centrifugal ultrafiltration (HFCF-UF) was used to prepare plasma samples for analysis of the free MTX concentration. Protein precipitation was employed to measure the total MTX concentration. The HFCF-UF is a simple method involving a step of ordinary centrifugation; the validation parameters for the methodological results were satisfactory and fell within the acceptance criteria. A linearity coefficient r² of 0.910 was obtained for the correlation between the free and total MTX plasma concentrations in 92 plasma samples. However, the free and total MTX concentrations was only weakly correlated in 16 clinical plasma specimens with total MTX concentrations >2 μmol L⁻¹ (r² = 0.760). Both the free and total MTX concentrations at 42 h were negatively correlated with the creatinine clearance (CCr) level (P = 0.023, r = −0.236 for total MTX and P = 0.020, r = −0.241for free MTX, respectively). The free MTX concentration could not be accurately estimated from the total MTX concentration for patients with high MTX levels which are conditions under which toxic reactions are more likely to occur. High plasma MTX levels could become a predictor of the occurrence of MTX nephrotoxicity to draw people's attention. The proposed HFCF-UF method is a simple and accurate way to evaluate efficacy and toxicity in clinical therapeutic drug monitoring.

Charcoal Hemoperfusion for Methotrexate Toxicity: A Safe and Effective Life-Rescue Alternative When Glucarpidase Is Not Available

Background: High dose methotrexate (HDMTX) is used for the treatment of pediatric hemato-oncological diseases. HDMTX can induce acute kidney injury in cases of delayed elimination. The use of leucovorin remains the most effective rescue action. Further treatment options are of difficult access in the rare cases where leucovorin fails to prevent renal failure from occurring. Glucarpidase is an effective treatment in cases of methotrexate (MTX) delayed elimination, but cost is high and availability is limited. Charcoal hemoperfusion (CHP) is a very efficient procedure to remove protein-bound drugs, promoting fast MTX elimination, but is rarely considered as a treatment option. Methods: We present three pediatric cases with prolonged exposure to MTX after HDMTX and delayed elimination in which hemoperfusion was performed as rescue treatment for methotrexate intoxication. Results: Charcoal hemoperfusion was performed with positive results and no complications as bridging until glucarpidase was available in two cases and in one case where two doses of glucarpidase led to insufficient reduction of MTX levels. Conclusions: CHP can be considered as a rescue treatment option in MTX intoxication, since it is an effective and safe extracorporeal method for removing MTX, in cases where rescue with leucovorin is insufficient and glucarpidase is not available or while waiting for delivery.

Model-Informed Precision Dosing of Antibiotics in Pediatric Patients: A Narrative Review

Optimal pharmacotherapy in pediatric patients with suspected infections requires understanding and integration of relevant data on the antibiotic, bacterial pathogen, and patient characteristics. Because of age-related physiological maturation and non-maturational covariates (e.g., disease state, inflammation, organ failure, co-morbidity, co-medication and extracorporeal systems), antibiotic pharmacokinetics is highly variable in pediatric patients and difficult to predict without using population pharmacokinetics models. The intra- and inter-individual variability can result in under- or overexposure in a significant proportion of patients. Therapeutic drug monitoring typically covers assessment of pharmacokinetics and pharmacodynamics, and concurrent dose adaptation after initial standard dosing and drug concentration analysis. Model-informed precision dosing (MIPD) captures drug, disease, and patient characteristics in modeling approaches and can be used to perform Bayesian forecasting and dose optimization. Incorporating MIPD in the electronic patient record system brings pharmacometrics to the bedside of the patient, with the aim of a consisted and optimal drug exposure. In this narrative review, we evaluated studies assessing optimization of antibiotic pharmacotherapy using MIPD in pediatric populations. Four eligible studies involving amikacin and vancomycin were identified from 418 records. Key articles, independent of year of publication, were also selected to highlight important attributes of MIPD. Although very little research has been conducted until this moment, the available data on vancomycin indicate that MIPD is superior compared to conventional dosing strategies with respect to target attainment. The utility of MIPD in pediatrics needs to be further confirmed in frequently used antibiotic classes, particularly aminoglycosides and beta-lactams.

Clinical implementation of pharmacogenetics and model-informed precision dosing to improve patient care

Providing maximal therapeutic efficacy without toxicity is a universal goal of rational drug therapy. However, substantial between-patient variability in drug response often impedes such successful treatments and brings the necessity of tailoring drug dose to individual needs for more precise therapy. In many cases plenty of patient characteristics, such as body size, genetic makeup and environmental factors, need to be taken into consideration to find the optimal dose in clinical practice. A pharmacokinetics and pharmacodynamics (PK/PD) model-informed approach offers integration of various patient information to provide an expectation of drug response and derive practical dose estimates to support clinicians' dosing decisions. Such an approach was pioneered in the late 1970s, but its broad clinical acceptance and implementation have been hampered by the lack of widespread computer technology, including user-friendly software tools. This has significantly changed in recent years. With the advent of electronic health records (EHRs) and the ubiquity of user-friendly software tools, we now experience a convergence of clinical information, pharmacogenetics, systems pharmacology and pharmacometrics, and technology. Advanced pharmacometrics research is now more appliable and implementable to improve health care. This article presents examples of successful development and implementation of pharmacogenetics-guided and PK/PD model-informed decision support to facilitate precision dosing, including the development of an EHR-embedded decision support tool. Through the integration of clinical decision support tools in EHRs, clinical pharmacometrics support can be brought directly to the clinical team and the bedside.