Intra-individual Pharmacokinetic Variability of Intravenous Busulfan in Hematopoietic Stem Cell-Transplanted Children

From Prospective Evaluation to Practice: Model-Informed Dose Optimization in Oncology

One dose does not fit all, especially in oncolytic drugs, where side effects and therapy failures highlight the need for personalized dosing approaches. In recent years, the quest to apply model-informed precision dosing to oncology drugs has gained significant momentum, reflecting its potential to revolutionize patient care by tailoring treatments to individual pharmacokinetic profiles. Despite this progress, model-informed precision dosing has not (yet) become widely integrated into routine clinical care. We aimed to explain model-informed precision dosing from a clinical viewpoint while addressing all prospective model-informed precision dosing implementation and validation studies in the field of oncology. We identified 16 different drugs for which prospective model-informed precision dosing validation/implementation has been performed. Although these studies are mostly focused on attaining adequate drug exposures and reducing inter-individual variability, improved clinical outcomes after performing model-informed precision dosing were shown for busulfan, and high-dose methotrexate. Toxicities were significantly reduced for busulfan and cyclophosphamide treatment. In contrast, for carboplatin, for which model-informed precision dosing has been used in the Calvert formula, no prospective validation on outcomes was deemed necessary as the therapeutic window had been extensively validated. Model-informed precision dosing has shown to be of added value in oncology and is expected to significantly change dosing regimens in the future.

A limited sampling strategy for estimating busulfan exposure in pediatric hematopoietic stem cell transplantation

Background

Busulfan (Bu) is the foundation of conditioning regimens for pediatric hematopoietic stem cell transplantation (HSCT). Evidence indicates that the efficacy and side effects of Bu are intimately tied to the area under its concentration-time curve (AUC). Given its cytotoxic nature and a small therapeutic index, coupled with marked inter-individual pharmacokinetic variability, Bu requires therapeutic drug monitoring to facilitate individualized therapy. However, research investigating the relationship between Bu exposure and clinical outcomes among the Chinese population remains scarce. This study aimed to develop a limited sampling strategy (LSS) for estimating Bu exposure in pediatric HSCT recipients using multiple linear regression (MLR) analysis to predict the AUC0-360.

Methods

We enrolled 26 pediatric patients who underwent Bu-based conditioning for HSCT. Blood samples were collected at 11 time points after Bu infusion. Pharmacokinetic parameters were calculated using non-compartmental methods. MLR models were developed using 1-4 sampling points to predict the AUC0-360. Model accuracy was assessed using the Jackknife and Bootstrap methods, with consistency evaluated via intraclass correlation coefficient (ICC) and Bland-Altman (BA) analyses.

Results

The mean ± standard deviation (SD) for AUC0-t, mean residence time 0-t, clearance, and volume of distribution were 845.54 ± 111.03 μmol min/L, 181.37 ± 10.55 min, 0.23 ± 0.04 L/h/kg, and 0.73 ± 0.15 L/kg, respectively. Models with 2-4 sampling points showed improved prediction accuracy compared to single-point models. The four-point model (60, 135, 240 and 360 min) demonstrated the highest accuracy with an adjusted r 2 of 0.965. Internal validation confirmed the models' stability and accuracy, with the four-point model exhibiting the best performance. External validation using three additional cases supported the predictive accuracy of the model.

Conclusion

The LSS model developed in this study accurately predicts the Bu AUC0-360 with 2-4 sampling points, offering a practical and clinically valuable tool for therapeutic drug monitoring in pediatric HSCT recipients. The four-point model was found to be the most accurate and is recommended for clinical applications.

A practical guide to therapeutic drug monitoring in busulfan: recommendations from the Pharmacist Committee of the European Society for Blood and Marrow Transplantation (EBMT)

Busulfan (Bu) is an important component of many conditioning regimens for allogeneic hematopoietic cell transplantation. The therapeutic window of Bu is well characterized, with strong associations between Bu exposure and the clinical outcome in adults (strongest evidence in myelo-ablative setting) and children (all settings). We provide an overview of the literature on Bu as well as a step-by-step guide to the implementation of Bu therapeutic drug monitoring (TDM). The guide covers the clinical, pharmacological, laboratory and administrative aspects of the procedure. Through this document, we aim to support centers in implementing TDM for Bu to further enhance the success rates of HCT and improve patient outcomes. The Pharmacist Committee of the European Society for Blood and Marrow Transplantation (EBMT) encourages all centers to perform TDM for Bu in the aforementioned indications.

Importance of Sex-Dependent Differences for Dosing Selection and Optimization of Chemotherapeutic Drugs

BACKGROUND

Despite major advances in cancer treatment in the past years, there is a need to optimize chemotherapeutic drug dosing strategies to reduce toxicities, suboptimal responses, and the risk of relapse. Most cancer drugs have a narrow therapeutic index with substantial pharmacokinetics variability. Yet, current dosing approaches do not fully account for the complex pathophysiological characteristics of the patients. In this regard, the effect of sex on anticancer chemotherapeutic drugs' disposition is still underexplored. In this article, we review sex differences in chemotherapeutic drug pharmacokinetics; we suggest a novel approach that integrates sex into the traditional a priori body surface area (BSA) dosing selection model, and finally, we provide an overview of the potential benefits of a broader use of therapeutic drug monitoring (TDM) in oncology.

SUMMARY

To date, anticancer chemotherapeutic drug dosing is most often determined by BSA, a method widely used for its ease of practice, despite criticism for not accounting for individual factors, notably sex. Anatomical, physiological, and biological differences between males and females can affect pharmacokinetics, including drug metabolism and clearance. At equivalent doses, females tend to display higher circulating exposure and more organ toxicities, which has been formally demonstrated at present for about 20% of chemotherapeutic drugs. An alternative could be the sex-adjusted BSA (SABSA), incorporating a 10% increase in dosing for males and a 10% decrease for females, though this approach still lacks formal clinical validation. Another strategy to reduce treatment-related toxicity and potentially enhance clinical outcomes could be a more widespread use of TDM, for which a benefit has been demonstrated for 5-fluorouracil, busulfan, methotrexate, or thiopurines.

KEY MESSAGES

The inclusion of sex besides BSA in an easy-to-implement formula such as SABSA could improve a priori chemotherapy dosing selection, even though it still requires clinical validation. The a posteriori use of TDM could further enhance treatment efficacy and safety in oncology.

Busulfan Exposure Target Attainment in Adults Undergoing Allogeneic Hematopoietic Cell Transplantation: A Single Day Versus a Multiple Day Therapeutic Drug Monitoring Regimen

Busulfan exposure has previously been linked to clinical outcomes, hence the need for therapeutic drug monitoring (TDM). Study objective was to evaluate the effect of day 1 TDM-guided dosing (regimen d1) versus days 1 + 2 TDM-guided dosing (regimen d1 + 2) on attaining adequate busulfan exposure. In this observational study, we included all adults who received an allogeneic HCT with intravenous once daily busulfan over 4 days as part of the conditioning regimen at the University Medical Centre Utrecht or between July 31, 2014 and November 12, 2021. The primary outcome was attainment of the therapeutic busulfan target (cumulative area under the curve [AUCcum] 80-100 mg*h/L). Dose adjustment was based on the estimated AUC of the preceding dosing day(s). Additional TDM was performed in the event of large dose adjustments (≥25%). The choice of TDM regimen was solely based on the first day the busulfan dose was administered (regimen d1 + 2 occurred when conditioning started on a Saturday). In all patients, blood sampling was performed on day 4 for evaluation. The AUCcum was estimated using a validated population pharmacokinetic model. Busulfan target exposure was compared between both TDM regimen groups using a propensity score adjusted logistic regression model. The variance in the AUCcum between the TDM regimens was compared using the F-test. Patients were stratified for age (categorical). In regimen d1, 87.6% (n = 113/129) attained a therapeutic busulfan exposure, while in regimen d1 + 2 a proportion of 97.4% was found (n = 74/76, adjusted odds ratio for non-therapeutic AUC = 0.19, 95% confidence interval [95% CI]: 0.04-0.89). Variance of busulfan exposure in the regimen d1 group (SD = 6.8 mg*h/L) differed significantly from the variance in the regimen d1 + 2 group (SD = 3.6 mg*h/L, F-test, P < .001). Performing busulfan TDM on both day 1 and day 2, rather than only on day 1, improves busulfan target exposure attainment in adults undergoing HCT, provided that subsequent TDM is carried out if required.

Simulation-Based Optimization of Sampling Schedules for Model-Informed Precision Dosing of Once-Daily and 4-Times-Daily Busulfan in Pediatric Patients

BACKGROUND

Therapeutic drug monitoring (TDM) is crucial in optimizing the outcomes of hematopoietic stem cell transplantation by guiding busulfan (Bu) dosing. Limited sampling strategies show promise for efficiently adjusting drug doses. However, comprehensive assessments and optimization of sampling schedules for Bu TDM in pediatric patients are limited. We aimed to establish optimal sampling designs for model-informed precision dosing (MIPD) of once-daily (q24h) and 4-times-daily (q6h) Bu administration in pediatric patients.

METHODS

Simulated data sets were used to evaluate the population pharmacokinetic model-based Bayesian estimation of the area under the concentration-time curve (AUC) for different limited sampling strategy designs. The evaluation was based on the mean prediction error for accuracy and root mean square error for precision. These findings were validated using patient-observed data. In addition, the MIPD protocol was implemented in the Tucuxi software, and its performance was assessed.

RESULTS

Our Bayesian estimation approach allowed for flexible sampling times while maintaining mean prediction error within ±5% and root mean square error below 10%. Accurate and precise AUC0-24h and cumulative AUC estimations were obtained using 2-sample and single-sample schedules for q6h and q24h dosing, respectively. TDM on 2 separate days was necessary to accurately estimate cumulative exposure, especially in patients receiving q6h Bu. Validation with observed patient data confirmed the precision of the proposed limited sampling scenarios. Implementing the MIPD protocol in Tucuxi software yielded reliable AUC estimations.

CONCLUSIONS

Our study successfully established precise limited sampling protocols for MIPD of Bu in pediatric patients. Our findings underscore the importance of TDM on at least 2 occasions to accurately achieve desired Bu exposures. The developed MIPD protocol and its implementation in Tucuxi software provide a valuable tool for routine TDM in pediatric hematopoietic stem cell transplantation.

Model-Informed Precision Dosing of Intravenous Busulfan in Thai Pediatrics Undergoing Hematopoietic Stem Cell Transplantation

BACKGROUND

Conditioning bifunctional agent, busulfan, is commonly used on children before hematopoietic stem cell transplantation. Currently, at the Ramathibodi hospital, Bangkok, Thailand, initial dosing is calculated according to age and body surface area, and 7 samples per day are used for therapeutic drug monitoring (TDM). This study aimed to identify the best strategies for individual dosages a priori from patient characteristics and a posteriori based on TDM.

METHODS

The pharmacokinetic data set consisted of 2018 plasma concentrations measured in 135 Thai (n = 135) pediatric patients (median age = 8 years) and were analyzed using a population approach.

RESULTS

Body weight, presence of malignant disease, and genetic polymorphism of Glutathione S-transferase Alpha-1 (GSTA1) were predictors of clearance. The optimum sampling times for TDM concentration measurements were 0.25, 2, and 5 hours after a 3-hour infusion. This was sufficient to obtain a Bayesian estimate of clearance a posteriori. Simulations showed the poor performance of a priori formula-based dose calculations with 90% of patients demonstrating a 69%-151% exposure interval around the target. This interval shrank to 85%-124% if TDM was carried out only at day 1 and to 90%-116% with TDM at days 1 and 3.

CONCLUSIONS

This comprehensive study reinforces the interest of TDM in managing interindividual variability in busulfan exposure. Therapeutic drug monitoring can reliably be implemented from 3 samples using the Bayesian approach, preferably over 2 days. If using the latter is not possible, the formulas developed herein could present an alternative in Thai patients.

Impact of prophylactic echinocandin on the development of neurological complications in patients receiving busulfan-containing conditioning regimens for stem cell transplantation: A single-center retrospective study

BACKGROUND

Although neurotoxicity is a major adverse event associated with busulfan, little information is available regarding the association between drug interactions and neurological symptoms during busulfan-based regimens. This study evaluated the association between prophylactic echinocandins and neurological complications in patients receiving busulfan-containing conditioning regimens for stem cell transplantation.

METHODS

We retrospectively included consecutive patients who administered intravenous busulfan as a conditioning regimen at our facility between 2007 and 2022. Prophylactic echinocandin use was defined as the use of an echinocandin antifungal drug to prevent invasive fungal disease in SCT recipients. The primary outcome was the incidence of neurological complications within 7 days of busulfan initiation and was compared between the echinocandin group (patients received prophylactic echinocandin) and nonechinocandin group (patients received prophylactic antifungal drugs other than echinocandin and those without antifungal prophylaxis).

RESULTS

Among the 59 patients included in this study, the incidence of neurological complications in the echinocandin (n = 26) and nonechinocandin groups (n = 33) was 30.8% and 63.6%, respectively. We observed a negative association between prophylactic echinocandin use and the development of neurological complications after adjusting for the propensity score for receiving prophylactic echinocandins (adjusted odds ratio 0.294, 95% confidence interval 0.090 to 0.959). We observed a lower incidence of neurological complications in the echinocandin group than in the nonechinocandin group.

CONCLUSION

Our results suggested that the choice of antifungal prophylaxis is associated with busulfan neurotoxicity.

Population Pharmacokinetic Modeling for Twice-Daily Intravenous Busulfan in a Large Cohort of Pediatric Patients Undergoing Hematopoietic Stem Cell Transplantation-A 10-Year Single-Center Experience

Reaching target exposure of busulfan-based conditioning prior to hematopoietic stem cell transplantation is vital for favorable therapy outcomes. Yet, a wide inter-patient and inter-occasion variability in busulfan exposure has been reported, especially in children. We aimed to identify factors associated with the variability of busulfan pharmacokinetics in 124 consecutive patients transplanted at the University Children's Hospital Zurich between October 2010 and February 2020. Clinical data and busulfan plasma levels after twice-daily intravenous administration were analyzed retrospectively by population pharmacokinetic modeling. The volume of distribution correlated with total body water. The elimination rate constant followed an age-dependent maturation function, as previously suggested, and correlated with the levels of serum albumin. Acute lymphoblastic leukemia reduced busulfan clearance by 20%. Clearance significantly decreased by 17% on average from the start to the third day of busulfan administration, in agreement with other studies. An average reduction of 31% was found in patients with hemophagocytic lymphohistiocytosis and X-linked lymphoproliferative disease. In conclusion, we demonstrate that in addition to known factors, underlying disease and serum albumin significantly impact busulfan pharmacokinetics in pediatric patients; yet, substantial unexplained variability in some patients remained. Thus, we consider repeated pharmacokinetic assessment essential to achieve the desired target exposure in twice-daily busulfan administration.

Busulfan target exposure attainment in children undergoing allogeneic hematopoietic cell transplantation: a single day versus a multiday therapeutic drug monitoring regimen

Busulfan exposure has previously been linked to clinical outcomes, hence the need for therapeutic drug monitoring (TDM). Study objective was to evaluate the effect of day 1 TDM-guided dosing (regimen d1) versus days 1 + 2 TDM-guided dosing (regimen d1 + 2) on attaining adequate busulfan exposure. In this observational study, we included all children receiving busulfan-based allogeneic hematopoietic cell transplantation. Primary outcome was the percentage of patients achieving busulfan target attainment in both TDM regimens. Secondary outcomes were the variance in busulfan exposure and day-4 clearance (Clday4) estimates between both TDM regimens and dosing day 1 and 2. In regimen d1, 84.3% (n = 91/108) attained a therapeutic busulfan exposure, while in regimen d1 + 2 a proportion of 90.9% was found (n = 30/33, not-significant). Variance of Clday4 estimate based on busulfan day 2 concentrations was significantly smaller than the variance of Clday4 estimates based on day 1 concentrations (p < 0.001). Therefore, day 1-guided TDM (pharmacometric model-based) of busulfan may be sufficient for attaining optimal target exposure, provided that subsequent TDM is carried out if required. However, performing TDM on subsequent days may be beneficial, as measurements on day 2 seemed to reduce the variance in the estimated clearance as compared to day 1 sampling.

Predicting busulfan exposure in patients undergoing hematopoietic stem cell transplantation using machine learning techniques

PURPOSE

This study aimed to establish an optimal model to predict the busulfan (BU) area under the curve at steady state (AUCss) by using machine learning (ML).

PATIENTS AND METHODS

Seventy-nine adult patients (age ≥18 years) who received BU intravenously and underwent therapeutic drug monitoring from 2013 to 2021 at Fujian Medical University Union Hospital were enrolled in this retrospective study. The whole dataset was divided into a training group and test group at the ratio of 8:2. BU AUCss were considered as the target variable. Nine different ML algorithms and one population pharmacokinetic (pop PK) model were developed and validated, and their predictive performance was compared.

RESULTS

All ML models were superior to the pop PK model (R2 = 0.751, MSE = 0.722, 14 and RMSE = 0.830) in model fitting and had better predictive accuracy. The ML model of BU AUCss established through support vector regression (SVR) and gradient boosted regression trees (GBRT) had the best predictive ability (R2 = 0.953 and 0.953, MSE = 0.323 and 0.326, and RMSE = 0.423 and 0.425).

CONCLUSION

All the ML models can potentially be used to estimate BU AUCss with the aim of facilitating rational use of BU on the individualized level, especially models built by SVR and GBRT algorithms.

Precision Oncology by Point-of-Care Therapeutic Drug Monitoring and Dosage Adjustment of Conventional Cytotoxic Chemotherapies: A Perspective

Therapeutic drug monitoring (TDM) of conventional cytotoxic chemotherapies is strongly supported yet poorly implemented in daily practice in hospitals. Analytical methods for the quantification of cytotoxic drugs are instead widely presented in the scientific literature, while the use of these therapeutics is expected to keep going for longer. There are two main issues hindering the implementation of TDM: turnaround time, which is incompatible with the dosage profiles of these drugs, and exposure surrogate marker, namely total area under the curve (AUC). Therefore, this perspective article aims to define the adjustment needed from current to efficient TDM practice for cytotoxics, namely point-of-care (POC) TDM. For real-time dose adjustment, which is required for chemotherapies, such POC TDM is only achievable with analytical methods that match the sensitivity and selectivity of current methods, such as chromatography, as well as model-informed precision dosing platforms to assist the oncologist with dose fine-tuning based on quantification results and targeted intervals.

Individualizing busulfan dose in specific populations and evaluating the risk of pharmacokinetic drug-drug interactions

INTRODUCTION

Busulfan is an alkylating agent widely used in the conditioning of hematopoietic stem cell transplantation possessing a complex metabolism and a large interindividual and intra-individual variability, especially in children. Combined with the strong rationale of busulfan PK/PD relationships, factors altering its clearance (e.g., weight, age, and GST-A genetic polymorphism mainly) can also affect clinical outcomes.

AREAS COVERED

This review aims to provide an overview of the current knowledge on busulfan pharmacokinetics, its pharmacokinetics variabilities in pediatric populations, drug-drug interactions (DDI), and their consequences regarding dose individualization. This review was based on medical literature up until October 2021.

EXPERT OPINION

To ensure effective busulfan exposure in pediatrics, different weight-based nomograms have been established to determine busulfan dosage and provided improved results (65 - 80% of patients correctly exposed). In addition to nomograms, therapeutic drug monitoring (TDM) of busulfan measuring plasmatic concentrations to estimate busulfan pharmacokinetic parameters can be used. TDM is now widely carried out in routine practices and aims to ensure the targeting of the reported therapeutic windows by individualizing busulfan dosing based on the clearance estimations from a previous dose.

Individualized busulfan dosing improves outcomes compared to fixed-dose administration in pre-transplant minimal residual disease-positive acute myeloid leukemia patients with intermediate-risk undergoing allogeneic stem cell transplantation in CR

Pre-transplant minimal residual disease (MRD) impacts negatively on post-transplant relapse risk in acute myeloid leukemia (AML). Therapeutic drug monitoring by calculating area under the curve (AUC) was developed to optimize busulfan (Bu) exposure. Here, we compared post-transplant outcomes after individualized versus fixed busulfan dosage in intermediate-risk AML who achieved CR prior to allograft focusing on pre-transplant flow-MRD. Eighty-seven patients (median, 56 years) with intermediate-risk AML and pre-transplant flow-MRD ("different from normal") were included. Thirty-two patients received individualized busulfan; 54 fixed dosages. Individualized dosage was adjusted in 25/32 patients: increased, n = 18/25 (72%); decreased: n = 7/25 (28%). After median follow-up of 27 months, we observed lower 3-year relapses (6%, 2%-19% vs. 35%, 23%-49% p = 0.02), improved 3-year leukemia-free survival (LFS) (78%, 54%-91% vs. 55%, 40%-70% p = 0.009) and - overall survival (OS) (82%, 60%-93% vs. 69%, 54%-81% p = 0.05) after individualized compared to fixed Bu. Non-relapsed mortality (NRM) and acute graft versus host disease (GvHD) were not different. In multivariate analysis, fixed Bu showed unfavorable impact on OS (hazard ratio [HR] 4.6, p = 0.044), LFS (HR 3.6, p = 0.018) and relapses (HR 3.6, p = 0.033). Fixed Bu also had unfavorable impact on LFS (3.6, 1.1-12.6, p = 0.041) in pre-transplant MRD-positive patients. Individualized, AUC-based, busulfan is associated with lower relapses in intermediate-risk AML patients allografted in CR and may overcome pre-transplant MRD-positivity.

Evaluation of different pharmacokinetically guided IV busulfan exposure ranges on adult patient outcomes after hematopoietic stem cell transplantation

Conditioning intensity contributes significantly to outcomes in allogeneic hematopoietic stem cell transplantation (allo-HSCT). We evaluated two myeloablative conditioning dosing ranges of intravenous (IV) busulfan (Bu) in combination with fludarabine in 70 patients. In 2015, our practice changed to target busulfan area under the curve (AUC) of ≥ 19.7 mg*h/L. We assessed responses in patients receiving busulfan AUCs of < 19.7 mg*h/L (Low-Bu) and ≥ 19.7 mg*h/L (High-Bu). At 18-month median follow-up, no differences in overall survival (OS) and relapse-free survival (RFS) were found between Low-Bu and High-Bu groups (p = 0.35 and p = 0.29, respectively). Relapses occurred in 25.7% of patients. No differences in median time to relapse were noted. Minimal residual disease (MRD)-positive patients had a shorter median OS and RFS than MRD-negative patients. No differences were found in OS and RFS between Low-Bu and High-Bu groups in MRD-positive patients (p = 0.86 and p = 0.83, respectively), or MRD-negative patients (p = 0.56 and p = 0.38, respectively). Non-relapsed mortality (NRM) at 100 days was 3.4% vs. 4.1% in the Low-Bu vs. High-Bu groups. There were no significant differences in the incidence of acute-graft-versus-host disease (aGVHD) (71.4% vs. 63.4%) or chronic GVHD (cGVHD) (48.3% vs. 43.9%) between the groups. The cumulative incidence of grades III-IV aGVHD was 24.1% in Low-Bu group and 22.4% in High-Bu group. In conclusion, targeting a busulfan AUC of > 19.7 mg*h/L with fludarabine does not appear to add an advantage in OS and RFS.

Role of therapeutic drug monitoring of intravenous Busulfan for prevention of sinusoidal obstructive syndrome in children

BACKGROUND

Therapeutic drug monitoring (TDM) of intravenous busulfan (Bu) has been recommended for safe engraftment and decreased toxicity in children undergoing hematopoietic stem cell transplantation (HSCT). This study aims to compare HSCT-related outcomes, such as acute or chronic graft-versus-host disease (GvHD), sinusoidal obstructive syndrome (SOS), event-free survival (EFS), and overall survival (OS) in children with and without TDM for busulfan.

METHODS

This retrospective study conducted between February 2012 and February 2021 at our Bone Marrow Transplantation Unit included 172 patients (34% girls) with a median age of 4.70 years (IQR 2.41-10.01). Group A consisted of 46 patients whose Bu doses were adjusted according to actual body weight, and group B consisted of 126 patients whose Bu dose adjustments made according to TDM.

RESULTS

Totally, 32 patients (19%) developed moderate or severe SOS. The incidence of SOS was significantly higher in the group without TDM (29% vs. 15%, p = .041). A multivariable analysis showed that the presence of acute GvHD and one alkylating drug-containing conditioning regimen compared with two or three were associated with SOS (p = .03 and p = .002, respectively). In patients with TDM, cumulative Bu dose and area under curve also were not associated with SOS. Other HSCT-related outcomes such as acute or chronic GvHD, relapse and graft rejection rates, OS and EFS rates did not differ between the groups.

CONCLUSIONS

TDM and making dose adjustments with Bayesian forecasting over four days of Bu therapy optimizes exposure and reduces the risk of SOS in children undergoing HSCT.

External Evaluation of Population Pharmacokinetic Models of Busulfan in Chinese Adult Hematopoietic Stem Cell Transplantation Recipients

Objective: Busulfan (BU) is a bi-functional DNA-alkylating agent used in patients undergoing hematopoietic stem cell transplantation (HSCT). Over the last decades, several population pharmacokinetic (pop PK) models of BU have been established, but external evaluation has not been performed for almost all models. The purpose of the study was to evaluate the predictive performance of published pop PK models of intravenous BU in adults using an independent dataset from Chinese HSCT patients, and to identify the best model to guide personalized dosing.

Methods: The external evaluation methods included prediction-based diagnostics, simulation-based diagnostics, and Bayesian forecasting. In prediction-based diagnostics, the relative prediction error (PE%) was calculated by comparing the population predicted concentration (PRED) with the observations. Simulation-based diagnostics included the prediction- and variability-corrected visual predictive check (pvcVPC) and the normalized prediction distribution error (NPDE). Bayesian forecasting was executed by giving prior one to four observations. The factors influencing the model predictability, including the impact of structural models, were assessed.

Results: A total of 440 concentrations (110 patients) were obtained for analysis. Based on prediction-based diagnostics and Bayesian forecasting, preferable predictive performance was observed in the model developed by Huang et al. The median PE% was -1.44% which was closest to 0, and the maximum F₂₀ of 57.27% and F₃₀ of 72.73% were achieved. Bayesian forecasting demonstrated that prior concentrations remarkably improved the prediction precision and accuracy of all models, even with only one prior concentration.

Conclusion: This is the first study to comprehensively evaluate published pop PK models of BU. The model built by Huang et al. had satisfactory predictive performance, which can be used to guide individualized dosage adjustment of BU in Chinese patients.

The Correlation Between Busulfan Exposure and Clinical Outcomes in Chinese Pediatric Patients: A Population Pharmacokinetic Study

Aims: The aims of the study were to 1) establish a population pharmacokinetic (Pop-PK) model for busulfan in Chinese pediatric patients undergoing hematopoietic stem cell transplantation (HSCT) and then estimate busulfan exposure and 2) explore the association between busulfan exposure and clinical outcomes.

Methods: A total of 128 patients with 467 busulfan concentrations were obtained for Pop-PK modeling using nonlinear mixed effect model (NONMEM) software. Sixty-three patients who received the 16-dose busulfan conditioning regimen were enrolled to explore the correlations between clinical outcomes and the busulfan area under the concentration–time curve (AUC) using the Cox proportional hazards regression model, Kaplan–Meier method and logistic regression.

Results: The typical values for clearance (CL) and distribution volume (V) of busulfan were 7.71 L h⁻¹ and 42.4 L, respectively. The allometric normal fat mass (NFM) and maturation function (Fmat) can be used to describe the variability in CL, and the fat-free mass (FFM) can be used to describe the variability in V. Patients with AUCs of 950–1,600 µM × min had 83.7% (95% CI: 73.3–95.5) event-free survival (EFS) compared with 55.0% (95% CI: 37.0–81.8) for patients with low or high exposure (p = 0.024). The logistic regression analysis results showed no association between transplant-related toxicities and the busulfan AUC (p > 0.05).

Conclusions: The variability in busulfan CL was related to the NFM and Fmat, while busulfan V was related to the FFM. Preliminary analysis results suggested that a busulfan AUC of 950–1,600 µM × min was associated with better EFS in children receiving the 16-dose busulfan regimen.

Population Pharmacokinetics of Busulfan and Its Metabolite Sulfolane in Patients with Myelofibrosis Undergoing Hematopoietic Stem Cell Transplantation

For patients with myelofibrosis, allogeneic hematopoietic stem cell transplantation (allo-HSCT) remains the only curative treatment to date. Busulfan-based conditioning regimens are commonly used, although high inter-individual variability (IIV) in busulfan drug exposure makes individual dose selection challenging. Since data regarding the IIV in patients with myelofibrosis are sparse, this study aimed to develop a population pharmacokinetic (PopPK) model of busulfan and its metabolite sulfolane in patients with myelofibrosis. The influence of patient-specific covariates on the pharmacokinetics of drug and metabolite was assessed using non-linear mixed effects modeling in NONMEM^®. We obtained 523 plasma concentrations of busulfan and its metabolite sulfolane from 37 patients with myelofibrosis. The final model showed a population clearance (CL) and volume of distribution (V_d) of 0.217 L/h/kg and 0.82 L/kg for busulfan and 0.021 L/h/kg and 0.65 L/kg for its metabolite. Total body weight (TBW) and a single-nucleotide polymorphism of glutathione-S-transferase A1 (GSTA1 SNP) displayed a significant impact on volume of distribution and metabolite clearance, respectively. This is the first PopPK-model developed to describe busulfan’s pharmacokinetics in patients with myelofibrosis. Incorporating its metabolite sulfolane into the model not only allowed the characterization of the covariate relationship between GSTA1 and the clearance of the metabolite but also improved the understanding of busulfan’s metabolic pathway.

Can First-Dose Therapeutic Drug Monitoring Predict the Steady State Area Under the Blood Concentration-Time Curve of Busulfan in Pediatric Patients Undergoing Hematopoietic Stem Cell Transplantation?

Busulfan has high intra-individual variability and possible time-dependent changes in clearance, which complicates therapeutic drug monitoring (TDM), as first dose sampling may not predict the steady state concentrations. In this study, we aimed to use Bayesian pharmacokinetic parameters estimated from the first dose to predict the steady state AUC for busulfan. This observational study was conducted among pediatric patients at King Abdullah Specialist Children's Hospital. From each patient, we collected six blood samples (2, 2.25, 2.5, 3, 4, and 6 h after the start of IV infusion of the first dose). A subset of patients were also sampled at the steady state. First, we modeled the data using only the first dose. The model was used to estimate the empirical Bayesian estimates of clearance for each individual patient, then we used the empirical Bayesian estimates of clearance to predict the AUC_0-tau at steady state (i.e., predicted AUC_0-tau). Steady state AUC_0-tau was also calculated for patients sampled at steady state using the trapezoidal method using raw time concentration data; this was considered the reference AUC_0-tau.. Then, we compared the AUC_0-tau predicted using the Bayesian approach with the reference AUC_0-tau values. We calculated bias and precision to assess predictability. In total we had 33 patients sampled after first dose and at steady state. Using the Bayesian approach to predict the AUC_0-tau, bias was -2.8% and precision was 33%. This indicates that first dose concentrations cannot accurately predict steady state busulfan concentrations; therefore, follow-up TDM may be required for optimal dosing.

Can Published Population Pharmacokinetic Models of Busulfan Be Used for Individualized Dosing in Chinese Pediatric Patients Undergoing Hematopoietic Stem Cell Transplantation? An External Evaluation

Busulfan is a bifunctional alkylating agent that is widely used before hematopoietic stem cell transplantation (HSCT), in combination with other chemotherapeutic drugs. As of 2020, there is no population pharmacokinetic (popPK) model for busulfan in Chinese pediatric patients. A systemic external evaluation of 11 published popPK models was conducted in Chinese pediatric patients undergoing HSCT. Forty pediatric patients were enrolled in this study, with a total of 183 blood concentrations. The relative prediction error (PE%), median PE%, median absolute PE%, and percentage of PE% within ±20% and ±30% were calculated in prediction-based diagnostics. Simulation-based diagnostics were conducted through a prediction- and variability-corrected visual predictive check and the normalized prediction distribution error. The relative individual prediction error was calculated using Bayesian forecasting with 1 to 3 concentration points. The 1-compartment open linear popPK model, which was built by Su-jin Rhee et al (model H), incorporating the patient's body surface area, age, dosing day, and aspartate aminotransferase as significant covariates had preferable predictability than other popPK models. In prediction-based diagnostics, the median PE%, percentage of PE% within ±20%, and percentage of PE% within ±30% of model H were 8.48%, 45.35%, and 59.56%, respectively. The normalized prediction distribution error of model H showed that it followed the normal distribution. Based on Bayesian forecasting, model H showed good predictive performance. Thus, model H was the most appropriate model that can be used clinically for individualized dosage adjustments in Chinese pediatric HSCT patients.

Evaluation of the Robustness of Therapeutic Drug Monitoring Coupled with Bayesian Forecasting of Busulfan with Regard to Inaccurate Documentation

Background

Inaccurate documentation of sampling and infusion times is a potential source of error in personalizing busulfan doses using therapeutic drug monitoring (TDM). Planned times rather than the actual times for sampling and infusion time are often documented.

Therefore, this study aimed to evaluate the robustness of a limited sampling TDM of busulfan with regard to inaccurate documentation.

Methods

A pharmacometric analysis was conducted in NONMEM® 7.4.3 and “R” by performing stochastic simulation and estimation with four, two and one sample(s) per patient on the basis of a one-compartment- (1CMT) and two-compartment (2CMT) population pharmacokinetic model. The dosing regimens consisted of i.v. busulfan (0.8 mg/kg) every 6 h (Q6H) or 3.2 mg/kg every 24 h (Q24H) with a 2 h- and 3 h infusion time, respectively. The relative prediction error (rPE) and relative root-mean-square error (rRmse) were calculated in order to determine the accuracy and precision of the individual AUC estimation.

Results

A noticeable impact on the estimated AUC based on a 1CMT-model was only observed if uncertain documentation reached ± 30 min (1.60% for Q24H and 2.19% for Q6H). Calculated rPEs and rRmse for Q6H indicate a slightly lower level of accuracy and precision when compared to Q24H. Spread of rPE’s and rRmse for the 2CMT-model were wider and higher compared to estimations based on a 1CMT-model.

Conclusions

The estimated AUC was not affected substantially by inaccurate documentation of sampling and infusion time. The calculated rPEs and rRmses of estimated AUC indicate robustness and reliability for TDM of busulfan, even in presence of erroneous records.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11095-021-03115-8.

Precision dosing of intravenous busulfan in pediatric hematopoietic stem cell transplantation: Results from a multicenter population pharmacokinetic study

Busulfan (Bu) is a common component of conditioning regimens before hematopoietic stem cell transplantation (HSCT) and is known for high interpatient pharmacokinetic (PK) variability. This study aimed to develop and externally validate a multicentric, population PK (PopPK) model for intravenous Bu in pediatric patients before HSCT to first study the influence of glutathione‐s‐transferase A1 (GSTA1) polymorphisms on Bu's PK in a large multicentric pediatric population while accounting for fludarabine (Flu) coadministration and, second, to establish an individualized, model‐based, first‐dose recommendation for intravenous Bu that can be widely used in pediatric patients. The model was built using data from 302 patients from five transplantation centers who received a Bu‐based conditioning regimen. External model validation used data from 100 patients. The relationship between body weight and Bu clearance (CL) was best described by an age‐dependent allometric scaling of a body weight model. A stepwise covariate analysis identified Day 1 of Bu conditioning, GSTA1 metabolic groups based on GSTA1 polymorphisms, and Flu coadministration as significant covariates influencing Bu CL. The final model adequately predicted Bu first‐dose CL in the external cohort, with 81% of predicted area under the curves within the therapeutic window. The final model showed minimal bias (mean prediction error, −0.5%; 95% confidence interval [CI], −3.1% to 2.0%) and acceptable precision (mean absolute prediction error percentage, 18.7%; 95% CI, 17.0%–20.5%) in Bu CL prediction for dosing. This multicentric PopPK study confirmed the influence of GSTA1 polymorphisms and Flu coadministration on Bu CL. The developed model accurately predicted Bu CL and first doses in an external cohort of pediatric patients.

To Estimate or to Forecast? Lessons From a Comparative Analysis of Four Bayesian Fitting Methods Based on Nonparametric Models

ABSTRACT

Using pharmacokinetic (PK) models and Bayesian methods in dosing software facilitates the analysis of individual PK data and precision dosing. Several Bayesian methods are available for computing Bayesian posterior distributions using nonparametric population models. The objective of this study was to compare the performance of the maximum a posteriori (MAP) model, multiple model (MM), interacting MM (IMM), and novel hybrid MM(HMM) in estimating past concentrations and predicting future concentrations during therapy. Amikacin and vancomycin PK data were analyzed in older hospitalized patients using 2 strategies. First, the entire data set of each patient was fitted using each of the 4 methods implemented in BestDose software. Then, the 4 methods were used in each therapeutic drug monitoring occasion to estimate the past concentrations available at this time and to predict the subsequent concentrations to be observed on the next occasion. The bias and precision of the model predictions were compared among the methods. A total of 406 amikacin concentrations from 96 patients and 718 vancomycin concentrations from 133 patients were available for analysis. Overall, significant differences were observed in the predictive performance of the 4 Bayesian methods. The IMM method showed the best fit to past concentration data of amikacin and vancomycin, whereas the MM method was the least precise. However, MM best predicted the future concentrations of amikacin. The MAP and HMM methods showed a similar predictive performance and seemed to be more appropriate for the prediction of future vancomycin concentrations than the other models were. The richness of the prior distribution may explain the discrepancies between the results of the 2 drugs. Although further research with other drugs and models is necessary to confirm our findings, these results challenge the widely accepted assumption in PK modeling that a better data fit indicates better forecasting of future observations.

Evaluation of two software using Bayesian methods for monitoring exposure and dosing once-daily intravenous busulfan in paediatric patients receiving haematopoietic stem cell transplantation

AIM

To assess the ability of model-based personalised dosing tools to estimate busulfan exposure (i) in comparison to clinically used intensive sampling exposure estimation procedure, (ii) using limited sampling strategies and (iii) to predict changes in busulfan clearance during busulfan treatment.

METHODS

Data on intravenous busulfan dosing for patients with 4 consecutive days were entered into Bayesian forecasting software, InsightRX and NextDose. Prediction of busulfan cumulative exposure was compared to current clinical practice estimation, aiming for pre-defined individualised target of cumulative exposure. Estimation performance was tested given several limited sampling strategies.

RESULTS

Thirty-two paediatric patients (0.2-16.5 years) provided a total of 103 daily exposure measurements estimated using 7 samples taken per day (full sampling), with 19 patients having sampling following all doses administered. Both software tools utilising Bayesian methods provided acceptable relative bias and precision of cumulative exposure estimations under the tested sampling scenarios. Relative bias ranged from median RE of 0.1-14.6% using InsightRX and from 3.4-7.8% using NextDose. Precision ranged from median RMSE of 0.19-0.32 mg·h·L^-1 for InsightRX and 0.08-0.1 mg·h·L^-1 for NextDose. A median reduction in busulfan clearance from day 1 to day 4 was observed in the clinical data (-10.9%), when using InsightRX (-18.6%) and with NextDose (-14.7%).

CONCLUSION

Bayesian methods were shown to have relatively low bias and precisely estimate busulfan exposure using intensive sampling and several limited sampling strategies, which provides evidence for prospective studies to evaluate these tools in clinical practice. A trend to overestimation of exposure using Bayesian methods was observed compared to clinical practice. Reduction of busulfan clearance from day 1 to 4 of once daily dosing was confirmed and should be considered when adjusting doses.