Population pharmacokinetics and pharmacodynamics of busulfan with GSTA1 polymorphisms in patients undergoing allogeneic hematopoietic stem cell transplantation

Pharmacokinetic Modeling and Simulation with Pharmacogenetic Insights Support the Relevance of Therapeutic Drug Monitoring for Myeloablative Busulfan Dosing in Adult HSCT

Therapeutic drug monitoring (TDM) of busulfan (Bu) is well-established in pediatric hematopoietic stem cell transplantation (HSCT), but its use in adults is limited due to a lack of clear recommendations and scarcity of evidence regarding its utility. GSTA1 promoter variants are reported to affect Bu clearance in both adults and pediatric patients. This study aimed to evaluate the value of preemptive genotyping GSTA1 and body composition (obesity) in individualizing Bu dosing in adults, through pharmacokinetic (PK) modeling and simulations. A population pharmacokinetic (PopPK) model was developed and validated with data from 60 adults who underwent HSCT. Simulations assessed different dosing scenarios based on body size metrics and GSTA1 genotypes. Due to the limited number of obese patients in the cohort, the effect of obesity on Bu pharmacokinetics (PK) was evaluated in silico using a physiologically-based pharmacokinetic (PBPK) model and relevant virtual populations from Simcyp software. Patients with at least 1 GSTA1*B haplotype had 17% lower clearance on average. PopPK simulations indicated that adjusting doses based on genotype increased the probability of achieving the target exposure (3.7 to 5.5 mg.h/L) from 53% to 60 % in GSTA1*A homozygous patients, and from 50% to 61% in *B carriers. Still, Approximately 40% of patients would not achieve this therapeutic window without TDM. A 2-sample optimal design was validated for routine model-based Bu first dose AUC0-∞ estimation, and the model was implemented in the Tucuxi user-friendly TDM software. PBPK simulations confirmed body surface area-based doses of 29 to 31 mg/m2/6h as the most appropriate, regardless of obesity status. This study emphasizes the importance of individualized Bu dosing strategies in adults to achieve therapeutic targets. Preemptive genotyping alone may not have a significant clinical impact, and routine TDM may be necessary for optimal transplantation outcomes.

Saliva as a noninvasive sampling matrix for therapeutic drug monitoring of intravenous busulfan in Chinese patients undergoing hematopoietic stem cell transplantation: A prospective population pharmacokinetic and simulation study

Therapeutic drug monitoring (TDM) of busulfan (BU) is currently performed by plasma sampling in patients undergoing hematopoietic stem cell transplantation (HSCT). Saliva samples are considered a noninvasive TDM matrix. Currently, no salivary population pharmacokinetics (PopPKs) model for BU available. This study aimed to develop a PopPK model that can describe the relationship between plasma and saliva kinetics in patients receiving intravenous BU. The performance of the model in predicting the area under the concentration-time curve at steady state (AUCss ) based on saliva samples is evaluated. Sixty-six patients with HSCT were recruited and administered 0.8 mg/kg BU intravenously. A PopPK model for saliva and plasma was developed using the nonlinear mixed effects model. Bayesian maximum a posteriori (MAP) optimization was used to estimate the model's predictive performance. Plasma and saliva PKs were adequately described with a one-compartment model and a scaled central compartment. Body surface area correlated positively with both clearance and apparent volume of distribution (Vd), whereas alkaline phosphatase correlated negatively with Vd. Simulations demonstrated that the percentage root mean squared prediction error and lower and upper limits of agreements reduced to 10.02% and -16.96% to 22.86% based on five saliva samples. Saliva can be used as an alternative matrix to plasma in TDM of BU. The AUCss can be predicted from saliva concentration by Bayesian MAP optimization, which can be used to design personalized dosing for BU.

Effect of pharmacokinetics and pharmacogenomics in adults with allogeneic hematopoietic cell transplantation conditioned with Busulfan

Busulfan (Bu) combined with cyclophosphamide (Cy) is commonly used as a myeloablative conditioning regimen for allogeneic hematopoietic cell transplantation (allo-HCT). There is inter-individual variability of Bu pharmacokinetics (PK) and hence in toxicity and efficacy. The introduction of therapeutic drug monitoring (TDM) of Bu has decreased toxicity of the regimen. Hepatic metabolism of Bu is mediated through Glutathione-S-Transferases (GSTs), mainly GSTA1. Patients with GSTA1*A variants are considered normal metabolizers and GSTA1*B corresponds to poor metabolism, defined by nucleotide changes at -52 or -69 locus in GSTA1 promoter region. The aim of the study was to explore the correlation between GSTA1 polymorphisms and Bu-PK in 60 adult patients receiving an allo-HCT in the BuCyBu clinical study (ClinicalTrials.gov I, ID NCT01779882) comparing the sequence BuCy to CyBu. DNA samples prior to conditioning were genotyped for candidate variants at -52 (rs3957356) and -69 (rs3957357) loci in the GSTA1 promoter. Thirty-three % of patients were GSTA1*A*A, 49% GSTA1*A*B and 18% GSTA1*B*B. In GSTA1*A*A patients, median Bu-AUC was 3.6 ± 0.7 mg*h/L, in GSTA1*A*B 4.5 ± 1.6 and in GSTA1*B*B 4.9 ± 1.4 (AUC 35% higher than GSTA1*A*A, p = 0.03), with a similar significant correlation with Bu-clearance (p = 0.04). The correlation between GSTA1 polymorphism and AUC remained significant in multivariate linear regression analysis. There was a trend for lower non-relapse mortality (NRM) in patients with low AUC. We could not demonstrate a correlation between GSTA1 polymorphisms and NRM, acute graft-versus-host disease (aGvHD) in this small cohort, but there is a trend of higher aGvHD incidence in GSTA1*B*B patients.

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.

Population Pharmacokinetic Model of Intravenous Busulfan in Hematopoietic Cell Transplantation: Systematic Review and Comparative Simulations

BACKGROUND

Busulfan is commonly used in the chemotherapy prior to hematopoietic cell transplantation (HCT). Busulfan has a narrow therapeutic window and a well-established exposure-response relationship with important clinical outcomes. Model-informed precision dosing (MIPD) based on population pharmacokinetic (popPK) models has been implemented in the clinical settings. We aimed to systematically review existing literature on popPK models of intravenous busulfan.

METHODS

We systematically searched Ovid MEDLINE, EMBASE, Cochrane Library, Scopus, and Web of Science databases from inception to December 2022 to identify original popPK models (nonlinear mixed-effect modeling) of intravenous busulfan in HCT population. Model-predicted busulfan clearance (CL) was compared using US population data.

RESULTS

Of the 44 eligible popPK studies published since 2002, 68% were developed predominantly in children, 20% in adults, and 11% in both children and adults. The majority of the models were described using first-order elimination or time-varying CL (69% and 26%, respectively). All but three included a body-size descriptor (e.g., body weight, body surface area). Other commonly included covariates were age (30%) and GSTA1 variant (15%). Median between-subject and between-occasion variabilities of CL were 20% and 11%, respectively. Between-model variabilities in predicted median CL were < 20% in all of the weight tiers (10-110 kg) in the simulation based on US population data.

CONCLUSION

Busulfan PK is commonly described using a first-order elimination or time-varying CL. A simple model with limited covariates were generally sufficient to attain relatively small unexplained variabilities. However, therapeutic drug monitoring may still be necessary to attain a narrow target exposure.

Personalized hematopoietic stem cell transplantation for inborn errors of immunity

Patients with inborn errors of immunity (IEI) have been transplanted for more than 50 years. Many long-term survivors have ongoing medical issues showing the need for further improvements in how hematopoietic stem cell transplantation (HSCT) is performed if patients in the future are to have a normal quality of life. Precise genetic diagnosis enables early treatment before recurrent infection, autoimmunity and organ impairment occur. Newborn screening for severe combined immunodeficiency (SCID) is established in many countries. For newly described disorders the decision to transplant is not straight-forward. Specific biologic therapies are effective for some diseases and can be used as a bridge to HSCT to improve outcome. Developments in reduced toxicity conditioning and methods of T-cell depletion for mismatched donors have made transplant an option for all eligible patients. Further refinements in conditioning plus precise graft composition and additional cellular therapy are emerging as techniques to personalize the approach to HSCT for each patient.

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.

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.

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.

Effect of GSTA1 Variants on Busulfan-Based Conditioning Regimen Prior to Allogenic Hematopoietic Stem-Cell Transplantation in Pediatric Asians

Busulfan is widely used as a chemotherapy treatment before hematopoietic stem-cell transplantation (HSCT). However, the response of busulfan is highly variable and unpredictable, whereby the pharmacogenetic interference of glutathione S-transferase (GST) has strong evidence in Caucasians and some adult Asians but not in pediatric Asian patients. This study was aimed at investigating the associations of GST genetic polymorphisms with variations in the pharmacokinetic (PK) properties of busulfan in pediatric Asian patients. This retrospective cohort study recruited 92 pediatric patients. The polymorphism of GSTA1 was genotyped by Sanger sequencing, and GSTM1 and GSTP1 were genotyped by real-time PCR. Drug concentration and PK estimation were identified using an LC-MS/MS method and a noncompartmental model. Statistical analysis was performed by R software. Out of 92 patients, 48 (53%) were males, the mean age was 8.4 ± 5.12 years old, and the average weight was 26.52 ± 14.75 kg. The allele frequencies of GSTA1*B and of GSTM1 and GSTP1* deletions were 16.9%, 68.5%, and 21.2%, respectively. Patients with GSTA1*B had a statistically significant impact on the PK of busulfan, whereas those with GSTM1 and GSTP1 did not (p > 0.05). The carriers of GSTA1*B showed a significant difference compared to noncarriers in terms of t1/2 (for first dose: 161.9 vs. 134.3 min, p = 0.0016; for second dose: 156.1 vs. 129.8, p = 0.012), CL (88.74 vs. 124.23 mL/min, p = 0.0089), Cmax (4232.6 vs. 3675.5 ng/mL, p = 0.0021), and AUC (5310.6 vs. 4177.1 µM/min, p = 0.00033). The augmentation of AUC was around 27.1% in patients carrying the GSTA1*B variant. The GSTA1 polymorphism was significantly associated with variations of the pharmacokinetic properties of busulfan treatment in pediatric Asian patients.

Clinical pharmacology of cytotoxic drugs in neonates and infants: Providing evidence-based dosing guidance

Cancer in neonates and infants is a rare but challenging entity. Treatment is complicated by marked physiological changes during the first year of life, excess rates of toxicity, mortality, and late effects. Dose optimisation of chemotherapeutics may be an important step to improving outcomes. Body size–based dosing is used for most anticancer drugs used in infants. However, dose regimens are generally not evidence based, and dosing strategies are frequently inconsistent between tumour types and treatment protocols. In this review, we collate available pharmacological evidence supporting dosing regimens in infants for a wide range of cytotoxic drugs. A systematic review was conducted, and available data ranked by a level of evidence (1–5) and a grade of recommendation (A–D) provided on a consensus basis, with recommended dosing approaches indicated as appropriate. For 9 of 29 drugs (busulfan, carboplatin, cyclophosphamide, daunorubicin, etoposide, fludarabine, isotretinoin, melphalan and vincristine), grade A was scored, indicating sufficient pharmacological evidence to recommend a dosing algorithm for infants. For busulfan and carboplatin, sufficient data were available to recommend therapeutic drug monitoring in infants. For eight drugs (actinomycin D, blinatumomab, dinutuximab, doxorubicin, mercaptopurine, pegaspargase, thioguanine and topotecan), some pharmacological evidence was available to guide dosing (graded as B). For the remaining drugs, including commonly used agents such as cisplatin, cytarabine, ifosfamide, and methotrexate, pharmacological evidence for dosing in infants was limited or non-existent: grades C and D were scored for 10 and 2 drugs, respectively. The review provides clinically relevant evidence-based dosing guidance for cytotoxic drugs in neonates and infants.

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Treating cancer in neonates and infants is challenging.

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Dose optimisation of cytotoxic drugs is an important step to improving outcomes.

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Clinical pharmacological evidence supporting dosing regimens in infants was collated.

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All available pharmacological evidence was ranked by a level of evidence.

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A grade of recommendation was derived and a recommended dose per agent provided.

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.

Therapeutic drug monitoring of intravenous busulfan in Thai children undergoing hematopoietic stem cell transplantation: A pilot study

Busulfan (Bu) is commonly used in myeloablative conditioning regimens for children undergoing hematopoietic stem cell transplantation. The standard target area under the concentration-time curve (AUC) of Bu is approximately 900-1500 µM min. In previous studies using five fixed doses (0.8-1.2 mg/kg) for Bu without dose adjustment, 75% patients achieved the target AUC. The aim of this pilot study was to determine the percentage of target AUC for intravenous (IV) Bu in Thai children. IV Bu was administered every 6 h over 16 doses. Blood samples were collected for pharmacokinetic (PK) analysis after the first, ninth, and thirteenth doses of Bu. Seven patients (2-14 years; median 6 years) were diagnosed with thalassemia (n = 4), acute myeloid leukemia (n = 2), and pure red cell aplasia. Three, two, and two patients received Bu at 1.1, 1.2, and 0.8 mg/kg, respectively. The AUC of Bu varied from 292-1714 µM min (median = 804). Nine (42.86%), eleven (52.38%), and one (4.76%) AUC values were within, below, and above the target, respectively. The median (range) Bu clearance was 5.93 (1.91-14.65) mL/min/kg. In this study, 42.86% AUC value achieved the target, which was lower than that in previous studies. Therapeutic drug monitoring (TDM) of Bu should be considered in Thai children receiving five fixed doses of IV Bu, and dose adjustment should be performed as necessary. Further PK studies for Bu with a larger sample size are warranted for confirming the necessity of TDM in every step dose of Bu.(Trial registration numbers; TCTR20190528003).

The analysis of GSTA1 promoter genetic and functional diversity of human populations

GSTA1 encodes a member of a family of enzymes that function to add glutathione to target electrophilic compounds, including carcinogens, therapeutic drugs, environmental toxins, and products of oxidative stress. GSTA1 has several functional SNPs within its promoter region that are responsible for a change in its expression by altering promoter function. This study aims to investigate distributions of GSTA1 promoter haplotypes across different human populations and to assess their impact on the expression of GSTA1. PHASE 2.1.1 was used to infer haplotypes and diplotypes of six GSTA1 promoter SNPs on 2501 individuals from 26 populations classified by the 1000 Genomes Project into five super-populations that included Africa (N = 660), America (N = 347), East Asia (N = 504), Europe (N = 502), and South Asia (N = 488). We used pairwise FST analysis to compare sub-populations and luciferase reporter assay (LRA) to evaluate the impact of each SNP on activation of transcription and interaction with other SNPs. The distributions of GSTA1 promoter haplotypes and diplotypes were significantly different among the different human populations. Three new promoter haplotypes were found in the African super-population. LRA demonstrated that SNPs at -52 and -69 has the most impact on GSTA1 expression, however other SNPs have a significant impact on transcriptional activity. Based on LRA, a new model of cis-elements interaction is presented. Due to the significant differences in GSTA1 diplotype population frequencies, future pharmacogenomics or disease-related studies would benefit from the inclusion of the complete GSTA1 promoter haplotype based on the newly proposed metabolic grouping derived from the LRA results.

Optimization of Busulfan Dosing Regimen in Pediatric Patients Using a Population Pharmacokinetic Model Incorporating GST Mutations

Purpose

The aim of this study was to develop a novel busulfan dosing regimen, based on a population pharmacokinetic (PPK) model in Chinese children, and to achieve better area under the concentration-time curve (AUC) targeting.

Patients and Methods

We collected busulfan concentration-time samples from 69 children who received intravenous busulfan prior to allogeneic hematopoietic stem cell transplantation (allo-HSCT). A population pharmacokinetic model for busulfan was developed by nonlinear mixed effect modelling and was validated by an external dataset (n=14). A novel busulfan dosing regimen was developed through simulated patients, and has been verified on real patients. Limited sampling strategy (LSS) was established by Bayesian forecasting. Mean absolute prediction error (MAPE) and relative root mean Squared error (rRMSE) were calculated to evaluate predictive accuracy.

Results

A one-compartment model with first-order elimination best described the data. GSTA1 genotypes, body surface area (BSA) and aspartate aminotransferase (AST) were found to be significant covariates of Bu clearance, and BSA had significant impact of the volume of distribution. Moreover, two equations were obtained for recommended dose regimens: dose (mg)=34.14×BSA (m²)+3.75 (for GSTA1 *A/*A), Dose (mg)=30.99×BSA (m²)+3.21 (for GSTA1 *A/*B). We also presented a piecewise dosage based on BSA categories for each GSTA1 mutation. A two-point LSS, two hours and four hours after dosing, behaved well with acceptable prediction precision (rRMSE=1.026%, MAPE=6.55%).

Conclusion

We recommend a GSTA1-BSA and BSA-based dosing (Q6 h) based on a PPK model for personalizing busulfan therapy in pediatric population. Additionally, an optimal LSS (C_2h and C_4h) provides convenience for therapeutic drug monitoring (TDM) in the future.

Total Body Irradiation Forever? Optimising Chemotherapeutic Options for Irradiation-Free Conditioning for Paediatric Acute Lymphoblastic Leukaemia

Total-body irradiation (TBI) based conditioning prior to allogeneic hematopoietic stem cell transplantation (HSCT) is generally regarded as the gold-standard for children >4 years of age with acute lymphoblastic leukaemia (ALL). Retrospective studies in the 1990's suggested better survival with irradiation, confirmed in a small randomised, prospective study in the early 2000's. Most recently, this was reconfirmed by the early results of the large, randomised, international, phase III FORUM study published in 2020. But we know survivors will suffer a multitude of long-term sequelae after TBI, including second malignancies, neurocognitive, endocrine and cardiometabolic effects. The drive to avoid TBI directs us to continue optimising irradiation-free, myeloablative conditioning. In chemotherapy-based conditioning, the dominant myeloablative effect is provided by the alkylating agents, most commonly busulfan or treosulfan. Busulfan with cyclophosphamide is a long-established alternative to TBI-based conditioning in ALL patients. Substituting fludarabine for cyclophosphamide reduces toxicity, but may not be as effective, prompting the addition of a third agent, such as thiotepa, melphalan, and now clofarabine. For busulfan, it's wide pharmacokinetic (PK) variability and narrow therapeutic window is well-known, with widespread use of therapeutic drug monitoring (TDM) to individualise dosing and control the cumulative busulfan exposure. The development of first-dose selection algorithms has helped achieve early, accurate busulfan levels within the targeted therapeutic window. In the future, predictive genetic variants, associated with differing busulfan exposures and toxicities, could be employed to further tailor individualised busulfan-based conditioning for ALL patients. Treosulfan-based conditioning leads to comparable outcomes to busulfan-based conditioning in paediatric ALL, without the need for TDM to date. Future PK evaluation and modelling may optimise therapy and improve outcome. More recently, the addition of clofarabine to busulfan/fludarabine has shown encouraging results when compared to TBI-based regimens. The combination shows activity in ALL as well as AML and deserves further evaluation. Like busulfan, optimization of chemotherapy conditioning may be enhanced by understanding not just the PK of clofarabine, fludarabine, treosulfan and other agents, but also the pharmacodynamics and pharmacogenetics, ideally in the context of a single disease such as ALL.

A semi-mechanistic model based on glutathione depletion to describe intra-individual reduction in busulfan clearance

Aim

To develop a semi‐mechanistic model, based on glutathione depletion and predict a previously identified intra‐individual reduction in busulfan clearance to aid in more precise dosing.

Methods

Busulfan concentration data, measured as part of regular care for allogeneic hematopoietic cell transplantation (HCT) patients, were used to develop a semi‐mechanistic model and compare it to a previously developed empirical model. The latter included an empirically estimated time effect, where the semi‐mechanistic model included theoretical glutathione depletion. As older age has been related to lower glutathione levels, this was tested as a covariate in the semi‐mechanistic model. Lastly, a therapeutic drug monitoring (TDM) simulation was performed comparing the two models in target attainment.

Results

In both models, a similar clearance decrease of 7% (range −82% to 44%), with a proportionality to busulfan metabolism, was found. After 40 years of age, the time effect increased with 4% per year of age (0.6–8%, P = 0.009), causing the effect to increase more than a 2‐fold over the observed age‐range (0–73 years). Compared to the empirical model, the final semi‐mechanistic model increased target attainment from 74% to 76%, mainly through better predictions for adult patients.

Conclusion

These results suggest that the time‐dependent decrease in busulfan clearance may be related to gluthathione depletion. This effect increased with older age (>40 years) and was proportional to busulfan metabolism. The newly constructed semi‐mechanistic model could be used to further improve TDM‐guided exposure target attainment of busulfan in patients undergoing HCT.

Population pharmacokinetics of busulfan in Saudi pediatric patients undergoing hematopoietic stem cell transplantation

Background Busulfan is an antineoplastic drug that is used widely as part of a conditioning regimen in pediatric patients undergoing hematopoietic stem cell transplantation. It has a narrow therapeutic index and highly variable pharmacokinetics; therefore therapeutic drug monitoring is recommended to optimize busulfan dosing. Objective To study the population pharmacokinetics of busulfan in Saudi pediatric patients to optimize its dosing. Settings King Abdullah Specialist Children's Hospital in Riyadh, Saudi Arabia. Methods This pharmacokinetic observational study was conducted between January 2016 and December 2018. All pediatric patients receiving IV busulfan and undergoing routine therapeutic drug monitoring were included. Population pharmacokinetics modeling was conducted using Monolix2019R1. Pharmacokinetic data of busulfan in children. Results The study included 59 patients and 513 samples. The mean ± SD age was 6.10 ± 3.17 years, and the dose administered was 0.994 ± 0.15 mg/kg. The mean ± SD Cmax and area under the curve (AUC) were 900.60 ± 402.8 ng/mL and 1031.14 ± 300.75 µM min, respectively. Based on our simulations, the European Medicines Agency recommended dose were adequate for most patient's groups to achieve the conventional target of an AUC_0-tau of 900-1350 µM min. For patients in the lower weight group < 9 kg, higher doses were need at 1.2 mg/kg. With regards to the newly proposed target of AUC 78-101 mg h/mL, all of the doses we tested had low probability of achieving it. Conclusions Most of our patients had less than a proportional increase in busulfan concentration suggesting autoinduction. The high interindividual variability and autoinduction make dose adjustments challenging and AUC at steady state difficult to predict from the first dose. One approach to improve dose predictions is to use Bayesian dosing software. Based on our simulations, the European Medicines Agency recommended doses were adequate for most patient groups, except those in the lower (< 9 kg) and higher weight groups (> 34 kg).

Population pharmacokinetic analysis of intravenous busulfan: GSTA1 genotype is not a predictive factor of initial dose in Chinese adult patients undergoing hematopoietic stem cell transplantation

PURPOSE

This study aimed to develop a population pharmacokinetic (PPK) model to investigate the impact of GSTA1, GSTP1, and GSTM1 genotypes on busulfan pharmacokinetic (PK) variability in Chinese adult patients.

METHODS

Forty-three and 19 adult patients who underwent hematopoietic stem cell transplantation (HSCT) were enrolled for modeling group and validation group, respectively. All patients received twice-daily intravenous busulfan as part of conditioning regimen before HSCT. The PPK model was developed by nonlinear mixed-effect modeling. Covariates investigated were age, sex, actual body weight, body surface area, diagnoses, hepatic function markers, GST genotypes and conditioning regimen.

RESULTS

A total of 488 busulfan concentrations from 43 patients were obtained for the PPK model. The PK of intravenous busulfan was described by one-compartment model with first-order elimination with estimated clearance (CL) of 14.2 L/h and volume of distribution of 64.1 L. Inclusion of GSTA1 genotype as a covariate accounted for 1.1% of the inter-individual variability of busulfan CL (from 17.8% in the basic model to 16.7% in the final model). The accuracy and applicability of the final model were externally validated in the independent group. The difference of busulfan PK between Chinese patients and Caucasian patients existed because of the rarity of haplotype *B in Chinese population.

CONCLUSIONS

Although the GSTA1 genotype-based PPK model of intravenous busulfan was successfully developed and externally validated, the GSTA1 genotype was not considered to be clinically relevant to busulfan CL. We did not suggest the guidance of GSTA1 genotype on initial busulfan dose in Chinese adult patients.

Impact of GSTA1 Polymorphisms on Busulfan Oral Clearance in Adult Patients Undergoing Hematopoietic Stem Cell Transplantation

Background: Busulfan pharmacokinetics exhibit large inter-subject variability. Our objective was to evaluate the influence of glutathione S-transferase A1 (GSTA1) gene variants on busulfan oral clearance (CLo) in a population of patients undergoing hematopoietic stem cell transplantation. Methods: This is a quasi-experimental retrospective study in adult patients (n = 87 included in the final analyses) receiving oral busulfan. Pharmacokinetics data (area under the plasma concentration-time curve (AUC) determined from 10 blood samples) were retrieved from patients’ files and GSTA1 *A and *B allele polymorphisms determined from banked DNA samples. Three different limited sampling methods (LSM) using four blood samples were also compared. Results: Carriers of GSTA1*B exhibited lower busulfan CLo than patients with an *A/*A genotype (p < 0.002): Busulfan CLo was 166 ± 31, 187 ± 37 vs. 207 ± 47 mL/min for GSTA1*B/*B,*A/*B and *A/*A genotypes, respectively. Similar results were obtained with the tested LSMs. Using the standard AUC method, distribution of patients above the therapeutic range after the first dose was 29% for GSTA1*A/*A, 50% for *A/*B, and 65% for *B/*B. The LSMs correctly identified ≥91% of patients with an AUC above the therapeutic range. The misclassified patients had a mean difference less than 5% in their AUCs. Conclusion: Patients carrying GSTA1 loss of function *B allele were at increased risk of overdosing on their initial busulfan oral dose. Genetic polymorphisms associated with GSTA1 explain a significant part of busulfan CLo variability which could be captured by LSM strategies.

Effect of glutathione S-transferase genetic polymorphisms on busulfan pharmacokinetics and veno-occlusive disease in hematopoietic stem cell transplantation: A meta-analysis

This meta-analysis was conducted to derive an integrated conclusion about the influence of glutathione S-transferase (GST) genetic polymorphisms on busulfan pharmacokinetic (PK) parameters and veno-occlusive disease (VOD). Studies which analysed the effect of GST genetic polymorphisms on area under the curve (AUC), clearance (CL) or VOD were searched for and selected. A pooled analysis was conducted using Comprehensive Meta-Analysis programme. Nineteen studies were included in this meta-analysis. GSTA1*B and GSTM1 null genotypes significantly decreased CL_IV of busulfan (standardized difference in means (SDM) = -1.103; P = 0.019 and SDM = -0.418; P = 0.002, respectively). GSTA1*B significantly increased AUC_IV of busulfan (SDM = 0.832; P = 0.046), whereas GSTM1 did not (SDM = 0.155; P = 0.478). The PK parameters of oral busulfan did not differ according to GST genotype. GSTA1, GSTM1 and GSTP1 were not significantly associated with VOD occurrence. GSTA1 and GSTM1 genotypes affected CL_IV of busulfan, but only GSTA1 affected AUC_IV . There was no significant difference in the PK parameters of oral busulfan (CL_PO and AUC_PO ) and VOD when only GST genotypes were considered.

Glutathione S-transferase π: a potential role in antitumor therapy

Glutathione S-transferase π (GSTπ) is a Phase II metabolic enzyme that is an important facilitator of cellular detoxification. Traditional dogma asserts that GSTπ functions to catalyze glutathione (GSH)-substrate conjunction to preserve the macromolecule upon exposure to oxidative stress, thus defending cells against various toxic compounds. Over the past 20 years, abnormal GSTπ expression has been linked to the occurrence of tumor resistance to chemotherapy drugs, demonstrating that this enzyme possesses functions beyond metabolism. This revelation reveals exciting possibilities in the realm of drug discovery, as GSTπ inhibitors and its prodrugs offer a feasible strategy in designing anticancer drugs with the primary purpose of reversing tumor resistance. In connection with the authors' current research, we provide a review on the biological function of GSTπ and current developments in GSTπ-targeting drugs, as well as the prospects of future strategies.

Incorporation of GSTA1 genetic variations into a population pharmacokinetic model for IV busulfan in paediatric hematopoietic stem cell transplantation

AIMS

The aim of this study is to develop a population pharmacokinetic (PopPK) model for intravenous busulfan in children that incorporates variants of GSTA1, gene coding for the main enzyme in busulfan metabolism.

METHODS

Busulfan concentration-time data was collected from 112 children and adolescents (median 5.4 years old, range: 0.1-20) who received intravenous busulfan during the conditioning regimen prior to stem cell transplantation. Weight, sex, baseline disease (malignant vs. non-malignant), age, conditioning regimen and GSTA1 diplotypes were evaluated as covariates of pharmacokinetic parameters by using nonlinear mixed effects analysis. The ability to achieve the target AUC_24h (3600-6000 μM min^-1 ) was assessed by estimating the first dose based on the present PopPK model and by comparing the results with other available models in children.

RESULTS

A one-compartment model with first-order elimination best described the data. Allometric scaling of weight and a factor of busulfan metabolism maturation were included in the base model. GSTA1 diplotypes were found to be a significant covariate of busulfan clearance, which was 7% faster in rapid metabolizers and 12% slower in poor metabolizers, in comparison with normal ones. Busulfan doses calculated using the parameters of the proposed PopPK model were estimated to achieve the target AUC in 85.2% of the cases (95% CI 78.7-91.7%).

CONCLUSION

This is the first PopPK for busulfan that successfully incorporated GSTA1 genotype in a paediatric population. Its use may contribute to better prediction of busulfan exposure in children and adolescents since the first dose, by tailoring the dose according to the individual metabolic capacity.

Population pharmacokinetics analysis of intravenous busulfan in Chinese patients undergoing hematopoietic stem cell transplantation

There are several reports describing population pharmacokinetic (popPK) models of busulfan (BU). However, limited information is available in Chinese hematopoietic stem cell transplantation (HSCT) patients. The present study aimed to establish a popPK model of intravenous BU in Chinese HSCT patients for individualized drug therapy. The popPK model of BU was developed from a total of 284 concentration-time points from 53 patients. The effects of demographic and biochemical covariates were investigated by nonlinear mixed effect model (NONMEM) software. Plots, visual predictive check (VPC), bootstrap and normalized prediction distribution error (NPDE) were performed to determine the stability and the reliability of the final model. A one-compartment model with first-order elimination process was confirmed as the final structural model for BU. For a typical patient whose body surface area (BSA) is 1.7 m² , the population typical values of CL and Vd were 11.86 L/h, and 48.2 L, respectively. The result suggested BSA showed significant influence on CL and Vd (P<.001). Plots revealed the final model was performing a goodness fit. The steady rate verified by bootstrap was 100%, relative deviation was less than 4.00%, estimated value of final model was in the 95% confidence interval (CI). The VPC results showed the observed values were almost all positioned within the 5th and 95th CIs. The mean and variance of the NPDE were 0.0363 (Wilcoxon signed-rank test, 0.298) and 0.877 (Fisher variance test, 0.134; SW test of normality, 0.108), respectively. The global adjusted P value was 0.305, which indicated that the prediction of the BU popPK model was adequate. A physician-friendly Microsoft Excel-base tool was implemented using the final popPK model for designing individualized dosing regimens.

GSTA1 diplotypes affect busulfan clearance and toxicity in children undergoing allogeneic hematopoietic stem cell transplantation: a multicenter study

Busulfan (BU) dose adjustment following therapeutic drug monitoring contributes to better outcome of hematopoietic stem cell transplantation (HSCT). Further improvement could be achieved through genotype-guided BU dose adjustments. To investigate this aspect, polymorphism within glutathione S transferase genes were assessed. Particularly, promoter haplotypes of the glutathione S transferase A1 (GSTA1) were evaluated in vitro, with reporter gene assays and clinically, in a pediatric multi-center study (N =138) through association with BU pharmacokinetics (PK) and clinical outcomes. Promoter activity significantly differed between the GSTA1 haplotypes (p<0.001) supporting their importance in capturing PK variability. Four GSTA1 diplotype groups that significantly correlated with clearance (p=0.009) were distinguished. Diplotypes underlying fast and slow metabolizing capacity showed higher and lower BU clearance (ml/min/kg), respectively. GSTA1 diplotypes with slow metabolizing capacity were associated with higher incidence of sinusoidal obstruction syndrome, acute graft versus host disease and combined treatment-related toxicity (p<0.0005). Among other GST genes investigated, GSTP1 313GG correlated with acute graft versus host disease grade 1-4 (p=0.01) and GSTM1 non-null genotype was associated with hemorrhagic cystitis (p=0.003). This study further strengthens the hypothesis that GST diplotypes/genotypes could be incorporated into already existing population pharmacokinetic models for improving first BU dose prediction and HSCT outcomes. (N^o Clinicaltrials.gov identifier: NCT01257854. Registered 8 December 2010, retrospectively registered).

GSTA1 Genetic Variants and Conditioning Regimen: Missing Key Factors in Dosing Guidelines of Busulfan in Pediatric Hematopoietic Stem Cell Transplantation

Busulfan (Bu) is a key component of conditioning regimens used before hematopoietic stem cell transplantation (SCT) in children. Different predictive methods have been used to calculate the first dose of Bu. To evaluate the necessity of further improvements, we retrospectively analyzed the currently available weight- and age-based guidelines to calculate the first doses in 101 children who underwent allogenic SCT in CHU Sainte-Justine, Montreal, after an intravenous Bu-containing conditioning regimen according to genetic and clinical factors. The measured areas under the curve (AUCs) were within target (900 to 1500 µM/min) in 38.7% of patients after the administration of the first dose calculated based on age and weight, as locally recommended. GSTA1 diplotypes linked to poor Bu metabolism (G3) and fludarabine-containing regimens were the only factors associated with AUC within target (OR, 4.7 [95% CI, 1.1 to 19.8, P = .04]; and OR, 9.9 [95% CI, 1.6 to 61.7, P = .01], respectively). From the 11 methods selected for dose calculation, the percentage of AUCs within the target varied between 16% and 74%. In some models G3 was associated with AUCs within the therapeutic and the toxic range, whereas rapid metabolizers (G1) were correlated with subtherapeutic AUCs when different methods were used. These associations were confirmed by clearance-prediction analysis, in which GSTA1 diplotypes consistently influenced the prediction errors of the methods. These findings suggest that these factors should be considered in Bu dose prediction in addition to the anthropometric data from patients. Furthermore, our data indicated that GSTA1 diplotypes was a factor that should be included in future population pharmacokinetic models, including similar conditioning regiments, to improve the prediction of Bu exposure after its initial dose.

Personalised dosing of medicines for children

Objectives

Doses for most drugs are determined from population-level information, resulting in a standard ?one-size-fits-all’ dose range for all individuals. This review explores how doses can be personalised through the use of the individuals’ pharmacokinetic (PK)-pharmacodynamic (PD) profile, its particular application in children, and therapy areas where such approaches have made inroads.

Key findings

The Bayesian forecasting approach, based on population PK/PD models that account for variability in exposure and response, is a potent method for personalising drug therapy. Its potential utility is even greater in young children where additional sources of variability are observed such as maturation of eliminating enzymes and organs. The benefits of personalised dosing are most easily demonstrated for drugs with narrow therapeutic ranges such as antibiotics and cytotoxics and limited studies have shown improved outcomes. However, for a variety of reasons the approach has struggled to make more widespread impact at the bedside: complex dosing algorithms, high level of technical skills required, lack of randomised controlled clinical trials and the need for regulatory approval.

Summary

Personalised dosing will be a necessary corollary of the new precision medicine initiative. However, it faces a number of challenges that need to be overcome before such an approach to dosing in children becomes the norm.