Prediction of Busulfan Clearance by Predose Plasma Metabolomic Profiling

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.

Maximum a posteriori Bayesian methods out-perform non-compartmental analysis for busulfan precision dosing

Dose personalization improves patient outcomes for many drugs with a narrow therapeutic index and high inter-individuality variability, including busulfan. Non-compartmental analysis (NCA) and model-based methods like maximum a posteriori Bayesian (MAP) approaches are two methods routinely used for dose optimization. These approaches vary in how they estimate patient-specific pharmacokinetic parameters to inform a dose and the impact of these differences is not well-understood. Using busulfan as an example application and area under the concentration-time curve (AUC) as a target exposure metric, these estimation methods were compared using retrospective patient data (N = 246) and simulated precision dosing treatment courses. NCA was performed with or without peak extension, and MAP Bayesian estimation was performed using either the one-compartment Shukla model or the two-compartment McCune model. All methods showed good agreement on real-world data (correlation coefficients of 0.945-0.998) as assessed by Bland-Altman plots, although agreement between NCA and MAP methods was higher during the first dosing interval (0.982-0.994) compared to subsequent dosing intervals (0.918-0.938). In dose adjustment simulations, both NCA and MAP estimated high target attainment (> 98%) although true simulated target attainment was lower for NCA (63-66%) versus MAP (91-93%). The largest differences in AUC estimation were due to different assumptions for the shape of the concentration curve during the infusion phase, followed by how the methods considered time-dependent clearance and concentration-time points collected in earlier intervals. In conclusion, although AUC estimates between the two methods showed good correlation, in a simulated study, MAP lead to higher target attainment. When changing from one method to another, or changing infusion duration and other factors, optimum estimated exposure targets may require adjusting to maintain a consistent exposure.

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.

Push forward LC-MS-based therapeutic drug monitoring and pharmacometabolomics for anti-tuberculosis precision dosing and comprehensive clinical management

The spread of tuberculosis (TB), especially multidrug-resistant TB and extensively drug-resistant TB, has strongly motivated the research and development of new anti-TB drugs. New strategies to facilitate drug combinations, including pharmacokinetics-guided dose optimization and toxicology studies of first- and second-line anti-TB drugs have also been introduced and recommended. Liquid chromatography-mass spectrometry (LC-MS) has arguably become the gold standard in the analysis of both endo- and exo-genous compounds. This technique has been applied successfully not only for therapeutic drug monitoring (TDM) but also for pharmacometabolomics analysis. TDM improves the effectiveness of treatment, reduces adverse drug reactions, and the likelihood of drug resistance development in TB patients by determining dosage regimens that produce concentrations within the therapeutic target window. Based on TDM, the dose would be optimized individually to achieve favorable outcomes. Pharmacometabolomics is essential in generating and validating hypotheses regarding the metabolism of anti-TB drugs, aiding in the discovery of potential biomarkers for TB diagnostics, treatment monitoring, and outcome evaluation. This article highlighted the current progresses in TDM of anti-TB drugs based on LC-MS bioassay in the last two decades. Besides, we discussed the advantages and disadvantages of this technique in practical use. The pressing need for non-invasive sampling approaches and stability studies of anti-TB drugs was highlighted. Lastly, we provided perspectives on the prospects of combining LC-MS-based TDM and pharmacometabolomics with other advanced strategies (pharmacometrics, drug and vaccine developments, machine learning/artificial intelligence, among others) to encapsulate in an all-inclusive approach to improve treatment outcomes of TB patients.

The presence of busulfan metabolites and pharmacometabolomics in plasma drawn immediately before allograft infusion in hematopoietic cell transplant recipients

Busulfan is hepatically metabolized through glutathione (GSH) conjugation; in vitro, this process depletes hepatocyte GSH stores and generates the cytotoxic metabolite γ-glutamyldehydroalanylglycine, which is too unstable to be quantitated in vivo. We sought to evaluate if pre-graft (i.e., immediately before allograft infusion) concentrations of busulfan metabolites' and of endogenous metabolomic compounds (EMCs) representing the glutathione pathway were associated with clinical outcomes in hematopoietic cell transplant (HCT) recipients receiving busulfan. The clinical outcomes evaluated were relapse, acute graft versus host disease (GVHD), chronic GVHD, non-relapse mortality, and neutrophil nadir. In pre-graft samples obtained from patients immediately before allograft infusion, our objectives were to evaluate for: (1) the presence of busulfan and its metabolites tetrahydrothiophenium ion (THT+), tetrahydrothiophene 1-oxide, sulfolane, and 3-hydroxysulfolane (N = 124); (2) EMCs using a global metabolomics assay (N = 77); and (3) the association of the busulfan metabolites and the EMCs with clinical outcomes. In the pre-graft samples, busulfan and THT+ could not be detected. THT 1-oxide, sulfolane, and 3-hydroxysulfolane were quantitated in 9.6%, 26%, and 58% of pre-graft samples; their concentrations were not associated with clinical outcomes. Four pre-graft EMCs were statistically significantly associated with the neutrophil nadir. The pre-graft EMCs were not associated with the other clinical outcomes. In conclusion, busulfan's metabolites are present in patients' plasma immediately before allograft infusion; the neutrophil nadir is associated with pre-graft EMCs. Future research should investigate the association of clinical outcomes with the concentrations of busulfan's metabolites and EMCs in the pre-graft plasma from allogeneic HCT recipients.

Pharmacokinetics in Pharmacometabolomics: Towards Personalized Medication

Indiscriminate drug administration may lead to drug therapy results with varying effects on patients, and the proposal of personalized medication can help patients to receive effective drug therapy. Conventional ways of personalized medication, such as pharmacogenomics and therapeutic drug monitoring (TDM), can only be implemented from a single perspective. The development of pharmacometabolomics provides a research method for the realization of precise drug administration, which integrates the environmental and genetic factors, and applies metabolomics technology to study how to predict different drug therapeutic responses of organisms based on baseline metabolic levels. The published research on pharmacometabolomics has achieved satisfactory results in predicting the pharmacokinetics, pharmacodynamics, and the discovery of biomarkers of drugs. Among them, the pharmacokinetics related to pharmacometabolomics are used to explore individual variability in drug metabolism from the level of metabolism of the drugs in vivo and the level of endogenous metabolite changes. By searching for relevant literature with the keyword "pharmacometabolomics" on the two major literature retrieval websites, PubMed and Web of Science, from 2006 to 2023, we reviewed articles in the field of pharmacometabolomics that incorporated pharmacokinetics into their research. This review explains the therapeutic effects of drugs on the body from the perspective of endogenous metabolites and pharmacokinetic principles, and reports the latest advances in pharmacometabolomics related to pharmacokinetics to provide research ideas and methods for advancing the implementation of personalized medication.

Pharmacometabolomics of trabectedin in metastatic soft tissue sarcoma patients

Objective: Trabectedin is an anti-cancer drug commonly used for the treatment of patients with metastatic soft tissue sarcoma (mSTS). Despite its recognized efficacy, significant variability in pharmacological response has been observed among mSTS patients. To address this issue, this pharmacometabolomics study aimed to identify pre-dose plasma metabolomics signatures that can explain individual variations in trabectedin pharmacokinetics and overall clinical response to treatment. Methods: In this study, 40 mSTS patients treated with trabectedin administered by 24 h-intravenous infusion at a dose of 1.5 mg/m2 were enrolled. The patients' baseline plasma metabolomics profiles, which included derivatives of amino acids and bile acids, were analyzed using multiple reaction monitoring LC-MS/MS together with their pharmacokinetics profile of trabectedin. Multivariate Partial least squares regression and univariate statistical analyses were utilized to identify correlations between baseline metabolite concentrations and trabectedin pharmacokinetics, while Partial Least Squares-Discriminant Analysis was employed to evaluate associations with clinical response. Results: The multiple regression model, derived from the correlation between the AUC of trabectedin and pre-dose metabolomics, exhibited the best performance by incorporating cystathionine, hemoglobin, taurocholic acid, citrulline, and the phenylalanine/tyrosine ratio. This model demonstrated a bias of 4.6% and a precision of 17.4% in predicting drug AUC, effectively accounting for up to 70% of the inter-individual pharmacokinetic variability. Through the use of Partial least squares-Discriminant Analysis, cystathionine and hemoglobin were identified as specific metabolic signatures that effectively distinguish patients with stable disease from those with progressive disease. Conclusions: The findings from this study provide compelling evidence to support the utilization of pre-dose metabolomics in uncovering the underlying causes of pharmacokinetic variability of trabectedin, as well as facilitating the identification of patients who are most likely to benefit from this treatment.

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.

Precision sirolimus dosing in children: The potential for model-informed dosing and novel drug monitoring

The mTOR inhibitor sirolimus is prescribed to treat children with varying diseases, ranging from vascular anomalies to sporadic lymphangioleiomyomatosis to transplantation (solid organ or hematopoietic cell). Precision dosing of sirolimus using therapeutic drug monitoring (TDM) of sirolimus concentrations in whole blood drawn at the trough (before the next dose) time-point is the current standard of care. For sirolimus, trough concentrations are only modestly correlated with the area under the curve, with R 2 values ranging from 0.52 to 0.84. Thus, it should not be surprising, even with the use of sirolimus TDM, that patients treated with sirolimus have variable pharmacokinetics, toxicity, and effectiveness. Model-informed precision dosing (MIPD) will be beneficial and should be implemented. The data do not suggest dried blood spots point-of-care sampling of sirolimus concentrations for precision dosing of sirolimus. Future research on precision dosing of sirolimus should focus on pharmacogenomic and pharmacometabolomic tools to predict sirolimus pharmacokinetics and wearables for point-of-care quantitation and MIPD.