Population pharmacokinetics of ganciclovir and valganciclovir in paediatric solid organ and stem cell transplant recipients

Assessment of patients' characteristics associated with the efficacy and safety of oral valganciclovir treatment for infants with symptomatic congenital cytomegalovirus disease

INTRODUCTION

Insurance coverage for oral valganciclovir (VGCV) began in Japan in April 2023 on the basis of results, including our clinical trials for symptomatic congenital cytomegalovirus (CMV) disease. The VGCV treatment is available throughout Japan, so clinicians must consider the likelihood of hearing improvement and the possibility of neutropenia before dosing.

MATERIALS AND METHODS

We performed a substudy of an investigator-initiated, single-arm, prospective, multicenter, clinical trial in which 24 infants with symptomatic congenital CMV disease were orally administered 16 mg/kg VGCV twice daily for 6 months as an intervention. We examined the infants' baseline characteristics associated with improved hearing impairment or a severely reduced neutrophil count.

RESULTS

Of the 24 patients, 4 had normal hearing on assessment of their ear with the best hearing. Hearing impairment improved in 14 patients and did not respond to VGCV treatment in 6 patients at the 6-month hearing assessment. CMV DNA levels in plasma at baseline were higher in patients in whom hearing did not respond to treatment. A neutrophil count <500/mm3 occurred in 5 (21%) patients for the first 6 weeks and in 8 (33%) patients for the first 6 months. A neutrophil count at screening and the lowest neutrophil count over the 6 months showed the highest correlation (r = 0.477, p = 0.019).

CONCLUSIONS

Infants with a low plasma viral load at screening tend to have an improvement in hearing impairment. Clinicians should be aware of neutropenia during VGCV treatment particularly in patients with a low neutrophil count during screening.

Application of machine-learning models to predict the ganciclovir and valganciclovir exposure in children using a limited sampling strategy

Intravenous ganciclovir and oral valganciclovir display significant variability in ganciclovir pharmacokinetics, particularly in children. Therapeutic drug monitoring currently relies on the area under the concentration-time (AUC). Machine-learning (ML) algorithms represent an interesting alternative to Maximum-a-Posteriori Bayesian-estimators for AUC estimation. The goal of our study was to develop and validate an ML-based limited sampling strategy (LSS) approach to determine ganciclovir AUC0-24 after administration of either intravenous ganciclovir or oral valganciclovir in children. Pharmacokinetic parameters from four published population pharmacokinetic models, in addition to the World Health Organization growth curve for children, were used in the mrgsolve R package to simulate 10,800 pharmacokinetic profiles of children. Different ML algorithms were trained to predict AUC0-24 based on different combinations of two or three samples. Performances were evaluated in a simulated test set and in an external data set of real patients. The best estimation performances in the test set were obtained with the Xgboost algorithm using a 2 and 6 hours post dose LSS for oral valganciclovir (relative mean prediction error [rMPE] = 0.4% and relative root mean square error [rRMSE] = 5.7%) and 0 and 2 hours post dose LSS for intravenous ganciclovir (rMPE = 0.9% and rRMSE = 12.4%). In the external data set, the performance based on these two sample LSS was acceptable: rMPE = 0.2% and rRMSE = 16.5% for valganciclovir and rMPE = -9.7% and rRMSE = 17.2% for intravenous ganciclovir. The Xgboost algorithm developed resulted in a clinically relevant individual estimation using only two blood samples. This will improve the implementation of AUC-targeted ganciclovir therapeutic drug monitoring in children.

Optimization of Ganciclovir and Valganciclovir Starting Dose in Children by Machine Learning

BACKGROUND AND OBJECTIVES

Ganciclovir (GCV) and valganciclovir (VGCV) show large interindividual pharmacokinetic variability, particularly in children. The objectives of this study were (1) to develop machine learning (ML) algorithms trained on simulated pharmacokinetics profiles obtained by Monte Carlo simulations to estimate the best ganciclovir or valganciclovir starting dose in children and (2) to compare its performances on real-world profiles to previously published equation derived from literature population pharmacokinetic (POPPK) models achieving about 20% of profiles within the target.

MATERIALS AND METHODS

The pharmacokinetic parameters of four literature POPPK models in addition to the World Health Organization (WHO) growth curve for children were used in the mrgsolve R package to simulate 10,800 pharmacokinetic profiles. ML algorithms were developed and benchmarked to predict the probability to reach the steady-state, area-under-the-curve target (AUC0-24 within 40-60 mg × h/L) based on demographic characteristics only. The best ML algorithm was then used to calculate the starting dose maximizing the target attainment. Performances were evaluated for ML and literature formula in a test set and in an external set of 32 and 31 actual patients (GCV and VGCV, respectively).

RESULTS

A combination of Xgboost, neural network, and random forest algorithms yielded the best performances and highest target attainment in the test set (36.8% for GCV and 35.3% for the VGCV). In actual patients, the best GCV ML starting dose yielded the highest target attainment rate (25.8%) and performed equally for VGCV with the Franck model formula (35.3% for both).

CONCLUSION

The ML algorithms exhibit good performances in comparison with previously validated models and should be evaluated prospectively.

Evidence supporting the use of therapeutic drug monitoring of ganciclovir in transplantation

PURPOSE OF REVIEW

This review describes current knowledge of ganciclovir (GCV) and valganciclovir (ValGCV) pharmacokinetic/pharmacodynamic characteristics, highlighting the likely contribution from host genetic factors to interpatient variability. The evidence and challenges surrounding optimization of drug dosing through therapeutic drug monitoring (TDM) are examined, with recommendations made.

RECENT FINDINGS

Pharmacokinetic studies of current dosing guidelines have shown high interindividual and intraindividual variability of GCV concentrations. This is sometimes associated with a slow decline in cytomegalovirus (CMV) viral load in some transplant recipients. A high incidence of GCV-associated myelosuppression has limited the use of this drug in the transplant setting. Patient groups identified to benefit from GCV TDM include pediatric patients, cystic fibrosis with lung transplantation, obese with kidney transplantation, and patients with fluctuating renal function or on hemodialysis. The emergence of refractory resistant CMV, particularly in immune compromised patients, highlights the importance of appropriate dosing of these antivirals. Host genetic factors need to be considered where recently, two host genes were shown to account for interpatient variation during ganciclovir therapy. Therapeutic Drug Monitoring has been shown to improve target antiviral-level attainment. The use of TDM may guide concentration-based dose adjustment, potentially improving virological and clinical outcomes. However, evidence supporting the use of TDM in clinical practice remains limited and further study is needed in the transplant cohort.

SUMMARY

Further studies examining novel biomarkers are needed to guide target concentrations in prophylaxis and treatment. The use of TDM in transplant recipients is likely to improve the clinical efficacy of current antivirals and optimize outcomes in transplant recipients.

Bridging the Worlds of Pharmacometrics and Machine Learning

Precision medicine requires individualized modeling of disease and drug dynamics, with machine learning-based computational techniques gaining increasing popularity. The complexity of either field, however, makes current pharmacological problems opaque to machine learning practitioners, and state-of-the-art machine learning methods inaccessible to pharmacometricians. To help bridge the two worlds, we provide an introduction to current problems and techniques in pharmacometrics that ranges from pharmacokinetic and pharmacodynamic modeling to pharmacometric simulations, model-informed precision dosing, and systems pharmacology, and review some of the machine learning approaches to address them. We hope this would facilitate collaboration between experts, with complementary strengths of principled pharmacometric modeling and flexibility of machine learning leading to synergistic effects in pharmacological applications.

Optimizing ganciclovir and valganciclovir dosing regimens in pediatric patients with cytomegalovirus infection: a spotlight on therapeutic drug monitoring

INTRODUCTION

Infants and immunocompromised children with cytomegalovirus (CMV) infection have significant morbidity and mortality. Ganciclovir (GCV) and its oral prodrug valganciclovir (VGCV) are the major antiviral options of choice for the prophylaxis and treatment of CMV infection. However, with the currently recommended dosing regimens used in pediatric patients, large intra- and inter-individual variability of pharmacokinetic (PK) parameters and exposure are observed.

AREAS COVERED

This review describes the PK and pharmacodynamic (PD) characteristics of GCV and VGCV in pediatrics. Moreover, the role of therapeutic drug monitoring (TDM) and current clinical practice for GCV and VGCV dosing regimens optimization in pediatrics are discussed.

EXPERT OPINION

GCV/VGCV TDM has shown the potential value to improve the benefit/risk ratio in pediatrics when using the therapeutic ranges derived from adults. However, well-designed studies are required to evaluate the relationship of TDM with clinical outcomes. Furthermore, studies to explore the children-specific dose-response-effect relationships will be helpful to facilitate the TDM practice. In the clinical setting, optimal sampling methods such as limited sampling strategies for pediatrics can be used in TDM and intracellular ganciclovir triphosphate may be used as an alternative TDM marker.

Therapeutic Drug Monitoring of Ganciclovir: Where Are We?

BACKGROUND

Ganciclovir is the mainstay of therapy for the prophylaxis and treatment of Cytomegalovirus. However, therapy with this antiviral agent is hindered by side effects such as myelosuppression, which often leads to therapy cessation. Underdosing, as an attempt to prevent side effects, can lead to drug resistance and therapy failure. Therapeutic drug monitoring (TDM) has been used to overcome these problems. The purpose of this narrative review was to give an overview of ganciclovir TDM, available assays, population pharmacokinetic models, and discuss the current knowledge gaps.

METHODS

For this narrative review, a nonsystematic literature search was performed on the PubMed database in April 2021. The following search terms were used: ganciclovir, valganciclovir, pharmacokinetics, pharmacodynamics, population pharmacokinetics, therapeutic drug monitoring, bioassay, liquid chromatography coupled with tandem mass spectrometry, liquid chromatography, chromatography, spectrophotometry, and toxicity. In addition, the reference lists of the included articles were screened.

RESULTS

The most common bioanalysis method identified was liquid chromatography coupled with tandem mass spectrometry. There are different models presenting ganciclovir IC50; however, establishing a pharmacokinetic/pharmacodynamic target for ganciclovir based on preclinical data is difficult because there are no studies combining dynamic drug exposure in relation to inhibition of viral replication. The data on ganciclovir TDM show large interindividual variability, indicating that TDM may play a role in modifying the dose to reduce toxicity and prevent treatment failure related to low concentrations. The main hurdle for implementing TDM is the lack of robust data to define a therapeutic window.

CONCLUSIONS

Although the pharmacokinetics (PK) involved is relatively well-described, both the pharmacodynamics (PD) and pharmacokinetic/pharmacodynamic relationship are not. This is because the studies conducted to date have mainly focused on estimating ganciclovir exposure, and owing to the limited therapeutic options for CMV infections, future studies on ganciclovir are warranted.

Pharmacokinetics, Pharmacodynamics, and Therapeutic Drug Monitoring of Valganciclovir and Ganciclovir in Transplantation

Ganciclovir and valganciclovir are first choice drugs for the prevention and treatment of cytomegalovirus infection and disease in solid organ and stem cell transplant recipients. Only a few studies on the pharmacokinetics and exposure/efficacy or exposure/safety relationships of ganciclovir and valganciclovir in transplant recipients have been published so far, and there are still controversies about the exposure parameter to use for therapeutic drug monitoring (TDM). We performed an extensive literature review of the clinical pharmacokinetics data, the exposure/effect relationships in terms of efficacy and safety, and the available tools for valganciclovir and ganciclovir TDM in adults and pediatrics transplant recipients. The pharmacokinetics of ganciclovir and valganciclovir is well described in adults and children, and a high interindividual variability is commonly observed. In contrast, the drug pharmacodynamics has been poorly described in adults and barely in children. The average 24-hour area under the concentration-time curve (AUC_0-24h ) seems to be the best predictor of efficacy and toxicity. The benefit of TDM remains controversial in adult patients but should be considered in children due to higher interindividual variability and lower probability of target attainment. Several bayesian estimators based on limited sampling strategies have been developed with this aim and may be used in clinical practice for the AUC-based individual dose adjustment of ganciclovir and valganciclovir.