Population Pharmacokinetic/Pharmacodynamic Modeling and Terapeutic Drug Monitoring of Vancomycin in Neonates and Preterm Neonates

Objective: The primary objective of this study revolves around the development of a population pharmacokinetic (PPK) model for vancomycin in neonatal subjects, with the objective of providing a theoretical basis for judicious therapeutic interventions.Methods: In this study, a retrospective collection encompassed 75 neonatal patients, contributing to a total of 89 vancomycin blood concentration monitoring datasets. The establishment of the PPK model is carried out utilizing the nonlinear mixed effects model methodology. The PPK model was constructed employing a one‐compartment model with proportional residual error, and the influence of covariates on pharmacokinetic parameters was systematically assessed through forward stepwise addition and backward elimination methods. The stability and predictive accuracy of the final model were assessed using goodness‐of‐fit plots, nonparametric bootstrap validation, visual predictive checks, and normalized prediction distribution errors. Furthermore, Monte Carlo simulations were employed to predict vancomycin concentrations in neonatal patients with typical characteristics.Results: The final PPK model yielded population‐typical values of 0.24 L/h for vancomycin clearance (CL). Noteworthy contributors to vancomycin CL were identified as body weight, gestational age, creatinine clearance rate (CLcr), and sex. Internal validation results of the model indicate that it possesses stability, efficacy, and demonstrates a favorable predictive capacity. Monte Carlo simulations indicate that for a male neonatal patient characterized by a gestational age of 37 weeks, a body weight of 2.5 kg, and a CLcr of 60 mL/min, the recommended dosing regimen is 25.5 to 41.5 mg every 8 h.Conclusion: This investigation has successfully formulated a PPK model for vancomycin in neonatal patients, offering the capacity to estimate individual CL. The dosing regimen for neonates should take into account factors such as body weight, gestational age, CLcr, and sex.

Vancomycin is commonly used in the prevention and treatment of intracranial infections in postoperative neurosurgical patients with narrow therapeutic window and large pharmacokinetic variations. Several population pharmacokinetic (PPK) models of vancomycin have been established for neurosurgical patients. But comprehensive external evaluation has not been performed for almost all models. The objective of this study was to evaluate the predictive ability of published vancomycin PPK models in adult postoperative neurosurgical patients using an independent dataset. PubMed, Embase and China National Knowledge Internet databases were searched to identify published vancomycin PPK models in adult postoperative neurosurgical patients. Prediction-based and simulation-based diagnostics were used to evaluate model predictability. Bayesian forecasting was used to assess the influence of prior concentration on model prediction performance. A total of 763 vancomycin plasma concentrations from 493 postoperative neurosurgical patients were included in the external dataset. Eight population pharmacokinetic models of vancomycin in postoperative neurosurgical patients were included and evaluated. The model by Zhang et al. exhibited the best predictive performance in prediction-based diagnostics and prediction-corrected visual predictive checks, followed by the model by Shen et al. The predictive performance of other models was not satisfactory. The normalized predictive distribution error test shows that none of the models is suitable to describe our data. The predictive performance of vancomycin models was obviously improved by maximum a posteriori Bayesian forecasting. The published PPK models for adult postoperative neurosurgical patients show extensive variation in predictive performance in our patients. Although it is challenging to recommend initial doses of vancomycin from these predictive models, the combination of model-based prediction and therapeutic drug monitoring can be used for dose optimization.

Guidelines for vancomycin therapeutic monitoring recommend using a Bayesian approach with a population pharmacokinetic model to estimate the 24 h area under the concentration-time curve over first-order equations. Thus, we performed an external evaluation of population pharmacokinetic models of vancomycin in neonates and compared Bayesian results with those observed in clinical practice via pharmacokinetic equations to improve therapeutic monitoring by proposing optimized initial dosing nomograms and assessing the feasibility of reduced blood sampling strategies using the most predictive models. Models were identified from the literature and evaluated via an external neonatal population. A priori predictive performance was first assessed by prediction-based diagnostics, then by simulation-based diagnostics and a posteriori analyses only if deemed satisfactory; model-informed vancomycin exposure was also compared with reference first-order pharmacokinetic equations. The best-performing models were ultimately subjected to Monte Carlo simulations to develop new initial dosing nomograms offering the highest probability of achieving therapeutic target. A total of 28 population pharmacokinetic models were evaluated in the external dataset, which includes 72 neonates and 380 vancomycin concentrations. Eleven models had an adequate predictive performance with bias ≤ ± 15% and imprecision 30%, while the Bayesian approach yielded over 75% agreement with reference exposure values in most cases. Nonetheless, Capparelli etal. and Mehrotra etal. models performed the best overall, showing the lowest imprecisions of 16.8% and 16.9%, respectively; both models recommended higher dosage regimens than the theoretical nomogram currently applied to favor therapeutic target attainment. We externally evaluated numerous neonatal population pharmacokinetic models of vancomycin and used the most predictive ones to advocate new initial dosing nomograms. Clinical implementation of the Bayesian approach could reduce the time needed to reach therapeutic target and limit the number of blood samples in newborns compared with traditional pharmacokinetic equations.

The pharmacokinetics of vancomycin vary among neonates, and we aimed to conduct population pharmacokinetic analysis to determine the optimal dosage of vancomycin in Korean neonates. From a retrospective chart review, neonates treated with vancomycin from 2008 to 2017 in a neonatal intensive care unit (NICU) were included. Vancomycin concentrations were collected based on therapeutic drug monitoring, and other patient characteristics were gathered through electronic medical records. We applied nonlinear mixed-effect modeling to build the population pharmacokinetic model. One- and two-compartment models with first-order elimination were evaluated as potential structural pharmacokinetic models. Allometric and isometric scaling was applied to standardize pharmacokinetic parameters for clearance and volume of distribution, respectively, using fixed powers (0.75 and 1, respectively, for clearance and volume). The predictive performance of the final model was developed, and dosing strategies were explored using Monte Carlo simulations with AUC0–24 targets 400–600. The patient cohort included 207 neonates, and 900 vancomycin concentrations were analyzed. Only 37.4% of the analyzed concentrations were within trough concentrations 5–15 µg/mL. A one-compartment model with first-order elimination best described the vancomycin pharmacokinetics in neonates. Postmenstrual age (PMA) and creatinine clearance (CLcr) affected the clearance of vancomycin, and model evaluation confirmed the robustness of the final model. Population pharmacokinetic modeling and dose optimization of vancomycin in Korean neonates showed that vancomycin clearance was related to PMA and CLcr, as well as body weight. A higher dosage regimen than the typical recommendation is suggested.

BackgroundVancomycin is commonly used for treatment of severe Gram+ neonatal infections. Currently, even with the use of optimized dosing regimens and therapeutic drug monitoring (TDM), target attainment rates are abominable,...

The aims of this study were to demonstrate the correlation between alfentanil-induced miosis evaluation and alfentanil pharmacokinetics (PK) as a CYP3A4 and 3A5 activity probe in volunteers and to explain the variability in pupilar response and in alfentanil PK. In ambient light, the miosis kinetic parameters were significantly correlated with PK (CLs: r = 0.9, P = .00; AUCs: r = 0.8, P = .01). In dark, a similar correlation was observed between miosis and alfentanil clearances (r = 0.85, P = .03). In 6 volunteers, the sigmoid E(max) model was applicable (average E(max) = 2.5 +/- 0.7 mm, gamma = 2.5 +/- 1.6 and EC(50) = 76.8 +/- 22.3 ng/mL), and in 3, the simple E(max) model was applicable (average E(max) = 2.8 +/- 0.3 mm and EC(50) = 19.9 +/- 8.5 ng/mL). There was a large interindividual variability in PK parameters (coefficient of variation = 19.7%-31.2%). Free drug fraction concentrations were negatively correlated with plasma alpha(1)-AGP (r = -0.9, P = .04) and albumin levels (r = -0.94, P = .02). Alfentanil-induced miosis clearance as a noninvasive CYP3A4 and 3A5 activity measure can be done in both ambient and dark conditions. Drug free fraction may be responsible for large intersubject variability in alfentanil PK.

Levetiracetam (LEV) is a broad spectrum antiepileptic drug (AED) that has a more favorable side effect profile compared to older AEDs. Therapeutic drug monitoring (TDM) of LEV is generally unnecessary given its linear and predictable dose-serum concentration relationship, lack of drug-drug interactions, and broad therapeutic window. However, there is growing evidence showing that alteration of LEV pharmacokinetics (PK) may occur in special populations calling for the need for TDM. The purpose of this review was to summarize current literature surrounding altered LEV PK in special patient populations and determine if there is a need for levetiracetam TDM. A literature search of MEDLINE (1946 - November 2017) database of available evidence pertaining to altered LEV PK in humans was conducted. A total of 51 articles were found. There has not been a positive correlation shown between LEV levels and efficacy or toxicity. Variable LEV levels are reported in the literature with respect to adverse effects, seizures and efficacy occurring below, within and above the supposed reference ranges. Age is a major contributor to altered pharmacokinetics of LEV as shown in elderly patients and pediatric patients. Compared to adults, clearance of LEV has been shown to be decreased by almost half in patients over 65 and increased by 30-40% in pediatric patients. LEV pharmacokinetics varied further when data from its use in neonates was explored. LEV clearance declined in a linear fashion with declining estimates of creatinine clearance but was variable in patients with end-stage renal failure or those requiring renal replacement therapy. In patients who were critically ill, LEV clearance may be augmented and these patients may require higher doses of medications to maintain drug levels. In patients who are pregnant, LEV levels are likely to decline as pregnancy progresses due to changes in glomerular filtration rate and remain variable in the post-partum period. Routine TDM of levetiracetam is not recommended for all populations, however, it may be beneficial to maintain an individual therapeutic range in patients where the PK of LEV may be altered, such as in patients who are critically ill patients, pregnant, pediatrics or elderly.

A new generation of antiepileptic drugs (AEDs) has reached the market in recent years with ten new compounds: felbamate, gabapentin, lamotrigine, levetiracetam, oxcarbazepine, pregabalin, tiagabine, topiramate, vigabatrin and zonisamide. The newer AEDs in general have more predictable pharmacokinetics than older AEDs such as phenytoin, carbamazepine and valproic acid (valproate sodium), which have a pronounced inter-individual variability in their pharmacokinetics and a narrow therapeutic range. For these older drugs it has been common practice to adjust the dosage to achieve a serum drug concentration within a predefined 'therapeutic range', representing an interval where most patients are expected to show an optimal response. However, such ranges must be interpreted with caution, since many patients are optimally treated when they have serum concentrations below or above the suggested range. It is often said that there is less need for therapeutic drug monitoring (TDM) with the newer AEDs, although this is partially based on the lack of documented correlation between serum concentration and drug effects. Nevertheless, TDM may be useful despite the shortcomings of existing therapeutic ranges, by utilisation of the concept of 'individual reference concentrations' based on intra-individual comparisons of drug serum concentrations. With this concept, TDM may be indicated regardless of the existence or lack of a well-defined therapeutic range. The ten newer AEDs all have different pharmacological properties, and therefore, the usefulness of TDM for these drugs has to be assessed individually. For vigabatrin, a clear relationship between drug concentration and clinical effect cannot be expected because of its unique mode of action. Therefore, TDM of vigabatrin is mainly to check compliance. The mode of action of the other new AEDs would not preclude the applicability of TDM. For the prodrug oxcarbazepine, TDM is also useful, since the active metabolite licarbazepine is measured. For drugs that are eliminated renally completely unchanged (gabapentin, pregabalin and vigabatrin) or mainly unchanged (levetiracetam and topiramate), the pharmacokinetic variability is less pronounced and more predictable. However, the dose-dependent absorption of gabapentin increases its pharmacokinetic variability. Drug interactions can affect topiramate concentrations markedly, and individual factors such as age, pregnancy and renal function will contribute to the pharmacokinetic variability of all renally eliminated AEDs. For those of the newer AEDs that are metabolised (felbamate, lamotrigine, oxcarbazepine, tiagabine and zonisamide), pharmacokinetic variability is just as relevant as for many of the older AEDs. Therefore, TDM is likely to be useful in many clinical settings for the newer AEDs. The purpose of the present review is to discuss individually the potential value of TDM of these newer AEDs, with emphasis on pharmacokinetic variability.

Background. The undesirable side effects in the process of pharmacotherapy are forced to look for ways to prevent them. The most effective means for this is to carry out individual therapeutic drug monitoring. This is especially true for patients who undergo chemotherapy. A narrow therapeutic range of antineoplastic agent concentrations requires an individual approach to the management of each patient. The purpose of this study is to justify the need for therapeutic drug monitoring to provide the safety of antitumor drugs. Methods. Methods for the quantitative determination of the active metabolite of fludarabine, imatinib and gefitinib in human blood plasma have been developed and validated. A study of pharmacokinetics of antitumor drugs: fludarabine - 36 patients, gefitinib - 24 healthy volunteers, imatinib - 24 healthy volunteers. Results and Discussion. The work shows the magnitude of interindividual differences of the pharmacokinetics of various antitumor drugs. High interindividual variability of pharmacokinetic parameters was revealed both in patients and in healthy volunteers. Conclusion. Experience of the Research Laboratory of Toxicology and Drug Monitoring, The Nikiforov Russian Center of Emergency and Radiation Medicine, EMERCOM of Russia on the application of therapeutic drug monitoring showed its relevance and effectiveness for patients undergoing chemotherapy. (For citation: Rodionov GG, Shantyr II, Ushal IE, et al. Experience of determination of antitumor drugs concentrations as a method of providing the safety of pharmacotherapy. Reviews on Clinical Pharmacology and Drug Therapy. 2018;16(1):64-70. doi: 10.17816/RCF16164-70).

A population pharmacokinetic model for vancomycin in neonatal intensive care unit neonates was developed. Daily fluid input and the use of diuretic agents were identified as new significant covariates influencing drug clearance. Based on these covariates, a dosing regimen was developed that provides clinicians with individualized dosing recommendations.

Fungal infections are frequent life-threatening complications in immune compromised patient sand in patients admitted in ICU wards [1]. Voriconazole (VRC) is a second-generation wide-spectrum antifungal triazole recommended for the treatment of potentially lifethreatening fungal infections including invasive aspergillosis, disseminated candidasies, and other infections caused by Fusarium and Scedosporium spp. [2,3]. This compound can be administered as an intravenous infusion and oral formulations. Studies with healthy volunteers demonstrated bioavailability of >90% after oral administration [4]. A steady-state level is achieved in three days with two loading doses of 400 mg for the first day, followed by a maintenance dose of 200 mg every 12 hours thereafter [5]. Investigations have shown both within and between individual's variability in VRC steady-state plasma concentration and non-linear pharmacokinetics due to saturation of its metabolism with respect to dose. This variability was observed with both intravenous and oral formulations [6]. Other pharmacokinetic variability's include decreased absorption of oral VRC with meals, interactions with comedications, patient's age, hepatic inefficiency and genetic polymorphisms of cytochrome P450 (CYP) iso-enzymes, mainly CYP2C19 enzyme [6,7]. Generally accepted plasma level for VRC is 1-5.5 mg/L. There have been reports that a clear relationship exists between drug concentration and drug response. High levels (>5.5 mg/L) are associated with variant adverse drug reactions. The most frequently side effects of VRC are vomiting , nausea , fever, skin rash, vision color changes, visual disturbances, blurred vision, hepatotoxicity, liver enzyme elevation, encephalopathy, and electrolyte abnormalities. Levels of VRC (<1 mg/L) have been associated with therapeutic failures and breakthrough infection [8]. In addition, using recommended dosing regimens in both adults and pediatrics has shown a significant relationship between VRC plasma levels and clinical efficacy and/or toxicity indicating a need for therapeutic drug monitoring (TDM). TDM may enable clinicians to make a better use of VRC, and is recommended as a tool to individualize VRC doses and may be particularly helpful in the context of preventing drug-related side effects. Therefore, TDM of VRC concentrations is highly recommended to maximize efficacy and minimize adverse events [9].

In this review, the authors summarized the latest developments in costimulatory blockade to prevent rejection after solid organ transplantation (SOT) and discussed possibilities for future research and the need for therapeutic drug monitoring (TDM) of these agents. Studies about costimulatory blockers in SOT in humans or animal transplant models in the past decade (2014-2024) were systematically reviewed in PubMed, European Union clinical trials (EudraCT), and ClinicalTrials.gov . Seventy-five registered clinical trials and 58 published articles were found on costimulation blockade of the CD28-CD80/86, CD40-CD40L, and OX40-OX40L pathways. Belatacept, an antagonist of the CD28-CD80/86 pathway, is the only approved costimulatory agent in SOT, hence accounting for most of the research. Other identified costimulatory blocking agents included abatacept and CD28 antagonists tegoprubart, dazodalibep, and TNX-1500. Although tegoprubart was unsuccessful in pancreas transplantation in nonhuman primates, trials in human kidney transplantation are underway. Dazodalibep trials faced recruitment challenges. TNX-1500 was unsuccessful in animal studies and is currently not pursued in humans. After discontinuation of iscalimab (CD40-CD154 pathway antagonist) in SOT, the alternatives, bleselumab and KPL404, showed promising results in kidney transplantation and cardiac xenotransplantation. Studies on secondary costimulatory pathway antagonists, such as OX40-OX40L, have only used animal models. Despite the low interindividual variability in pharmacokinetics (PK) in all studied agents, TDM could be useful for optimizing dosing in PK/pharmacodynamic (PD) studies. The routine use of costimulation blockade in SOT is hindered by problems in efficacy compared with the standard of care. Costimulatory inhibitors could be combined in a calcineurin inhibitor-free regimen. Future PK/pharmacodynamic studies in costimulatory agents and personalized medicine could warrant TDM of these agents.

Objective: Vancomycin is commonly used in postoperative neurosurgical patients for empirical anti-infective treatment due to the low success rate of bacterial culture in cerebrospinal fluid (about 20%) and the high mortality of intracranial infection. At conventional doses, the rate of target achievement for vancomycin trough concentration is low and the pharmacokinetics of vancomycin varies greatly in these patients, which often leads to treatment failure. The objective of this study was to establish a population pharmacokinetic (PPK) model of vancomycin in postoperative neurosurgical patients for precision medicine.Method: A total of 895 vancomycin plasma concentrations from 560 patients (497 postoperative neurosurgical patients) were retrospectively collected. The model was analyzed by nonlinear mixed effects modeling method. One-compartment model and mixed residual model was employed. The influence of covariates on model parameters was tested by forward addition and backward elimination. Goodness-of-fit, bootstrap and visual predictive check were used for model evaluation. Monte Carlo simulations were employed for dosing strategies with AUC24 targets 400–600.Result: Estimated glomerular filtration rate (eGFR), body weight (BW) and mannitol had significant influence on vancomycin clearance (CL). , for female, a = 0.7, Scr 0.7 mg/dl, b = −0.329, Scr 0.7 mg/dl, b = −1.209; for male, a = 0.9, Scr 0.9 mg/dl, b = −0.411, Scr 0.9 mg/dl, b = −1.210. Vancomycin clearance was accelerated when co-medicated with mannitol and increased with eGFR and BW. In the final model, the population typical value is 7.98 L/h for CL and 60.2 L for apparent distribution volume, , where A = 0.13 when co-medicated with mannitol, otherwise A = 0. The model is stable and effective, with good predictability.Conclusion: In postoperative neurosurgical patients, a higher dose of vancomycin may be required due to the augmented renal function and the commonly used mannitol, especially in those with high body weight. Our vancomycin PPK model could be used for individualized treatment in postoperative neurosurgical patients.

WHAT IS KNOWN ANDOBJECTIVE: Although patients may have received vancomycin therapy with therapeutic drug monitoring (TDM), those treated with high-strength and long-term vancomycin therapy might have unstable and time-varying renal function. The methods used to estimate renal function should not be considered interchangeable with pharmacokinetic (PK) modeling and model-based estimation of vancomycin pharmacokinetics. While Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) for renal function estimation has been widely integrated into clinical practice, a population PK model including CKD-EPI has not been established.The study was aimed at developing a new population PK model for optimal vancomycin prediction in patients with time-varying and variable renal function to evaluate the interchangeability of estimation methods. METHODS: The most suitable population PK model was explored and evaluated using non-linear mixed-effect modelling for the best fit of vancomycin concentrations from patients who needed to maintain high trough vancomycin concentrations of >10mg/L or >15mg/L. Renal function was estimated using the Cockcroft-Gault (CG), Modification of Diet in Renal Disease (MDRD) and CKD-EPI equations. NONMEM 7.4 was used to develop the population PK model. RESULTS: A total of 328 vancomycin concentrations in 99 patients were used to develop the population PK model. Vancomycin pharmacokinetics was best described by a two-compartment model. The CKD-EPI equation for vancomycin clearance was included in the final model among the estimation methods of renal function. A new covariate model, including extended covariate parameters that explain changes in renal function from the population-predicted value and individual dosing time, provided the best explanation for vancomycin pharmacokinetics among the various models tested. WHAT IS NEW ANDCONCLUSION: A new extended covariate model for vancomycin using the CKD-EPI method may afford suitable dose adjustment for high-strength and long-term vancomycin therapy that results in unstable renal function.

The review includes studies dated 2011–2021 presenting the newest information on voriconazole (VCZ), mycophenolic acid (MPA), and vancomycin (VAN) therapeutic drug monitoring (TDM) in children. The need of TDM in pediatric patients has been emphasized by providing the information on the differences in the drugs pharmacokinetics. TDM of VCZ should be mandatory for all pediatric patients with invasive fungal infections (IFIs). Wide inter- and intrapatient variability in VCZ pharmacokinetics cause achieving and maintaining therapeutic concentration during therapy challenging in this population. Demonstrated studies showed, in most cases, VCZ plasma concentrations to be subtherapeutic, despite the updated dosages recommendations. Only repeated TDM can predict drug exposure and individualizing dosing in antifungal therapy in children. In children treated with mycophenolate mofetil (MMF), similarly as in adult patients, the role of TDM for MMF active form, MPA, has not been well established and is undergoing continued debate. Studies on the MPA TDM have been carried out in children after renal transplantation, other organ transplantation such as heart, liver, or intestine, in children after hematopoietic stem cell transplantation or cord blood transplantation, and in children with lupus, nephrotic syndrome, Henoch-Schönlein purpura, and other autoimmune diseases. MPA TDM is based on the area under the concentration–time curve; however, the proposed values differ according to the treatment indication, and other approaches such as pharmacodynamic and pharmacogenetic biomarkers have been proposed. VAN is a bactericidal agent that requires TDM to prevent an acute kidney disease. The particular group of patients is the pediatric one. For this group, the general recommendations of the dosing may not be valid due to the change of the elimination rate and volume of distribution between the subjects. The other factor is the variability among patients that concerns the free fraction of the drug. It may be caused by both the patients’ population and sample preconditioning. Although VCZ, MMF, and VAN have been applied in pediatric patients for many years, there are still few issues to be solve regarding TDM of these drugs to ensure safe and effective treatment. Except for pharmacokinetic approach, pharmacodynamics and pharmacogenetics have been more often proposed for TDM.