Model-informed Precision Dosing Research Articles

Model-informed precision dosing of vancomycin in clinical practice: an intervention development study.

Current guidelines recommend dosing vancomycin based on the area under the concentration time curve (AUC) to maximise efficacy and minimise the risk of nephrotoxicity. The preferred approach to AUC-guided therapy is to apply model-informed precision dosing (MIPD). However, the adoption in clinical practice has been slow. We aimed to develop an intervention, including a standardised MIPD workflow and an implementation plan for vancomycin AUC-guided dosing, in a Swedish tertiary hospital. The intervention was developed in a framework-guided process. The design phase included stakeholder feedback (nurses, pharmacists, physicians), local data collection and feasibility testing of intervention components with parallel consideration of implementation aspects. The hypothesised relationships between the different components, implementation strategies and the mechanism of action resulting in expected outcomes were represented by a logic model. The final intervention consisted of a workflow for MIPD, with defined roles and responsibilities, as well as processes for data and information transfer. Details were provided in supportive documents; an instruction on therapeutic drug monitoring (TDM) sampling and documentation for nurses, and a detailed dosing software instruction for MIPD consultants and clinical pharmacists. Activities to facilitate implementation included the development of a local clinical routine for vancomycin dosing, staff training and recurring MIPD rounds. An intervention for MIPD, with an implementation plan for AUC-guided dosing of vancomycin, was developed for a tertiary hospital setting. The process can be used as guidance for other institutions with similar context wishing to initiate MIPD.

Population Pharmacokinetic Quantification of CYP2D6 Activity in Codeine Metabolism in Ambulatory Surgical Patients for Model-Informed Precision Dosing.

Codeine metabolism in humans is complex due to the involvement of multiple cytochrome P450 (CYP) enzymes, and has a strong genetic underpinning, which determines the levels of relevant CYP450 enzyme expression in vivo. Polymorphic CYP2D6 metabolises codeine to morphine via O-demethylation, while a strong correlation between CYP2D6 phenotype and opioidergic adverse effects of codeine is well documented. The aim of this study was to quantify the effect of CYP2D6 genotype on the biotransformation of codeine. We conducted a prospective clinical trial with 1000 patients, during which ambulatory patients were administered 60 mg of codeine preoperatively and the association between CYP2D6 activity and morphine exposure across various CYP2D6 genotypes was quantified using a population pharmacokinetic model. Plasma concentration data for codeine and its primary metabolites were obtained from 997 patients and CYP2D6 genotype was screened for study subjects, and respective sums of activity scores assigned for each CYP2D6 allele were used as covariates in model development. Our final model predicts the disposition of codeine and the formation of morphine, codeine-6-glucuronide and morphine-3-glucuronide adequately while accounting for variability in morphine exposure on the basis of CYP2D6 genotype. In agreement with previous results, patients with decreased function alleles (CYP2D6*10 and *41) showed varying levels of decrease in CYP2D6 activity that were inconsistent with increasing activity scores. Model simulations demonstrate that morphine concentrations in ultrarapid CYP2D6 metabolisers reach systemic concentrations that can potentially cause respiratory depression (over 9.1 ng/mL), and have 218% higher exposure (19 versus 8.7 µg · h/L, p < 0.001) to morphine than normal metabolisers. Similarly, poor and intermediate metabolisers had significantly reduced morphine exposure (1.0 and 3.7 versus 8.7 µg · h/L, p < 0.001) as compared with normal metabolisers. Our final model leads the way in implementing model-informed precision dosing in codeine therapy and identifies the use of genetic testing as an integral component in the effort to implement rational pharmacotherapy with codeine.

A multicentric, randomized, controlled clinical trial to study the impact of bedside model-informed precision dosing of vancomycin in critically ill children—BENEFICIAL trial

BackgroundVancomycin is a commonly prescribed antibiotic to treat serious Gram-positive infections in children. The efficacy of vancomycin is known to be directly related to the pharmacokinetic/pharmacodynamic (PK/PD) index of the area under the concentration–time curve (AUC) divided by the minimal inhibitory concentration (MIC) of the pathogen. In most countries, steady-state plasma concentrations are used as a surrogate parameter for this target AUC/MIC, but this practice has some drawbacks. Hence, AUC-based dosing using model-informed precision dosing (MIPD) tools has been proposed for increasing the target attainment rate and reducing vancomycin-related nephrotoxicity. Solid scientific evidence for these claimed benefits is lacking in children. This randomized controlled trial aims to investigate the large-scale utility of MIPD dosing of vancomycin in critically ill children.MethodsParticipants from 14 neonatal intensive care, pediatric intensive care, and pediatric hemo-oncology ward units from 7 hospitals are randomly allocated to the intervention or standard-of-care comparator group. In the intervention group, a MIPD dosing calculator is used for AUC-based dosing, in combination with extra sampling for therapeutic drug monitoring in the first hours of treatment, as compared to standard-of-care. An AUC24h between 400 and 600 is targeted, assuming an MIC of 1 mg/L. Patients in the comparator group receive standard-of-care dosing and monitoring according to institutional guidelines. The primary endpoint is the proportion of patients reaching the target AUC24h/MIC of 400–600 between 24 and 48 h after the start of vancomycin treatment. Secondary endpoints are the proportion of patients with (worsening) acute kidney injury during vancomycin treatment, the proportion of patients reaching target AUC24h/MIC of 400–600 between 48 and 72 h after the start of vancomycin treatment, time to clinical cure, ward unit length-of-stay, hospital length-of-stay, and 30-day all-cause mortality.DiscussionThis trial will clarify the propagated benefits and provide new insights into how to optimally monitor vancomycin treatment in critically ill children.Trial registrationEudract number: 2019–004538-40. Registered on 2020–09-08ClinicalTrials.gov NCT046666948. Registered on 2020–11-28

Impacts of age and BMI on vancomycin model choice in a Bayesian software: Lessons from a very large multi-site retrospective study.

Model-informed precision dosing (MIPD) optimizes drug doses based on pharmacokinetic (PK) model predictions, necessitating careful selection of models tailored to patient characteristics. This study evaluates the predictive performance of various vancomycin PK models across diverse age and BMI categories, drawing insights from a large multi-site database. Adults receiving vancomycin intravenous therapy at United States health systems between January 1, 2022, and December 31, 2023, were included. Patient demographics, vancomycin administration records, and therapeutic drug monitoring levels (TDMs) were collected from the InsightRX database. Age and body mass index (BMI)-based subgroups were formed to assess model performance, with predictions made iteratively. The optimal model for each age-BMI subgroup was chosen based on predefined criteria: models were filtered for mean percentage error (MPE) ≤ 20% and normalized root mean squared error (RMSE) < 8 mg/L, and then the most accurate among them was selected. A total of 384,876 treatment courses across 155 US health systems were analyzed, contributing 841,604 TDMs. Eleven models were compared, showing varying accuracy across age-BMI categories (41%-73%), with higher accuracy observed once TDMs were available for Bayesian estimates of individual PK parameters. Models performed more poorly in younger adults compared to older adults, and the optimal model differed depending on age-BMI categories and prediction methods. Notably, in the a priori period, the Colin model performed best in adults aged 18-64 years across most BMI categories; the Goti/Tong model performed best in the older, non-obese adults; and the Hughes model performed best in many of the obese categories. Our study identifies specific vancomycin PK models that demonstrate superior predictions across age-BMI categories in MIPD applications. Our findings underscore the importance of tailored model selection for vancomycin management, especially highlighting the need for improved models in younger adult patients. Further research into the clinical implications of model performance is warranted to enhance patient care outcomes.

Model-Informed Precision Dosing for Personalized Ustekinumab Treatment in Plaque Psoriasis.

Implementing model-informed precision dosing (MIPD) strategies guided by population pharmacokinetic/pharmacodynamic (PK/PD) models could enhance the management of inflammatory diseases such as psoriasis. However, the extent of individual experimental data gathered during MIPD significantly influences the uncertainty in estimating individual PK/PD parameters, affecting clinical dose selection decisions. This study proposes a methodology to individualize ustekinumab (UTK) dosing strategies for 23 Spanish patients with moderate to severe chronic plaque psoriasis., considering the uncertainty of individual parameters within a population PK/PD model. An indirect response model from previous research was used to describe the PK/PD relationship between UTK serum concentrations and the Psoriasis Area and Severity Index (PASI) score. A maximum inhibition drug effect (Imax) model was selected, and a first-order remission constant rate of psoriatic skin lesion (kout = 0.016 d-1) was estimated. The MIPD approach predicted that 35% and 26% of the patients would need an optimized and intensified dosage regimen, respectively, compared to the regimen typically used in clinical practice. This analysis demonstrated its utility as a tool for selecting personalized UTK dosing regimens in clinical practice in order to optimize the probability of achieving targeted clinical outcomes in patients with psoriasis.

Pharmacokinetic model-guided enoxaparin dosing in the Neonatal ICU: Retrospective cohort study to plan for prospective feasibility trial.

Traditional milligram per kilogram (mg/kg) dosing of enoxaparin in neonates frequently fails to achieve target anti-Xa levels promptly, necessitating repeated laboratory monitoring and dose adjustments. This study investigated whether a personalized dosing strategy based on predicted individual clearance and volume of distribution could improve outcomes, comparing standard-of-care (SOC) mg/kg dosing to pharmacokinetic (PK) model-informed precision dosing (MIPD). A retrospective analysis was conducted on hospitalized neonates treated with enoxaparin at less than 44 weeks postmenstrual age from 2019 to 2022. Data on demographics, drug dosing, PK model covariates, and clinical outcomes were extracted from electronic health records and analyzed using the Pumas-AI Lyv dosing tool. The primary focus was on comparing the initial SOC dose to the MIPD-recommended dose. The secondary outcome measured was the time required to achieve therapeutic anti-Xa levels. The study included 168 neonates with a median postnatal age of 15 days (range 1-149) and a median dosing weight of 3.1 kg (range: 0.82-5.2). MIPD-recommended initial doses were 20%-60% higher than SOC doses in 32% of the cases and over 60% higher in 11% of cases. Neonates who received SOC doses that were much lower than the MIPD recommendation showed the longest delays in reaching therapeutic anti-Xa levels. The results indicate that PK model-informed of enoxaparin dosing leads to higher initial dosages than SOC in neonates, potentially reducing the time to therapeutic anti-Xa levels. These findings are being utilized to define dosing limits for a prospective trial of MIPD in neonatal intensive care settings.

Safety and efficacy of personalised versus standard dosing of linezolid in patients with sepsis (SePkLin): a pragmatic, multicentre, randomised, controlled and superiority clinical trial protocol.

Linezolid is a broadly used antibiotic to treat complicated infections caused by gram-positive bacteria. Therapeutic drug monitoring of linezolid concentrations is recommended to maximise its efficacy and safety, mainly haematological toxicity. Different pharmacokinetic/pharmacodynamic targets have been proposed to improve linezolid exposure: the ratio of the area under the concentration-time curve during a 24-hour period to minimum inhibitory concentration (MIC) between 80 and 120; percentage of time that the drug concentration remains above the MIC during a dosing interval greater than 85% and the trough concentration between 2 and 7 mg/L. This clinical trial aims to evaluate the safety, efficacy and the clinical and economic utility of personalised dosing of linezolid using Bayesian forecasting methods to attain pharmacokinetic/pharmacodynamic targets, known as model-informed precision dosing. This is a pragmatic, multicentre, randomised, parallel, controlled, phase IV and low intervention trial. Participants will be randomly assigned 1:1 to each group (n=346 per group). Control group will receive the standard dose of linezolid. Intervention group will receive personalised dosage of linezolid based on pharmacokinetic-pharmacodynamic adjustments. The primary outcome will be the incidence of thrombocytopenia in both groups. This protocol was approved by the Ethical Committee of the Investigation with Medicines of Galicia (code 2022/140) and authorised by the Spanish Agency for Medicines and Medical Devices. The trial is implemented in accordance with the Declaration of Helsinki and the international ethical and scientific quality standard, the Good Clinical Practice. The results will be published in peer-reviewed journals. EudraCT registration code: 2022-000144-30.

Everolimus Personalized Therapy: Second Consensus Report by the International Association of Therapeutic Drug Monitoring and Clinical Toxicology.

The Immunosuppressive Drugs Scientific Committee of the International Association of Therapeutic Drug Monitoring and Clinical Toxicology established the second consensus report to guide Therapeutic Drug Monitoring (TDM) of everolimus (EVR) and its optimal use in clinical practice 7 years after the first version was published in 2016. This version provides information focused on new developments that have arisen in the last 7 years. For the general aspects of the pharmacology and TDM of EVR that have retained their relevance, readers can refer to the 2016 document. This edition includes new evidence from the literature, focusing on the topics updated during the last 7 years, including indirect pharmacological effects of EVR on the mammalian target of rapamycin complex 2 with the major mechanism of direct inhibition of the mammalian target of rapamycin complex 1. In addition, various concepts and technical options to monitor EVR concentrations, improve analytical performance, and increase the number of options available for immunochemical analytical methods have been included. Only limited new pharmacogenetic information regarding EVR has emerged; however, pharmacometrics and model-informed precision dosing have been constructed using physiological parameters as covariates, including pharmacogenetic information. In clinical settings, EVR is combined with a decreased dose of calcineurin inhibitors, such as tacrolimus and cyclosporine, instead of mycophenolic acid. The literature and recommendations for specific organ transplantations, such as that of the kidneys, liver, heart, and lungs, as well as for oncology and pediatrics have been updated. EVR TDM for pancreatic and islet transplantation has been added to this edition. The pharmacodynamic monitoring of EVR in organ transplantation has also been updated. These updates and additions, along with the previous version of this consensus document, will be helpful to clinicians and researchers treating patients receiving EVR.

Pharmacokinetic Model of Drug Interaction of Tacrolimus with Combined Administration of CYP3A4 Inhibitors Voriconazole and Clarithromycin After Bone Marrow Transplantation.

A pharmacokinetic model has been developed to quantify the drug-drug interactions of tacrolimus with concentration-dependent inhibition of cytochrome P450 (CYP) 3A4 from voriconazole and clarithromycin based on the CYP3A5 and CYP2C19 genotypes. This retrospective study recruited unrelated bone marrow transplant recipients receiving oral tacrolimus concomitantly with voriconazole and clarithromycin. The published population pharmacokinetic model that implemented genotypes of CYP3A5 (tacrolimus) and CYP2C19 (voriconazole) was integrated. The tested CYP3A4 inhibition models (Sigmoid efficacy maximum [Emax], Emax, log-linear, and linear) were a function of competitive inhibition of voriconazole and mechanism-based inhibition of clarithromycin in a virtual enzyme compartment. The total tacrolimus trough concentrations were 119 points, with a median of 4.3 (range: 2.0-9.9) ng/mL (n = 3). The final model comprised the Sigmoid Emax model for voriconazole and clarithromycin, which depicted time-course alterations in tacrolimus concentration and clearance when given voriconazole and clarithromycin. These findings could facilitate the model-informed precision dosing of tacrolimus after unrelated bone marrow transplant.

Model-Informed Precision Dosing of Tacrolimus: A Systematic Review of Population Pharmacokinetic Models and a Benchmark Study of Software Tools.

Tacrolimus is an immunosuppressant commonly administered after solid organ transplantation. It is characterized by a narrow therapeutic window and high variability in exposure, demanding personalized dosing. In recent years, population pharmacokinetic models have been suggested to guide model-informed precision dosing of tacrolimus. We aimed to provide a comprehensive overview of population pharmacokinetic models and model-informed precision dosing software modules of tacrolimus in all solid organ transplant settings, including a simulation-based investigation of the impact of covariates on exposure and target attainment. We performed a systematic literature search to identify population pharmacokinetic models of tacrolimus in solid organ transplant recipients. We integrated selected population pharmacokinetic models into an interactive software tool that allows dosing simulations, Bayesian forecasting, and investigation of the impact of covariates on exposure and target attainment. We conducted a web survey amongst model-informed precision dosing software tool providers and benchmarked publicly available tools in terms of models, target populations, and clinical integration. We identified 80 population pharmacokinetic models, including 44 one-compartment and 36 two-compartment models. The most frequently retained covariates on clearance and distribution parameters were cytochrome P450 3A5 polymorphisms and body weight, respectively. Our simulation tool, hosted at https://lpmx.shinyapps.io/tacrolimus/ , allows thorough investigation of the impact of covariates on exposure and target attainment. We identified 15 model-informed precision dosing software tool providers, of which ten offer a tacrolimus solution and nine completed the survey. Our work provides a comprehensive overview of the landscape of available tacrolimus population pharmacokinetic models and model-informed precision dosing software modules. Our simulation tool allows an interactive thorough exploration of covariates on exposure and target attainment.

Dosing Evaluation of Ceftazidime-Avibactam in Intensive Care Unit Patients Based on Pharmacokinetic/Pharmacodynamic (PK/PD) Modeling and Simulation.

P. aeruginosa is the most common microorganism involved in many ICU-acquired infections. A correct dosage regimen is pivotal to avoiding resistance development, worse outcomes and higher mortality rates. The aim of this study was to perform a pharmacokinetic-pharmacodynamic (PK/PD) evaluation of recommended dosing regimens of ceftazidime-avibactam (CAZ-AVI) in ICU patients with different degrees of renal function for a specific strain of Pseudomonas aeruginosa. A semi-mechanistic PK/PD model has been developed. It allows for the simulation of CAZ-AVI steady-state plasma level curves and the evolution of bacterial growth curves. The percentage of bacterial load reduction and the value of the recommended PK/PD indices have been taken into account to define the success or failure of the regimens. Probabilistic analysis was performed using Monte Carlo simulations of two populations: control and ICU. In both populations, dosing regimens endorsed for patients with CLcr higher than 10 mL/min reach the PK/PD indices recommended, T > MIC > 90% and Cmin/MIC > 1.3. While dosage regimens endorsed for patients with CLcr of 10 mL/min or lower fail (T > MIC < 60% and Cmin/MIC < 0.35). However, proposed dosing regimens based on shortening dosing intervals for these patients would be successful, increasing bacterial load reduction by almost 50% and reaching the proposed PK/PD indices. Therefore, CAZ-AVI dosing strategies based on model-informed precision dosing (MIPD) could directly influence the efficacy of results in ICU patients with renal insufficiency.

A small step toward precision dosing of caffeine in preterm infants: An external evaluation of published population pharmacokinetic models

BackgroundSeveral population pharmacokinetic (PopPK) models of caffeine in preterm infants have been published, but the extrapolation of these models to facilitate model-informed precision dosing (MIPD) in clinical practice is uncertain. This study aimed to comprehensively evaluate their predictive performance using an external, independent dataset. MethodsData used for external evaluation were based on an independent cohort of preterm infants. Currently available PopPK models for caffeine in preterm infants were identified and re-established. Prediction- and simulation-based diagnostics were used to assess model predictability. The influence of prior information was assessed using Bayesian forecasting. Results120 plasma samples from 76 preterm infants were included in the evaluation dataset. Twelve PopPK models of caffeine in preterm infants were re-established based on our previously published study. Although two models showed superior predictive performance, none of the 12 PopPK models met all the clinical acceptance criteria of these external evaluation items. Besides, the external predictive performances of most models were unsatisfactory in prediction- and simulation-based diagnostics. Nevertheless, the application of Bayesian forecasting significantly improved the predictive performance, even with only one prior observation. ConclusionsTwo models that included the most covariates had the best predictive performance across all external assessments. Inclusion of different covariates, heterogeneity of preterm infant characteristics, and different study designs influenced predictive performance. Thorough evaluation is needed before these PopPK models can be implemented in clinical practice. The implementation of MIPD for caffeine in preterm infants could benefit from the combination of PopPK models and Bayesian forecasting as a helpful tool.

Precision Dosing of Meropenem in Adults with Normal Renal Function: Insights from a Population Pharmacokinetic and Monte Carlo Simulation Study.

This study aimed to develop a population pharmacokinetic (PK) model for meropenem in healthy adults and explore optimal dosing regimens for patients with normal renal function. PK samples were obtained from 12 healthy participants, which were analyzed using noncompartmental analysis and nonlinear mixed-effect modeling. The PK profiles of meropenem were characterized using a two-compartment model, and serum creatinine level was identified as a significant covariate affecting total clearance. Monte Carlo simulations were conducted using this model to inform dosing recommendations. The target index for meropenem efficacy was defined as the cumulative percentage over 24 h during which free (f) drug concentration exceeded the minimum inhibitory concentration (MIC) under steady state conditions (fT>MIC). These simulations indicated that the current dosage regimen of 1 g for 30 min infusions every 8 h achieved a 90% probability of target attainment (PTA) for 40%fT>MIC when the MIC was <2 mg/L. However, to achieve more stringent therapeutic targets, such as a 90%PTA for 100%fT>MIC or a 90%PTA for 100%fT>4MIC, higher doses administered as 3 h extended infusions or as continuous infusions may be necessary. These results highlight the need for model-informed precision dosing to enhance the efficacy of meropenem therapy across various MIC levels and therapeutic targets.

Physiologically Based Pharmacokinetic Modeling of Vancomycin and its Comparison with Population Pharmacokinetic Model in Neonates.

Vancomycin has a narrow therapeutic window and a high inter-individual pharmacokinetic variability, especially in neonates with fast maturational and pathophysiological changes, that needs individualized dosing. Physiologically based pharmacokinetic (PBPK) model and population pharmacokinetic (PopPK) model are both useful tools in model-informed precision dosing, while the former is under research in application of vancomycin in neonates. This study aimed to develop a PBPK model of vancomycin in adult and pediatric population, and compared it with published PopPK model (priori or Bayesian method) in predicting vancomycin concentration in 230 neonatal patients (postmenstrual age, PMA, 25-45 weeks). The developed PBPK model showed a good fit between predictions and observations. PBPK model and PopPK model are complementary in different clinical scenarios of vancomycin application. The physiological-change description of PBPK model showed a superior advantage in initial dosing optimization. As for subsequent dose optimization, PopPK Bayesian forecasting performed better than the PBPK estimation in neonates. However, initial precision dosing tools for early neonates (with PMA < 36 weeks) still need further exploitation.

Development and application of a population pharmacokinetic model repository for caffeine dose tailoring in preterm infants

ABSTRACT Background Considerable interindividual variability for the pharmacokinetics of caffeine in preterm infants has been demonstrated, emphasizing the importance of personalized dosing. This study aimed to develop and apply a repository of currently published population pharmacokinetic (PopPK) models of caffeine in preterm infants to facilitate model-informed precision dosing (MIPD). Research design and methods Literature search was conducted using PubMed, Embase, Scopus, and Web of Science databases. Relevant publications were screened, and their quality was assessed. PopPK models were reestablished to develop the model repository. Covariate effects were evaluated and the concentration–time profiles were simulated. An online simulation and calculation tool was developed as an instance. Results Twelve PopPK models were finally included in the repository. Preterm infants’ age and body size, especially the postnatal age and current weight, were identified as the most clinically critical covariates. Simulated blood concentration–time profiles across these models were comparable. Caffeine citrate-dose regimen should be adjusted according to the age and body size of preterm infants. The developed online tool can be used to facilitate clinical decision-making. Conclusions The first developed repository of PopPK models for caffeine in preterm infants has a wide range of potential applications in the MIPD of caffeine.

Predictive performance of multi-model approaches for model-informed precision dosing of piperacillin in critically ill patients

ObjectivesPiperacillin (PIP)/tazobactam is a frequently prescribed antibiotic; however, over- or underdosing may contribute to toxicity, therapeutic failure, and development of antimicrobial resistance. An external evaluation of 24 published PIP-models demonstrated that model-informed precision dosing (MIPD) can enhance target attainment. Employing various candidate models, this study aimed to assess the predictive performance of different MIPD-approaches comparing (i) a single-model approach, (ii) a model selection algorithm (MSA) and (iii) a model averaging algorithm (MAA). MethodsPrecision, accuracy and expected target attainment, considering either initial (B1) or initial and secondary (B2) therapeutic drug monitoring (TDM)-samples per patient, were assessed in a multicentre dataset (561 patients, 11 German centres, 3654 TDM-samples). ResultsThe results demonstrated a slight superiority in predictive performance using MAA in B1, regardless of the candidate models, compared to MSA and the best single models (MAA, MSA, best single models: inaccuracy ±3%, ±10%, ±8%; imprecision: <25%, <31%, <28%; expected target attainment >77%, >71%, >73%). The inclusion of a second TDM-sample notably improved precision and target attainment for all MIPD-approaches, particularly within the context of MSA and most of the single models. The expected target attainment is maximized (up to >90%) when the TDM-sample is integrated within 24 h. ConclusionsIn conclusion, MAA streamlines MIPD by reducing the risk of selecting an inappropriate model for specific patients. Therefore, MIPD of PIP using MAA implicates further optimisation of antibiotic exposure in critically ill patients, by improving predictive performance with only one sample available for Bayesian forecasting, safety, and usability in clinical practice.

Optimization of oral isavuconazole dose for population in special physiological or pathological state: a physiologically based pharmacokinetics model-informed precision dosing.

To recommend precision dosing and improve therapeutic efficacy against invasive fungal disease, a physiologically based pharmacokinetic model (PBPK) of oral isavuconazole (ISA) was established and used to explore its disposition across populations in different physiological and pathological states. Twenty-five pharmacokinetic (PK) studies of oral ISA were identified through a systematic search of PubMed. Concentration-time data were extracted using WebPlotDigitizer. Physiochemical parameters were obtained from published literature and DrugBank. Model development and simulation used the Simcyp population-based simulator, and visual predictive check and predictive error were used for the model evaluation. Probability of target attainment and the cumulative fraction of response analyses were performed for dose optimization. The developed PBPK model was successfully validated in different populations. Most predicted concentration-time points aligned with the observed data, with acceptable predictive errors for the critical parameters. We predicted the PK profiles and parameters of ISA in a population with severe hepatic impairment (HI), a population with obesity and paediatric patients aged 1 to less than 6 years old. The probability of target attainment and cumulative fraction of response analyses indicated that the population with severe HI should have half the maintenance dose. The population with obesity and population with severe HI should have a loading dose of 300 mg every 8 h for 2 days. For paediatric patients aged 1 to less than 6 years old, a weight-based dosing regimen (5.38 mg/kg) of ISA was suggested. The predicted value aligns with observations, suggesting ISA's potential predictability in PK profiles for other populations. The recommended dosing regimens increase our understanding of the use of ISA in special populations.

The potential for therapeutic drug monitoring of belatacept and other biologicals in solid organ transplantation.

In solid organ transplantation (SOT), biologicals such as recombinant therapeutic proteins, monoclonal antibodies, fusion proteins and conjugates are increasingly used for immunosuppression, desensitization, ABO (blood group) incompatibility, antibody-mediated rejections and atypical haemolytic uremic syndrome. In this paper, we review the medical evidence available for biologicals used in SOT and the potential for improvement by the application of therapeutic drug monitoring (TDM) and model-informed precision dosing. Biologicals are used for off-label indications within the field of SOT, building on the experience from their use on labelled indications. Dosing is currently mostly standard, and experience vs. effect and toxicity is limited. Pharmacokinetic characteristics of these large, partly also immunogenic molecules differ from those of traditional small molecules. Individualization by concentration measurements and modelling has mostly been proof-of-concept or feasibility studies that lack the power to provide evidence for improvement in clinical outcome. For some drugs such as alemtuzumab, eculizumab, rituximab, tocilizumab and belatacept, studies have demonstrated significant interindividual variability in pharmacokinetics. Variability in absorption from subcutaneous administration may increase interindividual variability. There is also an economic aspect of appropriate dosing that needs to be pursued. Available assays and models to refine interpretation are in place, but trials of adequate size to document the usefulness of TDM and MIPD are scarce. Collaboration within the TDM community seems mandatory to establish studies of sufficient strength to provide evidence for the use of biologicals that are currently used off-label in SOT and furthermore to identify the settings where TDM may be beneficial.

External Evaluation of Population Pharmacokinetic Models of Piperacillin in Preterm and Term Patients from Neonatal Intensive Care.

Piperacillin/tazobactam is extensively used off-label to treat late-onset neonatal sepsis, but safety and pharmacokinetic data in this population are limited. Additionally, the organic immaturity of the newborns contributes to a high piperacillin pharmacokinetic variability. This affects the clinical efficacy of the antibiotic treatment and increases the probability of developing drug resistance. This study aimed to evaluate the predictive performance of reported piperacillin population pharmacokinetic models for their application in a model-informed precision dosing strategy in preterm and term Mexican neonatal intensive care patients. Published population pharmacokinetic models for piperacillin which included neonates in their study population were identified. From the reference models, structured models, population pharmacokinetic parameters, and interindividual and residual variability data were extracted to be replicated in pharmacokinetic software (NONMEM® version 7.4). For the clinical study, a sampling schedule was designed, and 2-3 blood samples of 250 µL were taken from neonates who met the inclusion criteria. Piperacillin plasma concentrations were determined by liquid chromatography/tandem mass spectrometry. The clinical treatment data were collected, and piperacillin plasma concentrations were estimated using reference pharmacokinetic models for an a priori or Bayesian approach. Statistical methods were used in terms of bias and precision to evaluate the differences between observed and estimated neonatal piperacillin plasma concentrations with the different approaches and to identify the pharmacokinetic model that best fits the neonatal data. A total of 70 plasma samples were collected from 25 neonatal patients, of which 15 were preterm neonates. The overall median value (range) postnatal age, gestational age, body weight, and serum creatinine at the sampling collecting day were 12 (3-26) days, 34.2 (26-41.1) weeks, 1.78 (0.08-3.90) Kg, 0.47 (0.20-0.90) mg/dL, respectively. Three population pharmacokinetic models for piperacillin in infants up to 2months were identified, and their predictive performance in neonatal data was evaluated. No pharmacokinetic model was suitable for our population using an a priori approach. The model published by Cohen-Wolkowiez et al. in 2014 with a Bayesian approach showed the best performance of the pharmacokinetic models evaluated in our neonatal data. The procedure requires two blood samples (predose and postdose), and, when applied, it predicted 66.6% of the observations with a relative median absolute predicted error of less than 30%. The population pharmacokinetic model developed by Cohen-Wolkowiez et al. in 2014 demonstrated superior performance in predicting the plasma concentration of piperacillin in preterm and term Mexican neonatal intensive care patients. The Bayesian approach, including two different piperacillin plasma concentrations, was clinically acceptable regarding bias and precision. Its application for model-informed precision dosing can be an option to optimize the piperacillin dosage in our population.

Personalized Dosing of Medicines for Children: A Primer on Pediatric Pharmacometrics for Clinicians.

The widespread use of drugs for unapproved purposes remains common in children, primarily attributable to practical, ethical, and financial constraints associated with pediatric drug research. Pharmacometrics, the scientific discipline that involves the application of mathematical models to understand and quantify drug effects, holds promise in advancing pediatric pharmacotherapy by expediting drug development, extending applications, and personalizing dosing. In this review, we delineate the principles of pharmacometrics, and explore its clinical applications and prospects. The fundamental aspect of any pharmacometric analysis lies in the selection of appropriate methods for quantifying pharmacokinetics and pharmacodynamics. Population pharmacokinetic modeling is a data-driven method ('top-down' approach) to approximate population-level pharmacokinetic parameters, while identifying factors contributing to inter-individual variability. Model-informed precision dosing is increasingly used to leverage population pharmacokinetic models and patient data, to formulate individualized dosing recommendations. Physiologically based pharmacokinetic models integrate physicochemical drug properties with biological parameters ('bottom-up approach'), and is particularly valuable in situations with limited clinical data, such as early drug development, assessing drug-drug interactions, or adapting dosing for patients with specific comorbidities. The effective implementation of these complex models hinges on strong collaboration between clinicians and pharmacometricians, given the pivotal role of data availability. Promising advancements aimed at improving data availability encompass innovative techniques such as opportunistic sampling, minimally invasive sampling approaches, microdialysis, and in vitro investigations. Additionally, ongoing research efforts to enhance measurement instruments for evaluating pharmacodynamics responses, including biomarkers and clinical scoring systems, are expected to significantly bolster our capacity to understand drug effects in children.