Pharmacokinetic modelling and Bayesian estimation-assisted decision tools to optimize vancomycin dosage in neonates: only one piece of the puzzle

Optimizing Individualized Antimicrobial Dosing in Pediatric Patients: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

BACKGROUND

Therapeutic drug monitoring (TDM) and target concentration intervention (TCI) represent significant advancements in individualized medicine, aiming to tailor dosages based on patient-specific characteristics. These approaches account for intra- and inter-individual physiological and clinical variability, with the goal of improving target attainment and clinical remission while reducing treatment failure and adverse effects.

OBJECTIVES

The objective is to assess and enhance the current body of randomized controlled trials (RCTs) that have investigated alternative personalized dosing strategies, such as TDM and TCI, in terms of their efficacy and safety for individualized antimicrobial dosing in pediatric populations. Only studies that compared different dosing regimens and reported plasma concentrations were included in the analysis.

METHODS

Databases such as MEDLINE, Embase, Web of Science, and the Cochrane Central Register of Controlled Trials were searched until January 3rd, 2024. Only published, peer-reviewed RCTs were considered for inclusion. The study focused on human subjects aged < 18 years who were receiving an antimicrobial drug. The interventions compared experimental dosing versus standard dosing with TDM or TCI. The risk of bias was assessed using version 2 of the Cochrane risk-of-bias tool for randomized trials. The primary outcome was the attainment of target concentrations, while secondary outcomes included adverse effects, clinical remission, and treatment failure. Data synthesis was performed using the restricted maximum likelihood method, and the risk ratio (RR) was used as the measure of effect size.

RESULTS

Only 11 TDM-based RCTs were included in the study [experimental vs standard doses: 592 (51.3%) patients vs 563 (48.7%) patients]. Experimental dose was significantly associated with improvement in target attainment (RR 1.2587, OR 1.0717-1.4786; p = 0.0051). However, experimental antimicrobial dose optimization was non-significantly associated with a numerical decrease in treatment failure (RR 0.8966, OR 0.7749-1.0374; p = 0.1424). In addition, it was not significant associated with higher adverse effects [RR 1.3408, odds ratio (OR) 0.1783-10.0825; p = 0.7757] and clinical remission rates (RR 4.0589, OR 0.2494-66.0558; p = 0.3250).

CONCLUSIONS

This meta-analysis showed that only target attainment using TDM was significantly improved in pediatric patients treated with experimental doses of antimicrobials compared to standard doses. Larger TCI-focused RCTs are needed to significantly improve treatment failure, adverse effects, and clinical remission.

Physiologically Based Pharmacokinetic Modeling of Vancomycin in Critically Ill Neonates: Assessing the Impact of Pathophysiological Changes

Dosing vancomycin for critically ill neonates is challenging owing to substantial alterations in pharmacokinetics (PKs) caused by variability in physiology, disease, and clinical interventions. Therefore, an adequate PK model is needed to characterize these pathophysiological changes. The intent of this study was to develop a physiologically based pharmacokinetic (PBPK) model that reflects vancomycin PK and pathophysiological changes in neonates under intensive care. PK-sim software was used for PBPK modeling. An adult model (model 0) was established and verified using PK profiles from previous studies. A neonatal model (model 1) was then extrapolated from model 0 by scaling age-dependent parameters. Another neonatal model (model 2) was developed based not only on scaled age-dependent parameters but also on quantitative information on pathophysiological changes obtained via a comprehensive literature search. The predictive performances of models 1 and 2 were evaluated using a retrospectively collected dataset from neonates under intensive care (chictr.org.cn, ChiCTR1900027919), comprising 65 neonates and 92 vancomycin serum concentrations. Integrating literature-based parameter changes related to hypoalbuminemia, small-for-gestational-age, and co-medication, model 2 offered more optimized precision than model 1, as shown by a decrease in the overall mean absolute percentage error (50.6% for model 1; 37.8% for model 2). In conclusion, incorporating literature-based pathophysiological changes effectively improved PBPK modeling for critically ill neonates. Furthermore, this model allows for dosing optimization before serum concentration measurements can be obtained in clinical practice.

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.

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.

CDC Guidelines for the Prevention and Treatment of Anthrax, 2023

This report updates previous CDC guidelines and recommendations on preferred prevention and treatment regimens regarding naturally occurring anthrax. Also provided are a wide range of alternative regimens to first-line antimicrobial drugs for use if patients have contraindications or intolerances or after a wide-area aerosol release of

Bacillus anthracis spores if resources become limited or a multidrug-resistant B. anthracis strain is used (Hendricks KA, Wright ME, Shadomy SV, et al.; Workgroup on Anthrax Clinical Guidelines. Centers for Disease Control and Prevention expert panel meetings on prevention and treatment of anthrax in adults. Emerg Infect Dis 2014;20:e130687; Meaney-Delman D, Rasmussen SA, Beigi RH, et al. Prophylaxis and treatment of anthrax in pregnant women. Obstet Gynecol 2013;122:885-900; Bradley JS, Peacock G, Krug SE, et al. Pediatric anthrax clinical management. Pediatrics 2014;133:e1411-36). Specifically, this report updates antimicrobial drug and antitoxin use for both postexposure prophylaxis (PEP) and treatment from these previous guidelines best practices and is based on systematic reviews of the literature regarding 1) in vitro antimicrobial drug activity against B. anthracis; 2) in vivo antimicrobial drug efficacy for PEP and treatment; 3) in vivo and human antitoxin efficacy for PEP, treatment, or both; and 4) human survival after antimicrobial drug PEP and treatment of localized anthrax, systemic anthrax, and anthrax meningitis.

Changes from previous CDC guidelines and recommendations include an expanded list of alternative antimicrobial drugs to use when first-line antimicrobial drugs are contraindicated or not tolerated or after a bioterrorism event when first-line antimicrobial drugs are depleted or ineffective against a genetically engineered resistant

B. anthracis strain. In addition, these updated guidelines include new recommendations regarding special considerations for the diagnosis and treatment of anthrax meningitis, including comorbid, social, and clinical predictors of anthrax meningitis. The previously published CDC guidelines and recommendations described potentially beneficial critical care measures and clinical assessment tools and procedures for persons with anthrax, which have not changed and are not addressed in this update. In addition, no changes were made to the Advisory Committee on Immunization Practices recommendations for use of anthrax vaccine (Bower WA, Schiffer J, Atmar RL, et al. Use of anthrax vaccine in the United States: recommendations of the Advisory Committee on Immunization Practices, 2019. MMWR Recomm Rep 2019;68[No. RR-4]:1-14). The updated guidelines in this report can be used by health care providers to prevent and treat anthrax and guide emergency preparedness officials and planners as they develop and update plans for a wide-area aerosol release of B. anthracis.

Use of Machine Learning for Dosage Individualization of Vancomycin in Neonates

BACKGROUND AND OBJECTIVE

High variability in vancomycin exposure in neonates requires advanced individualized dosing regimens. Achieving steady-state trough concentration (C0) and steady-state area-under-curve (AUC0-24) targets is important to optimize treatment. The objective was to evaluate whether machine learning (ML) can be used to predict these treatment targets to calculate optimal individual dosing regimens under intermittent administration conditions.

METHODS

C0 were retrieved from a large neonatal vancomycin dataset. Individual estimates of AUC0-24 were obtained from Bayesian post hoc estimation. Various ML algorithms were used for model building to C0 and AUC0-24. An external dataset was used for predictive performance evaluation.

RESULTS

Before starting treatment, C0 can be predicted a priori using the Catboost-based C0-ML model combined with dosing regimen and nine covariates. External validation results showed a 42.5% improvement in prediction accuracy by using the ML model compared with the population pharmacokinetic model. The virtual trial showed that using the ML optimized dose; 80.3% of the virtual neonates achieved the pharmacodynamic target (C0 in the range of 10-20 mg/L), much higher than the international standard dose (37.7-61.5%). Once therapeutic drug monitoring (TDM) measurements (C0) in patients have been obtained, AUC0-24 can be further predicted using the Catboost-based AUC-ML model combined with C0 and nine covariates. External validation results showed that the AUC-ML model can achieve an prediction accuracy of 80.3%.

CONCLUSION

C0-based and AUC0-24-based ML models were developed accurately and precisely. These can be used for individual dose recommendations of vancomycin in neonates before treatment and dose revision after the first TDM result is obtained, respectively.

Pharmacokinetic Model Based on Stochastic Simulation and Estimation for Therapeutic Drug Monitoring of Tacrolimus in Korean Adult Transplant Recipients

BACKGROUND

Tacrolimus shows high variability in inter- and intraindividual pharmacokinetics (PK); therefore, it is important to develop an appropriate model for accurate therapeutic drug monitoring (TDM) procedures. This study aimed to develop a pharmacokinetic model for tacrolimus that can be used for TDM procedures in Korean adult transplant recipients by integrating published models with acquired real-world TDM data and evaluating clinically meaningful covariates.

METHODS

Clinical data of 1829 trough blood samples from 269 subjects were merged with simulated data sets from published models and analyzed using a nonlinear mixed-effect model. The stochastic simulation and estimation (SSE) method was used to obtain the final parameter estimates.

RESULTS

The final estimated values for apparent clearance, the volume of distribution, and absorption rate were 21.2 L/h, 510 L, and 3.1/h, respectively. The number of postoperative days, age, body weight, and type of transplant organs were the major clinical factors affecting tacrolimus PK.

CONCLUSIONS

A tacrolimus PK model that can incorporate published PK models and newly collected data from the Korean population was developed using the SSE method. Despite the limitations in model development owing to the nature of TDM data, the SSE method was useful in retrieving complete information from the TDM data by integrating published PK models while maintaining the variability of the model.

An Audit to Evaluate Vancomycin Therapeutic Drug Monitoring in a Neonatal Intensive Care Unit

BACKGROUND

Therapeutic drug monitoring (TDM) is routinely used for optimization of vancomycin therapy, because of exposure-related efficacy and toxicity, in addition to significant variability in pharmacokinetics, which leads to unpredictable drug exposure.

OBJECTIVE

The aim of this study was to evaluate target attainment and TDM of vancomycin in neonates.

METHODS

The authors conducted a retrospective study and collected data from medical records of all neonates who received vancomycin therapy in the neonatal intensive care unit between January 2019 and December 2019. The primary outcome was the proportion of vancomycin courses that reached target trough concentrations of 10-20 mg/L based on appropriate TDM samples collection. Secondary outcomes included proportion of courses with appropriate dose and dose frequency, and proportion of patients who achieved target concentrations after the first dose adjustment.

RESULTS

In total, 69 patients were included, with 129 vancomycin courses. The median initial vancomycin trough concentration was 12 (range: 4-36) mg/L. The target trough concentration was achieved in 75% of courses after the initial dose with appropriate TDM, and 84% of courses after TDM-guided dose adjustments. Patients were dosed appropriately in 121/129 courses and TDM was performed correctly according to protocol in 51/93 courses. A dose adjustment was performed in 18/29 courses, to increase target attainment.

CONCLUSIONS

This study showed that there is a need for an increase in dose to improve target attainment. There is also a need to explore more effective TDM strategies to increase the proportion of neonatal patients attaining vancomycin target trough concentrations.

Optimal exposure targets for vancomycin in the treatment of neonatal coagulase-negative Staphylococcus infection: A retrospective study based on electronic medical records

BACKGROUND

The currently advocated ratio of area under the curve (AUC) over 24 h to minimum inhibitory concentration (AUC/MIC) > 400 and AUC < 600 mg h/L as the therapeutic drug monitoring (TDM) target of vancomycin is based on data from multiple observational studies in adult patients with methicillin-resistant Staphylococcus aureus (MRSA) infection. It may not be applicable to newborns with coagulase-negative Staphylococcus (CoNS) infection. We conducted a retrospective study to identify the optimal exposure targets for vancomycin in the treatment of neonatal CoNS infection.

METHODS

Based on the inclusion and exclusion criteria, serum vancomycin concentration, demographics, clinical data, and related laboratory data of newborns who received vancomycin intravenous infusion from June 1, 2016 to February 1, 2021 were collected retrospectively. The AUC was calculated using the maximum a posteriori Bayesian (MAPB) method. The vancomycin exposure threshold of AUC/MIC for efficacy and AUC for toxicity (acute kidney injury, AKI) were determined based on receiver operating characteristic (ROC) curve analysis. The correlation between vancomycin exposure and both clinical effect and nephrotoxicity was analyzed using logistic multivariate regression.

RESULTS

In total, 153 patients and 245 vancomycin concentrations (160 trough and 85 peak concentrations) were included. The ROC curve analysis showed that the exposure thresholds of AUC/MIC for clinical efficacy and AUC for nephrotoxicity were 281 and 602 mg h/L, respectively. The multivariate regression analysis showed that AUC/MIC > 280 was a predictor of efficacy (OR: 13.960, 95% CI: 1.891-103.078, P < 0.05) and AUC > 600 mg h/L was associated with AKI (OR: 9.008, 95% CI: 2.706-29.983, P < 0.05). The vancomycin AUC/MIC threshold for treating neonatal CoNS infection with vancomycin is lower than the currently advocated AUC/MIC >400.

CONCLUSION

The optimal exposure targets for vancomycin in neonatal CoNS infection were AUC/MIC > 280 and AUC < 600 mg h/L.

Knowledge gaps in late-onset neonatal sepsis in preterm neonates: a roadmap for future research

Late-onset neonatal sepsis (LONS) remains an important threat to the health of preterm neonates in the neonatal intensive care unit. Strategies to optimize care for preterm neonates with LONS are likely to improve survival and long-term neurocognitive outcomes. However, many important questions on how to improve the prevention, early detection, and therapy for LONS in preterm neonates remain unanswered. This review identifies important knowledge gaps in the management of LONS and describe possible methods and technologies that can be used to resolve these knowledge gaps. The availability of computational medicine and hypothesis-free-omics approaches give way to building bedside feedback tools to guide clinicians in personalized management of LONS. Despite advances in technology, implementation in clinical practice is largely lacking although such tools would help clinicians to optimize many aspects of the management of LONS. We outline which steps are needed to get possible research findings implemented on the neonatal intensive care unit and provide a roadmap for future research initiatives. IMPACT: This review identifies knowledge gaps in prevention, early detection, antibiotic, and additional therapy of late-onset neonatal sepsis in preterm neonates and provides a roadmap for future research efforts. Research opportunities are addressed, which could provide the means to fill knowledge gaps and the steps that need to be made before possible clinical use. Methods to personalize medicine and technologies feasible for bedside clinical use are described.

Target Attainment and Clinical Efficacy for Vancomycin in Neonates: Systematic Review

Vancomycin is commonly used as a treatment for neonatal infections. However, there is a lack of consensus establishing the optimal vancomycin therapeutic regimen and defining the most appropriate PK/PD parameter correlated with the efficacy. A recent guideline recommends AUC-guided therapeutic dosing in treating serious infections in neonates. However, in clinical practice, trough serum concentrations are commonly used as a surrogate PKPD index for AUC24. Despite this, target serum concentrations in a neonatal population remain poorly defined. The objective is to describe the relationship between therapeutic regimens and the achievement of clinical or pharmacokinetic outcomes in the neonatal population. The review was carried out following PRISMA guidelines. A bibliographic search was manually performed for studies published on PubMed and EMBASE. Clinical efficacy and/or target attainment and the safety of vancomycin treatment were evaluated through obtaining serum concentrations. A total of 476 articles were identified, of which 20 met the inclusion criteria. All of them evaluated the target attainment, but only two assessed the clinical efficacy. The enormous variability concerning target serum concentrations is noteworthy, which translates into a difficulty in determining which therapeutic regimen achieves the best results. Moreover, there are few studies that analyze clinical efficacy results obtained after reaching predefined trough serum concentrations, this information being essential for clinical practice.

Population pharmacokinetics and dose optimization of vancomycin in neonates

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 AUC_0–24 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.

Individualized Vancomycin Dosing with Therapeutic Drug Monitoring and Pharmacokinetic Consultation Service: A Large-Scale Retrospective Observational Study

Background

To date, outcome data with a large sample size and data regarding the clinical outcomes of pharmacokinetic-guided (PK) dosing of vancomycin are limited.

Aim

We evaluated the pharmacokinetic and clinical outcomes of a PK-guided dosing advisory program, pharmacokinetic consultation service (PKCS), in vancomycin treatment.

Methods

We investigated vancomycin therapeutic drug monitoring (TDM) and PKCS use through a retrospective review of patients who had serum vancomycin trough concentration data from October 2017 to November 2018. Among these patients, we selected non-critically ill adult patients satisfying our selection criteria to evaluate the effect of PKCS. Target trough attainment rate, time to target attainment, vancomycin-induced nephrotoxicity (VIN), vancomycin treatment failure rate, and duration of vancomycin therapy were compared between patients whose dosing was adjusted according to PKCS (PKCS group), and those whose dose was adjusted at the discretion of the attending physician (non-PKCS group).

Results

A total of 280 patients met the selection criteria for the VIN analysis (PKCS, n=134; non-PKCS, n=146). The incidence of VIN was similar between the two groups (PKCS, n=5; non-PKCS, n=5); however, the target attainment rate was higher in the PKCS group (75% vs 60%, P = 0.012). The time to target attainment was similar between the two groups. Further exclusions yielded 112 patients for the clinical outcome evaluation (PKCS, n=51; non-PKCS, n=61). The treatment failure rate was similar, and the duration of vancomycin therapy was longer in the PKCS group (12 vs 8 days, P = 0.008).

Conclusion

In non-critically ill patients, an increase in target trough achieved by PKCS did not lead to decreased vancomycin treatment failures, shorter vancomycin treatment, or decreased nephrotoxicity in vancomycin treatment. Considering the excessive amount of effort currently put into vancomycin dosing and monitoring, more selective criteria for individualized pharmacokinetic-guided dosing needs to be applied.

Optimizing the Use of Antibiotic Agents in the Pediatric Intensive Care Unit: A Narrative Review

Antibiotics are one of the most prescribed drug classes in the pediatric intensive care unit, yet the incidence of inappropriate antibiotic prescribing remains high in critically ill children. Optimizing the use of antibiotics in this population is imperative to guarantee adequate treatment, avoid toxicity and the occurrence of antibiotic resistance, both on a patient level and on a population level. Antibiotic stewardship encompasses all initiatives to promote responsible antibiotic usage and the PICU represents a major target environment for antibiotic stewardship programs. This narrative review provides a summary of the available knowledge on the optimal selection, duration, dosage, and route of administration of antibiotic treatment in critically ill children. Overall, more scientific evidence on how to optimize antibiotic treatment is warranted in this population. We also give our personal expert opinion on research priorities.

Pediatric Pharmacokinetics and Dose Predictions: A Report of a Satellite Meeting to the 10th Juvenile Toxicity Symposium

On April 24, 2019, a symposium on Pediatric Pharmacokinetics and Dose Predictions was held as a satellite meeting to the 10th Juvenile Toxicity Symposium. This symposium brought together scientists from academia, industry, and clinical research organizations with the aim to update each other on the current knowledge on pediatric drug development. Through more knowledge on specific ontogeny profiles of drug metabolism and transporter proteins, integrated into physiologically-based pharmacokinetic (PBPK) models, we have gained a more integrated understanding of age-related differences in pharmacokinetics (PKs), Relevant examples were presented during the meeting. PBPK may be considered the gold standard for pediatric PK prediction, but still it is important to know that simpler methods, such as allometry, allometry combined with maturation function, functions based on the elimination pathway, or linear models, also perform well, depending on the age range or the mechanisms involved. Knowledge from different methods and information sources should be combined (e.g., microdosing can reveal early read-out of age-related differences in exposure), and such results can be a value to verify models. To further establish best practices for dose setting in pediatrics, more in vitro and in vivo research is needed on aspects such as age-related changes in the exposure-response relationship and the impact of disease on PK. New information coupled with the refining of model-based drug development approaches will allow faster targeting of intended age groups and allow more efficient design of pediatric clinical trials.

Therapeutic Drug Monitoring Is a Feasible Tool to Personalize Drug Administration in Neonates Using New Techniques: An Overview on the Pharmacokinetics and Pharmacodynamics in Neonatal Age

Therapeutic drug monitoring (TDM) should be adopted in all neonatal intensive care units (NICUs), where the most preterm and fragile babies are hospitalized and treated with many drugs, considering that organs and metabolic pathways undergo deep and progressive maturation processes after birth. Different developmental changes are involved in interindividual variability in response to drugs. A crucial point of TDM is the choice of the bioanalytical method and of the sample to use. TDM in neonates is primarily used for antibiotics, antifungals, and antiepileptic drugs in clinical practice. TDM appears to be particularly promising in specific populations: neonates who undergo therapeutic hypothermia or extracorporeal life support, preterm infants, infants who need a tailored dose of anticancer drugs. This review provides an overview of the latest advances in this field, showing options for a personalized therapy in newborns and infants.

In silico trials: Verification, validation and uncertainty quantification of predictive models used in the regulatory evaluation of biomedical products

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Regulators now consider also evidences produced in silico.

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We need accepted methods to evaluate the credibility of models.

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In this paper we describe the use of the ASME V&V-40 technical standard.

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We also discuss its application to various types of modelling methods.

Historically, the evidences of safety and efficacy that companies provide to regulatory agencies as support to the request for marketing authorization of a new medical product have been produced experimentally, either in vitro or in vivo. More recently, regulatory agencies started receiving and accepting evidences obtained in silico, i.e. through modelling and simulation. However, before any method (experimental or computational) can be acceptable for regulatory submission, the method itself must be considered “qualified” by the regulatory agency. This involves the assessment of the overall “credibility” that such a method has in providing specific evidence for a given regulatory procedure. In this paper, we describe a methodological framework for the credibility assessment of computational models built using mechanistic knowledge of physical and chemical phenomena, in addition to available biological and physiological knowledge; these are sometimes referred to as “biophysical” models. Using guiding examples, we explore the definition of the context of use, the risk analysis for the definition of the acceptability thresholds, and the various steps of a comprehensive verification, validation and uncertainty quantification process, to conclude with considerations on the credibility of a prediction for a specific context of use. While this paper does not provide a guideline for the formal qualification process, which only the regulatory agencies can provide, we expect it to help researchers to better appreciate the extent of scrutiny required, which should be considered early on in the development/use of any (new) in silico evidence.

External Validation of Model-Based Dosing Guidelines for Vancomycin, Gentamicin, and Tobramycin in Critically Ill Neonates and Children: A Pragmatic Two-Center Study

BACKGROUND

The Dutch Pediatric Formulary (DPF) increasingly bases its guidelines on model-based dosing simulations from pharmacokinetic studies. This resulted in nationwide dose changes for vancomycin, gentamicin, and tobramycin in 2015.

OBJECTIVE

We aimed to evaluate target attainment of these altered, model-based doses in critically ill neonates and children.

METHODS

This was a retrospective cohort study in neonatal intensive care unit (NICU) and pediatric ICU (PICU) patients receiving vancomycin, gentamicin, or tobramycin between January 2015 and March 2017 in two university hospitals. The first therapeutic drug monitoring concentration for each patient was collected, as was clinical and dosing information. Vancomycin and tobramycin target trough concentrations were 10-15 and ≤ 1 mg/L, respectively. Target gentamicin trough and peak concentrations were < 1 and 8-12 mg/L, respectively.

RESULTS

In total, 482 patients were included (vancomycin [PICU] n = 62, [NICU] n = 102; gentamicin [NICU] n = 97; tobramycin [NICU] n = 221). Overall, median trough concentrations were within the target range for all cohorts but showed large interindividual variability, causing nontarget attainment. Trough concentrations were outside the target range in 66.1%, 60.8%, 14.7%, and 23.1% of patients in these four cohorts, respectively. Gentamicin peak concentrations were outside the range in 69% of NICU patients (term neonates 87.1%, preterm infants 57.1%). Higher creatinine concentrations were associated with higher vancomycin and tobramycin trough concentrations.

CONCLUSION

This study illustrates the need to validate model-based dosing advice in the real-world setting as both sub- and supratherapeutic concentrations of vancomycin, gentamicin, and tobramycin were very prevalent. Our data underline the necessity for further individualization by addressing the high interindividual variability to improve target attainment.