Model-Informed Precision Dosing of Antibiotics in Pediatric Patients: A Narrative Review

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.

Implications of Artificial Intelligence in Addressing Antimicrobial Resistance: Innovations, Global Challenges, and Healthcare's Future

Antibiotic resistance poses a significant threat to global public health due to complex interactions between bacterial genetic factors and external influences such as antibiotic misuse. Artificial intelligence (AI) offers innovative strategies to address this crisis. For example, AI can analyze genomic data to detect resistance markers early on, enabling early interventions. In addition, AI-powered decision support systems can optimize antibiotic use by recommending the most effective treatments based on patient data and local resistance patterns. AI can accelerate drug discovery by predicting the efficacy of new compounds and identifying potential antibacterial agents. Although progress has been made, challenges persist, including data quality, model interpretability, and real-world implementation. A multidisciplinary approach that integrates AI with other emerging technologies, such as synthetic biology and nanomedicine, could pave the way for effective prevention and mitigation of antimicrobial resistance, preserving the efficacy of antibiotics for future generations.

Population pharmacokinetics of intravenous daptomycin in critically ill patients: implications for selection of dosage regimens

Daptomycin is gaining prominence for the treatment of methicillin-resistant Staphylococcus aureus infections. However, the dosage selection for daptomycin in critically ill patients remains uncertain, especially in Chinese patients. This study aimed to establish the population pharmacokinetics of daptomycin in critically ill patients, optimize clinical administration plans, and recommend appropriate dosage for critically ill patients in China. The study included 64 critically ill patients. Blood samples were collected at the designated times. The blood daptomycin concentration was determined using validated liquid chromatography-tandem mass spectrometry. A nonlinear mixed-effects model was applied for the population pharmacokinetic analysis and Monte Carlo simulations of daptomycin. The results showed a two-compartment population pharmacokinetic model of daptomycin in critically ill adult Han Chinese patients. Monte Carlo simulations revealed that a daily dose of 400 mg of daptomycin was insufficient for the majority of critically ill adult patients to achieve the anti-infective target. For critically ill adult patients with normal renal function (creatinine clearance rate >90 mL/min), the probability of achieving the target only reached 90% when the daily dose was increased to 700 mg. For patients undergoing continuous renal replacement therapy (CRRT), 24 h administration of 500 mg met the pharmacodynamic goals and did not exceed the safety threshold in most patients. Therefore, considering its efficacy and safety, intravenous daptomycin doses are best scaled according to creatinine clearance, and an increased dose is recommended for critically ill patients with hyperrenalism. For patients receiving CRRT, medication is recommended at 24 h intervals.

Applied pharmacokinetics to improve pharmacotherapy in neonatal and paediatric intensive care units: focus on correct dose selection

Drug dosing and exposure throughout childhood are constantly affected by maturational changes like weight, age or body surface area. In neonatal and paediatric intensive care units (NICU and PICU, respectively), drug dosing and exposure are further impacted by non-maturational changes. These changes are related to factors such as sepsis, cardiac failure, acute kidney injury, extracorporeal circuits or drug-drug interactions (DDIs) resulting from polypharmacy.This potentially complex situation may alter drug pharmacokinetics to result in greater-than-usual intrapatient and interpatient drug exposure variability. These effects may call for individual dosage adjustments. Dosage adjustments may apply to both loading doses or maintenance doses, which should be used as appropriate, depending on the specific characteristics of a given drug. Phenobarbital and vancomycin dosing are hereby used as illustrations.To optimise dose selection in NICU/PICU settings, we suggest to consider therapeutic drug monitoring integrated in model-informed precision dosing, and to familiarise oneself with existing paediatric drug formularies as well as DDI databases/search engines. Paediatric clinical pharmacologists and pharmacists can hereby guide clinicians with no prior experience on how to properly apply these data sources to day-to-day practice in individual patients or specific subpopulations of NICU or PICU patients.

External Validation of Obese/Critically Ill Vancomycin Population Pharmacokinetic Models in Critically Ill Patients Who Are Obese

Obesity combined with critical illness might increase the risk of acquiring infections and hence mortality. In this patient population the pharmacokinetics of antimicrobials vary significantly, making antimicrobial dosing challenging. The objective of this study was to assess the predictive performance of published population pharmacokinetic models of vancomycin in patients who are critically ill or obese for a cohort of critically ill patients who are obese. This was a multi-center retrospective study conducted at 2 hospitals. Adult patients with a body mass index of ≥30 kg/m2 were included. PubMed was searched for published population pharmacokinetic studies in patients who were critically ill or obese. External validation was performed using Monolix software. A total of 4 models were identified in patients who were obese and 5 models were identified in patients who were critically ill. In total, 138 patients who were critically ill and obese were included, and the most accurate models for these patients were the Goti and Roberts models. In our analysis, models in patients who were critically ill outperformed models in patients who were obese. When looking at the most accurate models, both the Goti and the Roberts models had patient characteristics similar to ours in terms of age and creatinine clearance. This indicates that when selecting the proper model to apply in practice, it is important to account for all relevant variables, besides obesity.

Pharmacokinetic and Pharmacodynamic Considerations of Antibiotic Use in Neonates

The selection of an appropriate dose of a given antibiotic for a neonate not only requires knowledge of the drug's basic pharmacokinetic (PK) and pharmacodynamic (PD) properties but also the profound effects that organ development might have on the volume of distribution and clearance, both of which may affect the PK/PD of a drug. Interest has grown in alternative antibiotic dosing strategies that are better aligned with the antibiotic's PK and PD properties. These strategies should be used in conjunction with minimum inhibitory concentration measurements and therapeutic drug monitoring to measure their potential success. They can also guide the clinician in tailoring the delivery of antibiotics to suit an individual patient's needs. Model-informed precision dosing, such as Bayesian forecasting dosing software (which incorporates PK/PD population models), may be utilized to optimize antibiotic exposure in neonatal populations. Consequently, optimizing the antibiotic dose and exposure in each newborn requires expertise in different fields. It drives the collaboration of physicians together with lab technicians and quantitative clinical pharmacologists.

Aminoglycosides-Related Ototoxicity: Mechanisms, Risk Factors, and Prevention in Pediatric Patients

Aminoglycosides are broad-spectrum antibiotics largely used in children, but they have potential toxic side effects, including ototoxicity. Ototoxicity from aminoglycosides is permanent and is a consequence of its action on the inner ear cells via multiple mechanisms. Both uncontrollable risk factors and controllable risk factors are involved in the pathogenesis of aminoglycoside-related ototoxicity and, because of the irreversibility of ototoxicity, an important undertaking for preventing ototoxicity includes antibiotic stewardship to limit the use of aminoglycosides. Aminoglycosides are fundamental in the treatment of numerous infectious conditions at neonatal and pediatric age. In childhood, normal auditory function ensures adequate neurocognitive and social development. Hearing damage from aminoglycosides can therefore strongly affect the normal growth of the child. This review describes the molecular mechanisms of aminoglycoside-related ototoxicity and analyzes the risk factors and the potential otoprotective strategies in pediatric patients.

Bayesian prediction-based individualized dosing of anti-methicillin-resistant Staphylococcus aureus treatment: Recent advancements and prospects in therapeutic drug monitoring

As one of the efficient techniques for TDM, the population pharmacokinetic (popPK) model approach for dose individualization has been developed due to the rapidly growing innovative progress in computer technology and has recently been considered as a part of model-informed precision dosing (MIPD). Initial dose individualization and measurement followed by maximum a posteriori (MAP)-Bayesian prediction using a popPK model are the most classical and widely used approach among a class of MIPD strategies. MAP-Bayesian prediction offers the possibility of dose optimization based on measurement even before reaching a pharmacokinetically steady state, such as in an emergency, especially for infectious diseases requiring urgent antimicrobial treatment. As the pharmacokinetic processes in critically ill patients are affected and highly variable due to pathophysiological disturbances, the advantages offered by the popPK model approach make it highly recommended and required for effective and appropriate antimicrobial treatment. In this review, we focus on novel insights and beneficial aspects of the popPK model approach, especially in the treatment of infectious diseases with anti-methicillin-resistant Staphylococcus aureus agents represented by vancomycin, and discuss the recent advancements and prospects in TDM practice.

Population Pharmacokinetics and AUC-Guided Dosing of Tobramycin in the Treatment of Infections Caused by Glucose-Nonfermenting Gram-Negative Bacteria

PURPOSE

Tobramycin (TOB) exhibits variable pharmacokinetic properties due to the clinical condition of patients. This study aimed to investigate the AUC-guided dosing of TOB based on population pharmacokinetic analysis in the treatment of infections caused by Pseudomonas aeruginosa, Acinetobacter baumannii, and Stenotrophomonas maltophilia.

METHODS

This retrospective study was conducted between January 2010 and December 2020 after obtaining approval from our institutional review board. For 53 patients who received therapeutic drug monitoring of TOB, a population pharmacokinetic model was developed with covariates of estimated glomerular filtration rate using serum creatinine (eGFRcre) on clearance (CL) and weight on both CL and V_d in exponential error modeling (CL = 2.84 × [weight/70] × eGFRcre^0.568, interindividual variability [IIV] = 31.1%; V_d = 26.3 × [weight/70], IIV = 20.2%; residual variability = 28.8%).

FINDINGS

The final regression model for predicting 30-day mortality was developed with risk factors of AUC during a 24-hour period after the first dose to MIC ratio (odds ratio [OR] = 0.996; 95% CI, 0.968-1.003) and serum albumin (OR = 0.137; 95% CI, 0.022-0.632). The final regression model for predicting acute kidney injury was developed with the risk factors of C-reactive protein (OR = 1.136; 95% CI, 1.040-1.266) and AUC during a 72-hour period after the first dose (OR = 1.004; 95% CI, 1.000-1.001). A dose of 8 or 15 mg/kg was beneficial for achievement of AUC during a 24-hour period after the first dose/MIC >80 and trough concentration <1 µg/mL in patients with preserved kidney function and TOB CL >4.47 L/h/70 kg in the events of MIC of 1 or 2 µg/mL, respectively. We propose that the first dose of 15, 11, 10, 8, and 7 mg/kg for eGFRcre >90, 60 to 89, 45 to 59, 30 to 44, and 15 to 29 mL/min/1.73 m² be followed by therapeutic drug monitoring at peak and 24 hours after the first dose.

IMPLICATIONS

This study suggests that TOB use encourages the replacement of trough- and peak-targeted dosing with AUC-guided dosing.

Advancing evidence-based treatment of infectious diseases in children with real-world data: Opportunities and challenges

There is an increased interest in utilizing real-world data (RWD) for pharmaceutical research and regulatory decision-making. The development and use of pediatric medicines could benefit greatly from real-world data studies given nearly half of drugs prescribed to children are "off-label", meaning there is a lack of pediatric-specific evidence from controlled trials, while there is an abundance of data from routine clinical practice. Currently, the use of real-world data, such as data from electronic health records, is lacking in pediatric research, especially within infectious diseases. Here, we discuss opportunities and challenges for real-world data to generate evidence on the optimal treatment and management of infectious diseases in children.

Population pharmacokinetics of vancomycin in very low birth weight neonates

Introduction

Vancomycin dosing in very low birth weight (VLBW) neonates is challenging. Compared with the general neonatal population, VLBW neonates are less likely to achieve the vancomycin therapeutic targets. Current dosing recommendations are based on studies of the general neonatal population, as only a very limited number of studies have evaluated vancomycin pharmacokinetics in VLBW neonates. The main aim of this study was to develop a vancomycin population pharmacokinetic model to optimize vancomycin dosing in VLBW neonates.

Methods

This multicenter study was conducted at six major hospitals in Saudi Arabia. The study included VLBW neonates who received vancomycin and had at least one vancomycin serum trough concentration measurement at a steady state. We developed a pharmacokinetic model and performed Monte Carlo simulations to develop an optimized dosing regimen for VLBW infants. We evaluated two different targets: AUC_0-24 of 400-600 or 400-800 µg. h/mL. We also estimated the probability of trough concentrations >15 and 20 µg/mL.

Results

In total, we included 236 neonates, 162 in the training dataset, and 74 in the validation dataset. A one-compartment model was used, and the distribution volume was significantly associated only with weight, whereas clearance was significantly associated with weight, postmenstrual age (PMA), and serum creatinine (Scr).

Discussion

We developed dosing regimens for VLBW neonates, considering the probability of achieving vancomycin therapeutic targets, as well as different toxicity thresholds. The dosing regimens were classified according to PMA and Scr. These dosing regimens can be used to optimize the initial dose of vancomycin in VLBW neonates.

Predicting treatment response to vancomycin using bacterial DNA load as a pharmacodynamic marker in premature and very low birth weight neonates: A population PKPD study

Background: While positive blood cultures are the gold standard for late-onset sepsis (LOS) diagnosis in premature and very low birth weight (VLBW) newborns, these results can take days, and early markers of possible treatment efficacy are lacking. The objective of the present study was to investigate whether the response to vancomycin could be quantified using bacterial DNA loads (BDLs) determined by real-time quantitative polymerase chain reaction (RT-qPCR). Methods: VLBW and premature neonates with suspected LOS were included in a prospective observational study. Serial blood samples were collected to measure BDL and vancomycin concentrations. BDLs were measured with RT-qPCR, whereas vancomycin concentrations were measured by LC-MS/MS. Population pharmacokinetic-pharmacodynamic modeling was performed with NONMEM. Results: Twenty-eight patients with LOS treated with vancomycin were included. A one-compartment model with post-menstrual age (PMA) and weight as covariates was used to describe the time PK profile of vancomycin concentrations. In 16 of these patients, time profiles of BDL could be described with a pharmacodynamic turnover model. The relationship between vancomycin concentration and first-order BDL elimination was described with a linear-effect model. Slope S increased with increasing PMA. In 12 patients, no decrease in BDL over time was observed, which corresponded with clinical non-response. Discussion: BDLs determined through RT-qPCR were adequately described with the developed population PKPD model, and treatment response to vancomycin using BDL in LOS can be assessed as early as 8 h after treatment initiation.

Evaluation of vancomycin individualized model-based dosing approach in neonates

BACKGROUND

Vancomycin is commonly used to treat methicillin-resistant staphylococcal infections in neonates. Consensus on its ideal dosing in neonates has not been achieved. Model-based dosing recently has evolved as an important tool to optimize vancomycin initial dosing. The aim of this is to evaluate a population pharmacokinetic model-based approach in achieving the vancomycin therapeutic target of an AUC_0-24 400 as recommended by the recent IDSA treatment guidelines. This model was implemented as a simple Excel calculator to individualize and optimize vancomycin initial dosing in neonates.

METHODS

An Excel calculator was developed using a previously published population pharmacokinetic model in neonates. It was evaluated using retrospectively retrieved data. For each patient, the initial empiric dose was calculated using the proposed Excel model and the most widely used neonatal dosing references. The probability of achieving the target AUC_0-24 of >400 mg h/L using the model-based method was calculated and compared with that of the empiric doses using other references.

RESULTS

This analysis included 225 neonates. The probability of achieving the target AUC_0-24 >400 was 89% using our model-based approach compared with 11%-59% using tertiary neonatal dosing references (p < 0.01 for all comparisons).

CONCLUSION

These innovative personalized dosing calculators are promising to improve vancomycin initial dosing in neonates and are easily applicable in routine practices.

Dose optimization of β-lactams antibiotics in pediatrics and adults: A systematic review

Background: β-lactams remain the cornerstone of the empirical therapy to treat various bacterial infections. This systematic review aimed to analyze the data describing the dosing regimen of β-lactams.

Methods: Systematic scientific and grey literature was performed in accordance with Preferred Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. The studies were retrieved and screened on the basis of pre-defined exclusion and inclusion criteria. The cohort studies, randomized controlled trials (RCT) and case reports that reported the dosing schedule of β-lactams are included in this study.

Results: A total of 52 studies met the inclusion criteria, of which 40 were cohort studies, 2 were case reports and 10 were RCTs. The majority of the studies (34/52) studied the pharmacokinetic (PK) parameters of a drug. A total of 20 studies proposed dosing schedule in pediatrics while 32 studies proposed dosing regimen among adults. Piperacillin (12/52) and Meropenem (11/52) were the most commonly used β-lactams used in hospitalized patients. As per available evidence, continuous infusion is considered as the most appropriate mode of administration to optimize the safety and efficacy of the treatment and improve the clinical outcomes.

Conclusion: Appropriate antibiotic therapy is challenging due to pathophysiological changes among different age groups. The optimization of pharmacokinetic/pharmacodynamic parameters is useful to support alternative dosing regimens such as an increase in dosing interval, continuous infusion, and increased bolus doses.

Population pharmacokinetics of posaconazole in Chinese pediatric patients with acute leukaemia: effect of food on bioavailability and dose optimization

This study aimed to investigate the effect of food on the pharmacokinetics of posaconazole suspension in pediatric patients with acute leukaemia and to recommend optimal dosing strategies. This single-site, prospective, open-label, observational study was conducted in 42 patients and included 186 plasma concentrations of posaconazole. Sparse data were analyzed using population pharmacokinetic modeling. Monte Carlo simulations were conducted to predict the morning trough concentrations at steady-state with the proposed dose of 2-7 mg/kg three times daily (tid) or four times daily (qid) for bodyweights of 10-36 kg. The target concentrations were 700 ng/mL for prophylaxis and 1000 ng/mL for treatment. Dosage regimens with percentage of target attainment (PTA) ≥70% were recommended. A one-compartment model with allometric scaling adequately described the pharmacokinetic profile. The apparent clearance was 9.05 L/h (95% confidence interval [CI] 7.14-11.09) and the apparent volume of distribution was 283 L (95% CI 168-491) for a typical individual of 17.5 kg. The relative bioavailability with high-fat diet was as high as 1.95-fold compared with regular food. Following the intake of regular meals, 4 mg/kg qid was adequate with a PTA ≥ 71.8% for prophylaxis. A dosage of 6 mg/kg qid under a regular diet reached a PTA ≥ 73.4% for treatment. The recommended dosage of posaconazole for prophylaxis and treatment could be predicted by the pharmacokinetic model based on bodyweight and diet type in pediatric patients.

Optimizing Antimicrobial Therapy by Integrating Multi-Omics With Pharmacokinetic/Pharmacodynamic Models and Precision Dosing

In the era of “Bad Bugs, No Drugs,” optimizing antibiotic therapy against multi-drug resistant (MDR) pathogens is crucial. Mathematical modelling has been employed to further optimize dosing regimens. These models include mechanism-based PK/PD models, systems-based models, quantitative systems pharmacology (QSP) and population PK models. Quantitative systems pharmacology has significant potential in precision antimicrobial chemotherapy in the clinic. Population PK models have been employed in model-informed precision dosing (MIPD). Several antibiotics require close monitoring and dose adjustments in order to ensure optimal outcomes in patients with infectious diseases. Success or failure of antibiotic therapy is dependent on the patient, antibiotic and bacterium. For some drugs, treatment responses vary greatly between individuals due to genotype and disease characteristics. Thus, for these drugs, tailored dosing is required for successful therapy. With antibiotics, inappropriate dosing such as insufficient dosing may put patients at risk of therapeutic failure which could lead to mortality. Conversely, doses that are too high could lead to toxicities. Hence, precision dosing which customizes doses to individual patients is crucial for antibiotics especially those with a narrow therapeutic index. In this review, we discuss the various strategies in optimizing antimicrobial therapy to address the challenges in the management of infectious diseases and delivering personalized therapy.

Implementation of a Vancomycin Dose-Optimization Protocol in Neonates: Impact on Vancomycin Exposure, Biological Parameters, and Clinical Outcomes

Vancomycin dosing used in neonates results frequently in insufficient concentrations. A vancomycin dose-optimization protocol consisting of an individualization of loading and maintenance doses (administered during continuous infusion) through a previously validated pharmacokinetic model was implemented in our center. This monocenter retrospective study aimed to compare vancomycin average concentration (Cavg) in the therapeutic range (15 to 25 mg/L) and biological and clinical parameters before and after implementation of this protocol. A total of 60 and 59 courses of vancomycin treatment in 45 and 49 patients were analyzed in groups before and after implementation, respectively. Initial vancomycin Cavg were more frequently in the therapeutic range in the group after implementation (74.6% versus 28.3%, P < 0.001), with 1.6-fold higher Cavg (20.3 [17.0-22.2] mg/L versus 12.9 [11.3-17.0] mg/L, P < 0.001). Considering all Cavg during longitudinal therapeutic drug monitoring (TDM), the frequency of therapeutic Cavg was higher in the group after implementation (74.8% [n = 103] versus 31% [n = 116], P < 0.001). The dose optimization protocol was also associated with a reduced time to obtain a negative blood culture (P < 0.001) and fewer antibiotic switches (P = 0.025), without increasing the frequency of nephrotoxicity. Clinical outcomes also appeared to be improved, with less periventricular leukomalacia (P = 0.021), trended toward less respiratory instability (P = 0.15) and a shorter duration of vasoactive drug use (P = 0.18) for neonates receiving personalized doses of vancomycin. This personalized vancomycin dose protocol improves vancomycin exposure in neonates, with good safety, and suggests an improvement in biological and clinical outcomes.

Therapeutic Drug Monitoring of Antibiotics in Critically Ill Children: An Observational Study in a Pediatric Intensive Care Unit

BACKGROUND

Septic critically ill children are at a high risk of inadequate antibiotic exposure, requiring them to undergo therapeutic drug monitoring (TDM). The aim of this study was to describe the use of TDM for antibiotics in critically ill children.

METHODS

The authors conducted a single-center observational study between June and December 2019, with all children treated with antibiotics in a pediatric intensive care unit located in a French university hospital. Standard clinical and laboratory data were recorded. Blood samples were collected for routine laboratory tests, and plasma antibiotic levels were assayed using validated analytical methods.

RESULTS

A total of 209 children received antibiotics. TDM was performed in 58 patients (27.8%) who had a greater mean organ dysfunction (according to the International Pediatric Sepsis Consensus Conference) (3 versus 1 in the non-TDM group; P < 0.05) and were treated with antibiotics for longer. A total of 208 samples were analyzed. The median [interquartile range] assay turnaround time was 3 (1-5) days, and 48 (46.2%) of the 104 initial antibiotic concentration values were below the pharmacokinetic/pharmacodynamic targets. A total of 34 (46%) of the 74 off-target TDM measurements available before the end of the antibiotic treatment prompted dose adjustment. This dose adjustment increased the proportion of on-target TDM measurements (70% versus 20% without adjustment). Subsequent measurements of the minimum inhibitory concentration showed that the use of the European Committee on Antimicrobial Susceptibility Testing's epidemiological cutoff values led to underestimation of pharmacokinetic/pharmacodynamic target attainment in 10 cases (20%).

CONCLUSIONS

TDM seems to be an effective means of optimizing antibiotic exposure in critically ill children. This requires timely plasma antibiotic assays and minimum inhibitory concentration measurements. It is important to define which patients should undergo TDM and how this monitoring should be managed.

Clinical Practice Guidelines for Therapeutic Drug Monitoring of Vancomycin in the Framework of Model-Informed Precision Dosing: A Consensus Review by the Japanese Society of Chemotherapy and the Japanese Society of Therapeutic Drug Monitoring

Background: To promote model-informed precision dosing (MIPD) for vancomycin (VCM), we developed statements for therapeutic drug monitoring (TDM). Methods: Ten clinical questions were selected. The committee conducted a systematic review and meta-analysis as well as clinical studies to establish recommendations for area under the concentration-time curve (AUC)-guided dosing. Results: AUC-guided dosing tended to more strongly decrease the risk of acute kidney injury (AKI) than trough-guided dosing, and a lower risk of treatment failure was demonstrated for higher AUC/minimum inhibitory concentration (MIC) ratios (cut-off of 400). Higher AUCs (cut-off of 600 μg·h/mL) significantly increased the risk of AKI. Although Bayesian estimation with two-point measurement was recommended, the trough concentration alone may be used in patients with mild infections in whom VCM was administered with q12h. To increase the concentration on days 1–2, the routine use of a loading dose is required. TDM on day 2 before steady state is reached should be considered to optimize the dose in patients with serious infections and a high risk of AKI. Conclusions: These VCM TDM guidelines provide recommendations based on MIPD to increase treatment response while preventing adverse effects.

Barriers and Facilitators in the Clinical Implementation of Beta-Lactam Therapeutic Drug Monitoring in Critically Ill Patients: A Critical Review

BACKGROUND

With increasing knowledge of beta-lactam pharmacodynamics and interpatient and intrapatient variability in pharmacokinetics, the usefulness of therapeutic drug monitoring (TDM) is becoming increasingly clear. However, little research has been conducted to identify potential barriers and facilitators in the clinical implementation of beta-lactam TDM. This study provides an overview of the current practices of beta-lactam TDM and barriers and facilitators in its implementation.

METHODS

A systematic search was conducted using the Ovid MEDLINE database in April 2021, without restrictions on the publication date. All studies reporting the implementation of beta-lactam antibiotic TDM in critically ill patients through questionnaires or surveys were included in this review.

RESULTS

Six eligible studies were identified from 215 records, all of which were cross-sectional. All studies identified barriers and facilitators in the implementation of beta-lactam TDM in critically ill patients. The main barriers were insufficient knowledge about various aspects regarding the implementation of beta-lactam TDM and the unavailability of assays. Furthermore, a delay in the acquisition of TDM results reduces the probability of physicians altering drug dosages. Finally, doubts about the cost-effectiveness and clinical effectiveness of beta-lactam TDM in critically ill patients hinder broad implementation. Moreover, to improve the willingness of physicians to use beta-lactam TDM, collaboration between physicians and clinical pharmacists and clinical microbiologists should be strengthened.

CONCLUSIONS

Although the evidence for application of beta-lactam TDM continues to grow, its clinical implementation remains limited. To enable optimal implementation of these antibiotics in critically ill patients, several barriers need to be overcome regarding logistics, equipment availability, clinical evidence, and proof of cost-effectiveness.

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.

Pharmacokinetics of Antibiotics in Pediatric Intensive Care: Fostering Variability to Attain Precision Medicine

Children show important developmental and maturational changes, which may contribute greatly to pharmacokinetic (PK) variability observed in pediatric patients. These PK alterations are further enhanced by disease-related, non-maturational factors. Specific to the intensive care setting, such factors include critical illness, inflammatory status, augmented renal clearance (ARC), as well as therapeutic interventions (e.g., extracorporeal organ support systems or whole-body hypothermia [WBH]). This narrative review illustrates the relevance of both maturational and non-maturational changes in absorption, distribution, metabolism, and excretion (ADME) applied to antibiotics. It hereby provides a focused assessment of the available literature on the impact of critical illness—in general, and in specific subpopulations (ARC, extracorporeal organ support systems, WBH)—on PK and potential underexposure in children and neonates. Overall, literature discussing antibiotic PK alterations in pediatric intensive care is scarce. Most studies describe antibiotics commonly monitored in clinical practice such as vancomycin and aminoglycosides. Because of the large PK variability, therapeutic drug monitoring, further extended to other antibiotics, and integration of model-informed precision dosing in clinical practice are suggested to optimise antibiotic dose and exposure in each newborn, infant, or child during intensive care.

A hybrid machine learning/pharmacokinetic approach outperforms maximum a posteriori Bayesian estimation by selectively flattening model priors

Model‐informed precision dosing (MIPD) approaches typically apply maximum a posteriori (MAP) Bayesian estimation to determine individual pharmacokinetic (PK) parameters with the goal of optimizing future dosing regimens. This process combines knowledge about the individual, in the form of drug levels or pharmacodynamic biomarkers, with prior knowledge of the drug PK in the general population. Use of “flattened priors” (FPs), in which the weight of the model priors is reduced relative to observations about the patient, has been previously proposed to estimate individual PK parameters in instances where the patient is poorly described by the PK model. However, little is known about the predictive performance of FPs and when to apply FPs in MIPD. Here, FP is evaluated in a data set of 4679 adult patients treated with vancomycin. Depending on the PK model, prediction error could be reduced by applying FPs in 42–55% of PK parameter estimations. Machine learning (ML) models could identify instances where FPs would outperform MAPs with a specificity of 81–86%, reducing overall root mean squared error (RMSE) of PK model predictions by 12–22% (0.5–1.2 mg/L) relative to MAP alone. The factors most indicative of the use of FPs were past prediction residuals and bias in past PK predictions. A more clinically practical minimal model was developed using only these two features, reducing RMSE by 5–18% (0.20–0.93 mg/L) relative to MAP. This hybrid ML/PK approach advances the precision dosing toolkit by leveraging the power of ML while maintaining the mechanistic insight and interpretability of PK models.

Concept and utility of population pharmacokinetic and pharmacokinetic/pharmacodynamic models in drug development and clinical practice

Due to frequent clinical trial failures and consequently fewer new drug approvals, the need for improvement in drug development has, to a certain extent, been met using model-based drug development. Pharmacometrics is a part of pharmacology that quantifies drug behaviour, treatment response and disease progression based on different models (pharmacokinetic - PK, pharmacodynamic - PD, PK/PD models, etc.) and simulations. Regulatory bodies (European Medicines Agency, Food and Drug Administration) encourage the use of modelling and simulations to facilitate decision-making throughout all drug development phases. Moreover, the identification of factors that contribute to variability provides a basis for dose individualisation in routine clinical practice. This review summarises current knowledge regarding the application of pharmacometrics in drug development and clinical practice with emphasis on the population modelling approach.