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

BACKGROUND: Vancomycin 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. METHODS: Participants 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. DISCUSSION: This trial will clarify the propagated benefits and provide new insights into how to optimally monitor vancomycin treatment in critically ill children. TRIAL REGISTRATION: Eudract number: 2019-004538-40. Registered on 2020-09-08 ClinicalTrials.gov NCT046666948. Registered on 2020-11-28.

Toward a Clinical Decision Support System for Monitoring Therapeutic Antituberculosis Medical Drugs in Tanzania (Project TuberXpert): Protocol for an Algorithm' Development and Implementation.

BACKGROUND: The end tuberculosis (TB) strategy requires a novel patient treatment approach contrary to the one-size-fits-all model. It is well known that each patient's physiology is different and leads to various rates of drug elimination. Therapeutic drug monitoring (TDM) offers a way to manage drug dosage adaptation but requires trained pharmacologists, which is scarce in resource-limited settings. OBJECTIVE: We will develop an automated clinical decision support system (CDSS) to help practitioners with the dosage adaptation of rifampicin, one of the essential medical drugs targeting TB, that is known for large pharmacokinetic variability and frequent suboptimal blood exposure. Such an advanced system will encourage the spread of a dosage-individualization culture, including among practitioners not specialized in pharmacology. Thus, the objectives of this project are to (1) develop the appropriate population pharmacokinetic (popPK) model for rifampicin for Tanzanian patients, (2) optimize the reporting of relevant information to practitioners for drug dosage adjustment, (3) automate the delivery of the report in line with the measurement of drug concentration, and (4) validate and implement the final system in the field. METHODS: A total of 3 teams will combine their efforts to deliver the first automated TDM CDSS for TB. A cross-sectional study will be conducted to define the best way to display information to clinicians. In parallel, a rifampicin popPK model will be developed taking advantage of the published literature, complemented with data provided by existing literature data from the Pan-African Consortium for the Evaluation of Antituberculosis Antibiotics (panACEA), and samples collected within this project. A decision tree will be designed and implemented as a CDSS, and an automated report generation will be developed and validated through selected case studies. Expert pharmacologists will validate the CDSS, and finally, field implementation in Tanzania will occur, coupled with a prospective study to assess clinicians' adherence to the CDSS recommendations. RESULTS: The TuberXpert project started in November 2022. In July 2024, the clinical study in Tanzania was completed with the enrollment of 50 patients to gather the required data to build a popPK model for rifampicin, together with a qualitative study defining the report design, as well as the CDSS general architecture definition. CONCLUSIONS: At the end of the TuberXpert project, Tanzania will possess a new tool to help the practitioners with the adaptation of drug dosage targeting complicated TB cases (TB or HIV, TB or diabetes mellitus, and TB or malnutrition). This automated system will be validated and used in the field and will be proposed to other countries affected by endemic TB. In addition, this approach will serve as proof of concept regarding the feasibility and suitability of CDSS-assisted TDM for further anti-TB drugs in TB-burdened areas deprived of TDM experts, including second-line treatments considered important to monitor. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/58720.

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

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSION: 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.

Drug dosing optimization in critically ill children under continuous renal replacement therapy: from basic concepts to the bedside model informed precision dosing.

INTRODUCTION: Optimizing drug dosage in critically ill children undergoing Continuous Renal Replacement Therapy (CRRT) is mandatory and challenging, given the many factors impacting pharmacokinetics and pharmacodynamics coupled with the vulnerability of this population. AREAS COVERED: A good understanding of the mechanisms that determine drug elimination via the CRRT technique is useful to avoid prescription pitfalls, however limited by the high between and within subject variability. The developments of population pharmacokinetic and physiologically based pharmacokinetic models derived from in-vivo and in-vitro studies, are challenging, but remain the most appropriate tool to suggest adjusted dosage regimens for every patient, throughout treatment. We searched PubMed using the search string: 'pediatrics OR children' AN 'continuous renal replacement therapy' AND 'pharmacokinetics' AND 'model informed precision dosing' AND, 'physiologically based pharmacokinetics,' AND 'therapeutic drug monitoring' until January 2024, regardless of language or publication status. EXPERT OPINION: Familiarizing the pediatric intensivists with the therapeutic drug monitoring and providing clinicians the individualized prescribing software such as Model Informed Precision Dosing would be a significant step forward. The clinical benefit for patients remains to be demonstrated.

Optimizing Piperacillin Dosing in Pediatric Liver Transplant Recipients: A Case Series.

BACKGROUND: Pathophysiological changes post-liver transplantation impact the pharmacokinetics and pharmacodynamics of antibiotics. Piperacillin, often used in combination with tazobactam, is a key antibiotic after transplantation to its broad-spectrum activity, but there is a lack of specific pharmacokinetic data in this population. This study aims to describe the pharmacokinetic parameters and target attainment of piperacillin in pediatric liver transplant recipients. METHODS: Patients with preserved renal function (estimated glomerular filtration rate > 50 mL/min/1.73 m2) receiving intravenous piperacillin-tazobactam at 112.5 mg/kg every 8 h (100 mg piperacillin/12.5 mg tazobactam), with a rapid infusion (0.5-1 h), were included. Two blood samples per child were collected during the same interval within 48 h of starting therapy. A Bayesian approach was applied to estimate individual pharmacokinetic parameters and perform dosing recommendations against Enterococcus spp., Enterobacterales and Pseudomonas aeruginosa. RESULTS: Eight patients with median age of 8 months were included. Median piperacillin clearance and central volume of distribution for the cohort were 11.11 L/h/70 kg and 9.80 L/70 kg, respectively. Seven patients (87.5%) presented with concentrations below the target of 100% fT > MIC. Simulations suggested that these patients required more frequent dosing and extended duration of infusion to ensure target attainment. One patient (12.5%) had trough concentrations that exceed 16 mg/L and could receive a lower daily dose. CONCLUSIONS: This case series highlights the importance of personalized therapy in pediatric liver transplant recipients due to the unpredictable and highly variable piperacillin pharmacokinetics in this population.

Initial dosage optimization of olanzapine in patients with bipolar disorder based on model-informed precision dosing: a study from the real world.

Objectives: Olanzapine is used for treating bipolar disorder (BPD); however, the optimal initial dosing regimen is unclear. The present study aimed to investigate the optimal olanzapine initial dosage in patients with BPD via model-informed precision dosing (MIPD) based on a real-world study. Methods: Thirty-nine patients with BPD from the real-world study were collected to construct the MIPD model. Results: Weight, combined used quetiapine influenced olanzapine clearances in patients with BPD, where the clearance rates were 0.152:1 in patients with or without quetiapine under the same weight. We simulated olanzapine doses once a day or twice a day, of which twice a day was optimal. Without quetiapine, for twice-a-day olanzapine doses, 0.80, 0.70, and 0.60 mg/kg/day were suitable for 40- to 56-kg BPD patients, 56- to 74-kg BPD patients, and 74- to 100-kg BPD patients, respectively. With quetiapine, for twice-a-day olanzapine doses, 0.05 mg/kg/day was suitable for 40- to 100-kg BPD patients. Conclusion: This study was the first to investigate the optimal olanzapine initial dosage in patients with BPD via MIPD based on a real-world study, providing clinical reference for the precision medication of olanzapine in BPD patients.

Serum ganciclovir drug exposure in children receiving standard ganciclovir dosing.

Intravenous ganciclovir (GCV) is used for the treatment of cytomegalovirus (CMV) infection in immunocompromised children. Although the therapeutic target for treatment is unclear, studies have shown a serum area under the concentration-time curve (AUC24h) ≥40 mg/L·h correlates with effective CMV prevention. This study aimed to externally validate existing GCV population pharmacokinetic (PopPK) models and develop a model if needed and evaluate the serum AUC24h achieved with standard GCV dosing and propose an optimized dosing strategy for immunocompromised children. Ganciclovir drug monitoring data from two pediatric hospitals were retrospectively collected, and published pediatric PopPK models were externally validated. The population AUC24h with standard GCV dosing (5 mg/kg twice daily) was calculated, and an optimized dosing strategy was determined using Monte Carlo simulations to achieve an AUC24h between 40 and 100 mg/L·h. Overall, 161 samples from 23 children with a median (range) age of 9.0 years (0.4-17.0) and weight of 28.2 kg (5.6-73.3) were analyzed. Transferability of published pediatric PopPK models was limited. Thus, a one-compartment model with first-order absorption and elimination with weight and serum creatinine as covariates was developed. The median (5th-95th percentiles) steady state AUC24h with standard dosing was 38.3 mg/L·h (24.8-329.2) with 13 children having an AUC24h <40 mg/L·h, particularly those aged <4 years (8/13). An optimized simulated GCV dosing regimen, ranging from 2 to 13 mg/kg twice daily for children with normal renal function, achieved 61%-78% probability of target attainment. Standard GCV dosing likely results in inadequate drug exposure in more than half of the children, particularly those aged <4 years. An optimized dosing regimen has been proposed for clinical validation.

Towards precision dosing in psychiatry: Population pharmacokinetics meta-modelling of clozapine and lithium.

BACKGROUND: Treatment optimization is mandatory in psychiatric diseases and the use of population pharmacokinetics (popPK) models through model informed precision dosing (MIPD) has the potential to improve patient medical care. In this perspective, meta-modelling methods could provide popPK models with improved predictive performances and most of covariates of interest. The aims of this study were to develop meta-models of clozapine and lithium, assess their predictability and propose optimized dosing regimens for both drugs. METHODS: Two popPK models for each drug were retained to develop the meta-models. For clozapine, the model with the best predictive performances and gender as a covariate and one with smoking status were retained. For lithium, the model with the best predictive performances and fat-free mass as covariate and one with glomerular filtration rate were retained. RESULTS: Both meta-models showed improved predictability compared to the original models. Clozapine meta-model simulations allowed us to propose dosing regimen according to gender and smoking status. Steady-state doses ranged from 375 to 725 mg/day for clozapine once daily, and from 350 to 650 mg/day for clozapine twice daily. Lithium meta-model simulations allowed us to propose dosing regimen according to weight, body mass index, gender and GFR. Our steady-state dose propositions ranged from 625 to 1125 mg/day for males, and from 375 to 750 mg/day for females. CONCLUSION: Both meta-models met the acceptability criteria for use in clinical practice on all subpopulations of interest. Those models could be used in the perspective of MIPD for clozapine and lithium.

Model-informed precision dosing: State of the art and future perspectives.

Model-informed precision dosing (MIPD) stands as a significant development in personalized medicine to tailor drug dosing to individual patient characteristics. MIPD moves beyond traditional therapeutic drug monitoring (TDM) by integrating mathematical predictions of dosing, and considering patient-specific factors (patient characteristics, drug measurements) as well as different sources of variability. For this purpose, rigorous model qualification is required for the application of MIPD in patients. This review delves into new methods in model selection and validation, also highlighting the role of machine learning in improving MIPD, the utilization of biosensors for real-time monitoring, as well as the potential of models integrating biomarkers for efficacy or toxicity for precision dosing. The clinical evidence of TDM and MIPD is discussed for various medical fields including infection medicine, oncology, transplant medicine, and inflammatory bowel diseases, thereby underscoring the role of pharmacokinetics/pharmacodynamics and specific biomarkers. Further research, particularly randomized clinical trials, is warranted to corroborate the value of MIPD in enhancing patient outcomes and advancing personalized medicine.

Hepatic Metabolic Enzyme Activity with Endogenous Substances-current Status, Challenges and Limitations.

Precision dosing is essential in improving drug efficacy and minimizing adverse reactions, especially in liver impaired patients. However, there is no objective index to directly evaluate the body's ability to metabolize specific drugs. Many factors affect the activity of enzymes, and alter the systemic exposure of substrate drugs, like genetic polymorphism, drug-drug interactions and physiological/pathological state. So, quantifying the activities of enzymes dynamically would be helpful to make precision dosing. Recently, some endogenous substrates of enzymes, such as 6ß-hydroxycortisol (6ß-OH-cortisol)/cortisol and 6ß-hydroxycortisone, have been identified to investigate variations in drug enzymes in humans. Clinical data obtained support their performance as surrogate probes in terms of reflecting the activities of corresponding enzyme. Therefore, a group of Monitored endogenous biomarkers in multiple points can address the uncertainty in drug metabolization in the preclinical phase and have the potential to fulfill precision dosing. This review focuses on recent progress in the contribution of endogenous substances to drug precision dosing, factors that influence enzyme activities, and drug exposure in vivo.

Physiologically based pharmacokinetic modeling in obesity: applications and challenges.

INTRODUCTION: Rising global obesity rates pose a threat to people's health. Obesity causes a series of pathophysiologic changes, making the response of patients with obesity to drugs different from that of nonobese, thus affecting the treatment efficacy and even leading to adverse events. Therefore, understanding obesity's effects on pharmacokinetics is essential for the rational use of drugs in patients with obesity. AREAS COVERED: Articles related to physiologically based pharmacokinetic (PBPK) modeling in patients with obesity from inception to October 2023 were searched in PubMed, Embase, Web of Science and the Cochrane Library. This review outlines PBPK modeling applications in exploring factors influencing obesity's effects on pharmacokinetics, guiding clinical drug development and evaluating and optimizing clinical use of drugs in patients with obesity. EXPERT OPINION: Obesity-induced pathophysiologic alterations impact drug pharmacokinetics and drug-drug interactions (DDIs), altering drug exposure. However, there is a lack of universal body size indices or quantitative pharmacology models to predict the optimal for the patients with obesity. Therefore, dosage regimens for patients with obesity must consider individual physiological and biochemical information, and clinically individualize therapeutic drug monitoring for highly variable drugs to ensure effective drug dosing and avoid adverse effects.

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

OBJECTIVES: Piperacillin (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). METHODS: Precision, 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). RESULTS: The 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. CONCLUSIONS: In 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.

Acute kidney injury is associated with abnormal cefepime exposure among critically ill children and young adults.

BACKGROUND: Elevated cefepime blood concentrations can cause neurotoxicity in adults. The consequences of elevated cefepime concentrations among pediatric patients are unknown. Future exploration of such effects requires first identifying patients at risk for elevated cefepime exposure. We investigated the role of acute kidney injury as a risk factor for increased cefepime concentrations in critically ill children. METHODS: This was a retrospective analysis at a single pediatric intensive care unit. Analyzed patients received at least 24 h of cefepime and had at least two opportunistic samples collected for total cefepime concentration measurement. Individual pharmacokinetic (PK) profiles during treatment courses were reconstructed using Bayesian estimation with an established population PK model. Elevated trough concentration (Cmin) was defined as ≥ 30 mg/L based on adult toxicity studies. The effect of kidney dysfunction on cefepime PK profiles was interrogated using a mixed-effect model. RESULTS: Eighty-seven patients were included, of which 13 (14.9%) had at least one estimated Cmin ≥ 30 mg/L. Patients with elevated Cmin were more likely to have acute kidney injury (AKI) during their critical illness (92% vs. 57%, p = 0.015 for any AKI; 62% vs. 26%, p = 0.019 for severe AKI). Patients who had AKI during critical illness had significantly higher cefepime exposure, as quantified by the area under the concentration-time curve over 24 h (AUC24h) and Cmin. CONCLUSIONS: Among critically ill children, AKI is associated with elevated cefepime concentrations. Identifying these high-risk patients is the first step toward evaluating the clinical consequences of such exposures.

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

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.

Individualized sublingual immunotherapy with dynamic maintenance dose ascending for house dust mite-induced allergic rhinitis.

BACKGROUND: Precision dosing in sublingual immunotherapy (SLIT) has become a hotspot gradually, yet no standardized dose adjustment pattern for house dust mite (HDM)-SLIT. This study aims to investigate the clinical feasibility of the dynamic maintenance dose ascending regimen for individualized SLIT. METHODS: A total of 258 allergic rhinitis (AR) patients treated with HDM-SLIT were included in this retrospective study. Patients were divided into the regular dose (RD) group (n = 101) and the high dose (HD) group (n = 157) according to different maintenance dosages of SLIT. In the RD group, patients received the fixed dose recommended by the manufacturer. In the HD group, patients received a maximum tolerance dose determined by dynamic dose ascending. The clinical efficacy was evaluated by combined symptom and medication score (CSMS) and visual analogue scale score (VAS) at the baseline, 0.5-year, 1-year, and 2-year. The safety was evaluated by adverse events (AEs). RESULTS: Significant reductions of CSMS and VAS at 0.5-year, 1-year, and 2-year were observed in both the RD group and the HD group compared to the baseline (P < 0.05). In addition, greater improvements in these clinical parameters from 0.5- to 2-year were found in the HD group compared to the RD group (P < 0.05). For subgroup analysis in the HD group, no significant differences in CSMS and VAS were observed among subgroups of patients <14 years old and patients ≥14 years old (P > 0.05). No serious AEs in the two groups and no significant differences were observed between the AE incidence rate of the RD group and HD group during the incremental and maintenance phases. CONCLUSIONS: The 2-year HDM-SLIT with dynamic maintenance dose ascending regimen offers an "optimal" treatment for AR patients while maintaining safety. This study introduced a pattern for individualized dose adjustment in clinical practice, offering potential benefits for AR patients.

Impact of CYP2D6*2, CYP2D6*35, rs5758550, and related haplotypes on risperidone clearance in vivo.

PURPOSE: The CYP2D6 gene exhibits significant polymorphism, contributing to variability in responses to drugs metabolized by CYP2D6. While CYP2D6*2 and CYP2D6*35 are presently designated as alleles encoding normal metabolism, this classification is based on moderate level evidence. Additionally, the role of the formerly called "enhancer" single nucleotide polymorphism (SNP) rs5758550 is unclear. In this study, the impacts of CYP2D6*2, CYP2D6*35 and rs5758550 on CYP2D6 activity were investigated using risperidone clearance as CYP2D6 activity marker. METHODS: A joint parent-metabolite population pharmacokinetic model was used to describe 1,565 serum concentration measurements of risperidone and 9-hydroxyrisperidone in 512 subjects. Risperidone population clearance was modeled as the sum of a CYP2D6-independent clearance term and the partial clearances contributed from each individually expressed CYP2D6 allele or haplotype. In addition to the well-characterized CYP2D6 alleles (*3-*6, *9, *10 and *41), *2, *35 and two haplotypes assigned as CYP2D6*2-rs5758550G and CYP2D6*2-rs5758550A were evaluated. RESULTS: Each evaluated CYP2D6 allele was associated with significantly lower risperidone clearance than the reference normal function allele CYP2D6*1 (p < 0.001). Further, rs5758550 differentiated the effect of CYP2D6*2 (p = 0.005). The haplotype-specific clearances for CYP2D6*2-rs5758550A, CYP2D6*2-rs5758550G and CYP2D6*35 were estimated to 30%, 66% and 57%, respectively, relative to the clearance for CYP2D6*1. Notably, rs5758550 is in high linkage disequilibrium (R2 > 0.85) with at least 24 other SNPs and cannot be assigned as a functional SNP. CONCLUSION: CYP2D6*2 and CYP2D6*35 encode reduced risperidone clearance, and the extent of reduction for CYP2D6*2 is differentiated by rs5758550. Genotyping of these haplotypes might improve the precision of genotype-guided prediction of CYP2D6-mediated clearance.

Dose optimization of ß-lactam antibiotics in children: from population pharmacokinetics to individualized therapy.

INTRODUCTION: ß-Lactams are the most widely used antibiotics in children. Their optimal dosing is essential to maximize their efficacy, while minimizing the risk for toxicity and the further emergence of antimicrobial resistance. However, most ß-lactams were developed and licensed long before regulatory changes mandated pharmacokinetic studies in children. As a result, pediatric dosing practices are poorly harmonized and off-label use remains common today. AREAS COVERED: ß-Lactam pharmacokinetics and dose optimization strategies in pediatrics, including fixed dose regimens, therapeutic drug monitoring, and model-informed precision dosing are reviewed. EXPERT OPINION/COMMENTARY: Standard pediatric doses can result in subtherapeutic exposure and non-target attainment for specific patient subpopulations (neonates, critically ill children, e.g.). Such patients could benefit greatly from more individualized approaches to dose optimization, beyond a relatively simple dose adaptation based on weight, age, or renal function. In this context, Therapeutic Drug Monitoring (TDM) and Model-Informed Precision Dosing (MIPD) emerge as particularly promising avenues. Obstacles to their implementation include the lack of strong evidence of clinical benefit due to the paucity of randomized clinical trials, of standardized assays for monitoring concentrations, or of adequate markers for renal function. The development of precision medicine tools is urgently needed to individualize therapy in vulnerable pediatric subpopulations.

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.

A prediction method for the individual serum concentration and therapeutic effect for optimizing adalimumab therapy in inflammatory bowel disease.

OBJECTIVES: Adalimumab (ADM) therapy is effective for inflammatory bowel disease (IBD), but a significant number of IBD patients lose response to ADM. Thus, it is crucial to devise methods to enhance ADM's effectiveness. This study introduces a strategy to predict individual serum concentrations and therapeutic effects to optimize ADM therapy for IBD during the induction phase. METHODS: We predicted the individual serum concentration and therapeutic effect of ADM during the induction phase based on pharmacokinetic and pharmacodynamic (PK/PD) parameters calculated using the empirical Bayesian method. We then examined whether the predicted therapeutic effect, defined as clinical remission or treatment failure, matched the observed effect. RESULTS: Data were obtained from 11 IBD patients. The therapeutic effect during maintenance therapy was successfully predicted at 40 of 47 time points. Moreover, the predicted effects at each patient's final time point matched the observed effects in 9 of the 11 patients. CONCLUSION: This is the inaugural report predicting the individual serum concentration and therapeutic effect of ADM using the Bayesian method and PK/PD modelling during the induction phase. This strategy may aid in optimizing ADM therapy for IBD.