Alexander A. Vinks

Traditional dosing strategies often rely on a “one‐size‐fits‐all” paradigm, assuming an “average” patient with typical demographic and pharmacological characteristics. In reality, this often overlooks existing between‐patient variability and can lead to suboptimal drug exposure or toxicity. This issue is especially pronounced in pediatric patients, who experience rapid growth and development of organ functions. Although patient's age and body size are often considered when determining pediatric dose, those factors account for only a relatively small part of the variability. Pharmacometrics provides a rigorous framework for characterizing drug behavior, uncovering patient‐specific covariates driving variability, and allows translating insights derived from adults to pediatric populations. Model‐informed precision dosing (MIPD) integrates quantitative pharmacological models to leverage clinical data from patients (e.g., drug concentrations and biomarkers) to predict drug exposure and response, thereby informing optimal dosing strategies to maximize clinical benefits. While MIPD has demonstrated feasibility and clinical benefits, it remains underutilized in routine clinical practice. In this article, we describe the establishment and operation of an MIPD consultation service within an academic children's hospital. Through real‐world examples, we illustrate how precision dosing workflows can be integrated into routine clinical care and highlight key considerations for further dissemination. By sharing our experience, we aim to bridge a critical gap in the literature and provide a practical blueprint for operationalizing MIPD to advance personalized therapy in pediatrics.

Hydroxyurea provides effective disease-modifying treatment for people with sickle cell anemia (SCA), especially when escalated to maximum tolerated dose (MTD), which has wide interpatient dosing variability due to pharmacokinetic (PK) differences. Whether hydroxyurea PK parameters differ among children with SCA in different global regions is unknown. We compared hydroxyurea PK parameters among children with SCA from 5 clinical trials: HUSTLE (United States), TREAT (United States), NOHARM (Uganda), REACH (Uganda and Kenya), and EXTEND (Jamaica). Key hydroxyurea PK parameters were determined using HdxSim, a validated hydroxyurea PK software program. The results were compared across regions by analysis of variance. PK profiles from 451 children with SCA (146 from the United States, 265 from Africa, and 40 from the Caribbean) were included. Children from Africa had slightly lower volumes of distribution, but absorption rate and clearance were similar across regions. The PK-recommended doses to achieve MTD were statistically different but clinically similar across the United States (26.6 ± 5.9 mg/kg per day), Africa (27.6 ± 6.5 mg/kg per day), and the Caribbean (25.2 ± 4.7 mg/kg per day) (P = .04). In multivariable regression, younger age and increased reticulocyte counts were associated with higher PK-recommended doses. Hydroxyurea PK parameters in children with SCA differ minimally across global populations, predicting clinically similar doses to achieve MTD. Individualized hydroxyurea dosing based on a PK-population model derived from US children with SCA can be used broadly to maximize the benefits of this critical medication in other global populations. These trials were registered at www.ClinicalTrials.gov as #NCT00305175 (HUSTLE), #NCT02286154 (TREAT), #NCT01976416 (NOHARM), #NCT01966731 (REACH), and #NCT02556099 (EXTEND).

This article provides a summary of the Sumner Yaffe Award lecture presented at the annual meeting of the Pediatric Pharmacy Association in Portland, Oregon, on April 10, 2025. The article provides a short history of pediatric clinical pharmacology and elaborates on the ongoing paradox of precision medicine and the drug development process that is still geared toward the labeling of doses for the average patient. The article highlights contemporary clinical decision support approaches that integrate model-informed precision dosing (MIPD) to improve treatment outcomes in children. A series of case studies of successful implementation of model-informed clinical decision support tools is described including examples of full integration of such platforms into the electronic health record at Cincinnati Children’s Hospital Medical Center. These studies show that pediatric precision dosing is progressing beyond the conceptual and proof-of-concept stages toward implementation into clinical workflows. The evidence provided indicates that model-informed therapeutic drug management for children is clinically feasible, with an increasing number of studies documenting improved clinical outcomes as compared with standard of care.

Belatacept (BELA) pharmacokinetic (PK) studies informed dosing strategies used in phase 3 studies, where fixed mg/kg dosing compared a less intensive (LI) and more intensive (MI) regimen. The LI regimen was preferred due to a better risk/benefit profile. We compared PK parameters observed in the BELA Early Steroid Withdrawal Trial (BEST) with previous reports. BELA trough samples were analyzed using a validated quantitative enzyme‐linked immunoassay. Clearance (CL) was estimated with Bayesian estimation using a published BELA population PK model. Significantly higher CL was observed in subjects Trial Registration : ClinicalTrials.gov identifier: NCT 01729494

Pharmacokinetic (PK)‐guided dosing of hydroxyurea for children with sickle cell anaemia (SCA) could optimize dosing and improve outcomes, but its feasibility has not been demonstrated in low‐resource settings where the majority of affected children live. Alternative Dosing And Prevention of Transfusions (ADAPT) is a prospective trial evaluating blood transfusions and the feasibility of determining PK‐guided, hydroxyurea maximum tolerated doses (MTD) for children with SCA in Uganda, using portable high‐performance liquid chromatography (HPLC) and a novel PK software programme (HdxSim). ADAPT enrolled 106 participants, and 100% completed PK testing. PK‐guided doses were generated for 78%, of which 38% were within the protocol‐defined range. Accurately, measuring serum hydroxyurea concentrations via HPLC and the potential for hydroxyurea degradation impacted the feasibility. Ensuring that people with SCA globally have access to hydroxyurea is imperative, and improving treatment strategies requires ongoing innovation including PK‐guided dosing. ADAPT is registered at ClinicalTrials.gov (NCT05662098).

Sickle cell anemia (SCA) is an inherited blood disorder that leads to morbidity and early mortality. Hydroxyurea is an effective oral medication to treat SCA, and optimal dosing benefits from pharmacokinetic (PK)-based methods that require accurate analysis of hydroxyurea levels in timed patient blood samples. Current gold standard assay methods such as liquid chromatography-mass spectroscopy (LC-MS) require sophisticated instrumentation, trained personnel, and laborious sample pretreatment steps that may alter target molecule levels. Additionally, LC-MS is time-consuming and costly, leading to delays in treatment decisions, and is not feasible for use in low-resource settings. Herein, we report a novel approach for chemical analysis of serum hydroxyurea levels by using an array of intelligent electrochemical microsensors modified with thin films of nanomaterials to record the electrochemical signature of blood samples from 50 children treated with hydroxyurea. To analyze this complex dataset, multiple machine learning models were trained and optimized to predict hydroxyurea levels from microliter sample volumes. We evaluated three regression algorithms: elastic net, random forest (RF), and partial least squares regression (PLSR) across 11 different electrochemical feature matrices. Among these, PLSR demonstrated the best performance, achieving a root mean square error of 41.85 µM (3.18 μg/mL) and average prediction error of 7.24 µM (0.55 µg/mL), thereby enabling accurate analysis of hydroxyurea levels within the therapeutic range using microliter sample volumes from pediatric patients. With further miniaturization of such sensor arrays and integration into point-of-care testing devices, hydroxyurea PK-based dosing can be simplified for use in low-resource settings to improve SCA treatment outcomes worldwide.

Pharmacokinetic (PK)‐guided dosing of hydroxyurea for children with sickle cell anaemia (SCA) could optimize dosing and improve outcomes, but its feasibility has not been demonstrated in low‐resource settings where the majority of affected children live. Alternative Dosing And Prevention of Transfusions (ADAPT) is a prospective trial evaluating blood transfusions and the feasibility of determining PK‐guided, hydroxyurea maximum tolerated doses (MTD) for children with SCA in Uganda, using portable high‐performance liquid chromatography (HPLC) and a novel PK software programme (HdxSim). ADAPT enrolled 106 participants, and 100% completed PK testing. PK‐guided doses were generated for 78%, of which 38% were within the protocol‐defined range. Accurately, measuring serum hydroxyurea concentrations via HPLC and the potential for hydroxyurea degradation impacted the feasibility. Ensuring that people with SCA globally have access to hydroxyurea is imperative, and improving treatment strategies requires ongoing innovation including PK‐guided dosing. ADAPT is registered at ClinicalTrials.gov (NCT05662098).

The use of model‐informed precision dosing to personalize infliximab has been shown to improve both the acquisition of concentration targets and clinical outcomes during maintenance. Current iterations of infliximab pharmacokinetic models include time‐varying covariates of drug clearance, however, not accounting for the expected improvements in the covariates can lead to indiscriminate use of higher infliximab doses and imprecise drug exposure. The aim was to identify changes in the four biomarkers associated with infliximab clearance (Xiong et al. model) and determine if integration of these dynamic changes would improve model performance during induction and early maintenance. We analyzed two cohorts of children receiving infliximab for Crohn's Disease. The E_max method was used to assess time‐varying changes in covariates. Model performance (observed vs. predicted infliximab concentrations) was evaluated using median percentage error (bias) and median absolute percentage error (precision). The combined cohorts included 239 Crohn's disease patients. We found from baseline to dose 4, the maximum changes in weight, albumin, erythrocyte sedimentation rate, and neutrophil CD64 were 4.7%, +11.7%, −62.4%, and −26.5%, respectively. We also found the use of baseline covariates alone to forecast future trough concentration was inferior to the E_max time‐varying method with a significant improvement observed in bias (doses 2, 3, and 4) and precision (doses 2 and 4). The integration of the four time‐varying biomarkers of drug clearance with pharmacokinetic modeling improved the accuracy and precision of the predictions. This novel strategy may be key to improving drug exposure, minimizing indiscriminate dosing strategies, and reducing healthcare costs.

Sublingual buprenorphine is used for opioid use disorder and neonatal opioid withdrawal syndrome (NOWS). The study aimed to develop a full physiologically-based pharmacokinetic (PBPK) model that can adequately describe dose- and formulation-dependent bioavailability of buprenorphine. Simcyp (v21.0) was used for model construction. Four linear regression models (i.e. untransformed or log-transformed for dose or proportion sublingually absorbed) were explored to describe sublingual absorption of buprenorphine across dose. Published clinical trial data not used in model development were used for verification. The PBPK model9s predictive performance was deemed adequate if the geometric means of ratios between predicted and observed (P/O ratios) area under the curve (AUC), peak concentration (C_max), and time to reach C_max (T_max) fell within the 1.25-fold prediction error range. Sublingual buprenorphine absorption was best described by a regression model with logarithmically transformed dose. By integrating this nonlinear absorption profile, the PBPK model adequately predicted buprenorphine pharmacokinetics (PK) following administration of sublingual tablets and solution across a dose range of 2-32 mg, with geometric mean (95% confidence interval) P/O ratios for AUC and C_max equaling 0.99 (0.86-1.12) and 1.24 (1.09-1.40), respectively, and median (5th to 95th percentile) for T_max equaling 1.11 (0.69-1.57). A verified PBPK model was developed that adequately predicts dose- and formulation-dependent buprenorphine PK following sublingual administration. Significance Statement The PBPK model developed in this study is the first to adequately predict dose- and formulation-dependent sublingual buprenorphine pharmacokinetics. Accurate prediction was facilitated by the incorporation of a novel nonlinear absorption model. The developed model will serve as the foundation for fetomaternal PBPK modeling to predict maternal and fetal buprenorphine exposures to optimize buprenorphine treatment for neonatal opioid withdrawal syndrome (NOWS).