As chloroquine (CHQ) is part of the Dutch Centre for Infectious Disease Control coronavirus disease 2019 experimental treatment guideline, pediatric dosing guidelines are needed. Recent pediatric data suggest that existing World Health Organization (WHO) dosing guidelines for children with malaria are suboptimal. The aim of our study was to establish best-evidence to inform pediatric CHQ doses for children infected with COVID-19. A previously developed physiologically-based pharmacokinetic (PBPK) model for CHQ was used to simulate exposure in adults and children and verified against published pharmacokinetic data. The COVID-19 recommended adult dosage regimen of 44 mg/kg total was tested in adults and children to evaluate the extent of variation in exposure. Based on differences in area under the concentration-time curve from zero to 70 hours (AUC 0-70h ) the optimal CHQ dose was determined in children of different ages compared with adults. Revised doses were re-introduced into the model to verify that overall CHQ exposure in each age band was within 5% of the predicted adult value. Simulations showed differences in drug exposure in children of different ages and adults when the same body-weight based dose is given. As such, we propose the following total cumulative doses: 35 mg/kg (CHQ base) for children 0-1 month, 47 mg/kg for 1-6 months, 55 mg/kg for 6 months-12 years, and 44 mg/kg for adolescents and adults, not to exceed 3,300 mg in any patient. Our study supports age-adjusted CHQ dosing in children with COVID-19 in order to avoid suboptimal or toxic doses. The knowledge-driven, model-informed dose selection paradigm can serve as a science-based alternative to recommend pediatric dosing when pediatric clinical trial data is absent.With coronavirus disease 2019 (COVID-19) spreading rapidly across the globe, effective drug treatment is desperately needed. Based on Chinese population data, < 1% of the infected cases were children below the age of 10 years and clinical symptoms in these patients were milder compared with adults. 1 However, it is unknown how such numbers will evolve when a higher percentage of the entire world population with diverse ethnic and socioeconomical backgrounds is infected.

This study shows that the level of evidence for off-label pediatric pharmacotherapy is low: for only 14% of off-label records, high quality studies are available. Thirty-seven percent of offlabel records are not supported by any clinical studies at all. HOW MIGHT THIS CHANGE CLINICAL PHARMA COLOGY OR TRANSLATIONAL SCIENCE? Performing high quality randomized controlled trials for the > 2,000 off-label record is a very long pathway to close this information gap. Alternatively, modeling and simulation may be valuable approaches to strengthen the evidence base for offlabel use of drugs, especially in younger age groups.

Physiologically based pharmacokinetic (PBPK) modeling can be an attractive tool to increase the evidence base of pediatric drug dosing recommendations by making optimal use of existing pharmacokinetic (PK) data. A pragmatic approach of combining available compound models with a virtual pediatric physiology model can be a rational solution to predict PK and hence support dosing guidelines for children in real-life clinical care, when it can also be employed by individuals with little experience in PBPK modeling. This comes within reach as user-friendly PBPK modeling platforms exist and, for many drugs and populations, models are ready for use. We have identified a list of drugs that can serve as a starting point for pragmatic PBPK modeling to address current clinical dosing needs. Supplementary Information The online version contains supplementary material available at 10.1007/s40272-022-00535-w.

Background and Objective More than half of all drugs are still prescribed off-label to children. Pharmacokinetic (PK) data are needed to support off-label dosing, however for many drugs such data are either sparse or not representative. Physiologicallybased pharmacokinetic (PBPK) models are increasingly used to study PK and guide dosing decisions. Building compound models to study PK requires expertise and is time-consuming. Therefore, in this paper, we studied the feasibility of predicting pediatric exposure by pragmatically combining existing compound models, developed e.g. for studies in adults, with a pediatric and preterm physiology model. Methods Seven drugs, with various PK characteristics, were selected (meropenem, ceftazidime, azithromycin, propofol, midazolam, lorazepam, and caffeine) as a proof of concept. Simcyp ® v20 was used to predict exposure in adults, children, and (pre)term neonates, by combining an existing compound model with relevant virtual physiology models. Predictive performance was evaluated by calculating the ratios of predicted-to-observed PK parameter values (0.5-to 2-fold acceptance range) and by visual predictive checks with prediction error values. Results Overall, model predicted PK in infants, children and adolescents capture clinical data. Confidence in PBPK model performance was therefore considered high. Predictive performance tends to decrease when predicting PK in the (pre)term neonatal population. Conclusion Pragmatic PBPK modeling in pediatrics, based on compound models verified with adult data, is feasible. A thorough understanding of the model assumptions and limitations is required, before model-informed doses can be recommended for clinical use.Rick Greupink and Saskia N. de Wildt: Joint last author.

<b><i>Abstract:</i></b> Many drugs are used off-label in neonates which leads to large variation in prescribed drugs and dosages in neonatal intensive care units (NICUs). The NeoDose project aimed to develop best evidence dosing recommendations (DRs) for term and preterm neonates using a three-step approach: 1) drug selection, 2) establishing consensus-based DRs, and 3) establishing best evidence DRs. <b><i>Methods:</i></b> The selection of drugs was based on frequency of prescribing, availability of a neonatal DR in the Dutch Pediatric Formulary, and the labeling status. Clinical need, pharmacological diversity, and Working Group Neonatal Pharmacology (WGNP) preferences were also taken into account, using a consensus-based approach. For the second step, we requested local dosing protocols from all ten Dutch NICUs and established consensus-based DRs within the WGNP, consisting of neonatologists, clinical pharmacologists, hospital pharmacists, and researchers. In the third step, the consensus-based DRs were compared with the available literature, using standardized PubMed searches. <b><i>Results:</i></b> Fourteen drugs were selected for which the local dosing protocols were collected. These protocols differed mostly in total daily dose, dosing frequency, and/or route of administration. Strikingly, almost none of the dosing protocols of these 14 drugs distinguished between preterm and term neonates. The working group established consensus-based DRs, which after literature review needed modification in 56%, mainly in terms of a dose increase. Finally, we established 37 best evidence DRs, 22 for preterm and 15 for term neonates, representing 19 indications. <b><i>Conclusion:</i></b> This project showed the successful three-step approach for the development of DRs for term and preterm neonates.