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1.
Front Pediatr ; 11: 1288376, 2023.
Article in English | MEDLINE | ID: mdl-38078320

ABSTRACT

Introduction: Modeling and simulation can support dosing recommendations for clinical practice, but a simple framework is missing. In this proof-of-concept study, we aimed to develop neonatal and infant gentamicin dosing guidelines, supported by a pragmatic physiologically-based pharmacokinetic (PBPK) modeling approach and a decision framework for implementation. Methods: An already existing PBPK model was verified with data of 87 adults, 485 children and 912 neonates, based on visual predictive checks and predicted-to-observed pharmacokinetic (PK) parameter ratios. After acceptance of the model, dosages now recommended by the Dutch Pediatric Formulary (DPF) were simulated, along with several alternative dosing scenarios, aiming for recommended peak (i.e., 8-12 mg/L for neonates and 15-20 mg/L for infants) and trough (i.e., <1 mg/L) levels. We then used a decision framework to weigh benefits and risks for implementation. Results: The PBPK model adequately described gentamicin PK. Simulations of current DPF dosages showed that the dosing interval for term neonates up to 6 weeks of age should be extended to 36-48 h to reach trough levels <1 mg/L. For infants, a 7.5 mg/kg/24 h dose will reach adequate peak levels. The benefits of these dose adaptations outweigh remaining uncertainties which can be minimized by routine drug monitoring. Conclusion: We used a PBPK model to show that current DPF dosages for gentamicin in term neonates and infants needed to be optimized. In the context of potential uncertainties, the risk-benefit analysis proved positive; the model-informed dose is ready for clinical implementation.

2.
Clin Pharmacol Ther ; 114(5): 960-971, 2023 Nov.
Article in English | MEDLINE | ID: mdl-37553784

ABSTRACT

It is well-accepted that off-label drug dosing recommendations for pediatric patients should be based on the best available evidence. However, the available traditional evidence is often low. To bridge this gap, physiologically-based pharmacokinetic (PBPK) modeling is a scientifically well-founded tool that can be used to enable model-informed dosing (MID) recommendations in children in clinical practice. In this tutorial, we provide a pragmatic, PBPK-based pediatric modeling workflow. For this approach to be successfully implemented in pediatric clinical practice, a thorough understanding of the model assumptions and limitations is required. More importantly, careful evaluation of an MID approach within the context of overall benefits and the potential risks is crucial. The tutorial is aimed to help modelers, researchers, and clinicians, to effectively use PBPK simulations to support pediatric drug dosing.

3.
Pharmaceutics ; 15(5)2023 May 06.
Article in English | MEDLINE | ID: mdl-37242665

ABSTRACT

Dose recommendations for lamivudine or emtricitabine in children with HIV and chronic kidney disease (CKD) are absent or not supported by clinical data. Physiologically based pharmacokinetic (PBPK) models have the potential to facilitate dose selection for these drugs in this population. Existing lamivudine and emtricitabine compound models in Simcyp® (v21) were verified in adult populations with and without CKD and in non-CKD paediatric populations. We developed paediatric CKD population models reflecting subjects with a reduced glomerular filtration and tubular secretion, based on extrapolation from adult CKD population models. These models were verified using ganciclovir as a surrogate compound. Then, lamivudine and emtricitabine dosing strategies were simulated in virtual paediatric CKD populations. The compound and paediatric CKD population models were verified successfully (prediction error within 0.5- to 2-fold). The mean AUC ratios in children (GFR-adjusted dose in CKD population/standard dose in population with normal kidney function) were 1.15 and 1.23 for lamivudine, and 1.20 and 1.30 for emtricitabine, with grade-3- and -4-stage CKD, respectively. With the developed paediatric CKD population PBPK models, GFR-adjusted lamivudine and emtricitabine dosages in children with CKD resulted in adequate drug exposure, supporting paediatric GFR-adjusted dosing. Clinical studies are needed to confirm these findings.

4.
Paediatr Drugs ; 25(1): 5-11, 2023 Jan.
Article in English | MEDLINE | ID: mdl-36201128

ABSTRACT

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.


Subject(s)
Models, Biological , Child , Humans
5.
Clin Pharmacokinet ; 61(12): 1705-1717, 2022 Dec.
Article in English | MEDLINE | ID: mdl-36369327

ABSTRACT

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. Physiologically-based 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.


Subject(s)
Models, Biological , Propofol , Infant , Infant, Newborn , Adult , Adolescent , Child , Humans , Midazolam/pharmacokinetics , Computer Simulation
6.
Clin Toxicol (Phila) ; 60(11): 1240-1247, 2022 11.
Article in English | MEDLINE | ID: mdl-36149343

ABSTRACT

Introduction: The annual number of patients > 65 years old about whom the Dutch Poisons Information Center (DPIC) was consulted has more than doubled in the last decade. We aimed to gain insight in the type and circumstances of exposures reported to the DPIC involving older patients, in order to help prevent future poisonings. Methods: Enquiries to the DPIC involving patients > 65 years old were prospectively included from January 2019 to June 2019. Data were collected on patient characteristics (e.g., age, gender, and living situation) and exposure characteristics (e.g., type and exposure scenario). Results: In the first half of 2019, the DPIC was consulted about 1051 patients > 65 years old. The median age of the patients was 77 years old (range: 66-104 years) and women were over-represented (61%). A total of 1650 different substances were reported, 1213 pharmaceutical exposures (74%) and 437 non-pharmaceutical exposures (26%), mostly household products (n = 162). Most pharmaceutical exposures involved cardiovascular agents (n = 367, 30%), central and peripheral nervous system agents (n = 354, 29%), and analgesics (n = 152, 13%). In 71% of the patients exposed to pharmaceuticals, the drugs were taken unintentionally (n = 471), frequently caused by medication errors made by the patients themselves (n = 357, 76%). Most common scenarios included inadvertently taken/given a double (n = 140, 30%) or more than double (n = 94, 20%) dose or the wrong medication (n = 124, 26%). The most common scenario for unintentional exposure to non-pharmaceuticals was "mistook product for food/drink" (n = 122, 37%). Conclusions: The majority of intoxications in older adults are accidental and often involve medication errors. Unintentional poisoning is often preventable. If patients are cognitively impaired, potentially harmful substances should be kept out of their reach and medication should only be administered under direct supervision. Clear labelling, simplified drug regimens and the use of automatic medication dispensers could reduce the risk of medication errors in older patients.


Subject(s)
Poison Control Centers , Poisons , Humans , Female , Aged , Aged, 80 and over , Medication Errors , Analgesics , Information Centers
7.
Clin Pharmacol Ther ; 112(6): 1243-1253, 2022 12.
Article in English | MEDLINE | ID: mdl-36069288

ABSTRACT

Many drugs are still prescribed off-label to the pediatric population. Although off-label drug use not supported by high level of evidence is potentially harmful, a comprehensive overview of the quality of the evidence pertaining off-label drug use in children is lacking. The Dutch Pediatric Formulary (DPF) provides best evidence-based dosing guidelines for drugs used in children. For each drug-indication-age group combination-together compiling one record-we scored the highest available level of evidence: labeled use, systematic review or meta-analysis, randomized controlled trial (RCT), comparative research, noncomparative research, or consensus-based expert opinions. For records based on selected guidelines, the original sources were not reviewed. These records were scored as guideline. A total of 774 drugs were analyzed comprising a total of 6,426 records. Of all off-label records (n = 2,718), 14% were supported by high quality evidence (4% meta-analysis or systematic reviews, 10% RCTs of high quality), 20% by comparative research, 14% by noncomparative research, 37% by consensus-based expert opinions, and 15% by selected guidelines. Fifty-eight percent of all records were authorized, increasing with age from 30% in preterm neonates (n = 110) up to 64% in adolescents (n = 1,630). Many have advocated that off-label use is only justified when supported by a high level of evidence. We show that this prerequisite would seriously limit available drug treatment for children as the underlying evidence is low across ages and drug classes. Our data identify the drugs and therapeutic areas for which evidence is clearly missing and could drive the global research agenda.


Subject(s)
Drug Labeling , Off-Label Use , Adolescent , Child , Humans , Infant, Newborn , Consensus , Ethnicity
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