Development of a physiologically based pharmacokinetic model for mefloquine and its application alongside a clinical effectiveness model to select an optimal dose for prevention of malaria in young Caucasian children

Johnson, Trevor N.; Cleary, Yumi; Parrott, Neil; Reigner, Bruno; Smith, James; Toovey, Stephen

doi:10.1111/bcp.13764

Cited by 17 publications

(19 citation statements)

References 38 publications

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“…In the case of mefloquine, midazolam, and alfentanil, Upreti ontogeny improved model PK predictions in young children (0.5-2 years old). 42 In contrast, a tacrolimus pediatric PBPK model demonstrated that Salem ontogeny adjusted for disease effect in children (1-16 years old) in the intensive care unit provided results more consistent with observations. 43 In the case of imatinib PBPK model (children > 2 years old), no significant differences were observed.…”

Section: Discussionmentioning

confidence: 61%

“…Existing examples of applications of CYP3A4 hepatic ontogeny functions resulted in differing model predictive performance ( Table 1 ). In the case of mefloquine, midazolam, and alfentanil, Upreti ontogeny improved model PK predictions in young children (0.5‐2 years old) 42 . In contrast, a tacrolimus pediatric PBPK model demonstrated that Salem ontogeny adjusted for disease effect in children (1–16 years old) in the intensive care unit provided results more consistent with observations 43 .…”

Section: Discussionmentioning

confidence: 63%

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Impact of Hepatic CYP3A4 Ontogeny Functions on Drug–Drug Interaction Risk in Pediatric Physiologically‐Based Pharmacokinetic/Pharmacodynamic Modeling: Critical Literature Review and Ivabradine Case Study

Lang

Vincent

Chenel

et al. 2020

Clin Pharma and Therapeutics

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Clinical assessment of drug-drug interactions (DDIs) in children is not a common practice in drug development. Therefore, physiologically-based pharmacokinetic (PBPK) modeling can be beneficial for informing drug labeling. Using ivabradine and its metabolite (both cytochrome P450 3A4 enzyme (CYP3A4) substrates), the objectives were (i) to scale ivabradinemetabolite adult PBPK/PD to pediatrics, (ii) to predict the DDIs with a strong CYP3A4 inhibitor, and (iii) to compare the sensitivity of children to DDIs using two CYP3A4 hepatic ontogeny functions: Salem and Upreti. A scaled parent-metabolite PBPK/PD model from adults to children satisfactorily predicted pharmacokinetics (PK) and pharmacodynamics (PD) in 74 children (0.5-18 years) regardless of CYP3A4 hepatic ontogeny function applied. However, using the Salem ontogeny, mean predicted parent and metabolite area under the concentration-time curve over 12 hours (AUC 12h ) and heart rate change from baseline were 2-fold, 1.5-fold, and 1.4-fold higher in young children (0.5-3 years old) compared with Upreti ontogeny, respectively. Despite these differences, choice of appropriate hepatic CYP3A4 ontogeny was challenging due to sparse PK and PD data. Different sensitivity to ivabradine-ketoconazole DDIs was simulated in young children relative to adults depending on the choice of hepatic CYP3A4 ontogeny. Predicted ivabradine and metabolite AUC DDI /AUC control were 2-fold lower in the youngest children (0.5-1 year old) compared with adults (Salem function). In contrast, the Upreti function predicted comparable ivabradine DDIs across all age groups, although predicted metabolite AUC DDI/ AUC control was 1.3-fold higher between the youngest children and adults. In the case of PD, differences in predicted DDIs were minor across age groups and between both functions. Current work highlights the importance of careful consideration of hepatic CYP3A4 ontogeny function and implications on labeling recommendations in the pediatric population.

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Section: Discussionmentioning

confidence: 61%

Section: Discussionmentioning

confidence: 63%

Impact of Hepatic CYP3A4 Ontogeny Functions on Drug–Drug Interaction Risk in Pediatric Physiologically‐Based Pharmacokinetic/Pharmacodynamic Modeling: Critical Literature Review and Ivabradine Case Study

Lang

Vincent

Chenel

et al. 2020

Clin Pharma and Therapeutics

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“…However, considering the limitation of our knowledge, prediction may not always accurately match the clinical data. For example, some metabolic enzymes in children cannot be quantified ( 23 ). The PBPK model should reasonably describe all the parameters ( 12 ), but uncertainty analyses focus on the spread or distribution of simulated outputs due to the ambiguity surrounding input parameters and model structure.…”

Section: Physiologically Based Pharmacokinetic Modelmentioning

confidence: 99%

Physiologically Based Pharmacokinetic Models Are Effective Support for Pediatric Drug Development

et al. 2021

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Pediatric drug development faces many difficulties. Traditionally, pediatric drug doses are simply calculated linearly based on the body weight, age, and body surface area of adults. Due to the ontogeny of children, this simple linear scaling may lead to drug overdose in pediatric patients. The physiologically based pharmacokinetic (PBPK) model, as a mathematical model, contributes to the research and development of pediatric drugs. An example of a PBPK model guiding drug dose selection in pediatrics has emerged and has been approved by the relevant regulatory agencies. In this review, we discuss the principle of the PBPK model, emphasize the necessity of establishing a pediatric PBPK model, introduce the absorption, distribution, metabolism, and excretion of the pediatric PBPK model, and understand the various applications and related prospects of the pediatric PBPK model.

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“…The doses recommended for mefloquine in infants and young children weighing 5 to 10 kg vary from 32.25 to 62.5 mg. PBPK and clinical effective case models suggest a prophylactic dose of 62.5 mg weekly in 5‐ to 10‐kg white infants traveling to endemic countries 141 …”

Section: Antimalarial Dose Optimization In Vulnerable Groupsmentioning

confidence: 99%

“…134 The doses recommended for mefloquine in infants and young children weighing 5 to 10 kg vary from 32.25 to 62.5 mg. PBPK and clinical effective case models suggest a prophylactic dose of 62.5 mg weekly in 5-to 10-kg white infants traveling to endemic countries. 141 The currently recommended sulfadoxinepyrimethamine dose results in substantially lower plasma drug concentrations in young children. 142 The population-based PK modeling provides no evidence of underdosing in children with malaria as compared with adults.…”

Section: Antimalarial Dose Optimization In Vulnerable Groupsmentioning

confidence: 99%

The Role of Clinical Pharmacology in Chemotherapy of Multidrug‐Resistant Plasmodium falciparum

Karbwang

Na‐Bangchang

2020

The Journal of Clinical Pharma

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Malaria remains one of the major global public health problems due to the emergence and spread of multidrug‐resistant Plasmodium falciparum. In recent years, clinical pharmacology has significantly contributed to the optimal dosing regimens of antimalarial drugs. The application of pharmacometric modeling and simulation has assisted in the accurate characterization of pharmacokinetic‐pharmacodynamic relationships and the optimization of the dosage regimens of existing antimalarial drugs, including new antimalarial candidates for multidrug‐resistant P falciparum in different populations.

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Development of a physiologically based pharmacokinetic model for mefloquine and its application alongside a clinical effectiveness model to select an optimal dose for prevention of malaria in young Caucasian children

Cited by 17 publications

References 38 publications

Impact of Hepatic CYP3A4 Ontogeny Functions on Drug–Drug Interaction Risk in Pediatric Physiologically‐Based Pharmacokinetic/Pharmacodynamic Modeling: Critical Literature Review and Ivabradine Case Study

Impact of Hepatic CYP3A4 Ontogeny Functions on Drug–Drug Interaction Risk in Pediatric Physiologically‐Based Pharmacokinetic/Pharmacodynamic Modeling: Critical Literature Review and Ivabradine Case Study

Physiologically Based Pharmacokinetic Models Are Effective Support for Pediatric Drug Development

The Role of Clinical Pharmacology in Chemotherapy of Multidrug‐Resistant Plasmodium falciparum

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