A New Framework to Implement Model-Informed Dosing in Clinical Guidelines: Piperacillin and Amikacin as Proof of Concept

Abstract

Background: Modeling and simulation is increasingly used to study pediatric pharmacokinetics, but clinical implementation of age-appropriate doses lags behind. Therefore, we aimed to develop model-informed doses using published pharmacokinetic data and a decision framework to adjust dosing guidelines based on these doses, using piperacillin and amikacin in critically ill children as proof of concept.Methods: Piperacillin and amikacin pharmacokinetic models in critically ill children were extracted from literature. Concentration-time profiles were simulated for various dosing regimens for a virtual PICU patient dataset, including the current DPF dose and doses proposed in the studied publications. Probability of target attainment (PTA) was compared between the different dosing regimens. Next, updated dosing recommendations for the DPF were proposed, and evaluated using a new framework based on PK study quality and benefit-risk analysis of clinical implementation.Results: Three studies for piperacillin (critically ill children) and one for amikacin (critically ill pediatric burn patients) were included. Simulated concentration-time profiles were performed for a virtual dataset of 307 critically ill pediatric patients, age range 0.1–17.9 y. PTA for unbound piperacillin trough concentrations >16 mg/L was >90% only for continuous infusion regimens of 400 mg/kg/day vs. 9.7% for the current DPF dose (80 mg/kg/6 h, 30 min infusion). Amikacin PTA was >90% with 20 mg/kg/d, higher than the PTA of the DPF dose of 15 mg/kg/d (63.5%). Using our new decision framework, altered DPF doses were proposed for piperacillin (better PTA with loading dose plus continuous infusion), but not for amikacin (studied and target population were not comparable and risk for toxicity with higher dose).Conclusions: We show the feasibility to develop model-informed dosing guidelines for clinical implementation using existing pharmacokinetic data. This approach could complement literature and consensus-based dosing guidelines for off-label drugs in the absence of stronger evidence to support pediatricians in daily practice.

Benefit‐Risk Assessment of Off‐Label Drug Use in Children: The Bravo Framework

“…Modeling and simulation may be helpful to determine the appropriate dose when a target range is available. At this time, user friendly platforms for physicians/guideline committees are lacking, but pragmatic approaches are emerging like simulations using published PK and PBPK models (80,81) The application of such simulations is very helpful in determining a efficacious yet non-toxic dose, but requires a thorough understanding and experience in using these software applications.…”

“…Modeling and simulation may be helpful to determine the appropriate dose when a target range is available. At this time, user friendly platforms for physicians/guideline committees are lacking, but pragmatic approaches are emerging like simulations using published PK and PBPK models 80,81 …”

“…At this time, user friendly platforms for physicians/guideline committees are lacking, but pragmatic approaches are emerging like simulations using published PK and PBPK models. 80 , 81 …”

Status Toward the Implementation of Precision Dosing in Children

“…Formulary in the DPF context may be a bit misleading: This is not a preselection of reimbursed drugs for children (like hospital formularies), but an information source presenting pediatric drug doses and safety information. Most importantly, the DPF has included model‐based dosing in the Formulary 31,32 …”

Guideline for the management of pediatric off-label use of drugs in China (2021)

“…Instead, after studying and assessing the facts on pharmacokinetics, inferences must be drawn. In the absence of high-quality evidence, researchers have used data from pharmacokinetic models of piperacillin and amikacin in critically unwell infants to recreate the concentration–time curve and provide evidence related to the optimal dosage for clinicians to employ in their everyday practices [ 33 ]. Alternatively, precise drug dosages for neonates and babies can be produced by integrating dose validation, population pharmacokinetics, and mathematical models of drug clearance and distribution, allowing for safer and more effective off-label use of drugs [ 34 ].…”