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June 3, 2026Current Reviews in Clinical and Experimental Pharmacology0 citations

Model-Informed Precision Dosing in Pediatrics: Current Practices, Opportunities, and Challenges

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RPRohith Anandan PrabakarARAbilash ReddybathiniCRChandramouli Radhakrishnan

Key Points

  • This review examines pharmacokinetic differences and advancements in dosing strategies for children.
  • Compared traditional dosing approaches with Model-Informed Precision Dosing (MIPD) methods.
  • Outlined the use of Population Pharmacokinetic (PopPK) and Physiologically Based Pharmacokinetic (PBPK) modeling.
  • Evaluated Bayesian forecasting and AI for improving dosing accuracy.
  • Identified key challenges in regulatory standards for pediatric medication development.
  • Highlighted the potential of MIPD to enhance dosing precision in pediatrics.
  • Discussed future strategies for improving model-based dosing approaches.

Abstract

Recent advances in pediatric pharmacokinetics highlight substantial age-dependent physiological changes that require specialised approaches to optimise efficacy and minimise adverse effects in children. This review compares pharmacokinetic differences between adults and children, traditional dosing approaches, and recent developments in Model-Informed Precision Dosing (MIPD), with a focus on Population Pharmacokinetic (PopPK) and Physiologically Based Pharmacokinetic (PBPK) modeling strategies. Recent advances in Bayesian forecasting and the integration of artificial intelligence and machine learning are highlighted for their potential to improve dosing accuracy and clinical decision-making. This article examines current regulatory perspectives on pharmacometric approaches in pediatric medication development and offers insights into evolving standards and guidelines. It also addresses key technical, logistical, and regulatory challenges and potential solutions. Based on these insights, future strategies to improve model-based precision in pediatric dosing are discussed.

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Prabakar et al. (2026) studied this question.

synapsesocial.com/papers/6a1fc530dee9eb8c0dce68f6https://doi.org/10.2174/0127724328461249260523072801
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