Linking formulation composition to pharmacokinetic and pharmacodynamic responses: a predictive framework for sustained-release tablets

The development of sustained-release formulations remains largely empirical and often requires iterative in vitro and in vivo studies to achieve desired pharmacokinetic profiles and therapeutic outcomes. In this study, we developed a formulation-driven predictive framework that links formulation composition to pharmacokinetic and pharmacodynamic responses by integrating design of experiments (DoE), in vitro–in vivo correlation (IVIVC), and population pharmacokinetic/pharmacodynamic (PK/PD) modeling. This approach enables the prediction of both plasma concentration–time and pharmacodynamic response–time profiles directly from formulation composition. Using ticagrelor as a model drug, nineteen sustained-release formulations were prepared and characterized in vitro based on a mixture design with three formulation variables. Three formulations spanning fast, medium, and slow dissolution rates were selected for in vivo pharmacokinetic and pharmacodynamic evaluation in beagle dogs. In vitro dissolution kinetics were described using a Michaelis–Menten model, and the maximum dissolution rate (Vmax) was used as a common linking parameter across the DoE, IVIVC, and PK/PD components. A population PK/PD model incorporating time-dependent dissolution and site-dependent absorption processes was established, and a Level A IVIVC was developed by correlating in vitro and in vivo Vmax values. The framework was validated using both internal and external formulations and successfully predicted pharmacokinetic and pharmacodynamic profiles from formulation composition alone. Prediction errors were within 12.70% for internal validation formulations and within 9.67% for an additionally prepared external validation formulation, meeting FDA criteria for IVIVC predictability. This framework provides a mechanistically grounded strategy for model-informed optimization of sustained-release tablet delivery systems.

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Publication Details

Journal
Drug Delivery
Published
2026-10-27
DOI
https://doi.org/10.1080/10717544.2026.2752652
Primary Topic
Drug Solubulity and Delivery Systems
Type
article
Field-Weighted Citation Impact
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article

Linking formulation composition to pharmacokinetic and pharmacodynamic responses: a predictive framework for sustained-release tablets

Beom Soo Shin, Meoung Jun Park, Jun Hyung Pyo, Soyoung Shin et al.
1 links
Drug Delivery
Drug Solubulity and Delivery Systems
article

Linking formulation composition to pharmacokinetic and pharmacodynamic responses: a predictive framework for sustained-release tablets

Beom Soo Shin, Meoung Jun Park, Jun Hyung Pyo, Soyoung Shin, Tae Hwan Kim, Sungmin Song
article en

Abstract

The development of sustained-release formulations remains largely empirical and often requires iterative in vitro and in vivo studies to achieve desired pharmacokinetic profiles and therapeutic outcomes. In this study, we developed a formulation-driven predictive framework that links formulation composition to pharmacokinetic and pharmacodynamic responses by integrating design of experiments (DoE), in vitro–in vivo correlation (IVIVC), and population pharmacokinetic/pharmacodynamic (PK/PD) modeling. This approach enables the prediction of both plasma concentration–time and pharmacodynamic response–time profiles directly from formulation composition. Using ticagrelor as a model drug, nineteen sustained-release formulations were prepared and characterized in vitro based on a mixture design with three formulation variables. Three formulations spanning fast, medium, and slow dissolution rates were selected for in vivo pharmacokinetic and pharmacodynamic evaluation in beagle dogs. In vitro dissolution kinetics were described using a Michaelis–Menten model, and the maximum dissolution rate (Vmax) was used as a common linking parameter across the DoE, IVIVC, and PK/PD components. A population PK/PD model incorporating time-dependent dissolution and site-dependent absorption processes was established, and a Level A IVIVC was developed by correlating in vitro and in vivo Vmax values. The framework was validated using both internal and external formulations and successfully predicted pharmacokinetic and pharmacodynamic profiles from formulation composition alone. Prediction errors were within 12.70% for internal validation formulations and within 9.67% for an additionally prepared external validation formulation, meeting FDA criteria for IVIVC predictability. This framework provides a mechanistically grounded strategy for model-informed optimization of sustained-release tablet delivery systems.

Drug DeliveryVol. 33(1)
Daegu Catholic University (KR), Chung-Ang University (KR), Sungkyunkwan University (KR)
National Research Foundation of Korea
Good health and well-being
Openalex Percentile: Top 15%
Drug Solubulity and Delivery Systems
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