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Related Concept Videos

Drug Product Performance: In Vitro–In Vivo Correlation01:20

Drug Product Performance: In Vitro–In Vivo Correlation

In pharmaceutical development, it's crucial to establish a predictive in vitro–in vivo correlation (IVIVC) for two or more formulations to gain a comprehensive understanding of release properties. IVIVC reduces the need for costly in vivo studies and facilitates the establishment of meaningful dissolution specifications with significant cost savings and decreased regulatory burden. Furthermore, a meaningful IVIVC should predict Cmax and AUC within 20%, aligning with FDA guidance while adhering...
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Various dissolution methods are utilized to assess a drug’s dissolution rate, including the flow-through cell, paddle-over-disk, cylinder, and reciprocating disk methods.The flow-through cell apparatus (USP (United States Pharmacopeia) method 4) comprises a reservoir for the dissolution medium and a pump that propels the medium through the cell containing the test sample. This method is crucial for assessing modified-release dosage forms with minimally soluble active ingredients, maintaining...
In Vitro Drug Dissolution: Compendial Testing Models I01:13

In Vitro Drug Dissolution: Compendial Testing Models I

Compendial dissolution methods are standardized procedures defined by pharmacopeias to evaluate the rate at which a drug dissolves in a specific medium. These methods ensure batch-to-batch consistency, enable quality control, and support the prediction of drug bioavailability. They are critical for both immediate and modified-release drug products.The apparatuses used for dissolution testing differ in their design and mechanical function, but all aim to simulate the physiological environment of...
One-Compartment Open Model for IV Bolus Administration: Estimation of Elimination Rate Constant, Half-Life and Volume of Distribution01:09

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Drug response models describe how pharmacological agents interact with biological systems to produce measurable effects. Baseline responses are inherent physiological activities without a drug significantly influencing the observed pharmacological outcomes. Depending on the drug response model employed, these baseline responses may combine with the drug's effect in either an additive or proportional manner.Additive Drug Response ModelIn the additive model, the drug effect is independent of the...

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In vitro - In vivo correlation modeling of an oxcarbezapine extended-release formulation using numerical

Maziar Kakhi1, Hansong Chen2, Jason Chittenden3

  • 1Division of Product Quality Research, Office of Product Quality Research, Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA.

International Journal of Pharmaceutics
|May 17, 2026
PubMed
Summary

A robust in vitro-in vivo correlation (IVIVC) for oxcarbazepine (OXC) extended-release formulations was re-established using advanced methods. This improved IVIVC accurately predicts drug performance and informs dissolution criteria, enhancing regulatory science.

Keywords:
IVIVCInternal/external validationNumerical deconvolutionOver-discriminating dissolution

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High-throughput and Comprehensive Drug Surveillance Using Multisegment Injection-Capillary Electrophoresis-Mass Spectrometry

Published on: April 23, 2019

Area of Science:

  • Pharmaceutical Sciences
  • Pharmacokinetics
  • Drug Delivery Systems

Background:

  • In vitro-in vivo correlation (IVIVC) is crucial for assessing extended-release formulations.
  • An initial IVIVC for oxcarbazepine (OXC) extended-release was deemed inadequate for regulatory purposes.
  • Re-evaluation of IVIVC models is essential for ensuring product quality and performance.

Purpose of the Study:

  • To re-evaluate and establish a predictively robust IVIVC for an oxcarbazepine (OXC) extended-release formulation.
  • To apply the predictive IVIVC for determining appropriate dissolution acceptance criteria.
  • To compare the accuracy of IVIVCs based on the parent drug versus its active metabolite.

Main Methods:

  • Two-stage numerical deconvolution was employed for IVIVC analysis.
  • Enhanced unit impulse response (UIR) characterization and nonlinear mapping functions were utilized.
  • In vitro drug release data was correlated with in vivo pharmacokinetic data of OXC and its active metabolite.

Main Results:

  • The re-evaluated IVIVC met both internal and external validation criteria, demonstrating predictive robustness.
  • Application of the predictive IVIVC supported dissolution criteria that agreed well with existing approved criteria.
  • IVIVCs linking in vitro release to the active metabolite's in vivo response exhibited higher accuracy than those linked to the parent drug.

Conclusions:

  • Enhanced characterization and nonlinear mapping significantly improve IVIVC robustness and predictability.
  • A robust IVIVC can effectively guide the establishment of dissolution acceptance criteria for extended-release formulations.
  • Correlating in vitro data with the active metabolite's pharmacokinetics provides a more accurate IVIVC for OXC formulations.