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Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

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Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
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Physiological Pharmacokinetic Models: Assumption with Protein Binding01:13

Physiological Pharmacokinetic Models: Assumption with Protein Binding

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Physiological models with protein binding in pharmacokinetics offer a sophisticated approach to understanding drug disposition. These models consider drug-protein interactions, enabling them to effectively predict drug concentrations in different organs and tissues. This precision aids in accurate drug dosing, providing a significant advantage over conventional models. A key process within these models is equilibration, which ensures that drug concentrations achieve a steady state within the...
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Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models00:57

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models

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Physiological pharmacokinetic models, often called flow-limited or perfusion models, typically assume a swift drug distribution between tissue and venous blood, creating a rapid drug equilibrium. This premise is based on the idea that drug diffusion is extremely fast, and the cell membrane presents no barrier to drug permeation. In this scenario, where no drug binding occurs, the drug concentration in the tissue equals that of the venous blood leaving the tissue. This greatly simplifies the...
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Physiological Pharmacokinetic Models: Incorporating Hepatic Transporter-Mediated Clearance01:07

Physiological Pharmacokinetic Models: Incorporating Hepatic Transporter-Mediated Clearance

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Drug transporters are critical in drug absorption, distribution, and excretion processes. They should be included in physiological-based pharmacokinetic (PBPK) models, which help predict human drug disposition. However, predicting this is challenging during drug development, especially when liver transport is involved. However, with a realistic representation of body transport processes, an accurate model may be possible.
A recent model describes pravastatin's hepatobiliary excretion,...
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Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches01:14

Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches

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Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
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Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

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Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal...
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Related Experiment Video

Updated: Jan 22, 2026

Assessment of Global Ocular Structure Following Spaceflight Using a Micro-Computed Tomography Micro-CT Imaging Method
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Physiologically based ocular pharmacokinetic modeling using computational methods.

Paul J Missel1, Ramesh Sarangapani1

  • 1Data Science and Digital Solutions, Alcon Vision LLC, Fort Worth, TX, USA.

Drug Discovery Today
|July 19, 2019
PubMed
Summary

Computational fluid dynamics (CFD) models simulate ocular drug transport, enabling reliable animal-to-human translation of bioavailability. These physiologically based models improve predictions of human ocular pharmacokinetics (PK) from animal studies.

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Area of Science:

  • Ocular pharmacology and drug delivery
  • Computational fluid dynamics (CFD)
  • Physiologically based pharmacokinetic (PBPK) modeling

Background:

  • Accurate prediction of ocular drug bioavailability and pharmacokinetics (PK) is crucial for effective topical treatments.
  • Traditional models often lack the anatomical detail necessary for precise drug distribution analysis within the eye.
  • Translating animal study results to human ocular drug performance remains a significant challenge.

Purpose of the Study:

  • To apply physiologically based models for simulating ocular drug administration and mass transport.
  • To compare a non-anatomical model with a detailed computational fluid dynamics (CFD) model incorporating ocular anatomy.
  • To establish reliable methods for animal-to-human translation of ocular drug bioavailability and PK.

Main Methods:

  • Development and application of a non-anatomical model using a simplified theorem for ocular bioavailability calculation.
  • Implementation of a CFD model that integrates ocular physiology and anatomical data from rabbit, monkey, and human eyes.
  • Simulation of fluid dynamics, pressures, temperatures, convection, and drug advection using material properties and boundary conditions.

Main Results:

  • The CFD model provides regional drug distribution within ocular tissues, a level of detail not achievable with standard compartmental models.
  • Physiologically based models enable the simulation of drug mass transport within and between ocular tissue regions.
  • The CFD approach facilitates the translation of experimental results from animal models to human ocular pharmacokinetics (PK).

Conclusions:

  • Explicitly representing ocular anatomy in CFD simulations enhances the accuracy of drug mass transport modeling.
  • Physiologically based CFD models offer a superior approach for predicting human ocular drug bioavailability and PK compared to non-anatomical methods.
  • This methodology provides a robust framework for reliable extrapolation of animal ocular drug delivery data to human applications.