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Related Concept Videos

Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Sampling Plans01:23

Sampling Plans

Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...
Dosage Regimens: Partial Pharmacokinetic Parameters01:01

Dosage Regimens: Partial Pharmacokinetic Parameters

It is not uncommon for complete drug pharmacokinetic profiles to remain elusive in pharmacokinetics. This necessitates certain educated assumptions by pharmacokineticists to determine appropriate dosage regimens without comprehensive pharmacokinetic data from animal or human studies. One prevalent assumption is setting the bioavailability factor, denoted as F, to 1 or 100%. This assumption caters to the scenario where a drug doesn't achieve full systemic absorption, resulting in the patient...

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Updated: Jun 30, 2026

Evaluating Regional Pulmonary Deposition using Patient-Specific 3D Printed Lung Models
07:56

Evaluating Regional Pulmonary Deposition using Patient-Specific 3D Printed Lung Models

Published on: November 11, 2020

Informing Sampling Design for Lung Distribution Studies Using a Pulmonary Population Minimal PBPK Model.

Haini Wen1, Muhammad Waqas Sadiq2, Markus Fridén1,3

  • 1Department of Pharmacy, Uppsala University, Uppsala, Sweden.

Clinical Pharmacokinetics
|June 29, 2026
PubMed
Summary
This summary is machine-generated.

Developing a pulmonary physiologically based pharmacokinetic (PBPK) model for inhaled salbutamol using multiple sampling techniques improved predictions. Bronchosorption combined with biopsy was most informative, guiding optimized drug development study designs.

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Unilateral Lung Volume Analysis Using Micro-CT for Enhanced Assessment of Pulmonary Fibrosis in Preclinical Models
03:38

Unilateral Lung Volume Analysis Using Micro-CT for Enhanced Assessment of Pulmonary Fibrosis in Preclinical Models

Published on: June 20, 2025

Area of Science:

  • Pharmacokinetics and Drug Metabolism
  • Inhaled Drug Delivery Systems
  • Computational Modeling in Pharmacology

Background:

  • Understanding intrapulmonary pharmacokinetics (PK) is crucial for inhaled drug development.
  • Current lung sampling methods like bronchoalveolar lavage (BAL) and biopsy have limitations.
  • Bronchosorption offers enhanced regional specificity and reduced quantification errors for intrapulmonary drug analysis.

Purpose of the Study:

  • To develop a pulmonary population physiologically based pharmacokinetic (PBPK) model for inhaled salbutamol.
  • To integrate data from BAL, biopsy, and bronchosorption techniques for improved PK predictions.
  • To compare different intrapulmonary sampling strategies to optimize future study designs.

Main Methods:

  • Developed a population-based minimal PBPK model using existing salbutamol PK data.
  • Assessed the impact of permeability on pulmonary PK and epithelial lining fluid (ELF)-to-plasma ratios.
  • Employed stochastic simulation-estimation (SSE) to evaluate single and combined sampling techniques (BAL, biopsy, bronchosorption).
  • Compared uniform and staggered bronchosorption sampling strategies for drugs with varying permeability.

Main Results:

  • The PBPK model estimated key parameters: lung tissue-plasma partition coefficient (Kp,u,lung) of 11.0 and effective permeability (Peff) of 0.543 m/h for salbutamol.
  • Inter-individual variability was observed in plasma clearance and lung deposition, but not in Kp,u,lung or Peff.
  • Drug permeability influenced intrapulmonary distribution: low-permeability drugs concentrated in ELF, high-permeability drugs in lung tissue.
  • Bronchosorption plus biopsy was the most informative combination; bronchosorption alone was the best single technique.
  • Optimal sampling strategies (timing and duration) depended on drug permeability.

Conclusions:

  • A pulmonary population PBPK model integrating BAL, biopsy, and bronchosorption data was successfully developed for inhaled salbutamol.
  • Parameter estimates for Kp,u,lung and Peff were sensitive to the sampling technique used.
  • Staggered sampling strategies reduced bias, with optimal windows varying by drug permeability.
  • Findings support model-informed, permeability-driven study designs for inhaled drug development.