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Related Concept Videos

Volume of Distribution01:20

Volume of Distribution

The apparent volume of distribution (Vd) is a crucial pharmacokinetic parameter representing the hypothetical body fluid volume into which a drug disperses. It is calculated based on the total amount of drug in the body (estimated from the administered dose and bioavailability) divided by the plasma drug concentration. The total amount of drug in the body does not directly refer to the dose given but is derived by accounting for absorption, distribution, metabolism, and excretion processes.
Drug Distribution: Volume of Distribution01:25

Drug Distribution: Volume of Distribution

The volume of distribution refers to the theoretical volume necessary to contain the entire amount of an administered drug at the same concentration observed in the blood plasma. The body's intracellular fluid compartment, which makes up two-thirds of the total body water, is contrasted with the extracellular fluid compartment—comprising plasma and interstitial fluid—that accounts for one-third. The volume of distribution can vary depending on the characteristics of the drug.
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.
Measurement of Bioavailability: Pharmacodynamic Methods01:20

Measurement of Bioavailability: Pharmacodynamic Methods

Pharmacodynamic methods provide insights into a drug's effects on physiological processes over time and play a crucial role in understanding bioavailability and therapeutic efficacy. These methods can be broadly classified into acute pharmacological and therapeutic response approaches, each with distinct mechanisms and applications.The acute pharmacological response method directly correlates a drug's physiological effects, such as ECG or pupil diameter changes, to its time course in the body.
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...
Noncompartmental Analysis: Miscellaneous Pharmacokinetic Parameters00:54

Noncompartmental Analysis: Miscellaneous Pharmacokinetic Parameters

The noncompartmental approach is a widely used method in pharmacokinetics to assess drugs' behaviors in the body. It considers several factors, including clearance, bioavailability, and total volume of distribution.
One key aspect of the noncompartmental approach is determining a drug's total clearance. This can be done by dividing the drug dose by the area under the concentration-time curve from zero to infinity. The area under the concentration-time curve represents the drug's overall...

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Related Experiment Video

Updated: May 18, 2026

Mass-Sensitive Particle Tracking to Characterize Membrane-Associated Macromolecule Dynamics
13:30

Mass-Sensitive Particle Tracking to Characterize Membrane-Associated Macromolecule Dynamics

Published on: February 18, 2022

In search of physiologically based distribution volume estimates for macromolecules.

P D Garzone1, A J Atkinson

  • 1Clinical Research Department, Pfizer, Inc., South San Francisco, California, USA.

Clinical Pharmacology and Therapeutics
|September 21, 2012
PubMed
Summary
This summary is machine-generated.

The pharmacokinetic modeling of trastuzumab emtansine (T-DM1) used a two-compartment model that is physiologically implausible. This statistical approach may limit understanding of T-DM1 distribution kinetics.

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Mass-Sensitive Particle Tracking to Characterize Membrane-Associated Macromolecule Dynamics
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Published on: June 9, 2018

Area of Science:

  • Pharmacokinetics and pharmacodynamics
  • Biopharmaceutical modeling
  • Oncology drug development

Background:

  • Trastuzumab emtansine (T-DM1) is an antibody-drug conjugate used in cancer therapy.
  • Accurate pharmacokinetic (PK) modeling is crucial for optimizing T-DM1 efficacy and safety.
  • Previous PK analyses of T-DM1 and similar macromolecules have employed distribution models.

Purpose of the Study:

  • To evaluate the pharmacokinetic modeling approach used for trastuzumab emtansine (T-DM1).
  • To assess the physiological plausibility of the distribution models applied to T-DM1 pharmacokinetics.
  • To highlight the limitations of statistical versus physiological considerations in macromolecule PK modeling.

Main Methods:

  • Semimechanistic analysis of T-DM1 pharmacokinetics.
  • Modeling T-DM1 deconjugation using transit compartments for plasma volume.
  • Employing a single peripheral compartment in the distribution model.

Main Results:

  • The study identified the two-compartment distribution model used for T-DM1 as physiologically implausible.
  • This modeling approach, guided by statistical rather than physiological factors, may misrepresent T-DM1 distribution kinetics.
  • Similar limitations were noted in other recent analyses of trastuzumab and macromolecule distribution.

Conclusions:

  • The current pharmacokinetic modeling strategies for T-DM1 require re-evaluation.
  • Physiologically informed modeling is essential for a more accurate understanding of T-DM1 distribution and behavior.
  • Future research should prioritize biologically realistic models for antibody-drug conjugates.