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Model Approaches for Pharmacokinetic Data: Compartment Models

Model Approaches for Pharmacokinetic Data: Compartment Models

Compartmental analysis is a widely adopted approach to characterizing drug pharmacokinetics. It uses compartment models that conceptualize the body as a collection of reversibly communicating compartments, each representing a group of tissues exhibiting similar drug distribution characteristics. The movement rate of the drug between these compartments is typically described by first-order kinetics.
Two primary types of compartment models are recognized: mammillary and catenary. The more...

Model Approaches for Pharmacokinetic Data: Physiological Models

Model Approaches for Pharmacokinetic Data: Physiological Models

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...

Bioavailability Enhancement: Determination and Conceptual Approaches in Overcoming Bioavailability Problems

Bioavailability Enhancement: Determination and Conceptual Approaches in Overcoming Bioavailability Problems

Body:Bioavailability is a critical pharmacological concept that measures the extent and rate at which an active drug ingredient or therapeutic moiety enters the systemic circulation, remaining unchanged. It's a pivotal factor in determining a drug's efficacy and safety.The Biopharmaceutics Classification System (BCS) plays an essential role in drug development by categorizing drugs into four classes based on their solubility and permeability. This classification aids in understanding drug...

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

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...

Self-Evaluation: Self-Enhancement and Self-Verification

Self-Evaluation: Self-Enhancement and Self-Verification

Social psychologists have documented that feeling good about ourselves and maintaining positive self-esteem is a powerful motivator of human behavior (Tavris & Aronson, 2008). In the United States, members of the predominant culture typically think very highly of themselves and view themselves as good people who are above average on many desirable traits (Ehrlinger, Gilovich, & Ross, 2005). Often, our behavior, attitudes, and beliefs are affected when we experience a threat to our...

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Related Experiment Video

Updated: Feb 16, 2026

Highly Sensitive and Quantitative Detection of Proteins and Their Isoforms by Capillary Isoelectric Focusing Method

Highly Sensitive and Quantitative Detection of Proteins and Their Isoforms by Capillary Isoelectric Focusing Method

Published on: September 19, 2018

The FAQUIRE Approach: FAst, QUantitative, hIghly Resolved and sEnsitivity Enhanced ¹H, ¹³C Data.

Jonathan Farjon¹, Clément Milande¹, Estelle Martineau^1,2

¹Faculté des Sciences et Techniques de Nantes, UMR CNRS 6230- CEISAM, Equipe EBSI, LUNAM Université , 44322 Nantes, France.

Analytical Chemistry

|January 6, 2018

Summary

New FAQUIRE NMR methods accelerate metabolite analysis in complex mixtures. Quick QUIPU HSQC enhances sensitivity and resolution for faster, more accurate quantitative metabolite detection.

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Area of Science:

Analytical Chemistry
Biochemistry
Spectroscopy

Background:

Metabolite analysis in complex mixtures using Nuclear Magnetic Resonance (NMR) faces challenges in sensitivity, resolution, and speed.
Existing 2D NMR quantitative maps offer enhanced resolution but are time-consuming due to acquisition methods and scan requirements.

Purpose of the Study:

To introduce FAst, QUantitative, hIghly Resolved and sEnsitivity enhanced (FAQUIRE) NMR to overcome limitations in metabolite analysis.
To develop a faster quantitative 2D NMR method by accelerating the QUantItative Perfected and pUre shifted HSQC (QUIPU HSQC) technique.

Main Methods:

Implementation of the FAQUIRE concept using spectral aliasing, nonuniform sampling, and variable repetition time.
Development of the Quick QUIPU HSQC (Q QUIPU HSQC) technique to reduce acquisition time.
Evaluation of the Q QUIPU HSQC method on a model metabolite sample and breast-cell extracts.

Main Results:

Acquisition time for 2D quantitative maps was reduced by a factor of 6 to 9.
High spectral resolution was maintained through a pure shift approach.
The Q QUIPU HSQC method demonstrated analytical potential for detecting metabolites at millimolar to submillimolar concentrations.

Conclusions:

The Q QUIPU HSQC method significantly accelerates quantitative 2D NMR metabolite analysis.
FAQUIRE NMR, exemplified by Q QUIPU HSQC, pushes the boundaries for sensitive and resolved metabolite detection.
This technique shows promise for analyzing complex biological samples like breast-cell extracts.