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Related Concept Videos

Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

368
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...
368
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

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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...
327
Clearance Models: Physiological Models01:09

Clearance Models: Physiological Models

465
Drug clearance is a critical pharmacokinetic process involving the irreversible removal of drugs from the body through various organs over a specified time period. Physiological models are indispensable in determining organ-specific clearance, defined by the proportion of the drug eliminated per unit of time from the organ's blood volume.
The organ's clearance rate depends on the blood flow to the organ and the extraction ratio (E). The extraction ratio describes the organ's...
465
Model Approaches for Pharmacokinetic Data: Compartment Models01:14

Model Approaches for Pharmacokinetic Data: Compartment Models

863
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...
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Pharmacodynamic Models: Overview01:27

Pharmacodynamic Models: Overview

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Pharmacodynamic (PD) responses describe the interaction between a drug and its biological target, culminating in a physiological effect. These responses can be classified into different types: continuous variables, such as blood glucose levels; categorical outcomes, like survival rates; and time-to-event metrics, such as disease progression. Understanding and modeling PD responses are critical for optimizing drug efficacy and safety.PD models describe the relationship between drug concentration...
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Related Experiment Video

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Behavioral Phenotyping of Murine Disease Models with the Integrated Behavioral Station INBEST
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V-Model: a new perspective for EHR-based phenotyping.

Heekyong Park, Jinwook Choi1

  • 1Interdisciplinary Program of Biomedical Engineering, Seoul National University, Seoul, Republic of Korea. jinchoi@snu.ac.kr.

BMC Medical Informatics and Decision Making
|October 25, 2014
PubMed
Summary
This summary is machine-generated.

The V-Model enhances clinical data analysis by visualizing patient histories on a timeline. This novel approach improves the representation and readability of narrative medical events for better study efficiency.

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Area of Science:

  • Medical Informatics
  • Health Data Visualization

Background:

  • Electronic health records (EHRs) present challenges for clinical phenotyping due to narrative data.
  • Current timeline visualizations have limitations in depicting narrative clinical events effectively.

Purpose of the Study:

  • To introduce the V-Model, a novel temporal model for visualizing clinical narratives.
  • To enhance the efficiency of information-based studies by improving timeline representations of patient histories.

Main Methods:

  • Developed the V-Model, a graphical structure for modeling temporal clinical events.
  • Considered representation, reasoning, and visualization (readability) in the V-Model's design.
  • Evaluated the V-Model's usability and performance against a conventional timeline model with 80 medical professionals.

Main Results:

  • The V-Model demonstrated superiority in representing narrative medical events.
  • The V-Model provided sufficient information for temporal reasoning and outperformed conventional models in readability.
  • Usability assessments for the V-Model were positive.

Conclusions:

  • The V-Model effectively addresses visualization challenges in clinical documents.
  • The V-Model offers improved usability compared to traditional timeline models for analyzing patient histories.