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Related Concept Videos

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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Model Approaches for Pharmacokinetic Data: Compartment Models01:14

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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.
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A difference amplifier, a crucial component in numerous electronic devices, ideally amplifies only the difference-mode signal, which is the difference between two input signals. However, in practical circuits, the output voltage depends on both the differential gain and the common-mode gain.
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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.
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Related Experiment Video

Updated: Feb 9, 2026

Fabrication of Custom Agarose Wells for Cell Seeding and Tissue Ring Self-assembly Using 3D-Printed Molds
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Rapid customization system for 3D-printed splint using programmable modeling technique - a practical approach.

Jianyou Li1, Hiroya Tanaka1

  • 1Graduate School of Governance and Media, Keio University, 5322 Endo, Fujisawa-shi, Kanagawa 252-0882 Japan.

3D Printing in Medicine
|June 9, 2018
PubMed
Summary

This study introduces a semi-automatic 3D-printing design system for custom splints, simplifying the process for clinicians and improving patient comfort. The new method enhances efficiency and accessibility in creating 3D-printed orthopedic splints.

Keywords:
3D-printingCustomizationFracture immobilizationProgrammable modelingSplint

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Area of Science:

  • Biomedical Engineering
  • Rehabilitation Technology
  • Computer-Aided Design (CAD)

Background:

  • Traditional splinting is labor-intensive, irreversible, and often results in patient discomfort due to bulky, poorly ventilated designs.
  • 3D-printing offers a promising alternative but faces challenges with clinician CAD proficiency and anatomical model accuracy.
  • Existing limitations hinder the widespread adoption of 3D-printing for custom orthopedic splint fabrication.

Purpose of the Study:

  • To develop a semi-automatic design system using programmable modeling tools for efficient 3D-printable splint generation.
  • To overcome the limitations of manual CAD processes and improve accessibility for clinicians with varying technical skills.
  • To enhance the design process for 3D-printed splints, focusing on accuracy, customization, and ease of use.

Main Methods:

  • A programmable modeling tool was utilized to create a semi-automatic splint design system, divided into five stages.
  • The system incorporates automatic thickness calculation, lattice structure generation, and assembly methods for complex splints.
  • Clinicians define the splinting region by drawing curves, with the system automating model generation and flaw correction.

Main Results:

  • The system significantly reduces manual modeling time, generating final splint models within minutes.
  • It automatically corrects minor flaws in limb models and calculates optimal thickness and lattice density.
  • Complex splints can be segmented for multi-part printing, improving fabrication efficiency.

Conclusions:

  • Programmable modeling tools offer a viable solution to enhance 3D-printed splint design efficiency for clinicians with limited CAD experience.
  • The developed system aids in overcoming technical barriers, improving the overall clinical application of 3D-printed splints.
  • This approach facilitates better splint design, potentially leading to improved patient outcomes and satisfaction during rehabilitation.