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Related Concept Videos

Clearance Models: Physiological Models01:09

Clearance Models: Physiological Models

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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.
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Related Experiment Video

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The Virtual Physiological Human: Ten Years After.

Marco Viceconti1, Peter Hunter2

  • 1Department of Mechanical Engineering and Insigneo Institute for in silico Medicine, University of Sheffield, Sheffield S1 3JD, United Kingdom;

Annual Review of Biomedical Engineering
|July 16, 2016
PubMed
Summary
This summary is machine-generated.

The Virtual Physiological Human initiative aims to integrate complex biomedical data into predictive models for systemic diseases. This approach addresses the limitations of reductionist methods in understanding genotype-phenotype interactions for better healthcare.

Keywords:
Virtual Physiological Humancomputational physiologyin silico medicinephysiome

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Area of Science:

  • Computational physiology
  • Biomedical modeling
  • Systems biology

Background:

  • Modern healthcare faces complexity from advanced treatments.
  • Challenging diseases (cardiovascular, cancer, etc.) involve intricate genotype-phenotype interactions and systemic effects.
  • Traditional reductionist approaches struggle with these complex, systemic conditions.

Purpose of the Study:

  • To reflect on the original vision of the Virtual Physiological Human (VPH) concept proposed in 2005.
  • To assess the progress made in translating computational physiology into clinical practice.
  • To identify remaining challenges and future directions for VPH development.

Main Methods:

  • Conceptual reflection on the VPH initiative.
  • Review of advancements in computational physiology and modeling technologies since 2005.
  • Analysis of the integration of molecular, cellular, and tissue-level data into predictive hypermodels.

Main Results:

  • The VPH concept was formally proposed in 2005, inspired by the Physiome Project.
  • Initial limitations in methods and technologies hindered the realization of VPH in 2005.
  • Significant progress has been made over the past decade in developing necessary tools and understanding.

Conclusions:

  • The VPH initiative offers a promising framework to manage the complexity of systemic diseases.
  • Integrating fragmented knowledge into predictive hypermodels is key to overcoming reductionist limitations.
  • Continued development and reflection are crucial for realizing the full potential of VPH in clinical practice.