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Related Concept Videos

Clinical Trials01:16

Clinical Trials

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Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...
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Clinical Trials: Overview01:11

Clinical Trials: Overview

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Clinical development focuses on how the drug will interact with the human body and encompasses four key phases of clinical trials, each serving a specific purpose in assessing the safety and effectiveness of new drugs. These phases overlap and build upon one another. Phase I involves a small group of healthy volunteers (typically 20-80 individuals) or, in cases where significant toxicity is expected, patients with the targeted disease, such as cancer or AIDS. The volunteers are tested for...
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Virtual Work01:20

Virtual Work

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The principle of virtual work states that if a body is in static and dynamic equilibrium, then the sum of all the virtual work done by all external forces and couple moments for any given virtual displacement must be zero.
In static equilibrium, a body can experience an imaginary or virtual movement, such as displacement or rotation. The virtual work done by a force is equal to the dot product of force and virtual displacement in the direction of the force. When it comes to virtually rotating a...
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The Virtual Trial.

Willem de Haan1

  • 1Department of Neurology, VU University Medical Center Amsterdam, Netherlands.

Frontiers in Neuroscience
|March 23, 2017
PubMed
Summary
This summary is machine-generated.

Brain network analysis shows promise for understanding dementia. Network intervention modeling offers a virtual trial approach to predict clinical outcomes and develop countermeasures for neurodegenerative damage.

Keywords:
Alzheimercomputational modelingconnectivitygraph theorynetworkneurodegeneration

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Area of Science:

  • Neuroscience
  • Computational Biology
  • Medical Informatics

Background:

  • Brain network analysis, or connectomics, is an emerging field in neurodegenerative disease research.
  • Despite high expectations, current connectomics knowledge has not translated into practical clinical applications for dementia.
  • Physicians often view brain connectivity analysis as too technical and abstract for direct patient benefit.

Purpose of the Study:

  • To bridge the gap between brain connectivity research and clinical practice in neurodegenerative diseases.
  • To propose network intervention modeling as a method to translate connectomics insights into clinical utility.
  • To explore how computational modeling can enhance the understanding of neurodegenerative network damage.

Main Methods:

  • Utilizing network analysis to study complex brain system phenomena.
  • Employing computational modeling to simulate interventions on brain networks.
  • Developing a virtual trial approach to test influences on network integrity.

Main Results:

  • Network intervention modeling provides a test environment for exploring positive and negative influences on brain networks.
  • This approach can identify potential countermeasures against neurodegenerative network damage.
  • The virtual trial method facilitates the translation of connectome knowledge into clinical predictions.

Conclusions:

  • Network intervention modeling is a promising candidate for integrating connectomics into clinical practice.
  • This approach can help explain and predict the relationship between neurodegeneration pathology and cognitive symptoms.
  • The virtual trial approach may become a key tool for dementia and connectivity researchers, advancing clinical predictions.