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Related Concept Videos

Model Approaches for Pharmacokinetic Data: Compartment Models01:14

Model Approaches for Pharmacokinetic Data: Compartment Models

570
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...
570
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...
279
Chronic Pancreatitis II: Collaborative Care01:29

Chronic Pancreatitis II: Collaborative Care

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The management of chronic pancreatitis is multifaceted, involving a comprehensive approach that includes thorough assessment, diagnostic testing, and a variety of management strategies.
Assessment:
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Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis00:59

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

335
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...
335
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

249
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...
249
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches01:14

Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches

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Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
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WikiSensing: an online collaborative approach for sensor data management.

Dilshan Silva1, Moustafa Ghanem, Yike Guo

  • 1Department of Computer Science, Imperial College London, South Kensington Campus, London SW7 2AZ, UK. d.silva10@imperial.ac.uk

Sensors (Basel, Switzerland)
|December 4, 2012
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Summary
This summary is machine-generated.

WikiSensing offers a new way to manage sensor data collaboratively online. This system integrates online collaboration with sensor data management, improving data accessibility and usability.

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Area of Science:

  • Computer Science
  • Data Management
  • Collaborative Systems

Background:

  • Sensor data management faces challenges in accessibility and collaboration.
  • Existing sensor data management and online collaborative systems have limitations.

Purpose of the Study:

  • To introduce WikiSensing, a novel methodology for collaborative sensor data management.
  • To address the challenges in designing and developing online collaborative sensor data management systems.

Main Methods:

  • Developed a new methodology called WikiSensing.
  • Designed and presented the architecture of the WikiSensing system.
  • Described example scenarios to illustrate system functionality.

Main Results:

  • Investigated the performance of aggregate queries within WikiSensing.
  • Evaluated the scalability of the WikiSensing system.
  • Demonstrated the functionality of the system through various scenarios.

Conclusions:

  • WikiSensing provides a viable approach for collaborative sensor data management.
  • The system shows promising performance in aggregate queries and scalability.