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Related Concept Videos

Model Approaches for Pharmacokinetic Data: Physiological Models01:15

Model Approaches for Pharmacokinetic Data: Physiological Models

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

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

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

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

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...
Pharmacokinetic Models: Overview01:20

Pharmacokinetic Models: Overview

Pharmacokinetic models utilize mathematical analysis to achieve a detailed quantitative understanding of a drug's life cycle within the body. They are instrumental in simulating a drug's pharmacokinetic parameters, predicting drug concentrations over time, optimizing dosage regimens, linking concentrations with pharmacologic activity, and estimating potential toxicity.
There are three primary types of models: empirical, compartment, and physiological. Empirical models, with minimal assumptions,...
Pharmacokinetic Models: Comparison and Selection Criterion01:26

Pharmacokinetic Models: Comparison and Selection Criterion

Physiological and compartmental models are valuable tools used in studying biological systems. These models rely on differential equations to maintain mass balance within the system, ensuring an accurate representation of the dynamic processes at play.
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Model Approaches for Pharmacokinetic Data: Compartment Models01:14

Model Approaches for Pharmacokinetic Data: Compartment Models

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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Efficient Sampling of Genetically Encoded Biosensor Design Space Enabled with a Design of Experiments and Automation Workflow
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An engineering approach to biomedical sciences: advanced testing methods and pharmacokinetic modeling.

Gaetano Lamberti1, Sara Cascone, Giuseppe Titomanlio

  • 1Dipartimento di Ingegneria Industriale, Università di Salerno, Salerno, Italy.

Translational Medicine @ Unisa
|August 2, 2013
PubMed
Summary

This study introduces an engineering approach to pharmacology research, enhancing in-vitro testing and in-silico pharmacokinetic models. These methods reduce the need for costly and ethically challenging in-vivo experiments.

Keywords:
in-silicoin-vitroin-vivopharmacokineticstesting methods

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Area of Science:

  • Pharmacology
  • Bioengineering
  • Computational Biology

Background:

  • Traditional pharmacology research heavily relies on in-vivo measurements, which are expensive and raise ethical concerns.
  • There is a growing need for alternative methodologies in drug development and testing.

Purpose of the Study:

  • To describe an engineering-driven research philosophy in pharmacology.
  • To present improved in-vitro testing methods for pharmaceutical systems.
  • To introduce and validate mathematical models for pharmacokinetic analysis (in-silico techniques).

Main Methods:

  • Development and application of advanced in-vitro testing techniques.
  • Creation and evaluation of mathematical models for pharmacokinetic predictions.
  • Integration of engineering principles into pharmacological research methodologies.

Main Results:

  • Demonstrated improvements in pharmaceutical system testing using in-vitro approaches.
  • Successful proposal and testing of in-silico models for pharmacokinetic description.
  • Validation of methodologies that reduce reliance on in-vivo studies.

Conclusions:

  • An engineering approach offers efficient and ethical alternatives in pharmacology research.
  • In-vitro and in-silico techniques are valuable tools for reducing in-vivo measurements.
  • The presented methodologies and tools can significantly optimize drug development processes.