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Related Concept Videos

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,...

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A Full Skin Defect Model to Evaluate Vascularization of Biomaterials In Vivo
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Published on: August 28, 2014

Validated models for predicting skin penetration from different vehicles.

Taravat Ghafourian1, Eleftherios G Samaras, James D Brooks

  • 1Medway School of Pharmacy, Universities of Kent and Greenwich, Central Avenue, Chatham Maritime, Kent ME4 4TB, UK. t.ghafourian@kent.ac.uk

European Journal of Pharmaceutical Sciences : Official Journal of the European Federation for Pharmaceutical Sciences
|September 7, 2010
PubMed
Summary
This summary is machine-generated.

This study developed a Quantitative Structure Activity Relationship (QSAR) model to predict skin permeability coefficients. The model accurately forecasts how penetrant and vehicle properties influence skin absorption, aiding formulation development.

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Area of Science:

  • Pharmacokinetics and Drug Delivery
  • Computational Chemistry
  • Dermal Absorption Studies

Background:

  • Understanding skin permeability is crucial for drug delivery and toxicology.
  • Existing models often overlook the significant impact of vehicles and mixture components on penetrant absorption.
  • Quantitative Structure-Activity Relationship (QSAR) approaches offer a predictive framework for skin permeation.

Purpose of the Study:

  • To develop and validate a QSAR model for predicting skin permeability coefficients (kp) of compounds in various vehicles.
  • To identify key molecular descriptors influencing dermal penetration.
  • To elucidate mechanisms underlying skin permeation influenced by formulation components.

Main Methods:

  • Diffusion cell studies using porcine skin to measure kp for 96 penetrant-vehicle combinations.
  • Integration of new data with a prior dataset of 288 kp values for comprehensive QSAR analysis.
  • Stepwise regression analysis to select significant molecular descriptors and develop predictive models.
  • Internal validation using a leave-many-out procedure to assess model robustness.

Main Results:

  • A statistically validated QSAR model was successfully developed.
  • Key predictors included penetrant descriptors (Wiener topological index, total lipole moment), solvent boiling point, and melting point differences between penetrant and solvent.
  • The model achieved a mean absolute error of 0.454 for logkp values on the test set, demonstrating good predictive accuracy.

Conclusions:

  • The developed QSAR model provides a reliable tool for predicting skin permeability coefficients.
  • The findings highlight the importance of considering both penetrant and vehicle properties in dermal absorption.
  • This model can guide formulation design and reduce the need for extensive experimental testing in drug development.