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Structure-permeability Relationships for Transcorneal Penetration.

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Summary
This summary is machine-generated.

This study developed a structure-permeability relationship (SPR) to predict chemical transport across the cornea. Physicochemical properties like lipophilicity and molecular weight accurately forecast corneal permeability, aiding drug discovery.

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Area of Science:

  • Pharmacokinetics and Drug Delivery
  • Computational Chemistry
  • Ocular Pharmacology

Background:

  • Accurate prediction of corneal permeability is crucial for ophthalmic drug development.
  • Existing models often lack sufficient predictive power for diverse chemical structures.

Purpose of the Study:

  • To develop a statistically significant structure-permeability relationship (SPR) for predicting corneal transport.
  • To identify key physicochemical properties influencing corneal permeability.
  • To establish a robust SPR model for transcorneal delivery prediction.

Main Methods:

  • Literature data set of 112 corneal permeability measurements.
  • Multiple linear regression using logarithm of octanol-water partition coefficient (logP) and molecular weight (MW).
  • Stepwise regression analysis incorporating additional physicochemical properties.

Main Results:

  • A significant (p < 0.001) two-variable SPR (logP, MW) was established.
  • A three-variable SPR including lipophilicity (logP), molecular shape (kappa index [κ3]), and hydrogen-bonding capacity (nH) was also significant (p < 0.001).
  • Both models demonstrated stable coefficients and predictive capability.

Conclusions:

  • Physicochemical properties can effectively predict corneal permeability.
  • SPR models offer a valuable tool for early-stage drug discovery and optimizing transcorneal delivery.
  • Mechanistically based SPRs facilitate the prediction of drug transport across the cornea.