Predicting the complex phase behavior of self-assembling drug delivery nanoparticles

Mol Pharm. 2013 Apr 1;10(4):1368-77. doi: 10.1021/mp3006402. Epub 2013 Mar 20.

Abstract

Amphiphilic lyotropic liquid crystalline self-assembled nanomaterials have important applications in the delivery of therapeutic and imaging agents. However, little is known about the effect of the incorporated drug on the structure of nanoparticles. Predicting these properties is widely considered intractable. We present computational models for three drug delivery carriers, loaded with 10 drugs at six concentrations and two temperatures. These models predicted phase behavior for 11 new drugs. Subsequent synchrotron small-angle X-ray scattering experiments validated the predictions.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Bayes Theorem
  • Chemistry, Pharmaceutical / methods
  • Computer Simulation
  • Drug Delivery Systems*
  • Drug Design
  • Humans
  • Liquid Crystals
  • Micelles
  • Nanoparticles / chemistry*
  • Nanotechnology / methods*
  • Neural Networks, Computer
  • Solvents / chemistry
  • Synchrotrons
  • Temperature

Substances

  • Micelles
  • Solvents