title: Predicting the complex phase behavior of self-assembling drug delivery nanoparticles.
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.
authors: CSIRO Materials Science and Engineering, Bag 10, Clayton South MDC 3169, Australia.
authors: Tu C
authors: TC
authors: Le
authors: Xavier
authors: X
authors: Mulet
authors: Frank R
authors: FR
authors: Burden
authors: David A
authors: DA
authors: Winkler
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D002626:Chemistry, Pharmaceutical / Q000379:methods; D003198:Computer Simulation; D016503:Drug Delivery Systems; D015195:Drug Design; D006801:Humans; D050866:Liquid Crystals; D008823:Micelles; D053758:Nanoparticles / Q000737:chemistry*; D036103:Nanotechnology / Q000379:methods*; D016571:Neural Networks, Computer; D012997:Solvents / Q000737:chemistry; D017356:Synchrotrons; D013696:Temperature
chemical_list: D008823:Micelles; D012997:Solvents