Experiments to support modeling

By January 30th, 2016

The RAMP centre was acknowledged for their contribution to the preparation of sample libraries to support the work presented below.

 

Modeling the Influence of Fatty Acid Incorporation on Mesophase Formation in Amphiphilic Therapeutic Delivery Systems

By Tu C. Le†, Nhiem Tran†‡, Xavier Mulet†, and David A. Winkler*†§∥⊥
† CSIRO Manufacturing, Clayton 3169, Australia
‡ Australian Synchrotron, Clayton 3168, Australia
§ Monash Institute of Pharmaceutical Sciences, Parkville 3052, Australia
∥ Latrobe Institute for Molecular Science, Bundoora 3083, Australia
⊥ School of Chemical and Physical Sciences, Flinders University, Bedford Park 5042, Australia
Mol. Pharmaceutics, 2016, 13 (3), pp 996–1003
Publication Date (Web): January 29, 2016
Copyright Published 2016 by the American Chemical Society

Abstract

image from published abstract

Dispersed amphiphile-fatty acid systems are of great interest in drug delivery and gene therapies because of their potential for triggered release of their payload. The mesophase behavior of these systems is extremely complex and is affected by environmental factors such as drug loading, percentage and nature of incorporated fatty acids, temperature, pH, and so forth. It is important to study phase behavior of amphiphilic materials as the mesophases directly influence the release rate of the incorporated drugs. We describe a robust machine learning method for predicting the phase behavior of these systems. We have developed models for each mesophase that simultaneous and reliably model the effects of amphiphile and fatty acid structure, concentration, and temperature and that make accurate predictions of these mesophases for conditions not used to train the models.

Keywords:

amphiphilic drug delivery system; machine learning; mesophases; quantitative structure−property relationships modeling; triggered release