Document Type
Article
Publication Date
2011
Journal or Book Title
ACS Combinatorial Science
Volume
13
Issue
1
First Page
50
Last Page
58
DOI
10.1021/co100019d
Abstract
Polyanhydrides are a class of degradable biomaterials that have shown much promise for applications in drug and vaccine delivery. Their properties can be tailored for controlled drug release, drug/protein stability, and immune regulation (adjuvant effect). Identifying the relationship between the molecular structures of the polymers and the drug release kinetics profiles would help understand the release mechanism and aid in the accurate prediction of drug release and the rational design of polymer-based drug carrier systems. The molecular structure descriptors that had the most impact on the release kinetics were identified using a prediction/optimization data mining approach. Using this new approach for modeling nonlinear release kinetics behavior, we determined that the descriptors which had the greatest effect on the release kinetics were the number of backbone -COO- nonconjugated bonds, the number of aromatic rings, and the number of -CH 2- bonds.
Copyright Owner
American Chemical Society
Copyright Date
2011
Language
en
File Format
application/pdf
Recommended Citation
Li, Xue; Petersen, Latrisha K.; Broderick, Scott; Narasimhan, Balaji; and Rajan, Krishna, "Identifying factors controlling protein release from combinatorial biomaterial libraries via hybrid data mining methods" (2011). Chemical and Biological Engineering Publications. 194.
https://lib.dr.iastate.edu/cbe_pubs/194
Included in
Biological Engineering Commons, Chemical Engineering Commons, Materials Science and Engineering Commons
Comments
Reprinted (adapted) with permission from ACS Combinatorial Science 13 (2011): 50, doi: 10.1021/co100019d. Copyright 2011 American Chemical Society.