Recognitive polymer networks for therapeutic and diagnostic devices
Abstract
Polymeric materials based on recognition are the next generation of intelligent materials that will be used in the diagnosis and cure of many diseases. By mimicking the recognition processes of natural macromolecules such as enzymes and DNA, synthetic materials with similar selectivity and binding behavior can be designed. These materials, then, can be incorporated into diagnostic devices such as biosensors, or therapeutic devices such as modulated drug delivery devices with intrinsic detection and delivery capabilities. This will accomplish the ultimate goal of drug delivery, which is to effectively recreate the natural mechanisms and profiles of compounds in the body. We have designed recognitive polymers for small compounds by using molecular imprinting. By interaction of the biologically significant molecule with functional monomers during the polymerization reaction, specific sites for the molecule were created. As a result of hydrogen bonding, use of long chain poly(ethylene glycol) dimethacrylate cross-linking agents with 2-hydroxyethyl methacrylate-based networks and optimization of template concentrations during polymerization, increased affinity for D-glucose and 279% selective uptake was achieved for the molecule over enantiomer D-galactose. Increased functional site density by the use of 31 arm poly(ethylene glycol) star polymer networks cross-linked with dimethacrylates resulted in up to 313% selectivity for D-glucose over D-fructose. Investigation into the polymerization reaction and material properties showed increased stability during the reaction and increased strength as a result of the presence of the template. Possible applications include modulated drug delivery devices and biosensors.
Degree
Ph.D.
Advisors
Peppas, Purdue University.
Subject Area
Chemical engineering|Polymer chemistry
Off-Campus Purdue Users:
To access this dissertation, please log in to our
proxy server.