Graduation Year

2005

Document Type

Dissertation

Degree

Ph.D.

Degree Granting Department

Chemical Engineering

Major Professor

Richard Gilbert, Ph.D.

Co-Major Professor

Mark Jaraszeski, Ph.D.

Committee Member

Scott Campbell, Ph.D.

Committee Member

Richard Heller, Ph.D.

Committee Member

Andrew M. Hoff, Ph.D.

Keywords

Molecular delivery, Electrogenetherapy, Electrochemotherapy, Electroporation, Electrophoresis, Mathematical model, Tissue, Agarose gel

Abstract

Electroporation is a methodology for the introduction of drugs and genes into cells. This technique works by reducing the exclusionary nature of the cell membrane [125, 129, 186, 189]. Electroporation has successfully been used in electrochemotherapy and electrogenetherapy [57, 68, 86, 87, 110, 112, 131]. The two major components of electroporation are an induced transmembrane potential and the motion of the deliverable through a compromised cell membrane into the target cell [38, 55, 62, 114, 131]. These two components are both dependent on the electrophoretic motion of charged species in an applied electric field [45, 64, 75, 77, 177].

Currently, the methods outlined for understanding electroporation have been focused on either a phenomenological perspective, e.g. what works, or modeling the electric field strength in certain regions [12, 56, 87, 129, 146, 204, 205]. While this information is necessary for the clinician and the laboratory scientist, it doesn’t expand the understanding of how electric field mediated drug and gene delivery works or EFMDGD. To increase the understanding of EFMDGD, new models are required that predict the motion of ions and deliverables through tissues to target areas [75, 77].

This document examines the design and creation of an electric field mediated drug and gene delivery model, EFMDGDM. Two example scenarios, ionic motion in tissues and gel electrophoresis, are examined in depth using the EFMDGDM. The model requires tuning for each scenario but only utilizes experimental parameters and one tunable parameter that is computed from regressed experimental data. The EFMDGDM successfully describes the two examples.

Future work will incorporate the EFMDGDM as the backbone of an electric field mediated drug and gene delivery modeling package, EFMDGDMP. This modeling software package will be optimized to assist clinicians and scientists in the selection of electric field signatures for the delivery of drugs and genes. By utilizing a software package that fully describes the motion of ions and molecules in and around either in vitro or in vivo cell systems improved delivery could be accomplished.

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