Generalized linear models for in-vitro nanoparticle-cell interactions
Author
Çuhacı, Z. Gülce
Advisor
Dayanık, Savaş
Date
2013Publisher
Bilkent University
Language
English
Type
ThesisItem Usage Stats
74
views
views
34
downloads
downloads
Abstract
Nanomedicine techniques are quite promising in terms of treatment and detection of
cancerous cells. Targeted drug delivery plays an important role in this field of cancer
nanotechnology. A lot of studies have been conducted so far concerning nanoparticle
(NP)-cell interaction. Most of them fail to propose a mathematical model for a
quantitative prediction of cellular uptake rate with measurable accuracy. In this
thesis, we investigate cell-NP interactions and propose statistical models to predict
cellular uptake rate. Size, surface charge, chemical structure (type), concentration of
NPs and incubation time are known to affect the cellular uptake rate. Generalized
linear models are employed to explain the change in uptake rate with the
consideration of those effects and their interactions. The data set was obtained from
in-vitro NP-healthy cell experiments conducted by the Nanomedicine & Advanced
Technologies Research Center in Turkey. Statistical models predicting cellular uptake
rate are proposed for sphere-shaped Silica, polymethyl methacrylate (PMMA), and
polylactic acid (PLA) NPs.
Keywords
Nanomedicinenanoparticle-cell interaction
generalized linear models
logistic regression
splines