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Type: Journal article
Title: Prediction of size distribution of lipid -peptide -DNA vector particles using Monte Carlo simulation techniques
Author: Sarkar, S.
Zhang, H.
Levy, M.
Hart, S.
Hailes, H.
Tabor, A.
Shamlou, P.
Citation: Biotechnology and Applied Biochemistry, 2003; 38(1):95-102
Publisher: Portland Press
Issue Date: 2003
ISSN: 0885-4513
Statement of
Supti Sarkar, Hu Zhang, Susana M. Levy, Stephen L. Hart, Helen C. Hailes, Alethea B. Tabor and Parviz Ayazi Shamlou
Abstract: Concerns with insertional mutagenesis for retrovirus and immunogenicity for adenovirus have motivated research into development of non-viral vectors that can safely deliver desired gene constructs to target cells in tissues and organs. Many non-viral vectors suffer from unacceptably poor in vivo cell transfection and low transgene expression. Evidence suggests that cell transfection is linked to particle size - vector particles below about 200 nm are considered desirable. Experimental measurements indicate, however, that vector particles are susceptible to significant aggregation under most conditions of pH and ionic strength, including physiological conditions, although there are currently no means of predicting the kinetics of aggregation. The present paper addresses this challenge by presenting a mathematical framework based on the Monte Carlo simulation techniques for modelling the dynamics of aggregation. The approach is used to simulate the evolution of particle-size distribution for an integrin-targeting lipid-peptide-DNA vector system in buffers of different pH and ionic strength. The simulations required two input parameters, including the initial-size distribution of the particles and a fitting parameter (alpha). Comparison of simulations with experimental data showed that alpha was closely related to the zeta potential of the particles in the buffer medium, making simulations fully predictive. The modelling approach may be used in other vector systems.
Keywords: aggregation dynamics
lipid–peptide–DNA vector particles
Monte Carlo simulation
zeta potential.
DOI: 10.1042/BA20030073
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Chemical Engineering publications

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