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Prediction and validation of diffusion coefficients in a model drug delivery system using microsecond atomistic molecular dynamics simulation and vapour sorption analysis

Authors :
Yossef A. Elabd
Christopher Forrey
Eric M. Davis
Joshua S. Silverstein
Jack F. Douglas
David M. Saylor
Source :
Soft Matter. 10:7480-7494
Publication Year :
2014
Publisher :
Royal Society of Chemistry (RSC), 2014.

Abstract

Diffusion of small to medium sized molecules in polymeric medical device materials underlies a broad range of public health concerns related to unintended leaching from or uptake into implantable medical devices. However, obtaining accurate diffusion coefficients for such systems at physiological temperature represents a formidable challenge, both experimentally and computationally. While molecular dynamics simulation has been used to accurately predict the diffusion coefficients, D, of a handful of gases in various polymers, this success has not been extended to molecules larger than gases, e.g., condensable vapours, liquids, and drugs. We present atomistic molecular dynamics simulation predictions of diffusion in a model drug eluting system that represent a dramatic improvement in accuracy compared to previous simulation predictions for comparable systems. We find that, for simulations of insufficient duration, sub-diffusive dynamics can lead to dramatic over-prediction of D. We present useful metrics for monitoring the extent of sub-diffusive dynamics and explore how these metrics correlate to error in D. We also identify a relationship between diffusion and fast dynamics in our system, which may serve as a means to more rapidly predict diffusion in slowly diffusing systems. Our work provides important precedent and essential insights for utilizing atomistic molecular dynamics simulations to predict diffusion coefficients of small to medium sized molecules in condensed soft matter systems.

Details

ISSN :
17446848 and 1744683X
Volume :
10
Database :
OpenAIRE
Journal :
Soft Matter
Accession number :
edsair.doi.dedup.....28218ab1f9021f1e26ac6fcb80806ef6
Full Text :
https://doi.org/10.1039/c4sm01297f