Modelling of Implantable Drug Delivery System in Tumor Microenvironment Using Molecular Communication Paradigm

Al-Zu'Bi, MM; Mohan, AS

Modelling of Implantable Drug Delivery System in Tumor Microenvironment Using Molecular Communication Paradigm

Al-Zu'Bi, MM Mohan, AS

Permalink

Publication Type:: Journal Article
Citation:: IEEE Access, 2019, 7 pp. 141929 - 141940
Issue Date:: 2019-01-01

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download Published VersionAdobe PDF (6.02 MB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Al-Zu'Bi, MM	en_US
dc.contributor.author	Mohan, AS https://orcid.org/0000-0002-4503-5851	en_US
dc.date.issued	2019-01-01	en_US
dc.identifier.citation	IEEE Access, 2019, 7 pp. 141929 - 141940	en_US
dc.identifier.uri	http://hdl.handle.net/10453/138491
dc.description.abstract	© 2013 IEEE. Local delivery of anticancer drug in tumor using miniaturized implants over a prolonged period of time is a powerful treatment strategy that provides lower toxicity and higher drug bioavailability compared to conventional systemic chemotherapy. Prediction of anticancer drug distribution in tumor following implantation of the drug implant is necessary to improve and optimize the implantable drug delivery systems (IDDSs). In this paper, we develop mathematical and stochastic simulation models for the prediction of spatiotemporal concentration of anticancer doxorubicin following implantation of a dual-release implant in an isolated tumor microenvironment (TME). Our model utilizes mathematical convolution of the channel impulse response (CIR) with the drug release function based on the abstraction of molecular communication. The derived CIR can be used to obtain drug concentration profile in the surrounding tissue for various release profiles and different anticancer drugs. We derive closed-form analytical expression for anticancer drug concentration. The required release rates are obtained by fitting the experimental data on dual-release implant available in the literature to a mathematical expression. In addition, we also present a particle-based stochastic simulator and compare the results with those predicted by the analytical model. The accuracy of predictions by both the models is further verified by comparing with the published experimental data in the literature. Both the proposed models can be useful for the design optimization of the implantable drug delivery systems (IDDSs) in tumors and other tissues and can potentially reduce the number of animal experiments thus saving cost and time.	en_US
dc.relation.ispartof	IEEE Access	en_US
dc.relation.isbasedon	10.1109/ACCESS.2019.2944257	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.title	Modelling of Implantable Drug Delivery System in Tumor Microenvironment Using Molecular Communication Paradigm	en_US
dc.type	Journal Article
utslib.citation.volume	7	en_US
utslib.for	08 Information and Computing Sciences	en_US
utslib.for	09 Engineering	en_US
utslib.for	10 Technology	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Biomedical Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CHT - Health Technologies
utslib.copyright.status	open_access	*
pubs.publication-status	Published	en_US
pubs.volume	7	en_US

Abstract:

© 2013 IEEE. Local delivery of anticancer drug in tumor using miniaturized implants over a prolonged period of time is a powerful treatment strategy that provides lower toxicity and higher drug bioavailability compared to conventional systemic chemotherapy. Prediction of anticancer drug distribution in tumor following implantation of the drug implant is necessary to improve and optimize the implantable drug delivery systems (IDDSs). In this paper, we develop mathematical and stochastic simulation models for the prediction of spatiotemporal concentration of anticancer doxorubicin following implantation of a dual-release implant in an isolated tumor microenvironment (TME). Our model utilizes mathematical convolution of the channel impulse response (CIR) with the drug release function based on the abstraction of molecular communication. The derived CIR can be used to obtain drug concentration profile in the surrounding tissue for various release profiles and different anticancer drugs. We derive closed-form analytical expression for anticancer drug concentration. The required release rates are obtained by fitting the experimental data on dual-release implant available in the literature to a mathematical expression. In addition, we also present a particle-based stochastic simulator and compare the results with those predicted by the analytical model. The accuracy of predictions by both the models is further verified by comparing with the published experimental data in the literature. Both the proposed models can be useful for the design optimization of the implantable drug delivery systems (IDDSs) in tumors and other tissues and can potentially reduce the number of animal experiments thus saving cost and time.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/138491