NDLI: A hybrid cellular automaton model of bioreductive drug transportation with protein binding

Content Provider	IEEE Xplore Digital Library
Author	Kazmi, N. Hossain, M. A. Phillips, R.
Copyright Year	2011
Description	Author affiliation: School of Computing, Engineering and Information Sciences, Northumbria University, NE1 8ST, UK (Hossain, M. A.) \|\| School of Computing, Informatics and Media, University of Bradford, Bradford, BD7 1DP, UK (Kazmi, N.) \|\| Institute of Cancer Therapeutics, University of Bradford, Bradford, BD7 1DP, UK (Phillips, R.) Drug binding to its surrounding proteins is known as a resistive factor towards effective drug penetration that reduces the diffusing drug concentration inside the tumour. This drug reduction fails to remove tumour mass completely and becomes one cause of treatment failure and tumour recurrence. Various mathematical models have been developed to calculate bioreductive drug (particularly, tirapazamine) characteristics by assessing in-vitro and in-vivo experimental results. So far, no attempt has been reported that practices a computerized model to discover tirapazamine (TPZ) transport under the influence of protein binding inside the solid tumour and at cellular level. This paper presents an investigation into the development of an in-silico model that mimics the behavior of heterogeneous tumour mass towards its treatment with TPZ. An artificial Neural Network model is proposed demonstrate the dynamics of tumour growth model. The model is implemented through a set of experiments based on clinical and reported data. The model is used to monitor the influence of surrounding proteins on TPZ cytotoxicity, concentrations and metabolism at cellular level and demonstrated these impacts on tumour morphology and hypoxic cells survival fractions. The results showed no/less cytotoxicity for cells located at the most distal locations from the source (blood vessel) of drug supply. These results suggested that the impaired drug transport is the main cause of solid cancer treatment failure.
Starting Page	1
Ending Page	6
File Size	1219442
Page Count	6
File Format	PDF
ISBN	9781467302470
e-ISBN	9781467302487
DOI	10.1109/SKIMA.2011.6089973
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-09-08
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Drugs Solid modeling Computational modeling Biological system modeling Cytotoxicity Metabolism Proteins Automaton Model Solids Hypoxia Tirapazamine Tumors Protein binding
Content Type	Text
Resource Type	Article

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