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The Mouse Lives Longer
A recent paper, by author Dr. P. M. Darbyshire, shows how complex mathematical models describing tumour growth dynamics can be numerically solved in a fraction of the time of standard computational methods.
By Paul Darbyshire
Dec. 12, 2015

Developments in supercomputing and parallel processing technologies are paving the way for in silico experiments to take up the challenge of aiding in a curefor cancer outside of thelaboratory.

In the last decade in silico experiments focussed on simulating the different processes of solid tumour growth have become more readily accepted by the clinical and oncology community. A recent paper, by author Dr.P. M. Darbyshire, shows how complex mathematical models describing tumour growth dynamics can be numerically solved in a fraction of the time of standardcomputational methods.

“Progress in the understanding of tumour growth and cancer development has largely been driven by biological and clinical observations through in vitroand in vivoexperiments. When challenged with more complex cellular and biological systems, for example in studying the processes of angiogenesis in breast cancer or vascular brain tumours, the need for advanced computational techniques is paramount”, said Darbyshire.

It is envisaged that in-silico experiments and simulations, such as those being developedby Dr. Darbyshire and his team, will eventuallyprovide researchers, clinicians and oncologists with the tools and opportunity to observe effects of different treatments on cancers cells in realistic time frames. The challenging issues of cancer prevention and cure lie in the need for a more detailed knowledge of the dynamic processes and mechanisms of cellular behaviour and tumour growth dynamics. Rapid numerical solutions to such models and biological systems can greatly facilitate the role of clinicians and oncologists by performing time-saving in-silico experiments that have the potential to highlight new cancer treatments and therapies, outside of the laboratory.

Indeed, in the laboratory, mice will usually only live for two to three years despite the best efforts of the Methuselah Mouse Prize; a competition to breed or engineer extremely long-lived laboratory mice.Although our understanding of cancer and the effects of anti-cancer drugs and chemotherapy have been greatly advanced through animal testing, simulating realistic virtual environments with advanced computationaltechniquescan greatly reduce the need for unnecessary laboratory experiments.Consider, for example, the case of a particular cancer that is assumed to be in remission?This can last for several years without signs of reoccurrence even though the patient may still be undergoing regular check-ups and in some cases continued low-level treatment. Such a situation is clearly difficult, if not impossible, to replicate and monitorin a mouse with only a short longevity. “Acomputer mouse, however, most certainlylives longer,” Darbyshire said.In addition, post treatment in silico experiments can develop with the patient’s condition and track their progress continually whilst being able to detect signs of the re-emergence of cancer almost instantly. With the continued development of new and innovative uses of supercomputing technologies, such personalised medical care is fast becoming a reality.

Darbyshire and his team are already developingmore advanced numerical solutions to complex biological models of tumour dynamics and future work will involve incorporating fluidflowinto3D tumour models in order to understand in more detail the biological implications for tumour growth, invasion and metastasiswhilst helping to identify patient-enhancedtargeted treatment strategies.

Dr P. M. Darbyshire is Technical Director, Computational Biophysics Group, Algenet Cancer Research, Nottingham. UK.

Paper:
Performance Optimisations for a Numerical Solution to a 3D Model of Tumour-Induced Angiogenesis on a Parallel Programming Platform. doi: 10.11648/j.cb.20150303.11.

Paper link:
http://www.sciencepublishinggroup.com/journal/paperinfo?journalid=111&doi=10.11648/j.cb.20150303.11

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