Oncology scientist, Dr Kevin Hicks is a senior research fellow in the world-renowned Auckland Cancer Society Research Centre (ACSRC) at the University of Auckland.
He is the principal scientist in a team that has just won a $773913 Marsden grant to research agent-based modelling of drug and radiation action in tumours.
Failure rates during clinical development of new anti-cancer agents are very high, leading to requests for more collaboration between computational scientists and biologists to develop mechanistic models of cancer growth and therapy, says Dr Hicks.
One reason for slow progress in anti-cancer drug development is the failure to take into account the three dimensional structure of tumours. Most drugs are tested in tissue culture using single cells or cell monolayers, but these do not represent critically important changes in cell physiology due to the position in the tumour.
Dr Hicks and his research team have already developed a model which explicitly incorporates drug transport and have demonstrated that they can predict anti-tumour activity of hypoxia activated prodrugs in tumours. (Hypoxia is very low oxygen concentrations; in this case, in some parts of the tumour).
“The Marsden grant will help us extend the modelling work that has already proved successful in guiding anti-cancer drug development,” says Dr Hicks. “In particular, it will be extended to include the time dependence of drug and radiation effects, and the consequences for tumour growth.”
To achieve this Dr Hicks and Professor Bill Wilson from the ACSRC have teamed up with senior scientist Dr Gib Bogle at the Auckland Bioengineering Institute, (that leads the world in developing computer models of organs such as the heart).
Together they will “develop a model of growth of multicellular tumour spheroids which are three dimensional cell cultures used for investigating drug and radiation effects”, says Dr Hicks.
Using agent-based modelling, “the effect of treatment on each individual cell can be simulated and individual cell fates followed as it responds probabilistically to its environment”, says Dr Bogle.
“This is particularly important for modelling mixtures of sensitive and resistant cells, commonly found in tumours” says Dr Hicks.
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