Nicola Bellomo, Philip K.
Maini & Natasha Li Martin talk with
ScienceWatch.com and answer a few questions about
this month's New Hot Paper in the field of
Article Title: On the foundations of cancer
modelling: Selected topics, speculations, and
N;Li, NK;Maini, PK
Journal: MATH MODEL METHOD APPL SCI, Volume: 18, Issue: 4,
Page: 593-646, Year: APR 2008
* Politecn Turin, Dept Math, Corso Duca Abruzzi 24, I-10129
* Politecn Turin, Dept Math, I-10129 Turin, Italy.
* Math Inst, Ctr Math Biol, Oxford OX1 3LB, England.
* Oxford Ctr Integrat Syst Biol, Dept Biochem, Oxford OX1
Why do you think your paper is highly
It is becoming increasingly recognized that mathematical modelling may have
an important role to play in many biological systems. In the context of
disease, understanding cancer and developing treatment strategies is
obviously of great importance.
Mathematical modelling in this area has grown immensely as we strive to
develop a framework in which to interpret the enormous amount of
experimental data being generated. New mathematical methods have been
developed to capture aspects of the complexity of living matter, but many
important challenges lie ahead.
Indeed, the scientific community is becoming increasingly aware that the
great revolution of this century is going to be the mathematical
formalization of phenomena in the life sciences, much as the revolution of
the past two centuries was the development of the same approach in the
Does it describe a new discovery, methodology, or
synthesis of knowledge?
Philip K. Maini
Natasha Li Martin
This paper presents a review and critical analysis of some selected issues
related to the mathematical approach to the modelling of phenomena in
cancer, with the goal of introducing the technical challenges to a broad
range of applied mathematicians, armed with a wide variety of skills.
Particular attention is drawn to the multiscale aspects of the problem and
of the related mathematical approaches; strategies to select the correct
mathematical framework to deal with modelling at each scale; looking for
paradigms for the development of a mathematical biological theory related
to the complex system under consideration.
Would you summarize the significance of your paper
in layman's terms?
The aim of mathematics is to do for the life sciences what it did for
physics over the past two centuries. This paper extensively reviews the
relevant literature and sets out the mathematical problems that need to be
solved if we are to achieve this aim. It contains a preliminary attempt to
devise a biological mathematical theory.
How did you become involved in this research, and
were there any problems along the way?
The two senior authors have been involved in two consecutive large European
projects focused on the modelling of cancer phenomena and related
therapeutical actions. These projects, both directed by one of us, have
encouraged many more mathematicians from across Europe to move into this
Natasha Li Martin, at the time a Ph.D. student in Oxford, brought a great
deal of energy and enthusiasm, which was necessary for analyzing the 200
titles that have been reviewed in this paper.
Where do you see your research leading in the
Until now, cancer has been studied in terms of cellular growth, while
recent experimental research has increasingly focused on the crucial
underlying genetic and subcellular processes involved in tumor initiation.
The modelling approach must span the spatial scales, from genetic mutation
to tissue invasion, and must consider its dynamics in the context of an
ecological situation in which the population of tumor cells is in
competition with normal cells and the immune system.
Do you foresee any social or political implications
for your research?
It is clear that developing successful strategies for treating cancer will
have a huge impact on human health. Modelling and simulation of tumor
growth can play an important role in this.
It is true that mathematics alone cannot solve the problem of cancer.
However, applied mathematics may be able to provide a framework in which
experimental results can be interpreted, and a quantitative analysis of
external actions to control neoplastic growth can be developed.
Specifically, models and simulations can reduce the amount of
experimentation necessary for drug and therapy development. Moreover, the
mathematical theory developed might not only provide a detailed description
of the spatiotemporal evolution of the system, but also may help us
understand and manipulate aspects of the process that are difficult to
Nicola Bellomo, Ph.D.
Professor of Mathematical Physics and Applied Mathematics
Department of Mathematics
Facoltà di Ingegneria
Politecnico di Torino
Philip K. Maini, Ph.D.
Centre for Mathematical Biology
University of Oxford
Natasha Li Martin
Department of Social Medicine
University of Bristol
KEYWORDS: CANCER MODELLING; MULTISCALE MODELLING; COMPLEXITY IN
BIOLOGY; LIVING SYSTEMS.