Tumours are highly dynamical diseases characterized by multiple scales ranging from molecular to macroscopic events. The complexity of the most recent clinical-genomic tumor-related data in the age of Molecular Medicine implies that biostatistics and even bioinformatics analyses are no more sufficient to cope with such data in order to explain them as well as to produce useful predictions.
Mechanistic models of biomedical phenomena with complex outputs must be built, in order to open the road for tailored therapies and to bridge the bench to the bedside.
This represents a huge challenge at the frontier of the contemporary mathematical modelling.
This workshop will gather top-level worldwide scientists, who work on the most advanced frontiers of mathematical oncologic sciences and who have a strong awareness of the biomedical problems, as well as some experimental and clinical scientists who, symmetrically, are particularly aware of (and trusting in) dynamics modelling in bio-medicine.
The Workshop will be held in Erice, Italy, at the "E. Majorana" Centre for Scientific Culture.
This is the 57th Workshop of the International School of Mathematics "G. Stampacchia", the first on Mathematical and Computational Oncology.
Here more scientific information on the aims of the workshop can be found..
The future of cancer treatment has a name: Molecular Medicine, a science based on three pillars. Two of them are evident in its very name: medical science and molecular biology. However, there is a general unawareness that Molecular Medicine is firmly based on a third, and equally important, pillar: Computational Biosciences. Currently this term mainly denotes Bioinformatics and Biostatistics, but with increasingly relevance in the next future it shall have to include (and in part it does nowadays include) the highly interacting complex of various old and new topics such as Biophysics, Systems Biology, Mathematical Oncology, and Theoretical Computer Science.
The data from Molecular Medicine are inherently complex and heterogeneous (e.g. clinical data, -omics data) but - which is their most important feature - they are inherently dynamics. Indeed, cancers are a family of dynamic diseases, endowed by multiple temporal and spatial scales, and their polymorphic macroscopic instances are emergent properties arising from a wide number of microscopic interplays at intracellular and inter-cellular level.
The complexity of these multi-scale data means that the natural language reasoning is unable to decipher them, but also that a static computational analysis, uniquely based on the static data mining and on model-unrelated time series analyses, is no more sufficient to cope with such data in order to explain them as well as to produce meaningful and useful predictions.
As a consequence, it is mandatory to try to build mechanistic models of biomedical phenomena with complex outputs, since it is this complexity which allows a deeper understanding of the "internal mechanisms" of each patient or class of patients, opening the road, we hope, for tailored therapies.
This represents a huge challenge at the frontier of the contemporary mathematical modelling, since the dynamic modelling in molecular medicine is what allows it to bridge the bench to the bedside, and in perspective it will be more and more instrumental to pass from the bedside to the cure of the patients.
The aim of this workshop is to gather top-level worldwide scientists, who work on the most advanced frontiers of mathematical oncologic sciences and who have a strong awareness of the biomedical problems, as well as some experimental and clinical scientists who, symmetrically, are particularly aware of (and trusting in) the relevance of the contribution of dynamics modelling in biology and medicine.
The workshop will cover topics such as systems biology, basic mechanisms of tumour growth and invasion, neoangiogenesis, interaction between immune system and tumours, pharmacokinetics and pharmacodynamics of anti-tumor agents, anticancer treatments and their optimization.
Moreover, great relevance will be given to the most recent mathematical methodologies.
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