Almost every day brings news of an apparent breakthrough against cancer, infectious diseases, or metabolic conditions like diabetes, but these rarely translate into effective therapies or drugs, and even if they do clinical development usually takes well over a decade.
One reason is that medical research is conducted in highly fragmented groups focusing on specific pathways or components leading to drugs that turn out not to work properly or to have dangerous side effects after cycles of animal and then clinical testing in humans. This process is expensive and wasteful, resulting from the fact that at present researchers lack tools to assess in advance how candidate drugs work across the human's whole biological system. The discipline of systems biology represents an attempt to unite the medical research community behind a common approach to understanding and modelling the complex interactions of the human, leading to more effective and faster drug development.
Europe is now at the forefront of this growing movement that brings together a number of disciplines including mathematics, physics, statistics, bioinformatics, genetics and all the "omics" technologies dealing with genes, proteins, and biological pathways. Earlier this year leading specialists in systems biology met at an important conference organised jointly by the European Science Foundation and the University of Barcelona, providing a snapshot of current progress and a roadmap for future research.
The conference provided a platform to direct and accelerate other ongoing programmes in which the emerging tools of systems biology are being applied to specific areas of medicine, notably the SBMS (Systems Biology to combat Metabolic Syndrome) initiative. Metabolic syndrome is the term for various conditions that can lead to diseases such as type 2 diabetes where cells of the body develop resistance against insulin, impairing the regulation of blood glucose levels. The aim of SBMS is to understand the molecular and cellular systems that underlie risk factors associated with various diseases resulting from metabolic syndrome, by studying them at a systems wide level rather than focusing on individual specific components even when these appear to play a central role.