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Systems medicine approach to drug discovery

Complex diseases pose a challenge to the current drug development strategies. Researchers from different European institutions and companies teamed up to produce an innovative approach to identify putative drug therapies.


The pathobiology of complex diseases involves various mechanisms and pathways, and can be best resolved by using combination therapies to target each distinct pathway. In this scenario, computational models adopting a systems perspective and integrating the knowledge generated by omics technologies and clinical data could prove useful. Multiple sclerosis (MS) is a complex autoimmune disease that targets the nervous system. However, current therapies for MS are far from effective, at least in part because they target only part of the immune response. Scientists on the EU-funded COMBIMS (A novel drug discovery method based on systems biology: combination therapy and biomarkers for multiple sclerosis) project set out to understand the biological networks involved in MS and how current MS therapies affect these networks. In this context, they employed a systems biology approach to develop more effective combination therapies. Using proteomics, the consortium measured biological facets of the immune cells involved in signal transmission and compared them to healthy cells. They examined the pathogenic changes and the response to selected therapies in primary cells isolated from patients to define the molecular signature of clinical phenotypes. Computational modelling techniques were utilised to represent the phosphorylation networks and pathways as well as genotypes involved in MS. This model generated a list of 33 potential drug combinations that met the criteria of synergy and included combinations of current therapies with non-MS drugs. Suitable algorithms were then used to determine safety issues and the possible side effects associated with these drugs. They also tested these drug combinations in animals and generated promising results. Additional dynamic models suitable for different MS subtypes were generated alongside models that recapitulate the interaction between the immune system and the central nervous system. The COMBIMS consortium demonstrated the ability to predict novel therapeutic approaches for complex and less complex diseases via a systems medicine approach. Apart from the direct therapeutic benefits for MS patients, incorporation of this technology into the pharmaceutical industry could improve the drug discovery process.


Systems medicine, drug discovery, multiple sclerosis, proteomics, immune system

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