Systems biology is highly complex, and our understanding of it is still in the early stages. By looking at biochemical pathways, including metabolic and signaling pathways and gene regulatory networks, researchers can learn more about drug mechanisms at a molecular level. The challenge for systems biologists is to identify critical disease pathways and discover both on-and off-target effects of compounds. The concept of a linear drug discovery and development path is being replaced by more iterative and parallel processes. Knowledge gained on a systems level is applied at various points along the continuum.
The dynamic nature of biology is not easily modeled. The ultimate goal of systems biology analysis is the ability to simulate biological systems and thus predict the outcomes of specific perturbations. By combining disparate types of data and interpreting changes in genes, proteins, and metabolites on a cellular level, researchers hope to be able to provide a more definitive means of diagnosis and develop drugs that can act very specifically on disease outcome. With a computational approach, a pathway can be connected with a clinical endpoint and a small molecule drug. Researchers hope this will create predictive medicine that should improve the process of drug development and increase the number of efficacious compounds.
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