Translational research is a continuum between clinical and basic research where the patient is the center of the research process. It brings clinical research to a starting point for the drug discovery process, permitting the generation of a more robust pathophysiological hypothesis essential for a better selection of drug targets and candidate optimization. It also establishes the basis of early proof for clinical concept studies, preferably in phase I, for which biomarkers and surrogate endpoints can often be used. Systems biology is a prerequisite approach to translational research where technologies and expertise are integrated and articulated to support efficient and productive realization of this concept. The first component of systems biology relies on omics-based technologies and integrates the changes in variables, such as genes, proteins and metabolites, into networks that are responsible for an organism's normal and diseased state. The second component of systems biology is in the domain of computational methods, where simulation and modeling create hypotheses of signaling pathways, transcription networks, physiological processes or even cell- or organism-based models. The simulations aim to show the origin of perturbations of the system that lead to pathological states and what treatment could be achieved to ameliorate or normalize the system. This review discusses how translational research and systems biology together could improve global understanding of drug targets, suggest new targets and approaches for therapeutics, and provide a deeper understanding of drug effects. Taken together, these types of analyses can lead to new therapeutic options while improving the safety and efficacy of new and existing medications.