In a pandemic, such as the one caused by the coronavirus in 2020, fast action is required to provide insights into the disease mechanisms and to find potential drug targets to slow the progress of the disease and lower mortality. We developed CoVex, an interactive online platform for the exploration of the SARS-CoV-2 host interactome and the identification of drug candidates. CoVex integrates the virus-human protein interactions, human protein-protein interactions, and drug-target interactions, and allows for visual exploration of the data. The exploration is guided by network-based systems medicine algorithms that enable the assembly of ranked lists of candidates for already approved drugs. Unlike novel drugs, approved drugs have the advantage that most of their side effects and contraindications are known. Additionally, they are already available and can be distributed quickly, which makes them promising candidates to stop the uncontrolled spread of the disease early. CoVex is an example of how this could be achieved in future pandemics and provides valuable lessons on what is required in such a situation to maximize the potential of computational approaches that can significantly speed up drug discovery.