  Network science is already making an impact on the study of complex systems
and offers a promising variety of tools to understand their formation and
evolution (1-4) in many disparate fields from large communication networks
(5,6), transportation infrastructures (7) and social communities (8,9) to
biological systems (1,10,11). Even though new highthroughput technologies have
rapidly been generating large amounts of genomic data, drug design has not
followed the same development, and it is still complicated and expensive to
develop new single-target drugs. Nevertheless, recent approaches suggest that
multi-target drug design combined with a network-dependent approach and
large-scale systems-oriented strategies (12-14) create a promising framework to
combat complex multigenetic disorders like cancer or diabetes. Here, we
investigate the human network corresponding to the interactions between all US
approved drugs and human therapies, defined by known drug-therapy
relationships. Our results show that the key paths in this network are shorter
than three steps, indicating that distant therapies are separated by a
surprisingly low number of chemical compounds. We also identify a sub-network
composed by drugs with high centrality measures (15), which represent the
structural back-bone of the drug-therapy system and act as hubs routing
information between distant parts of the network. These findings provide for
the first time a global map of the largescale organization of all known drugs
and associated therapies, bringing new insights on possible strategies for
future drug development. Special attention should be given to drugs which
combine the two properties of (a) having a high centrality value and (b) acting
on multiple targets.
