An innovative approach to analyze the complexity of translating novel molecular
entities and nanomaterials into pharmaceutical alternatives (i.e., knowledge translation, KT)
is discussed. First, some key concepts on the organization and translation of the biomedical
knowledge (paradigms, homophily, power law distributions, hierarchy, modularity, and research
fronts) are reviewed. Then, we propose a model for the knowledge translation (KT)
in Drug Discovery that considers the complexity of interdisciplinary communication.
Specifically, we address two highly relevant aspects: 1) A successful KT requires the
emergence of organized bodies of inter-and transdisciplinary research, and 2) The hierarchical
and modular topological organization of these bodies of knowledge. We focused on
a set of previously-published studies on KT which rely on a combination of network analysis
and computer-assisted analysis of the contents of scientific literature and patents. The
selected studies provide a duo of complementary perspectives: the demand of knowledge
(cervical cancer and Ebola hemorrhagic fever) and the supply of knowledge (liposomes
and nanoparticles to treat cancer and the paradigmatic Doxil, the first nano- drug to be approved).