title: A Drug-Centric View of Drug Development: How Drugs Spread from Disease to Disease.
abstract: Drugs are often seen as ancillary to the purpose of fighting diseases. Here an alternative view is proposed in which they occupy a spearheading role. In this view, drugs are technologies with an inherent therapeutic potential. Once created, they can spread from disease to disease independently of the drug creator's original intentions. Through the analysis of extensive literature and clinical trial records, it can be observed that successful drugs follow a life cycle in which they are studied at an increasing rate, and for the treatment of an increasing number of diseases, leading to clinical advancement. Such initial growth, following a power law on average, has a degree of momentum, but eventually decelerates, leading to stagnation and decay. A network model can describe the propagation of drugs from disease to disease in which diseases communicate with each other by receiving and sending drugs. Within this model, some diseases appear more prone to influence other diseases than be influenced, and vice versa. Diseases can also be organized into a drug-centric disease taxonomy based on the drugs that each adopts. This taxonomy reflects not only biological similarities across diseases, but also the level of differentiation of existing therapies. In sum, this study shows that drugs can become contagious technologies playing a driving role in the fight against disease. By better understanding such dynamics, pharmaceutical developers may be able to manage drug projects more effectively.
authors.affiliation: Roche Pharmaceutical Research and Early Development, pRED Informatics, Roche Innovation Center, Basel, Switzerland.
authors.forename: Raul
authors.initials: R
authors.lastname: Rodriguez-Esteban
mesh_terms: D002986:Clinical Trials as Topic; D019295:Computational Biology; D062313:Databases, Pharmaceutical; D004194:Disease / Q000145:classification; D055808:Drug Discovery / Q000639:trends; D004358:Drug Therapy / Q000639:trends; D006801:Humans; D008954:Models, Biological