ABSTRACT

Why are pharmaceutical companies embracing translational medi-

cine (TM)? The answer is mainly because it is practical; they

must increase productivity and remain competitive. Drug develop-

ers seeking to improve R&D productivity are pursuing extrinsic

strategies, which include mergers and acquisitions, partnerships,

and licensing. At the same time they are looking to implement

intrinsic strategies, such as deciding which disease areas to pursue

through portfolio optimization, integration of tools, technologies,

approaches to development, and selection of appropriate mile-

stones. Companies need to make better decisions about what

targets to pursue, when and how to terminate specific development

programs, how to efficiently allocate resources, and what type of

development portfolio to build. Although many traditional drug

development approaches still have utility, they likely won’t produce

drug candidates at the pace the industry needs [1]. For one thing, the

medical information and research literature is so diverse, sometimes

contradictory, and becomes obsolete so fast that using it to assess

the commercial prospects of a medical product are generally confus-

ing, sometimes erroneous, and potentially dangerous. Translational

science, especially in medicine, is providing a better way to identify

promising molecules earlier in drug development by establishing

the drug’s risk/benefit profile earlier, for example, through the use

of biomarkers or better animal-to-human models [2]. In recent

years, all major pharmaceutical companies have implemented TM

activities in tandem with their traditional drug discovery and

development schemes. The mission of this new entity, which is

different from TM as an academic discipline, is simply to improve

predictability of the potential success of compounds as they transit

through the different stages of drug development toward fulfilling

a medical benefit [3]. While the mission of TM for industry is more

intensely and narrowly focused than it is for academia, industry is

motivated by much the same drivers and uses the same basic tools

as the academic discipline.