Towards a more robust approach to selecting and prosecuting promising targets and compounds

There are many factors that influence predictivity in drug discovery and impact on productivity within the pharmaceutical industry. This article will concentrate on just two aspects; first, the role of investigating target modulation within a (human) disease setting, from target selection through screening to animal models, and second, potential developments in the analysis and probing of the chemical space appropriate for drug discovery and, in particular, steps to improve predictivity thus moving to a more forward-looking process. The activities associated with target selection should develop significantly over the next 5-10 years leading to a more robust association of target modulation with disease modification. In addition, better understanding of the opportunities for target modulators should drive and improve the selection of ligands suitable for therapeutic applications. Within these areas it will be important to move away from a retrospective consideration of druggable targets towards a forward-looking approach based on holistic (disease context) profiling of both (progressable) targets and subsequently their ligands. Improvements in the predictive analysis and probing of the chemical space will be needed to confront both safety and efficacy end points that currently remain major reasons for failure in the clinic. It is hoped that improvements in data visualization together with chemocentric mining of the literature will facilitate better interrogation of development and clinical data, potentially modifying research project plans to better address these key issues.