Session Speaker

Bioinformatic approaches to signaling/metabolic pathways analysis: crucial tools for novel therapeutic design
Stuart R. Maudsley
USA

Disease development, progression and therapeutic intervention are highly complex biological traits that involve a vast array of networks of intertwined self- and cross-regulating physiological systems at both a molecular and systemic level. In addition to their static complexity, it is also highly likely that pathophysiological processes or drug actions in that process are also temporally plastic and pleiotropic. Despite such daunting predictions of insurmountable complexity, gaining a deeper understanding of these intricate systems could potentially yield vital information for novel therapeutic design. The control of complex signaling events at the cellular or gross physiological level has for long posed a great difficulty for multi-pathway systems analyses. Gaining a comprehensive understanding of disease processes or drug responses is highly desirable for therapeutic design with respect to enhancing efficacy and selectivity, while minimizing off-target actions and side-effects. Systems-level investigational approaches to the functional interface between pathophysiology and endogenous biologically-responsive systems could potentially become the norm for future therapeutic investigations. Current advances in genomic and proteomic technologies, and their combined use, has allowed the research community to generate highly informative and comprehensive datasets with respect to complex multi-level hormone and signaling activities in physiological systems. Functional annotation of large datasets and trans-dataset analyses facilitates greater experiment to experiment correlation, and also provides a more accurate and reliable dataset description and disease etiology prediction. In order to generate more rationally designed therapeutics, a marriage of systems-level understanding of both disease pathophysiology and drug response networks may present a promising and effective approach for the treatment of complex pathophysiology.