Despite technological advances, the conventional process of drug discovery and development still shows limited therapeutic efficacy. To date, we only partially understand disease pathophysiology, we see an overall deficiency in developing therapeutics that target overlapping dysregulated pathways, and the choice of therapeutically irrelevant drug targets.
A key difficulty lies in mining and interpretation of an ever-growing and overwhelming wealth of diverse data — data, that is disparate from global, systemic approaches with an increased granularity of evidence. A subsequent challenge is to determine the relative importance of different pieces of evidence when combining all the available information to suggest promising, sensible targets for drug discovery. Given the latest advances in AI, this enormous task can now be pursued.
Join this webinar to hear and see Irina giving some examples on such target characterization.