Since the time of the genomic revolution, networks have been key to understanding biology in health and disease. However, building networks and reconstructing disease pathways have always been a time-consuming and challenging processes. Artificial intelligence (AI) has been applied to nearly all aspects of drug development, including network construction and target identification.
By applying AI to these workflows, researchers can not only quickly and efficiently process the mountains of data generated from experimental analysis but also support confident, data-driven go/no-go decisions for greater success down the drug development pipeline. In this webinar, we discuss how companies can accelerate preclinical development, save time and money and speed time to market through AI.
Watch this on-demand webinar to learn: