While etiology and pathophysiology of most diseases are still poorly understood, there has never been a better time to fix this: Thore Bürgel (Pheiron) explains how they combine human genetics with multi-modal AI to resolve disease pathology, identify targets, and de-risk translation.

In drug discovery, excavating the right information about potential drug targets and molecules from the depths of the scientific literature is key to success in biotech. Large Language Models will change the nature of this game. Here is how, in three concrete examples.

Large Language Models are poised to become an indispensable tool for biotechs looking to find their ideal drug targets. Evidence-grounded LLMs can sift through millions of publications, finding highly specific pieces of evidence in seconds, unlocking overlooked drug target opportunities.

Data management at a biotech needs to work for everyone – from CEO’s courting investors to lab scientists designing the next experiment. Get it wrong and you’ll either need to put up with your system’s foibles or go through a painful migration to a new system.