Generative AI in Cancer

Abstract

As early-onset cancer becomes increasingly common, the need for innovative therapeutic approaches in targeted therapy grows.Generative AI has emerged as a powerful tool for de novo drug design, offering the potential to create targeted therapies against challenging cancer driver mutations.These mutations, including TP53 , KRAS , and EGFR , often confer gain-of-function effects that drive cancer progression and are notoriously difficult to target due to their unique biochemical properties.This review summarizes the shift from conventional drug design towards newfound generative AI models, highlighting their ability to optimize binding affinity, anticancer properties, and generate novel molecules against previously "undruggable" targets.This review explores how generative AI is revolutionizing the fight against prevalent cancer driver mutations, paving the way for personalized and effective cancer treatments.

Ähnliche Arbeiten