Year: 2025
Type: article
Abstract: Generative AI is revolutionizing drug discovery by drastically shortening the traditionally lengthy and costly development process. By leveraging advanced machine learning techniques like Variational Autoencoders, Generative Adversarial Networks, and reinforcement learning, AI systems can design novel therapeutic molecules with desired properties before synthesis occurs in the lab. These technologies enable pharmaceutical researchers to efficiently navigate the vast chemical space of potential drugs, simultaneously optimize for multiple molecular properties, create entirely new chemical structures, repurpose existing medications, and potentially reduce clinical failure rates. Integrating AI approaches with traditional drug discovery methods promises to accelerate innovation in therapeutics, particularly for diseases with significant unmet medical needs. It may fundamentally transform how new medicines reach patients in need.
Author: Bhavyateja Potineni
Institution: Genentech
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409797631