Genentech, USA.
World Journal of Advanced Engineering Technology and Sciences, 2025, 15(01), 1784-1794
Article DOI: 10.30574/wjaets.2025.15.1.0298
Received on 01 March 2025; revised on 08 April 2025; accepted on 11 April 2025
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.
Artificial Intelligence; Molecular Design; Drug Development; Computational Chemistry; Therapeutic Innovation
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Bhavyateja Potineni. Generative AI in drug discovery: Accelerating the search for new therapeutics. World Journal of Advanced Engineering Technology and Sciences, 2025, 15(01), 1784-1794. Article DOI: https://doi.org/10.30574/wjaets.2025.15.1.298.