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Updated: May 21, 2025

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
Published on: December 11, 2016
Artificial intelligence in anti-obesity drug discovery: unlocking next-generation therapeutics
Amit Gangwal1, Antonio Lavecchia2
1Department of Natural Product Chemistry, Shri Vile Parle Kelavani Mandal's Institute of Pharmacy, Dhule 424001 Maharashtra, India.
Abstract:
Obesity, a multifactorial disease linked to severe health risks, requires innovative treatments beyond lifestyle changes and current medications. Existing anti-obesity drugs face limitations regarding efficacy, side effects, weight regain and high costs. Artificial intelligence (AI) is emerging as a pivotal tool in drug discovery, expediting the identification of novel drug candidates and optimizing treatment strategies. This review examines AI's potential in developing next-generation anti-obesity therapeutics, with a focus on glucagon-like peptide-1 receptor agonists (GLP-1 RAs) and their role in discovering anti-obesity peptides. Additionally, it explores integration challenges and offers future perspectives on leveraging AI to reshape the landscape of anti-obesity drug discovery.
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