World Journal of
Pharmaceutical and Life Sciences

COGNISYNTH: AI-POWERED MOLECULAR CREATIVITY IN DE NOVO DRUG DESIGN

Bhaskar Vaitla*, Rama Prasanth Reddy Satti, Savithri Devi Vasa and Sravanthi Kurupudi

ABSTRACT

This article presents a comprehensive overview of an AI-driven methodological framework for de novo drug design, emphasizing its transformative impact on modern pharmaceutical innovation. By uniting retrosynthetic analysis with predictive pharmacokinetic/pharmacodynamic modeling, artificial intelligence enables rapid, data-informed generation of novel drug candidates. The framework also integrates virtual screening and molecular docking, facilitating efficient lead identification and optimization within expansive chemical spaces. Key AI models, including deep learning architectures and reinforcement algorithms, are highlighted for their role in enhancing molecular accuracy and clinical relevance. Beyond technological advancement, the manuscript critically examines the challenges of data integrity, algorithmic transparency, and ethical deployment. It also underscores the importance of regulatory adaptation to support responsible AI use in drug discovery. This synergistic approach signifies a shift from supportive computation to intelligent collaboration, reshaping how therapeutic molecules are designed, evaluated, and delivered.

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