Artificial intelligence (AI) is transforming drug development by improving precision, decreasing timelines and costs, and enabling AI-powered drug design. This paper examines current advances in deep generative models (DGMs) for de novo drug creation, including various techniques and their tremendous influence. It critically examines the issues that are inextricably linked to these technologies, providing methods to realize their full potential. It includes case studies of both triumphs and failures in moving medicines to clinical trials using AI. Finally, it presents a forwardlooking strategy for optimizing, DGMs in de novo drug design, resulting in speedier and more cost-effective drug development.
Artificial intelligence (AI), Drug Discovery, improving precision, decreasing timelines and costs, and enabling AI-powered drug design
Drug Discovery
In recent years, there has been a lot of interest in medicinal chemistry's application of artificial intelligence (AI) as a potential way to transform the pharmaceutical sector. [1] The process of finding and creating new drugs, or drug discovery, is a difficult and drawn-out undertaking that has historically relied on time-consuming methods like high-throughput screening and trial-and-error testing. However, by making it possible to analyze vast volumes of data more accurately and efficiently, artificial intelligence (AI) techniques like machine learning (ML) and natural language processing have the potential to speed up and enhance this process [2]. The scientists recently revealed the successful application of deep learning (DL) to accurately predict the potency of medicinal molecules. [3] . The toxicity of potential medications has also been predicted by AIbased techniques [4]. These and other studies have demonstrated AI's potential to increase the efficacy and efficiency of drug discovery procedures. But there are drawbacks and restrictions to using AI to create novel bioactive chemicals. To completely comprehend the benefits and limitations of AI in this field, more research is required, and ethical considerations must be taken into account. Notwithstanding these obstacles, it is anticipated that AI will play a major role in the creation of novel drugs and treatments during the coming years. [6].
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Sayali Pagire
Corresponding author
Pharmaceutics, SND college of pharmacy, Babhulgaon
Aadesh Varpe
Co-author
Pharmaceutics, SND college of pharmacy, Babhulgaon
Om Ugalmugale
Co-author
Pharmaceutics, SND college of pharmacy, Babhulgaon
Aditya Vighne
Co-author
Pharmaceutics, SND college of pharmacy, Babhulgaon
Aadesh Varpe, Om Ugalmugale, Sayali Pagire*, Aditya Vighne, Artificial Intelligence in Drug Discovery, Int. J. Sci. R. Tech., 2025, 2 (10), 435-444. https://doi.org/10.5281/zenodo.17444647
10.5281/zenodo.17444647