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].
Sayali Pagire*
Aadesh Varpe
Om Ugalmugale
Aditya Vighne
10.5281/zenodo.17444647