The development of deep learning neural networks and their variants with the corresponding increase in chemical data has resulted in a paradigm shift in information mining pertaining to the chemical space. The artificial intelligence approach has enabled the development of drug candidates in a more structured and economical manner and within a considerably shorter time period. The computational resources and algorithms in the drug discovery process utilize existing data to provide better analytics and assessment, from identifying a drug candidate to the pharmaceutical industry’s manufacturing process
The quantitative structure–activity relationship.
Deep learning (DL)based programme that utilizes CNN methodology for screening compounds against the desired target Convolutional Neural Networks (CNN) Generative model for SMILES (QSAR) QSAR model built with …..used to predict the biological activity of the chemical compounds