In recent years, artificial intelligence (AI) in the pharmaceutical industry has gained significant traction, especially in the drug discovery field, as this technology can identify and develop new medications, helping AI researchers and pharmaceutical scientists eliminate the traditional and labor-intensive techniques of trial-and-error experimentation and high-throughput screening. The successful application of AI techniques and their subsets, such as machine learning (ML) and natural language processing (NLP), also offers the potential to accelerate and improve the conventional method of accurate data analysis for large data sets. AI and ML-based methods such as deep learning (DL) predict the efficacy of drug compounds to understand the accrual and target audience of drug use.