RECENT ADVANCES IN AI-DRIVEN PHARMACEUTICAL CHEMISTRY AND DRUG DISCOVERY

Abstract

Artificial intelligence (AI) has emerged as a transformative force in pharmaceutical chemistry and drug discovery by fundamentally reshaping how therapeutic molecules are designed, optimized, and evaluated. Traditional drug discovery processes are highly complex, costly, and time-consuming, often requiring more than a decade and billions of dollars to bring a single drug to market. Moreover, high attrition rates during clinical development further reduce efficiency in conventional pipelines. AI technologies, including machine learning (ML), deep learning (DL), neural networks, and natural language processing (NLP), have significantly improved the ability to analyze large-scale biological, chemical, and clinical datasets with high precision. These computational systems enable accurate prediction of molecular properties, biological activities, toxicity profiles, and pharmacokinetic behavior, thereby accelerating early-stage drug discovery.

In pharmaceutical chemistry, AI assists in molecular modeling, quantitative structure–activity relationship (QSAR) analysis, de novo drug design, and virtual screening of chemical libraries. These approaches reduce experimental workload and enhance the probability of identifying promising drug candidates. Additionally, AI-driven drug repurposing has gained attention for identifying new therapeutic uses of existing drugs, particularly during global health emergencies such as the COVID-19 pandemic. Integration of AI with systems biology and precision medicine has further enabled patient-specific therapeutic optimization. Despite these advancements, challenges such as limited high-quality datasets, algorithmic bias, lack of interpretability, and regulatory concerns persist. However, continuous progress in computational power, big data analytics, and cloud-based AI platforms is expected to overcome these barriers. This review highlights recent advances, applications, and future perspectives of AI-driven pharmaceutical chemistry and drug discovery in modern healthcare systems.