Emerging trends in drug discovery: Harnessing artificial intelligence and machine learning for drug development

Abstract

The traditional drug discovery process is a resource-intensive, time-consuming, and expensive endeavor, often characterized by high failure rates and inefficiencies. Recent advancements in artificial intelligence (AI) and machine learning (ML) have introduced revolutionary tools that are transforming the pharmaceutical industry, enabling faster, more cost-effective, and precise drug development. This review examines the transformative role of AI and ML across key stages of drug discovery, including target identification, compound screening, lead optimization, and clinical trials. AI/ML technologies leverage vast biological datasets and employ advanced algorithms such as neural networks, natural language processing, and reinforcement learning to enhance the efficiency and accuracy of drug discovery pipelines. These tools enable the identification of novel drug targets, accurate prediction
of drug efficacy and safety profiles, and optimization of clinical trial designs, substantially reducing development timelines and costs. Real-world case studies highlight the success of AI/ML in delivering breakthrough therapies in areas such as oncology, neurodegenerative diseases, and rare genetic disorders. Despite these advancements, several challenges persist, including issues related to data quality, model interpretability, algorithmic bias, and regulatory compliance. Furthermore, ethical considerations surrounding data privacy, transparency, and decision-making in AI-driven processes are critical to address. This review also explores emerging trends, such as the integration of multi-omics datasets, advancements in quantum computing, and the growing focus on personalized medicine and precision drug development. Overcoming current challenges through interdisciplinary collaboration, innovation, and the implementation of robust ethical frameworks will be essential for unlocking AI/ ML’s full potential, ushering in a new era of patient-centric and precision-driven drug discovery and development.