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This comprehensive review investigates the cutting-edge tools and technologies that are revolutionizing modern pharmaceutical research. We analyze the integration of artificial intelligence and machine learning in drug discovery , lead optimization, and toxicity prediction, emphasizing their potential to significantly enhance research and development efficiency. The review also investigates the application of multi-omics technologies, including genomics, proteomics, and metabolomics, in elucidating disease mechanisms and identifying novel drug targets. We examine how these advanced approaches are transforming traditional experimental methods, ranging from high-throughput screening to pharmacodynamic and pharmacokinetic studies. The synergistic integration of computational methods with experimental techniques is highlighted, demonstrating its role in accelerating drug development pipelines and reducing associated costs. Furthermore, we investigate emerging trends such as personalized medicine, precision drug delivery systems , and gene therapy, evaluating their potential to address complex diseases and improve patient outcomes. The review also discusses the challenges and limitations of these novel technologies, providing a balanced perspective on their current capabilities and future potential. By providing a comprehensive analysis of the evolving landscape of pharmaceutical research, this review aims to inform researchers, clinicians, and industry professionals on leveraging these innovative tools to advance drug development and ultimately enhance human health.
Chen et al. (Sun,) studied this question.