Scientists have long been plagued by the complex process of drug discovery and development, often under-invested. However, with advances in experimental techniques and computer hardware, artificial intelligence (AI) has emerged as a major tool for analyzing rich, high-dimensional data.
In a new academic paper published in the journal engineering Entitled “Artificial Intelligence in Pharmaceutical Sciences,” the researchers detail the benefits of AI technology in all aspects of new drug research and development (R&D).
AI can discover new drugs more efficiently and at lower cost. Through the explosion of biomedical data, AI has revolutionized drug research and development, from target discovery to preclinical research, automated drug synthesis, and drug market impact. In this review, the authors provide an overview of common AI models in the field of drug discovery, followed by a summary and detailed discussion of their specific applications at various stages of drug discovery R&D.
The paper concludes that AI is advantageous in all aspects of new drug research and development. It can be used for drug target discovery, new drug design and development, preclinical research, clinical trial design, and post-marketing surveillance to assist in the design of safe and effective drugs.
AI significantly reduces cycle times and costs in pharmaceutical R&D. Although some limitations still remain in the AI-based drug R&D process, the authors believe AI is an essential technology in the drug R&D process. In the future, AI technology will change the pharmaceutical research and development paradigm to provide patients with personalized care.
The authors of the paper suggest further research to inject new energy into the field and maintain momentum. The advent of AI is gradually helping scientists unravel the mysteries of large, complex biological systems and is poised to revolutionize the pharmaceutical research and development process. As technology continues to evolve, the possibilities for AI in the pharmaceutical industry are endless.
For more information:
Mingkun Lu et al., Artificial Intelligence in Pharmaceutical Sciences, engineering (2023). DOI: 10.1016/j.eng.2023.01.014
