Utilizing Artificial Intelligence to Optimize Sustainable Modern Precision Drug Development
TL;DR
The findings reveal that AI significantly accelerates drug discovery, supports personalized medicine through multi-omics data integration, enhances sustainability by improving resource efficiency, and drives pharmaceutical innovation through generative AI technologies.
Abstract
Artificial Intelligence (AI) has emerged as a transformative technology in the pharmaceutical industry, offering innovative solutions to accelerate drug discovery, enhance precision medicine, and improve sustainability in healthcare systems. Conventional drug development is often characterized by lengthy timelines, high costs, and significant failure rates, creating a need for more efficient and data-driven approaches. This study aims to analyze the role of AI in optimizing sustainable modern precision drug development. The research employed a Systematic Literature Review (SLR) method following the PRISMA 2020 framework. Literature was collected from major scientific databases, including Scopus, Web of Science, PubMed, ScienceDirect, SpringerLink, IEEE Xplore, and Google Scholar. From an initial pool of 152 articles, 10 studies published between 2020 and 2025 met the inclusion criteria and were analyzed using thematic synthesis. The findings reveal that AI significantly accelerates drug discovery, supports personalized medicine through multi-omics data integration, enhances sustainability by improving resource efficiency, and drives pharmaceutical innovation through generative AI technologies. However, challenges related to data quality, transparency, ethics, and regulatory compliance remain critical barriers. Overall, AI represents a strategic enabler for sustainable, efficient, and patient-centered pharmaceutical development.