Application of artificial intelligence to toxicological assessment of plant: a bibliometric analysis and future research plans

Abstract

Artificial intelligence (AI) has gained attention in health science, with significant applications in the toxicological assessment of plants. However, a bibliometric analysis is essential to chart research trends and propose future advancements. This study explores key publications on AI’s role in plant toxicity assessment, identifying unresolved issues in pharmacological research. Articles from January 2008 to December 2023 were retrieved from the SCOPUS database, revealing a steady rise in publications, with a sharp increase from 2019 to 2023. A total of 75 research articles were analysed. The articles were categorised into four main clusters: AI applications, drug development, toxicity prediction models, and adverse drug event evaluations. ‘AI’ was the most frequently mentioned keyword, followed by ‘drug toxicity.’ Among 64 articles, the USA contributed 29, China 11, India 8, and the UK 4, with the UK having high citation rates. The findings highlight a growing trend toward AI-driven toxicity prediction in drug discovery. However, few studies provide definitive conclusions on AI’s potential in this field. The COVID-19 pandemic has heightened interest among researchers and policymakers. This study urges increased government and agency funding for AI-driven toxicity research. Advancing this field will enhance drug safety, reduce harmful testing, and promote sustainable plant use, aligning with SDGs 3, 12, and 15.