Ferdinand Ndikuryayo, Xue-Yan Gong, Ge-Fei Hao, Wen-Chao Yang
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How Artificial Intelligence Assists in Overcoming Drug Resistance?
The increasing prevalence of drug resistance (DR) and pesticide resistance poses a significant threat to public health, necessitating the development of innovative strategies to discover more effective drugs and pesticides. In this context, artificial intelligence (AI) has emerged as a promising solution. This review examines the roles of AI in tackling DR. An analysis of current literature reveals that AI can enhance the drug discovery process, facilitating the faster creation of effective and safer medications. Furthermore, AI is crucial in predicting and elucidating the mechanisms of DR and pesticide resistance. By offering decision support to healthcare providers, AI-driven precision medicine paves the way for personalized treatment options. Moreover, AI aids in identifying synergistic drug combinations essential for combating DR. Lessons from the recent use of AI in addressing DR demonstrate the potential of this versatile tool to offer solutions required for controlling infections and cancers in the era of DR. However, despite the advancements achieved, challenges such as data accessibility and ethical issues remain. This highlights the need for interdisciplinary collaboration and ethical consideration. Finally, we provide an outlook on future actions required to successfully implement AI-powered technologies in drug and pesticide discovery.
期刊介绍:
Medicinal Research Reviews is dedicated to publishing timely and critical reviews, as well as opinion-based articles, covering a broad spectrum of topics related to medicinal research. These contributions are authored by individuals who have made significant advancements in the field.
Encompassing a wide range of subjects, suitable topics include, but are not limited to, the underlying pathophysiology of crucial diseases and disease vectors, therapeutic approaches for diverse medical conditions, properties of molecular targets for therapeutic agents, innovative methodologies facilitating therapy discovery, genomics and proteomics, structure-activity correlations of drug series, development of new imaging and diagnostic tools, drug metabolism, drug delivery, and comprehensive examinations of the chemical, pharmacological, pharmacokinetic, pharmacodynamic, and clinical characteristics of significant drugs.