Background: Ivermectin has recently garnered significant scientific attention for its potential anticancer properties. Objective: This research aims a comprehensive literature review to evaluate IVM’s chemical characteristics and assess its applicability as an alternative therapeutic strategy in oncology. Methods: The methodology involved a systematic search and critical appraisal of data from peer-reviewed scientific databases, focusing on structural analyses, such as nuclear magnetic resonance (NMR), crystallography, and in silico modeling, as well as preclinical experimental studies. Results: The review highlights IVM’s distinct physicochemical profile, including high lipophilicity, poor aqueous solubility, and moderate acid stability, which collectively affect its bioavailability and pharmacokinetic behavior. Mechanistically, IVM has been shown to modulate multiple oncogenic signaling pathways, including Wnt/β-catenin, PI3K/Akt/mTOR, and STAT3. These interactions contribute to the induction of apoptosis, inhibition of tumor cell proliferation, and modulation of the tumor microenvironment across a range of malignancies. Despite encouraging preclinical evidence, clinical validation remains limited. Conclusions: Further investigation is needed to optimize IVM’s formulation for enhanced solubility and targeted delivery, as well as to design robust clinical trials assessing its safety and efficacy in oncology settings. This review provides a foundational framework for future interdisciplinary research on drug repurposing and highlights the potential of IVM as a cost-effective and accessible adjunct or alternative to modern cancer therapy.

Background: Artificial intelligence (AI) is transforming various fields, such as education and health. In education, text generation models, writing assistants and automatic translation have emerged, although it faces challenges in the detection of texts generated by Artificial Intelligence. Objective: an analysis of the existing information on Artificial Intelligence and nursing education: Challenges for its application in Higher Education was performed. Materials and Methods: this study corresponded to a search in scientific databases: Scopus, Web of Science, PubMed, Dialnet, Research Gate, Scielo and official pages of the World Health Organization, Pan American Health Organization and American Psychological Association. Results: a total of 41 documents were obtained and used for the preparation of this document. Nursing plays a crucial role in health care, and AI can facilitate the management of information to improve preventive and palliative care and general well-being. Conclusions: AI has positively impacted medicine and education, improving efficiency, accuracy, and personalization of services. However, ethical and data protection challenges must be addressed to ensure responsible and safe use of AI in various settings