Abstract Over the past decade, Big Data and Artificial Intelligence (AI) have emerged as transformative forces in healthcare, particularly in pharmaceutical policy, regulation, and drug safety surveillance. These technologies enable the systematic collection, integration, and analysis of large-scale and heterogeneous data, thereby strengthening evidence-based decision-making across the pharmaceutical lifecycle. International experience demonstrates that the integration of AI and Big Data supports early detection of adverse drug reactions (ADRs), enhances pharmacovigilance systems, automates regulatory processes, and accelerates drug discovery and development. AI-driven methods, including machine learning and natural language processing (NLP), facilitate the identification of latent patterns and risk signals from diverse data sources such as clinical trials, Real World Evidence (RWE), electronic health records, and spontaneous reporting systems.
Despite these global advances, the application of AI and Big Data within Mongolia’s pharmaceutical policy and regulatory framework remains limited. Key challenges include fragmented and poorly integrated data sources, insufficient data standardization, underdeveloped information technology infrastructure, limited human resource capacity, and gaps in legal and ethical governance. International initiatives offer valuable reference models for addressing these challenges. The World Health Organization’s VigiBase employs AI and NLP techniques to identify global ADR trends, the U.S. Food and Drug Administration’s Sentinel Initiative integrates RWE to support proactive drug safety monitoring, and the Republic of Korea’s Disease Control and Prevention Agency has implemented an NLP-based pharmacovigilance system for automated risk detection.
This study aims to assess the applicability of Big Data and AI in Mongolia’s pharmaceutical policy and regulatory system through a comparative analysis of international best practices and the identification of key implementation gaps. The findings emphasize the need for integrated data systems, harmonized standards, localized AI application models, and robust regulatory and ethical frameworks. Overall, the study highlights the potential of Big Data and AI to modernize pharmaceutical policy and regulation in Mongolia and provides evidence-based directions for sustainable implementation aligned with international best practices.

Introduction: In recent years, the global incidence of cancer has risen sharply, becoming the second leading cause of mortality after cardiovascular diseases. Beyond these major health concerns, free radicals are identified as key contributors to diabetes, hepatitis, Alzheimer’s disease, Parkinson’s disease, aging, and related disorders. These reactive molecules are intermediate products of various redox reactions, characterized by their electrically neutral, multi-atomic structures containing unpaired electrons. Antioxidants play a crucial role in inhibiting lipid peroxidation in cellular membranes, thereby protecting cells from oxidative damage and degradation.
Carthamus tinctorius L. is used to improve blood circulation and to treat cardiovascular and gynecological diseases. It has also been used as an antiseptic, analgesic, antipyretic, and antidote.
Therefore, as it has been widely used in traditional medicine, the extraction of Carthamus tinctorius L., determination of the qualitative and quantitative content of certain biologically active compounds, and evaluation of antioxidant activity formed the basis of this study. Methods: The study was conducted at the laboratory of the Mongolian National University of Pharmaceutical Sciences and the pharmaceutical chemistry sector of the Institude of Pharmaceutical Studies. The raw material of Carthamus tinctorius L. was used to prepare the extract, and in accordance with the Mongolian National Pharmacopoeia method, the total flavonoids, safflomin A, and antioxidant activity were determined. The following equipment was used in the study: thin-layer chromatography plates (Silica gel 60 F254, Germany), UV lamp (MZ-01, China), water bath (DK-98-IIA), Soxhlet apparatus (TC SIMAX 200 mL, 8730/200), and spectrophotometer (UV/Vis-1700, Macy, China). The aerial parts of Carthamus tinctorius L. were extracted using remaceration, repercolation, and circulation methods with 70% ethanol and distilled water (1:10). The qualitative analysis of total flavonoids in the extract was conducted by thin-layer chromatography, quantitative content was determined using spectrophotometry, and antioxidant activity was assessed using the DPPH method. Statistical analysis was performed using SPSS-22.0 software. Conclution The raw material of Carthamus tinctorius L. was extracted using 70% ethanol with remaceration, repercolation, and circulation methods to obtain an appropriate extract. The total flavonoid content in the extract was determined by spectrophotometry, with the circulation method proving to be the most suitable for extraction. Thin-layer chromatography (TLC) analysis of the ethanol extract of Carthamus finctorius L. showed a brown-yellow spot at the same level as the standard substance quercetin (Rf - 0.92), indicating the presence of flavonoids. High-performance liquid chromatography (HPLC) analysis of the ethanol extract revealed safflomin A at a concentration of 0.315 mg/mL at a retention time of 15.082 minutes. Antioxidant activity, as assessed by the DPPH method, showed inhibition of 93.625% for a 1 mL sample, 63.125% for a 3 mL sample, and 5.125% for a 5 mL sample.