Electronic Theses and Dissertation

Pemanfaatan Artificial Intelligence (AI) dalam farmakovigilans merupakan pendekatan inovatif yang berpotensi meningkatkan deteksi, pemantauan, dan pelaporan keamanan obat secara lebih cepat, akurat, dan efisien. Penelitian ini bertujuan menganalisis pemanfaatan AI dalam memperkuat peran apoteker pada sistem farmakovigilans secara global serta mengevaluasi relevansinya terhadap penguatan sistem farmakovigilans di Indonesia. Penelitian menggunakan metode Systematic Literature Review (SLR) berdasarkan pedoman PRISMA 2020. Pencarian literatur dilakukan pada database Scopus, Web of Science, dan PubMed dengan rentang publikasi tahun 2016–2025. Artikel dipilih berdasarkan kriteria inklusi dan dianalisis secara naratif yang didukung analisis bibliometrik. Hasil penelitian menunjukkan bahwa publikasi mengenai pemanfaatan AI dalam farmakovigilans mengalami peningkatan dari tahun ke tahun dan didominasi oleh pendekatan Natural Language Processing (NLP) serta text mining. AI berpotensi meningkatkan efisiensi deteksi sinyal keamanan obat, mendukung pengambilan keputusan klinis, serta memperkuat peran apoteker dalam pemantauan dan pelaporan efek samping obat. Implementasi AI masih menghadapi tantangan berupa keterbatasan regulasi, kualitas data, infrastruktur digital, dan kesiapan sumber daya manusia, terutama di negara berkembang termasuk Indonesia. Penelitian ini menyimpulkan bahwa AI berpotensi mendukung penguatan sistem farmakovigilans nasional apabila didukung oleh pengembangan infrastruktur, regulasi, dan kompetensi tenaga kesehatan.

Kata Kunci: Artificial Intelligence, Farmakovigilans, Apoteker, Systematic Literature Review, Analisis Bibliometrik.

The utilization of Artificial Intelligence (AI) in pharmacovigilance represents an innovative approach with the potential to enhance the detection, monitoring, and reporting of drug safety more rapidly, accurately, and efficiently. This study aims to analyze the application of AI in strengthening the role of pharmacists in pharmacovigilance systems globally, as well as to evaluate its relevance to strengthening the pharmacovigilance system in Indonesia. This research employed a Systematic Literature Review (SLR) method based on the PRISMA 2020 guidelines. Literature searches were conducted across the Scopus, Web of Science, and PubMed databases, covering publications from 2016 to 2025. Articles were selected based on predefined inclusion criteria and analyzed narratively, supported by bibliometric analysis. The results revealed a significant annual increase in publications on the use of AI in pharmacovigilance, predominantly utilizing Natural Language Processing (NLP) and text mining approaches. AI demonstrates strong potential to improve the efficiency of drug safety signal detection, support clinical decision-making, and strengthen the role of pharmacists in monitoring and reporting adverse drug reactions. However, AI implementation still faces several challenges, including limited regulatory frameworks, data quality issues, digital infrastructure constraints, and human resource readiness, particularly in developing countries such as Indonesia. This study concludes that AI holds substantial potential to support the strengthening of the national pharmacovigilance system, provided that it is accompanied by adequate infrastructure development, supportive regulations, and enhanced healthcare workforce competencies. Keywords: Artificial Intelligence, Pharmacovigilance, Pharmacist, Systematic Literature Review, Bibliometric Analysis.