Bioinformatics in Genomic Analysis: Opportunities and Challenges of Leveraging Big Data for Personalized Medicine

Abstract

Advances in bioinformatics and genomics technology have created great opportunities in realizing personalized medicine. This study aims to analyze the role of bioinformatics in the use of genomic big data, emphasizing the opportunities, challenges, and integration strategies needed. The research method used is qualitative with an exploratory approach. Data were collected through in-depth interviews, focus group discussions, and documentation studies, then analyzed using thematic analysis techniques. The results of the study show that bioinformatics offers a variety of opportunities, such as the utilization of pharmacogenomics for drug response prediction, disease biomarker identification, multi-omics data integration, machine learning algorithm development, and early detection of genetic diseases. However, a number of challenges still hinder implementation, including genomic data privacy and security issues, limited computing infrastructure, lack of interdisciplinary human resources, lack of standardization of data formats, and regulatory and policy barriers. This research also emphasizes the importance of the strategy of integrating bioinformatics and big data through strengthening technological infrastructure, global data standardization, the use of artificial intelligence, privacy protection based on adaptive regulations, international collaboration, and the development of interdisciplinary education. The implications of this research not only enrich the academic literature, but also provide a practical basis for the formulation of more precise and equitable health policies. Thus, this study confirms that the use of bioinformatics is a strategic path towards the transformation of data-based health services, which is oriented to individual needs while maintaining the ethics and sustainability of the health system.