A Integration of Next-Generation Sequencing in Health Biotechnology: A Systematic Synthesis and Meta-Analysis of Diagnostic, Clinical, and Economic Impacts.
DOI:
https://doi.org/10.69693/ijmst.v4i2.8037Keywords:
Next-Generation Sequencing, Diagnostik Molekuler, Bioteknologi Kesehatan; Systematic Literature Review, Precision Medicine, Cost-EffectivenessAbstract
Technological development Next-Generation Sequencing(NGS) has revolutionized the fields of molecular diagnostics and healthcare biotechnology through comprehensive, high-throughput, and precision genomic approaches. This study aims to systematically synthesize scientific evidence on the diagnostic, clinical, and economic impact of NGS implementation in modern healthcare. The methods used areSystematic Literature Review(SLR) with reference to the PRISMA guidelines, using the Scopus database for the 2020–2026 publication period. Of the 3,491 identified articles, 20 met the inclusion criteria and were analyzed qualitatively. The synthesis results showed that NGS significantly improves diagnostic sensitivity and accuracy, accelerates diagnosis, and supports the application of precision medicine, particularly in genetic diseases, cancer, and infections. Furthermore, the implementation of NGS has been shown to provide clinical benefits in the form of improved patient outcomes and therapy efficiency, and demonstrates potentialcost-effectivenesslong-term. However, challenges related to regulation, ethics, genomic data privacy, and access disparities remain major concerns. Overall, NGS is a crucial pillar in the sustainable transformation of genomics-based health systems.
References
Hilt, E. E., & Ferrieri, P. (2022). Next Generation and Other Sequencing Technologies in Diagnostic Microbiology and Infectious Diseases. Genes, 13(9), 1566. https://doi.org/10.3390/genes13091566
Isaic, A., Motofelea, N., Hoinoiu, T., Motofelea, A. C., Leancu, I. C., Stan, E., Gheorghe, S. R., Dutu, A. G., & Crintea, A. (2025). Next-Generation Sequencing: A Review of Its Transformative Impact on Cancer Diagnosis, Treatment, and Resistance Management. Diagnostics, 15(19), 2425. https://doi.org/10.3390/diagnostics15192425
Yadav, D., Patil-Takbhate, B., Khandagale, A., Bhawalkar, J., Tripathy, S., & Khopkar-Kale, P. (2023). Next-Generation sequencing transforming clinical practice and precision medicine. Clinica Chimica Acta, 551, 117568. https://doi.org/10.1016/j.cca.2023.117568
He, S., Xiong, Y., Tu, T., Feng, J., Fu, Y., Hu, X., Wang, N., & Li, D. (2024). Diagnostic performance of metagenomic next-generation sequencing for the detection of pathogens in cerebrospinal fluid in pediatric patients with central nervous system infection: A systematic review and meta-analysis. BMC Infectious Diseases, 24, 103. https://doi.org/10.1186/s12879-024-09010-y
Jiang, P., et al. (2020). Circulating tumor DNA analysis for non-invasive monitoring of cancer progression and treatment response. Nature Reviews Clinical Oncology, 17(7), 389–405.
Kumar, R., et al. (2024). Ethical considerations in genomic data and precision medicine. Frontiers in Genetics.
Mirza, M., et al. (2024). Economic evaluation of next-generation sequencing in oncology and rare pediatric disorders. Pharmacoeconomics, 42(6), 755–769.
Mosele, M. F., Westphalen, C. B., Stenzinger, A., Barlesi, F., Bayle, A., Bièche, I., … André, F. (2024). Recommendations for the use of next-generation sequencing (NGS) for patients with advanced cancer in 2024: a report from the ESMO Precision Medicine Working Group. Annals of Oncology, 35(7), 588–606. https://doi.org/10.1016/j.annonc.2024.04.005
Nurchis, M. C., Radio, F. C., Salmasi, L., Alizadeh, A. H., Raspolini, G. M., Altamura, G., … Damiani, G. (2024). Cost-Effectiveness of Whole-Genome vs Whole-Exome Sequencing Among Children With Suspected Genetic Disorders. JAMA Network Open, 7(1), e2353514. https://doi.org/10.1001/jamanetworkopen.2023.53514
Osei Sekyere, J. (2025). Next-generation sequencing in infectious-disease diagnostics: Economic, regulatory, and clinical pathways to adoption. MicrobiologyOpen, 14(6), e70104. https://doi.org/10.1002/mbo3.70104
Pandey, P., et al. (2024). Cloud computing in genomics: Opportunities and challenges. Bioinformatics Review.
Sepulveda, J. L. (2020). Clinical genomics and bioinformatics pipelines: Reproducibility and integration using R/Bioconductor. The Journal of Molecular Diagnostics, 22(6), 715–723.
Suresh Babu, V., et al. (2025). Artificial intelligence-driven variant classification in clinical genomics: Improving diagnostic accuracy. Bioinformatics Advances, 5(1), vbad021.
Wu, J., Song, W., Yan, H., Luo, C., Hu, W., Xie, L., & Tao, Y. (2024). Metagenomic next-generation sequencing in detecting pathogens in pediatric oncology patients with suspected bloodstream infections. Pediatric Research, 95, 843–851.
Yan, Q., & Wang, J. (2021). Advances in next-generation sequencing for molecular diagnosis and precision medicine. Molecular Diagnosis & Therapy, 25(3), 267–278.
Yadav, S., et al. (2023). Next-generation sequencing technologies in clinical diagnostics: Applications and future perspectives. Biotechnology Advances, 65, 108132.
Yunqian Zhu, Y., Gan, M., Ge, M., Dong, X., Zhou, Q., Yu, H., … Wenhao Zhou. (2023). Diagnostic performance and clinical impact of metagenomic next-generation sequencing for pediatric infectious diseases. Journal of Clinical Microbiology, 61(6), e0011523. https://doi.org/10.1128/jcm.00115-23
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Indonesian Journal of Multidisciplinary on Social and Technology

This work is licensed under a Creative Commons Attribution 4.0 International License.













