توالی یابی نسل جدید(NGS): تحولی در تشخیص پاتوژن ها و پزشکی شخص محور
کد: G-1669
نویسندگان: Hamidreza Alimirzaei * ℗
زمان بندی: زمان بندی نشده!
برچسب: تشخیص و درمان سرطان
دانلود: دانلود پوستر
خلاصه مقاله:
خلاصه مقاله
Background and aims: Next-Generation Sequencing (NGS) has emerged as a transformative technology in genomics, revolutionizing pathogen detection, antimicrobial resistance profiling, and personalized medicine. Its ability to rapidly analyze genetic material offers unprecedented opportunities for precise diagnostics and tailored therapies. This study aims to comprehensively evaluate the clinical applications of NGS in infectious disease management and oncology, address its technical and economic challenges, and highlight its role in advancing precision medicine. Additionally, the study explores comparative advantages of NGS over conventional diagnostic methods, such as culture-based techniques and Sanger sequencing. Method: This systematic review analyzed data from peer-reviewed articles, clinical trials, and scientific databases published between 2014 and 2024. Inclusion criteria prioritized studies focusing on NGS applications in pathogen identification, oncology, and antimicrobial resistance. Data extraction encompassed technological processes, diagnostic accuracy criteria, cost analyses, and case studies. Bioinformatics pipelines, such as BLASTn and Guppy-ont, were analyzed for their roles in data interpretation. Results: NGS demonstrated a 95% diagnostic accuracy in pathogen detection, reducing turnaround time from 48 hours (traditional methods) to under 24 hours. In polymicrobial infections, NGS identified co-infecting pathogens in 85% of cases, compared to 40% with culture-based methods. For antimicrobial resistance, NGS detected resistance genes (e.g., mecA, blaNDM-1) in 90% of samples, enabling targeted antibiotic regimens. In oncology, NGS-guided therapies improved treatment response rates by 80% in lung adenocarcinoma patients with EGFR or ALK mutations. However, challenges included high costs (50% higher than conventional methods), bioinformatics complexity, and variability in sensitivity (70–95%) across pathogens. Recent innovations, such as cloud-based data analysis and multiplex panels (e.g., PneumoSeq), enhanced scalability and reduced operational costs by 30%. Conclusion: While NGS holds immense potential for revolutionizing diagnostics and therapeutics, its clinical adoption remains hindered by financial barriers, technical expertise gaps, and data interpretation complexities. Strategic investments in bioinformatics training, cost-reduction initiatives (e.g., shared sequencing platforms), and regulatory standardization are critical to mainstream integration. Future research should focus on optimizing workflows for low-resource settings and validating NGS in emerging infectious diseases. By addressing these challenges, NGS can become a cornerstone of precision medicine, improving patient outcomes and public health surveillance.
کلمات کلیدی
NGS, Bioinformatics, Personalized Medicine
