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Establishing Standards for NGS Implementation in Clinical Molecular Pathology

NextEdge Admin

30 Apr 2024

2 min 31 sec

The integration of genomic profiling, particularly through Next Generation Sequencing (NGS), has revolutionized cancer diagnosis and management. NGS offers critical insights into mutational status, aiding in diagnosis, prognostication, therapy selection, and clinical trial enrollment across various cancer types. However, manual annotation of NGS-detected variants poses a significant challenge.

Despite automation in NGS analysis, variant annotation often requires manual curation, posing difficulties for pathologists unfamiliar with NGS technology. To address this, institutions are outsourcing NGS annotation to specialized vendors. This approach offers cost-effectiveness, expertise in NGS interpretation, access to large databases, and on-demand services, relieving pathologists and ensuring efficient resource utilization.

Moreover, the incorporation of artificial intelligence-driven solutions enhances efficiency and accuracy, addressing the need for re-annotation based on emerging scientific knowledge.

The development of standards for NGS implementation in clinical molecular pathology comprises laboratory guidelines and clinical requirements. Laboratory guidelines cover gene panel selection, sample handling, sequencing protocols, and reporting practices to ensure consistency and high quality. Clinical requirements focus on documentation, validation processes, and quality management to integrate NGS into routine practice, emphasizing pathologist training and adherence to international standards for reliability and accuracy.

Recognizing the complexity of NGS testing, separate standards are proposed for wet bench procedures and bioinformatics analysis. This allows flexibility, enabling laboratories to outsource certain aspects while maintaining compliance.

While foundational guidance is provided, detailed NGS checklists are required for standardization. This collaborative effort ensures adaptability to technological advancements and the evolving landscape of cancer genomics, aiming to improve patient care outcomes in personalized cancer medicine.