Weighing the Evidence: Variant Classification and Interpretation in Precision Oncology, US Food and Drug Administration Public Workshop—Workshop Proceedings

Abstract

PURPOSE: Next-generation sequencing (NGS) oncology panels are becoming integral in hospital and academic settings to guide patient treatment and enrollment in clinical trials. Although NGS technologies have revolutionized decision-making for cancer therapeutics, physicians may face many challenges in parsing and prioritizing NGS-based test results to determine the best course of treatment for individual patients. On January 29, 2018, the US Food and Drug Administration held a public workshop entitled, "Weighing the Evidence: Variant Classification and Interpretation in Precision Oncology." Here, we discuss the presentations and discussion highlights across the four sessions of the workshop. METHODS: The goal of the public workshop was to engage stakeholders and solicit input from experts in precision oncology to discuss the integration of complex NGS data into patient management and regulatory innovation within the precision oncology community. The US Food and Drug Administration gathered representatives from academia, industry, patient advocacy, government, and professional organizations for a series of presentations followed by panel discussions. After the workshop, the transcript and speaker presentation slides were reviewed and summarized for manuscript preparation. RESULTS: Speakers and panelists provided diverse perspectives on the integration of NGS technology into patient care for oncology and on the complexities that surround data interpretation and sharing. Discussions highlighted the challenges with standardization for variant classification while expressing the utility of consensus recommendations among stakeholders in oncology for driving innovation in the era of precision medicine. CONCLUSION: As precision medicine advances, clear communication within the field of precision oncology will be key to creating an environment that facilitates the generation and sharing of data that have value to patients.

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