Most medical treatments are designed for the “average patient” as a one-size-fits-all-approach, which may be successful for some patients but not for others. Precision medicine, sometimes known as “personalized medicine” is an innovative approach to tailoring disease prevention and treatment that takes into account differences in people’s genes, environments, and lifestyles. The goal of precision medicine is to target the right treatments to the right patients at the right time.

Advances in precision medicine have already led to powerful new discoveries and FDA-approved treatments that are tailored to specific characteristics of individuals, such as a person’s genetic makeup, or the genetic profile of an individual’s tumor. Patients with a variety of cancers routinely undergo molecular testing as part of patient care, enabling physicians to select treatments that improve chances of survival and reduce exposure to adverse effects.

Next Generation Sequencing (NGS) Tests

Precision care will only be as good as the tests that guide diagnosis and treatment. Next Generation Sequencing (NGS) tests are capable of rapidly identifying or ‘sequencing’ large sections of a person’s genome and are important advances in the clinical applications of precision medicine.
Patients, physicians and researchers can use these tests to find genetic variants that help them diagnose, treat, and understand more about human disease.

The FDA’s Role in Advancing Precision Medicine

The FDA is working to ensure the accuracy of NGS tests, so that patients and clinicians can receive accurate and clinically meaningful test results.

The vast amount of information generated through NGS poses novel regulatory issues for the FDA. While current regulatory approaches are appropriate for conventional diagnostics that detect a single disease or condition (such as blood glucose or cholesterol levels), these new sequencing techniques contain the equivalent of millions of tests in one. Because of this, the FDA has worked with stakeholders in industry, laboratories, academia, and patient and professional societies to develop a flexible regulatory approach to accommodate this rapidly evolving technology that leverages consensus standards, crowd-sourced data, and state-of-the-art open-source computing technology to support NGS test development. This approach will enable innovation in testing and research, and will speed access to accurate, reliable genetic tests.

Streamlining FDA’s Regulatory Oversight of NGS Tests

Flowchart for Next Generation Sequencing-based genetic tests. Databases flows into bioinformatic tools which flows into standards which flows back into databases. Databases: Would allow developers to use data from FDA-recognized public databases of genetic variants to support a test's clinical validity. Bioinformatics tools: a cloud-based community research and development portal that engages users across the world to experiment, share data and tools, and test new bioinformatics approaches for NGS. Standards: the FDA offers recommendations for designing, developing, and validating NGS tests that could also form the basis for community-developed consensus standards.

In April 2018, the FDA issued two final guidances that recommend approaches to streamline the submission and review of data supporting the clinical and analytical validity of NGS-based tests. These recommendations are intended to provide an efficient and flexible regulatory oversight approach: as technology advances, standards can rapidly evolve and be used to set appropriate metrics for fast growing fields such as NGS. Similarly, as clinical evidence improves, new assertions could be supported. This adaptive approach would ultimately foster innovation among test developers and improve patients’ access to these new technologies.

Clinical Databases Guidance

The final guidance “Use of Public Human Genetic Variant Databases to Support Clinical Validity for Genetic and Genomic-Based In Vitro Diagnostics” allows developers to use data from FDA-recognized public databases of genetic variants to help support a test’s clinical validity and outlines how database