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New FDA Guidances on NGS-Based Testing May Bolster Personalized Medicine

Guest Blog
by Neil A. Belson, J.D., of Counsel, Potomac Law Group

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Neil A. Belson

The U.S. Food and Drug Administration (FDA)’s recently issued final guidance documents related to next-generation sequencing (NGS) may encourage the development of personalized medicine by streamlining the regulatory pathway for NGS-based tests and expanding the role of real-world evidence for regulatory purposes.

Most observers believe NGS technologies, which can examine millions of DNA variants at a time related to numerous conditions and detect previously unidentified variants, will accelerate personalized medicine by allowing clinicians to match patients to suitable treatments with increased efficiency and precision. FDA recognizes that regulatory approaches developed for conventional diagnostics, which measure only a limited number of analytes, are not appropriate for reviewing NGS technologies. FDA is therefore seeking a more “flexible and adaptive” approach that accommodates the rapidly evolving nature of NGS technologies, while providing reasonable assurance of safety and effectiveness.

Streamlining Regulation of NGS-Based Tests

The first guidance, entitled Use of Public Human Genetic Variant Databases to Support Clinical Validity for Genetic and Genomic-Based In Vitro Diagnostics, seeks to encourage the expanded use of genetic variant databases in pre-market testing of NGS-based (and other genomic-based) diagnostics. FDA considers a “genetic variant database” to be a “publicly accessible database of human genetic variants that aggregates and curates reports of human genotype-phenotype relationships to a disease or condition” and includes publicly available documentation of evidence supporting such linkages.

FDA believes that evidence from publicly available databases could support clinical validity of genetic variant assertions if the database meets the following criteria:

  1. Operates in a manner which provides adequate information and assurances to assess the quality of its source data, evidence review and assertions regarding variants;
  2. Transparency, including its data sources and how it evaluates variant evidence
  3. Complies with data privacy and security requirements; and
  4. Contains genetic variant information generated using validated methods.

FDA believes that data and genetic variant assertions from databases that satisfy the agency’s guidance would generally constitute scientifically valid evidence to support clinical validity for FDA approvals. At present, potentially useful genetic variant data is often not stored in a publicly accessible manner. With its guidance, FDA hopes to encourage increased deposition of genetic data into public databases. This, in turn, would provide additional data for developers of NGS-based diagnostic tests to utilize in developing and gaining regulatory approvals for their products. Ultimately, the agency seeks a “well-defined process … to promote more rapid translation of genetic information into useful clinical evidence.”

FDA’s second guidance, Considerations for Design, Development, and Analytical Validation of Next Generation Sequencing (NGS)-Based In Vitro Diagnostics (IVDs) Intended to Aid in the Diagnosis of Suspected Germline Diseases, seeks to streamline FDA’s pre-market review of NGS-based tests for germline diseases “through a process that leverages appropriate standards, quality systems controls and community assessment of clinical validity.” FDA considers “germline diseases” to encompass genetic diseases arising from inherited or de novo germline variants.

With this guidance, FDA seeks to promote the development of consensus standards that can provide guidance to developers of NGS-based tests intended to diagnose suspected germline diseases. Test developers could certify conformity to such standards in their pre-market submissions, if such standards develop.

There are currently no legally marketed devices with a general intended use of aiding in diagnosis of suspected germline diseases. This absence of predicate devices would normally mean that NGS-based tests aimed at diagnosing suspected germline diseases would automatically have to meet pre-market approval requirements for Class III devices. FDA believes, however, that its recommendations, or standards that address them, could provide the reasonable assurance of safety and effectiveness that would allow such NGS-based tests (aimed at diagnosing suspected germline diseases) to be eligible for classification as Class II devices through the de novo process. The de novo process authorizes FDA to classify new devices which present low-to-moderate risks as Class I or Class II even where no predicate device exists. By making the de novo process available, FDA is streamlining regulatory approval and commercialization of NGS-based tests which meet the agency’s standards of safety and effectiveness. Furthermore, once FDA utilizes the de novo process to classify an initial NGS-based test aimed at diagnosing suspected germline disease as a Class II device, such a device could then become a predicate for future 510(k) submissions of NGS-based tests with similar intended uses.

Expanding the Role of Real-World Evidence for Regulatory Purposes

The guidances also create new incentives for the expanded use of real-world evidence in obtaining medical device approvals, which may lead to more efficient approval of personalized medicine tests. FDA issued a final guidance in 2017 stating that it would consider real-world evidence when making regulatory decisions relating to medical devices in both pre-market and post-market contexts.

FDA defines real-world evidence as “clinical evidence regarding the usage and potential benefits of a medical product derived from analysis” of real-world data, such as electronic health records, insurance claims, and data from disease registries (italics added). As the italicized words suggest, real-world evidence signifies something more than anecdotal data to the agency. Rather, like traditional randomized clinical trials, real-world evidence requires careful study designs. The main difference is that real-world evidence focuses on actual patient and health care delivery data in generating clinical evidence to support regulatory approvals. Real-world evidence can be faster, less costly and a better indication of a product’s performance under real-life conditions than randomized clinical trials.

The new guidances create incentives for NGS-based test developers to generate clinically valid real-world evidence in genetic variant databases or in conformance with consensus standards, which can guide the development of new products.