FDA Draft Guidance for GRAS Panels: Unintended Consequence?

Much to our surprise, we found the following recommendation for GRAS Panel members in FDA’s draft Guidance on GRAS Panels issued in November 16, 2017:

 . . . avoid filling a gap in the available data and information through theoretical considerations and relevant experience – e.g., making overly broad inferences . . . about safety of the substance in question based on the properties of other substances that are related in some way, or based on professional familiarity with a particular class of substances.

Inclusion of this recommendation in a Guidance that purports to address the potential for conflict of interest and procedures to avoid bias by GRAS panel members is inappropriate because:

1.  The statement falls outside the subject matter of the draft guidance

By including information that falls outside of the scope of the Guidance, the regulated industry and expert scientific community does not receive notice of the Agency’s “thinking.” In the Federal Register notice announcing the availability of the Guidance (82 Fed. Reg. 53433 (Nov. 16, 2017)), FDA stated that the draft guidance provides [the Agency’s] current thinking on best practices to identify GRAS panel members who have appropriate and balanced expertise; to take steps to reduce the risk that bias (or the appearance of bias) will affect the credibility of the GRAS panel’s output (often called a “GRAS panel report”), including the assessment of potential GRAS panel members for conflict of interest and the appearance of conflict of interest; and to limit the data and information provided to a GRAS panel to public information (e.g., by not providing the GRAS panel with information such as trade secret information).

Notably absent in the list of topics for the draft guidance is any mention of the Agency’s current thinking on the use of various safety assessment methodologies.

2.  Moreover, the statement can be interpreted as an FDA recommendation against the use of well-established and accepted safety assessment methods based on surrogate data derived from sources such as structure activity relationship, quantitative structure activity relationship, read-across and cluster-analysis, notwithstanding the fact that such approaches are widely applied in safety evaluations by various regulatory agencies, including FDA itself.

In comments submitted to FDA on May 15, 2018, we asked the agency to remove this statement from the guidance or, at the very least, revise the statement so it cannot be misinterpreted as excluding well-accepted and well-conducted surrogate/read-across rationales for safety assessments.