By Jessica Y. Washington, J.D.
Developers of biosimilar products seeking licensure under section S51(k) of the Public Health Service Act (PHS Act) (42 U.S.C. §262 (k)) now have additional guidance on the statistical approaches for evaluating analytical similarity to reference products licensed under Section 351(a) of the PHS Act. The FDA has issued a draft guidance that provides advice to biosimilar product sponsors with regard to the evaluation process, which is intended to demonstrate that a proposed biosimilar product is highly similar to a reference product. Specifically, the guidance describes the type of information a sponsor should obtain about the structural/physiochemical and functional attributes of the reference product, how that information is used in the development of an analytical similarity assessment plan for the proposed biosimilar, and the statistical approaches recommended for evaluating analytical similarity. This guidance is one in a series of guidance documents promulgated by the FDA to implement the Biologics Price Competition and Innovation Act of 2009 (BCPI Act) (Notice, 82 FR 44425, September 22, 2017).
Background. The BCPI Act created a pathway to licensure under the PHS Act for biological products shown to be biosimilar to or interchangeable with a U.S.-licensed biological reference product. Section 351(i) of the PHS Act, added by section 7002(b)(3) of the Patient Protection and Affordable Care Act (ACA) (P.L. 111-148), defines biosimilarity to mean "the biological product is highly similar to the reference product notwithstanding minor differences in clinically inactive components" and "there are no clinically meaningful differences between the biological product and the reference product in terms of the safety, purity, and potency." Therefore, a 351(k) application for a proposed biosimilar product must include information showing biosimilarity based on data derived from "analytical studies that demonstrate that the biological product is highly similar to the reference product notwithstanding minor differences in clinically inactive components."
Evaluation of analytical similarity. An appropriately conducted analytical similarity evaluation that compares structural/physiochemical and functional attributes using multiple lots of the proposed biosimilar product and the reference product can yield a high degree of accuracy and confidence in the results and reduce the potential for bias. However, there are several issues that can be problematic when designing a statistical analyses assessment: (1) a limited number of reference product lots may result in a biased sampling, which, in turn, may lead to imprecise or inaccurate estimates of the distributions of important quality attributes for the reference product; (2) there may be a limited number of proposed biosimilar lots, and the available lots may not reflect the true variability of biosimilar product manufacturing; and (3) subjecting a large number of potential quality attributes to comparison in formal statistical tests within the context of limited lots could lead to a false conclusion that a large number of truly highly similar products are not highly similar. In order to overcome these issues, the FDA recommends using the following three-step, risk-based approach in the analytical similarity assessment of quality attributes:
- Step one: Determine the quality attributes that characterize the reference product relative to its structural/physiochemical and functional properties.
- Step two: Rank the quality attributes according to their risk of potential clinical impact.
- Step three: Evaluate theses attributes/assays pursuant to one of three tiers of statistical approaches based on a consideration of risk ranking and other factors.
Analytical similarity assessment plans. Once the biosimilar developer understands the structural/physiochemical and functional attributes of the reference product, the FDA recommends that it develop an analytical similarity assessment plan, a key component of which is the description of the lots available for similarity testing. The plan should include the developer’s proposed statistical evaluation approach, which should be presented to the FDA as early in the development process as feasible. According to the FDA guidance, the analytical similarity assessment plan should identify and address all factors that could impact the determination of whether the proposed biosimilar is highly similar to the reference product, including differences in the age of the lots produced at testing, multiple testing results, assay performance, and differences in attributes that will be considered acceptable.
The FDA recommends that the analytical similarity assessment plan be developed in four stages:
- Stage one: Risk ranking of the reference product’s quality attributes based on potential impact on clinical performance categories;
- Stage two: Determination of statistical methods to be used for evaluating each quality attribute based on risk ranking and other factors (this requires the developer to define three tiers corresponding to the use of three different methods for comparing attributes);
- Stage three: Development of a statistical analysis plan; and
- Stage four: Finalization of the analytical similarity assessment plan.
Three tiers. The FDA believes that relative to the determination of the statistical methods to be used, the application of three tiers with appropriate similarity acceptance criteria should support a demonstration that the proposed biosimilar is highly similar to the reference product. Tier one, equivalence testing, is usually recommended for quality attributes with the highest risk ranking and should generally include assay(s) that evaluate clinically relevant mechanism(s) of action of the product for each indication for which approval is sought. Tier two is recommended for quality attributes with a lower risk ranking. Tier three, an approach that uses visual comparisons, is recommended for quality attributes with the lowest risk ranking. The factors to be considered when determining the appropriate tier include the level of the attribute, assays used for assessing the attribute, and types of attributes/assays.
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