Scientific and Regulatory Standards for Assessing Product Performance Using the Similarity Factor, f2

Abstract

The similarity factor, f2, measures the sameness of dissolution profiles. The following commentary is an overview of discussions and presentations from a group of industry and US regulatory experts that have integrated the science and regulatory research and practice for assessing product performance, particularly for modified-release (MR) dosage forms, using f2. For a drug development sponsor or applicant with an orally complex dosage formulation, it is critical to understand dissolution methods and the similarity factor and how and/or when to apply it in their NDA, ANDA, or PMA submission. As part of any regulatory submission, it is critical to justify that the product performance has not been impacted by any change in the manufacturing process and/or the delayed and/or prolonged drug release characteristics compared to a similar conventional or another orally complex dosage form. The purposes of this document are (1) to provide a description of appropriate dissolution methods, how is the f2 calculated and how it can be used to justify product performance similarity, or not; (2) to provide an overview of alternative methods available for dissolution profile comparisons, and (3) to illustrate how applying these concepts in a focused way supports approval of submissions and regulatory dossiers and aligns them with on-going science and regulatory initiatives. A case study will be used as an example to demonstrate how dissolution testing and the f2 calculation results can impact regulatory outcomes from an NDA (505(b)(1)), NDA (505(b)(2)), ANDA (505(j)), supplemental NDAs/ANDAs, or PMA perspective.

Application of Absorption Modeling in Rational Design of Drug Product Under Quality-by-Design Paradigm

“…In the absence of an in vitro-in vivo correlation, F2 similarity criteria are widely applied to assess the potential impact of dissolution changes and decide on the need for bioequivalence studies (31). It has been suggested before that for BCS III compounds, wider dissolution bounds may be acceptable (32).…”

Equivalence analyses of dissolution profiles with the Mahalanobis distance

“…A lower 95% confidence bound is determined by means of bootstrapping techniques (for details see Efron & Tibshirani 1993) and equivalence is concluded if > 50. In a simulation study from Ocana et al (2009) it turned out that the percentile method was superior to the BCA (abbreviation of Bias-Corrected and Accelerated) method regarding an approximate control of the type I error rate whereas in a simulation performed by Stevens et al (2015) the opposite result was found. Simulation studies show (Ma et al, 2000;Ocana et al, 2009) that both variants, percentile as well as BCA, can be considerably anticonservative.…”

“…For controlling the type I error rate of similarity decisions based on 2 several approaches exist: Zhai, Mathew, and Huang (2016) present tolerance limits for the distribution of 2 . Several papers suggest the construction of bootstrapping confidence intervals (Ma, Wang, Liu, & Tsong, 2000;Ocana, Frutos, & Sanchez, 2009;Stevens, Gray, Dorantes, Gold, & Pham, 2015;Mangas-Sanjuan, Colon-Useche, Gonzalez-Alvarez, Bermejo, & Garcia-Arieta, 2016;Paixão, Gouveia, Liva, & Morais, 2017, among others) to control the type I error rate when using 2 for the similarity decision. A lower 95% confidence bound is determined by means of bootstrapping techniques (for details see Efron & Tibshirani 1993) and equivalence is concluded if > 50.…”

Microparticles Formulation as a Targeting Drug Delivery System

“…Two general principles are involved in retarding drug release from most practically prolonged action formulations involving dosage form modification. These are the barrier and the embedded matrix principle [19][20][21][22].…”