Dissolution Profile Similarity Assessment-Best Practices, Decision Trees and Global Harmonization.

During the write-up of the meeting summary reports from the 2019 dissolution similarity workshop held at the University of Maryland's Center of Excellence in Regulatory Science and Innovation (M-CERSI), several coauthors continued their discussions to develop a "best-practice" document defining the steps required to assess dissolution profiles in support of certain biowaivers and postapproval changes. In previous reports, current challenges related to dissolution profile studies were discussed such that the steps outlined in the two flow charts ("decision trees") presented here can be applied. These decision trees include both recommendations for the use of equivalence procedures between reference and test products as well as application of the dissolution safe space concept. Common approaches towards establishing dissolution safe spaces are described. This paper encourages the preparation of protocols clearly describing why and how testing is performed along with the expected pass/fail criteria prior to generating data on the materials to be evaluated. The target audience of this manuscript includes CMC regulatory scientists, laboratory analysts, as well as statisticians from industry and regulatory health agencies involved in the assessment of product quality via in vitro dissolution testing. Building upon previous publications, this manuscript provides a solution to the current ambiguity related to dissolution profile comparison. The principles outlined in this and previous manuscripts provide a basis for global regulatory alignment in the application of dissolution profile assessment to support manufacturing changes and biowaiver requests.

DISSOLUTION PROFILE SIMILARITY ANALYSES-STATISTICAL PRINCIPLES, METHODS AND CONSIDERATIONS.

The pharmaceutical industry and regulatory agencies rely on dissolution similarity testing to make critical product decisions as part of drug product life cycle management. Accordingly, the application of mathematical approaches to evaluate dissolution profile similarity is described in regulatory guidance with the emphasis given to the similarity factor f2 with little discussion of alternative methods. In an effort to highlight current practices to assess dissolution profile similarity and to strive toward global harmonization, a workshop entitled "In Vitro Dissolution Similarity Assessment in Support of Drug Product Quality: What, How, When" was held on May 21-22, 2019 at the University of Maryland, Baltimore. This manuscript provides in-depth discussion of the mathematical principles of the model-independent statistical methods for dissolution profile similarity analyses presented in the workshop. Deeper understanding of the testing objective and statistical properties of the available statistical methods is essential to identify methods which are appropriate for application in practice. A decision tree is provided to aid in the selection of an appropriate statistical method based on the underlying characteristics of the drug product. Finally, the design of dissolution profile studies is addressed regarding analytical and statistical recommendations to sufficiently power the study. This includes a detailed discussion on evaluation of dissolution profile data for which several batches per reference and/or test product are available.