Current Approaches for Dissolution Similarity Assessment, Requirements, and Global Expectations

Application of bootstrap f2 to dissolution data from biorelevant media and evidence of the conservative nature of bootstrap f2

f2 with or without bootstrapping is the most common method to compare in vitro dissolution profiles, but methods to compare dissolution profiles have become less harmonized. The objective was to compare outcomes from bootstrap f2 and f2 (i.e. not-bootstrapped f2) using a large set of in vitro dissolution data. Non-parametric bootstrapping was performed on the 104 profile comparisons that did not meet the percent coefficient of variation (CV%) criteria to use average dissolution data. Bootstrap f2 was taken as the lower 90 % confidence interval of bootstrapped samples. There was concordance between bootstrap f2 and f2 in 92 of the 104 comparisons (88 %). There were no false positives. However, 12 % were false negative. Inspection of these discordance pairs suggests that bootstrap f2 serves as a conservative approach to assess profile similarity, particularly when a value of 50 is being used as decision criteria.

Effects of Apex Size on Dissolution Profiles in the USP II Paddle Apparatus

The use of apex vessels may solve coning problems associated with dissolution testing. However, excessive dissolution acceleration can reduce the discriminatory power. This study aimed to clarify how different apex vessel sizes affect the dissolution behavior of cone-forming formulations. Five apex vessels with different heights, centralities, and compendial vessels were used. The paddle rotation speed at which the coning phenomenon resolved was measured using standard particles of different densities. Three model formulations-USP prednisone tablets, atorvastatin calcium hydrate tablets, and levofloxacin fine granules-were selected, and dissolution tests were conducted at 30-100 revolutions per minute (rpm). Compared to the compendial vessels, the disappearance of standard particles at the apex base at lower paddle speeds in apex vessels was observed. Standard particles tended to remain in the center of the apex vessels and disappear at rotational speeds comparable to those of the compendial vessels. Dissolution increased in an apex height-dependent manner in the model formulations, except for the atorvastatin calcium hydrate tablets at 50 rpm. For levofloxacin fine granules, dissolution was also improved by reducing the paddle agitation speed to 30 rpm in the compendial vessels. Differences in apex centrality by 3 mm did not affect the dissolution rate. Our results indicate that apex vessels with low apex heights have a mount-resolving effect, but the degree of dissolution improvement by avoiding the coning phenomenon depends on the formulation characteristics used in the dissolution tests.

Dissolution Profiles Comparison Using Conventional and Bias Corrected and Accelerated f2 Bootstrap Approaches with Different Software's: Impact of Variability, Sample Size and Number of Bootstraps

Dissolution profiles comparison is an important element in order to support biowaivers, scale-up and post approval changes and site transfers. Highly variable dissolution can possess significant challenges for comparison and f2 bootstrap approach can be utilized in such cases. However, availability of different types of f2 and confidence intervals (CI) methods indicates necessity to understand each type of calculation thoroughly. Among all approaches, bias corrected and accelerated (BCa) can be an attractive choice as it corrects the bias and skewness of the distribution. In this manuscript, we have performed comparison of highly variable dissolution data using various software's by adopting percentile and BCa CI approaches. Diverse data with different variability's, number of samples and bootstraps were evaluated with JMP, DDSolver, R-software, SAS and PhEq. While all software's yielded similar observed f2 values, differences in lower percentile CI was observed. BCa with R-software and JMP provided superior lower percentile as compared to other computations. Expected f2 recommended by EMA has resulted as stringent criteria as compared to estimated f2. No impact of number of bootstraps on similarity analysis was observed whereas number of samples increased chance of acceptance. Variability has impacted similarity outcome with estimated f2 but chance of acceptance enhanced with BCa approach. Further, freely available R-software can be of attractive choice due to computation of various types of f2, percentile and BCa intervals. Overall, this work can enable regulatory submissions to enhance probability of similarity through appropriate selection of number of samples, technique based on variability of dissolution data.

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.

Physiologically Based Pharmacokinetics Modeling in Biopharmaceutics: Case Studies for Establishing the Bioequivalence Safe Space for Innovator and Generic Drugs

For successful oral drug development, defining a bioequivalence (BE) safe space is critical for the identification of newer bioequivalent formulations or for setting of clinically relevant in vitro specifications to ensure drug product quality. By definition, the safe space delineates the dissolution profile boundaries or other drug product quality attributes, within which the drug product variants are anticipated to be bioequivalent. Defining a BE safe space with physiologically based biopharmaceutics model (PBBM) allows the establishment of mechanistic in vitro and in vivo relationships (IVIVR) to better understand absorption mechanism and critical bioavailability attributes (CBA). Detailed case studies on how to use PBBM to establish a BE safe space for both innovator and generic drugs are described. New case studies and literature examples demonstrate BE safe space applications such as how to set in vitro dissolution/particle size distribution (PSD) specifications, widen dissolution specification to supersede f2 tests, or application toward a scale-up and post-approval changes (SUPAC) biowaiver. A workflow for detailed PBBM set-up and common clinical study data requirements to establish the safe space and knowledge space are discussed. Approaches to model in vitro dissolution profiles i.e. the diffusion layer model (DLM), Takano and Johnson models or the fitted PSD and Weibull function are described with a decision tree. The conduct of parameter sensitivity analyses on kinetic dissolution parameters for safe space and virtual bioequivalence (VBE) modeling for innovator and generic drugs are shared. The necessity for biopredictive dissolution method development and challenges with PBBM development and acceptance criteria are described.