Abstract. This article is part of a series of reports from the "Orlando Inhalation Conference-Approaches in International Regulation" which was held in March 2014, and coorganized by the University of Florida and the International Pharmaceutical Aerosol Consortium on Regulation and Science (IPAC-RS). The goal of the conference was to foster the exchange of ideas and knowledge across the global scientific and regulatory community in order to identify and help move towards strategies for internationally harmonized, science-based regulatory approaches for the development and marketing approval of inhalation medicines, including innovator and second entry products. This article provides an integrated perspective of case studies and discussion related to in vitro testing of orally inhaled products, including in vitro-in vivo correlations and requirements for in vitro data and statistical analysis that support quality or bioequivalence for regulatory applications.

The purpose of this article is to report final results of the evaluation of a chi-square ratio test proposed by the US Food and Drug Administration (FDA) for demonstrating equivalence of aerodynamic particle size distribution (APSD) profiles of nasal and orally inhaled drug products. A working group of the Product Quality Research Institute previously published results demonstrating some limitations of the proposed test. In an effort to overcome the test's limited discrimination, the group proposed a supplemental test, a population bioequivalence (PBE) test for impactor-sized mass (ISM). In this final report the group compares the chi-square ratio test to the ISM-PBE test and to the combination of both tests. The basis for comparison is a set of 55 realistic scenarios of cascade impactor data, which were evaluated for equivalence by the statistical tests and independently by the group members. In many instances, the combined application of these 2 tests appeared to increase the discriminating ability of the statistical procedure compared with the chi-square ratio test alone. In certain situations the chi-square ratio test alone was sufficient to determine equivalence of APSD profiles, while in other situations neither of the tests alone nor their combination was adequate. This report describes all of these scenarios and results. In the end, the group did not recommend a statistical test for APSD profile equivalence. The group did not investigate other in vitro tests, in vivo issues, or other statistical tests for APSD profile comparisons. The studied tests are not intended for routine quality control of APSD.

The purpose of this article is to present the thought process, methods, and interim results of a PQRI Working Group, which was charged with evaluating the chi-square ratio test as a potential method for determining in vitro equivalence of aerodynamic particle size distribution (APSD) profiles obtained from cascade impactor measurements. Because this test was designed with the intention of being used as a tool in regulatory review of drug applications, the capability of the test to detect differences in APSD profiles correctly and consistently was evaluated in a systematic way across a designed space of possible profiles. To establish a "base line," properties of the test in the simplest case of pairs of identical profiles were studied. Next, the test's performance was studied with pairs of profiles, where some difference was simulated in a systematic way on a single deposition site using realistic product profiles. The results obtained in these studies, which are presented in detail here, suggest that the chi-square ratio test in itself is not sufficient to determine equivalence of particle size distributions. This article, therefore, introduces the proposal to combine the chi-square ratio test with a test for impactor-sized mass based on Population Bioequivalence and describes methods for evaluating discrimination capabilities of the combined test. The approaches and results described in this article elucidate some of the capabilities and limitations of the original chi-square ratio test and provide rationale for development of additional tests capable of comparing APSD profiles of pharmaceutical aerosols.

Two experiments implement and evaluate a training scheme for learning to apply frequency formats to probability judgements couched in terms of percentages. Results indicate that both conditional and cumulative probability judgements can be improved in this manner, however the scheme is insufficient to promote any deeper understanding of the problem structure. In both experiments, training on one problem type only (either conditional or cumulative risk judgements) resulted in an inappropriate transfer of a learned method at test. The obstacles facing a frequency-based training programme for teaching appropriate use of probability data are discussed.

The purpose of this article is 2-fold: (1) to document in the public domain the considerations that led to the development of a regulatory statistical test for comparison of aerodynamic particle size distribution (APSD) of aerosolized drug formulations, which was proposed in a US Food and Drug Administration (FDA) draft guidance for industry; and (2) to explain the background and process for evaluation of that test through a working group involving scientists from the FDA, industry, academia, and the US Pharmacopeia, under the umbrella of the Product Quality Research Institute (PQRI). The article and the referenced additional statistical information posted on the PQRI Web site explain the reasoning and methods used in the development of the APSD test, which is one of the key tests required for demonstrating in vitro equivalence of orally inhaled and nasal aerosol drug products. The article also describes the process by which stakeholders with different perspectives have worked collaboratively to evaluate properties of the test by drawing on statistical models, historical and practical information, and scientific reasoning. Overall, this article provides background information to accompany the companion article's discussion of the study's methods and results.

Regulatory agencies, industry, and academia have acknowledged that in vitro assessments serve a role in establishing bioequivalence for second-entry drug product approvals as well as innovator post-approval drug product changes. For orally inhaled respiratory products (OIPs), the issues of correctly analyzing in vitro data and interpreting the results within the broader context of therapeutic equivalence have garnered significant attention. One of the recommended statistical tests for in vitro data is the population bioequivalence method (PBE). The current literature for assessing the PBE statistical approach for in vitro data assumes a log normal distribution. This paper focuses on an assessment of that assumption for in vitro delivered dose. Concepts in development of a statistical model are presented. The PBE criterion and hypotheses are written for the case when data follows a normal distribution, rather than log normal. Results of a simulation study are reported, characterizing the performance of the PBE approach when data are expected to be normally distributed, rather than log normal. In these cases, decisions using the PBE approach are not consistent for the same absolute mean difference that the test product is from the reference product. A conclusion of inequivalency will occur more often if the test product dose is lower than the reference product for the same deviation from target. These features suggest that more research is needed for statistical equivalency approaches for in vitro data.

This article reports performance characteristics of the population bioequivalence (PBE) statistical test recommended by the US Food and Drug Administration (FDA) for orally inhaled products. A PBE Working Group of the International Pharmaceutical Aerosol Consortium on Regulation and Science (IPAC-RS) assembled and considered a database comprising delivered dose measurements from 856 individual batches across 20 metered dose inhaler products submitted by industry. A review of the industry dataset identified variability between batches and a systematic lifestage effect that was not included in the FDA-prescribed model for PBE. A simulation study was designed to understand PBE performance when factors identified in the industry database were present. Neglecting between-batch variability in the PBE model inflated errors in the equivalence conclusion: (i) The probability of incorrectly concluding equivalence (type I error) often exceeded 15% for non-zero between-batch variability, and (ii) the probability of incorrectly rejecting equivalence (type II error) for identical products approached 20% when product and between-batch variabilities were high. Neglecting a systematic through-life increase in the PBE model did not substantially impact PBE performance for the magnitude of lifestage effect considered. Extreme values were present in 80% of the industry products considered, with low-dose extremes having a larger impact on equivalence conclusions. The dataset did not support the need for log-transformation prior to analysis, as requested by FDA. Log-transformation resulted in equivalence conclusions that depended on the direction of product mean differences. These results highlight a need for further refinement of in vitro equivalence methodology.

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