Journal of Aerosol Medicine and Pulmonary Drug DeliveryVol. 35, No. 4 Letters to the EditorMoving Forward from “Fine Particle Fraction: The Good and the Bad”Jolyon P. Mitchell, William Doub, J. David Christopher, Christopher J. Gruenloh, Rajni B. Patel, Mark Copley, Steven Tignor, Stephen W. Stein, Svetlana Lyapustina, and Stephen P. NewmanJolyon P. MitchellAddress correspondence to: Jolyon P. Mitchell, PhD, Jolyon Mitchell Inhaler Consulting Services, Inc., London N6H 2R1, Canada E-mail Address: mitchelljolyon@gmail.comhttps://orcid.org/0000-0001-5456-8425Jolyon Mitchell Inhaler Consulting Services, Inc., London, Canada.*Member of ISAM.Search for more papers by this author, William Doubhttps://orcid.org/0000-0003-3750-9049OINDP In Vitro Analysis, Kirkwood, Missouri, USA.*Member of ISAM.Search for more papers by this author, J. David ChristopherMerck Research Laboratories, Merck & Co., Inc., West Point, Pennsylvania, USA.Search for more papers by this author, Christopher J. GruenlohPPD, Part of Thermo Fisher Scientific, Middleton, Wisconsin, USA.Search for more papers by this author, Rajni B. PatelIntellectual Designs LLC, Brookfield, Connecticut, USA.Search for more papers by this author, Mark CopleyCopley Scientific Ltd., Nottingham, United Kingdom.Search for more papers by this author, Steven TignorMerck & Co., Inc., Rahway, New Jersey, USA.Search for more papers by this author, Stephen W. SteinKindeva Drug Delivery, Woodbury, Minnesota, USA.Search for more papers by this author, Svetlana LyapustinaFaegre Drinker Biddle & Reath LLP, Washington, District of Columbia, USA.Search for more papers by this author, and Stephen P. NewmanPrivate Consultant, Hunstanton, United Kingdom.*Member of ISAM.Search for more papers by this authorPublished Online:4 Aug 2022https://doi.org/10.1089/jamp.2022.0017AboutSectionsView articleView Full TextPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookTwitterLinked InRedditEmail View article"Moving Forward from “Fine Particle Fraction: The Good and the Bad”." Journal of Aerosol Medicine and Pulmonary Drug Delivery, 35(4), pp. 225–226FiguresReferencesRelatedDetails Volume 35Issue 4Aug 2022 InformationCopyright 2022, Mary Ann Liebert, Inc., publishersTo cite this article:Jolyon P. Mitchell, William Doub, J. David Christopher, Christopher J. Gruenloh, Rajni B. Patel, Mark Copley, Steven Tignor, Stephen W. Stein, Svetlana Lyapustina, and Stephen P. Newman.Moving Forward from “Fine Particle Fraction: The Good and the Bad”.Journal of Aerosol Medicine and Pulmonary Drug Delivery.Aug 2022.225-226.http://doi.org/10.1089/jamp.2022.0017Published in Volume: 35 Issue 4: August 4, 2022Online Ahead of Print:May 4, 2022PDF download

Batch-to-batch pharmacokinetic (PK) variability of orally inhaled drug products has been documented and can render single-batch PK bioequivalence (BE) studies unreliable; results from one batch may not be consistent with a repeated study using a different batch, yet the goal of PK BE is to deliver a product comparison that is interpretable beyond the specific batches used in the study. We characterized four multiple-batch PK BE approaches to improve outcome reliability without increasing the number of clinical study participants. Three approaches include multiple batches directly in the PK BE study with batch identity either excluded from the statistical model ("Superbatch") or included as a fixed or random effect ("Fixed Batch Effect," "Random Batch Effect"). A fourth approach uses a bio-predictive in vitro test to screen candidate batches, bringing the median batch of each product into the PK BE study ("Targeted Batch"). Three of these approaches (Fixed Batch Effect, Superbatch, Targeted Batch) continue the single-batch PK BE convention in which uncertainty in the Test/Reference ratio estimate due to batch sampling is omitted from the Test/Reference confidence interval. All three of these approaches provided higher power to correctly identify true bioequivalence than the standard single-batch approach with no increase in clinical burden. False equivalence (type I) error was inflated above the expected 5% level, but multiple batches controlled type I error better than a single batch. The Random Batch Effect approach restored 5% type I error, but had low power for small (e.g., <8) batch sample sizes using standard [0.8000, 1.2500] bioequivalence limits.

The objective of this work was to study the performance of the modified chi-square ratio statistic (mCSRS test) proposed for cascade impactor (CI) profile equivalence testing. The test (T) and reference (R) CI profile datasets were generated from different typical CI profile patterns either with or without inter-site correlation (ISC) through Monte Carlo simulations. The mCSRS test pass rate outcome employing previously published critical values was compared with that of critical values derived from different types of datasets. The influence of number of bootstrap iterations (B) on the consistency of the outcome was assessed within the range of 10–10,000 iterations. Power curves were constructed to study the effect of differences in T and R mean stage deposition, T/R variance ratios, differences between T and R profiles in high/low deposition sites, and sample size on the performance of the mCSRS test. The derived critical values exhibited trends based on R product variability: M1 rank-ordered without ISC (at low variability) and the previously published M8 critical values (at high variability) resulted in lowest pass rate outcomes. The precision of the outcome did not increase considerably beyond B = 2000 (default). The probability of showing equivalence between T and R CI profiles increased with (1) a decrease in mean deposition differences, (2) a decrease in T product variability, and (3) an increase in sample size. The mCSRS outcome is less sensitive to low deposition sites that are prone to analytical variability. In conclusion, the mCSRS test is a sensitive and robust method under most conditions.

Historically, ligand-binding assays for pharmacokinetic samples employed duplicate rather than singlet-based analysis. Herein, the Translational and absorption, distribution, metabolism and excretion (ADME) Sciences Leadership Group of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ) presents a study aiming to determine the value of duplicate versus singlet-based testing. Based on analysis of data collected from eight organizations for 20 drug candidates representing seven molecular types and four analytical platforms, statistical comparisons of validation and in-study quality controls and study unknown samples demonstrated good agreement across duplicate sets. Simulation models were also used to assess the impact of sample duplicate characteristics on bioequivalence outcomes. Results show that testing in singlet is acceptable for assays with %CV <= 15% between duplicates. Singlet-based approach is proposed as the default for ligand-binding assays while a duplicate-based approach is needed where imprecision and/or inaccuracy impede the validation of the assay.

The multi-stage cascade impactor (CI) is the mainstay method for the determination of the aerodynamic particle size distribution (APSD) of aerosols emitted from orally inhaled products (OIPs). CIs are designed to operate at a constant flow rate throughout the measurement process. However, it is necessary to mimic an inhalation maneuver to disperse the powder into an aerosol when testing passive dry powder inhalers (DPIs), which constitute a significant portion of available products in this inhaler class. Methods in the pharmacopeial compendia intended for product quality assurance initiate sampling by applying a vacuum to the measurement apparatus using a timer-operated solenoid valve located downstream of the CI, resulting in a period when the flow rate through the impactor rapidly increases from zero towards the target flow rate. This article provides recommendations for achieving consistent APSD measurements, including selection of the CI, pre-separator, and flow control equipment, as well as reviewing considerations that relate to the shape of the flow rate-sampling time profile. Evidence from comparisons of different DPIs delivering the same active pharmaceutical ingredients (APIs) is indicative that the compendial method for APSD measurement is insensitive as a predictor of pharmacokinetic outcomes. Although inappropriate for product quality testing, guidance is therefore provided towards adopting a more clinically realistic methodology, including the use of an anatomically appropriate inlet and mimicking patient inhalation at the DPI while operating the CI at constant flow rate. Many of these recommendations are applicable to the testing of other OIP classes.

This article extends previous work studying performance characteristics of the population bioequivalence (PBE) statistical test recommended by the US Food and Drug Administration (FDA) for orally inhaled and nasal drug products. Based on analysis of a metered dose inhaler database for impactor sized mass, a simulation study was designed to compare performance of the recommended PBE approach with several modified or alternative approaches. These included an extended PBE that separately modeled within-batch (can) and between-batch (batch) variability and average bioequivalence (ABE) tests that modeled with or without between-batch variability and with or without log-transformation. This work showed that separately modeling within- and between-batch variability while increasing the number of sampled batches addressed previously identified issues of the PBE approach when between-batch variability was present, namely, (a) increased risk for falsely concluding equivalence and (b) low probability of correctly concluding equivalence. The same modifications were also required of the ABE to achieve expected performance. However, these modifications did not successfully address the issue of equivalence conclusions that depended on the direction of product mean differences (asymmetric performance). This work highlights the importance of understanding decision-making error rates in developing regulatory recommendations to standardize bioequivalence outcomes across products.

The performances of three statistical approaches for assessing in vitro equivalence was evaluated with a set of 55 scenarios of realistic test (T) and reference (R) cascade impactor (CI) profiles (originally employed by the Product Quality Research Institute to evaluate the chi-square ratio statistic: CSRS) by comparing the outcomes against experts' opinion (surrogate for the truth). The three methods were (A) a stepwise aerodynamic particle size distribution (APSD) equivalence test integrating population bioequivalence (PBE) testing of impactor-sized mass (ISM) with the CSRS (PBE-CSRS approach), previously suggested by the USFDA; (B) the combination of PBE testing of single actuation content and ISM with the newly suggested modified CSRS (PBE-mCSRS approach), a method employing reference variance scaling; and (C) EMA's average bioequivalence (ABE approach). Based on Monte-Carlo simulations, both PBE-CSRS and ABE approaches resulted in high misclassification rates, the former with highest false-pass rate and the latter with highest false-fail rate at both ≥ 50% and ≥ 80% classification threshold values (the % of simulations or experts necessary to judge a given scenario as equivalent). Based on DeLong's tests, the PBE-mCSRS approach showed significantly better overall agreement with experts' opinion compared to the other approaches. Comparison of CSRS with mCSRS (both without PBE) suggested that the more discriminatory characteristics of the mCSRS method is based on the integration of variance scaling into the mCSRS method. Contrary to the ABE approach, the application of PBE-mCSRS approach for assessing APSD profiles of three dry powder inhaler (DPI) formulations supported the pharmacokinetic bioequivalence assessment of these formulations.

Many workflows in Pharmaceutical R&D involve the manipulation of defined amounts of powders. Automated powder dispensing platforms are currently available; however, these existing technologies do not meet the requirements for every high-throughput experimentation powder dispensing application. A Working Group (WG) composed of pharmaceutical researchers within the Enabling Technologies Consortium (ETC) evaluated automated platforms commercially available from three manufacturers using an objective, systematic testing protocol. This paper describes the selection of powders and testing conditions used in this evaluation, and it assesses the impact that the powders, testing conditions, equipment environment, and other factors had on the performance of the selected platforms.

The current International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) methods for determining the supported shelf life of a drug product, described in ICH guidance documents Q1A and Q1E, are evaluated in this paper. To support this evaluation, an industry data set is used which is comprised of 26 individual stability batches of a common drug product where most batches are measured over a 24 month storage period. Using randomly sampled sets of 3 or 6 batches from the industry data set, the current ICH methods are assessed from three perspectives. First, the distributional properties of the supported shelf lives are summarized and compared to the distributional properties of the true shelf lives associated with the industry data set, assuming the industry data set represents a finite population of drug product batches for discussion purposes. Second, the results of the ICH “poolability” tests for model selection are summarized and the separate shelf life distributions from the possible alternative models are compared. Finally, the ICH methods are evaluated in terms of their ability to manage risk. Shelf life estimates that are too long result in an unacceptable percentage of nonconforming batches at expiry while those that are too short put the manufacturer at risk of possibly having to prematurely discard safe and efficacious drug product. Based on the analysis of the industry data set, the ICH-recommended approach did not produce supported shelf lives that effectively managed risk. Alternative approaches are required.

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.

This article reports on results from a two-lab, multiple impactor experiment evaluating the abbreviated impactor measurement (AIM) concept, conducted by the Cascade Impaction Working Group of the International Pharmaceutical Aerosol Consortium on Regulation and Science (IPAC-RS). The goal of this experiment was to expand understanding of the performance of an AIM-type apparatus based on the Andersen eight-stage non-viable cascade impactor (ACI) for the assessment of inhalation aerosols and sprays, compared with the full-resolution version of that impactor described in the pharmacopeial compendia. The experiment was conducted at two centers with a representative commercially available pressurized metered dose inhaler (pMDI) containing albuterol (salbutamol) as active pharmaceutical ingredient (API). Metrics of interest were total mass (TM) emitted from the inhaler, impactor-sized mass (ISM), as well as the ratio of large particle mass (LPM) to small particle mass (SPM). ISM and the LPM/SPM ratio together comprise the efficient data analysis (EDA) metrics. The results of the comparison demonstrated that in this study, the AIM approach had adequate discrimination to detect changes in the mass median aerodynamic diameter (MMAD) of the ACI-sampled aerodynamic particle size distribution (APSD), and therefore could be employed for routine product quality control (QC). As with any test method considered for inclusion in a regulatory filing, the transition from an ACI (used in development) to an appropriate AIM/EDA methodology (used in QC) should be evaluated and supported by data on a product-by-product basis.

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.

Implicit in ICH Q1E (International Conference on Harmonization [ICH], 2003b) are definitions of batch shelf life (the time the batch mean crosses the acceptance limit) and product shelf life (the minimum batch shelf life). The distribution of batch means over time projects to a distribution of batch shelf lives on the x-axis. Assuming multivariate normality, shelf life is the ratio of correlated Gaussian variables. Using Hinkley (1969), we describe the relationship between quantiles of the distributions of batch shelf lives and batch means. Exploiting this relationship, a linear mixed model is used to estimate a target quantile of batch shelf lives to address the ICH objective.

The goal of shelf life estimation is to determine the storage time during which the entire product meets specification with acceptably high probability. The estimated shelf life should be applicable to all future batches (ICH Q1E, International Conference on Harmonization, 2003b). There is compelling evidence of issues with the International Conference on Harmonization (ICH) guidelines for shelf life estimation. Issues include fixed batch effects, poolability tests, and confidence intervals for the mean. Two conclusions from evaluating the ICH procedure are that batch effects should be random and that focus should be on a quantile. A procedure is needed that combines random batches with the ICH objective of estimating the minimum batch shelf life.

The purpose of this article is to review the suitability of the analytical and statistical techniques that have thus far been developed to assess the dissolution behavior of particles in the respirable aerodynamic size range, as generated by orally inhaled products (OIPs) such as metered-dose inhalers and dry powder inhalers. The review encompasses all analytical techniques publicized to date, namely, those using paddle-over-disk USP 2 dissolution apparatus, flow-through cell dissolution apparatus, and diffusion cell apparatus. The available techniques may have research value for both industry and academia, especially when developing modified-release formulations. The choice of a method should be guided by the question(s) that the research strives to answer, as well as by the strengths and weaknesses of the available techniques. There is still insufficient knowledge, however, for translating the dissolution data into statements about quality, performance, safety, or efficacy of OIPs in general. Any attempts to standardize a dissolution method for compendial inclusion or compendial use would therefore be premature. This review reinforces and expands on the 2008 stimulus article of the USP Inhalation Ad Hoc Advisory Panel, which “could not find compelling evidence suggesting that such dissolution testing is kinetically and/or clinically crucial for currently approved inhalation drug products.”