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The second in a series of articles from the IPAC-RS Cascade Impaction Working Group concerning the limitations of metrics commonly used in the assessment of aerodynamic particle size distributions (APSDs) of orally inhaled products (OIPs). This article explores the limitations of stage groupings, probing whether they are suitable for making batch disposition decisions based on inhaler performance testing. 10 August 2020 Inhalation Cascade impactor stage groupings: Poor decisions from degraded data The following is the second in a series of articles by the Cascade Impaction Working Group of the Inter- national Pharmaceutical Aerosol Consortium for Regulation and Science (IPAC-RS) concerning the limitations of metrics commonly used in the assess- ment of aerodynamic particle size distributions (APSDs) of orally inhaled products (OIPs). In the first of these articles, 1 we looked at the inability of the fine particle dose metric to detect size changes in APSD. Here, we turn our attention to the stage grouping met- rics favored by the US Food and Drug Administration (FDA). 2 ese articles are written to educate, to dispel common misconceptions, to raise awareness of risks and to encourage scientists to scrutinize current prac- tices. ese articles should not be mistaken for regula- tory guidance documents. Introduction Guidance documents concerning the quality of OIPs from a number of major health authorities include cascade impactor stage groupings as a means for con- trolling inhaler aerodynamic particle size distributions (APSDs). Health Canada and the European Medicines Agency (EMA), for example, identify stage groupings as an option if the fine particle mass alone is insuffi- cient to fully characterize the particle size distribution of the therapeutic dose. 3, 4 e United States Food and Drug Administration (FDA) goes even further, recom- mending this methodology as the principal approach for APSD control in their current draft guidance for industry for the determination of quality for pressur- ized metered dose inhalers (pMDIs) and dry powder inhalers (DPIs). 2 Despite their prevalence, however, stage groupings are remarkably ineffective at observing differences between APSDs. In the following article, we explore the limitations of stage groupings, probing whether they are suitable for making batch disposition decisions based on inhaler performance testing. Why stage groupings? ….Good question. Chances are, if your lab releases OIPs for distribu- tion, you have had to take cascade impaction data and reduce it to stage grouping metrics. Chances are, also, that this is the only instance in which you would treat the data in this manner. is is because the stage grouping metrics have no inherent value. ere is no demonstrated correlation between these metrics and any measure of in vivo performance (such as lung depo- sition or clinical outcomes), and they offer little more than an obscured view of the product's APSD. Indeed, if you have ever had to investigate an out-of-trend or out-of-specification cascade impactor (CI) result for a commercial orally inhaled product (OIP), you have likely had to sift through huge volumes of CI data. Almost certainly, you have immediately discarded the stage grouping data and insisted that the testing lab provide you with the original CI data from which the stage groupings were derived. Only then can you begin to investigate the nature of the problem and diagnose the root cause. What then is the purpose of reducing CI data to stage groupings? What benefits do these metrics offer? You will have to ask someone else these questions, for we certainly do not have those answers. What we can offer you, though, is a compelling demonstration of how little the stage grouping metrics offer you as a scientist who strives to understand and control your product's APSD, and how little they do to ensure the delivery of safe and efficacious medicines to your patients. Hopefully, this will steel your resolve to keep asking those questions. Rejecting another bad metric Adrian P. Goodey, PhD a ; Jolyon P. Mitchell, PhD, FRSC(UK), CChem, CSci b ; William H. Doub, PhD c and J. David Christopher, MSc a a Merck & Co., Inc. b Jolyon Mitchell Inhaler Consulting Services, Inc. c OINDP In Vitro Analysis