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AAPS PharmSciTech

, Volume 19, Issue 3, pp 1410–1425 | Cite as

Performance of the Population Bioequivalence (PBE) Statistical Test Using an IPAC-RS Database of Delivered Dose from Metered Dose Inhalers

  • Beth Morgan
  • Stephanie Chen
  • David Christopher
  • Göran Långström
  • Christopher Wiggenhorn
  • Elise Burmeister Getz
  • Hayden Beresford
  • Thomas Hoffelder
  • Daniela Acerbi
  • Stephen Andrews
  • Mark Berry
  • Monisha Dey
  • Keyur Joshi
  • Mary McKenry
  • Marisa Pertile
  • Helen Strickland
  • David Wilcox
  • Svetlana Lyapustina
Research Article
  • 181 Downloads

Abstract

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.

KEY WORDS

population bioequivalence inhalation products in vitro performance regulatory FDA 

Notes

Acknowledgements

The authors would like to acknowledge IPAC-RS member companies, board of directors, and all members of the PBE working group for supporting this work through discussions and by providing the data.

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Copyright information

© American Association of Pharmaceutical Scientists 2018

Authors and Affiliations

  • Beth Morgan
    • 1
  • Stephanie Chen
    • 2
  • David Christopher
    • 3
  • Göran Långström
    • 4
  • Christopher Wiggenhorn
    • 5
  • Elise Burmeister Getz
    • 6
  • Hayden Beresford
    • 7
  • Thomas Hoffelder
    • 8
  • Daniela Acerbi
    • 9
  • Stephen Andrews
    • 10
  • Mark Berry
    • 11
  • Monisha Dey
    • 3
  • Keyur Joshi
    • 12
  • Mary McKenry
    • 13
    • 14
  • Marisa Pertile
    • 15
  • Helen Strickland
    • 16
  • David Wilcox
    • 10
  • Svetlana Lyapustina
    • 17
  1. 1.StatisticsPearl TherapeuticsRaleighUSA
  2. 2.Department of StatisticsNorth Carolina State UniversityRaelighUSA
  3. 3.BiostatisticsMerck & Co.West PointUSA
  4. 4.Pharmaceutical Technology & DevelopmentAstraZeneca GothenburgMölndalSweden
  5. 5.Drug Delivery Systems Division3M CompanySt. PaulUSA
  6. 6.Clinical PharmacologyOriel/NovartisBerkeleyUSA
  7. 7.R&D, 3M Drug Delivery Systems Division3MLoughboroughUK
  8. 8.Global Biostatistics & Data SciencesBoehringer Ingelheim Pharma GmbH & Co. KGIngelheimGermany
  9. 9.Clinical PharmacologyChiesiParmaItaly
  10. 10.Inhalation Product DevelopmentCatalentMorrisvilleUSA
  11. 11.Global Respiratory GroupMylan Pharmaceuticals UK Ltd.SandwichUK
  12. 12.Pulmonary and Nasal Project ManagementCatalent Pharma SolutionsMorrisvilleUSA
  13. 13.Global BiostatisticsTeva PharmaceuticalsMiamiUSA
  14. 14.Department of Management ScienceUniversity of MiamiCoral GablesUSA
  15. 15.Drug Product Development–CMC–R&DChiesi Farmaceutici SpAParmaItaly
  16. 16.StatisticsGlaxoSmithKlineRaleighUSA
  17. 17.Pharmaceutical Practice GroupDrinker Biddle & Reath LLPWashingtonUSA

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