Evaluation of the Sensitivity and Robustness of Modified Chi-Square Ratio Statistic for Cascade Impactor Equivalence Testing Through Monte Carlo Simulations.

Monte Carlo simulations aerodynamic particle size distribution bioequivalence modified chi-square ratio statistic (mCSRS) power curves

Journal

AAPS PharmSciTech
ISSN: 1530-9932
Titre abrégé: AAPS PharmSciTech
Pays: United States
ID NLM: 100960111

Informations de publication

Date de publication:
20 May 2020
Historique:
received: 21 01 2020
accepted: 20 03 2020
entrez: 22 5 2020
pubmed: 22 5 2020
medline: 24 9 2020
Statut: epublish

Résumé

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.

Identifiants

pubmed: 32435854
doi: 10.1208/s12249-020-01664-6
pii: 10.1208/s12249-020-01664-6
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

147

Auteurs

Abhinav Kurumaddali (A)

Department of Pharmaceutics, College of Pharmacy, University of Florida, Box 100494, Gainesville, Florida, 32610, USA.

David Christopher (D)

Biostatistics, Merck & Co., West Point, Pennsylvania, USA.

Helen Strickland (H)

Statistics, GlaxoSmithKline, Raleigh, North Carolina, USA.

Beth Morgan (B)

Statistics, AstraZeneca, Durham, North Carolina, USA.

Christopher Wiggenhorn (C)

R&D, 3M Drug Delivery Systems Division, 3M Company, St. Paul, Minnesota, USA.

Stephen Stein (S)

R&D, 3M Drug Delivery Systems Division, 3M Company, St. Paul, Minnesota, USA.

Svetlana Lyapustina (S)

Pharmaceutical Practice Group, Drinker Biddle and Reath LLP, Washington, District of Columbia, USA.

Günther Hochhaus (G)

Department of Pharmaceutics, College of Pharmacy, University of Florida, Box 100494, Gainesville, Florida, 32610, USA. Hochhaus@cop.ufl.edu.

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Classifications MeSH