Abstract
In this chapter, APSD data are examined from real products using several different strategies to compare the ability of EDA to detect APSD changes with grouped stages from full-resolution CI measurements. These comparisons were made relative to decision making associated with OIP disposition in the QC environment. The strategies involve (1) measurement system analysis (MSA), (2) operating characteristic curves (OCC), and (3) principal component analysis (PCA). A general description of these techniques and their basic concepts is provided in the first part of the chapter, while the computational details and results for each of the employed strategies are given following the same order in the later part of the chapter. All results point to the conclusion that compared to grouped stages, the LPM/SPM ratio from EDA is more accurate and more sensitive to APSD changes. Each of the examination strategies used different statistical methodologies, based on different assumptions, and one of the approaches used a different set of data independent of the other two. Yet the same qualitative conclusion validating the superior decision-making ability of the EDA concept was reached, regardless of approach.
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Notes
- 1.
It should be noted that the assumed limits were established by computing a goodness-of-fit statistic between each displaced cumulative APSD and the target cumulative APSD. Several levels of this statistic (0.9, 0.8, 0.7, and 0.6) were applied to each studied product, and the resulting limits are provided in Table 8.6. While this provided a systematic process for establishing assumed limits, the actual values are not critical. The important constraint for comparing the performance of the two metrics is that each particular limit was converted to equivalent requirements with respect to each metric.
References
US Food and Drug Administration (FDA) (1998) CDER. Draft guidance for industry metered dose inhaler (MDI) and dry powder inhaler (DPI) drug products chemistry, manufacturing, and controls documentation, Rockville, MD, USA. http://www.fda.gov/cder/guidance/2180dft.pdf. Accessed 15 July 2012
Peri P (2011) Assessing quality of inhaled products and links to efficacy and safety. Presentation at the IPAC-RS Conference “Bringing value to the patient in a changing world”, Rockville, MD, USA. http://ipacrs.com/2011%20Conference.html. Accessed 13 July 2012
Tougas TP, Christopher D, Mitchell JP, Strickland H, Wyka B, Van Oort M, Lyapustina S (2009) Improved quality control metrics for cascade impaction measurements of orally inhaled drug products (OIPs). AAPS PharmSciTech 10(4):1276–1285
Wheeler DJ (2006) EMP (evaluating the measurement process) III: using imperfect data. SPC, Knoxville, TN
AIAG (Automotive Industry Action Group) (2010) Measurement system analysis, Reference Manual, 4th edn. AIAG, Southfield, MI, USA, ISBN#: 978-1-60-534211-5
Eisenhart C (1963) Realistic evaluation of the precision and accuracy of instrument calibration. J Res Natl Bur Stds 67C:161–187 [Reprinted, with corrections, in (1969) Precision measurement and calibration: statistical concepts and procedures In: Ku HH (ed) Natl Bur Stds Spec Publ 300 1:21–48]
American Society for Testing and Materials (2012) Standard terminology for relating to quality and statistics ASTM E456-12, West Conshohocken, PA, USA. http://www.astm.org/Standards/E456.htm. Accessed 15 July 2012
Christopher JD, Dey M, Lyapustina S, Mitchell J, Tougas T, Van Oort M, Strickland H, Wyka B (2010) Generalized simplified approaches for MMAD determination. Pharma Forum 36(3):812–823
Sandell D, Tougas T (2012) Quality considerations in the establishment of specifications for pharmaceuticals. Stat Biopharm Res 4(2):125–135
Jolliffe IT (2002) Principal component analysis. Springer, New York
Jackson JE (1959) Quality control methods for several related variables. Technometrics 1(4):359–377
Berntsson O, Danielsson LG, Johansson MO, Folestad S (2000) Quantitative determination of content in binary powder mixtures using diffuse reflectance near infrared spectrometry and multivariate analysis. Anal Chim Acta 419(1):45–54
Eriksson L, Hagberg P, Johansson E, Rännar S, Whelehan O, Åström A, Lindgren T (2001) Multivariate process monitoring of a newsprint mill: application to modeling and predicting COD load resulting from de-inking of recycled paper. J Chemometr 15(4):337–352
Euerby MR, Petersson P (2003) Chromatographic classification and comparison of commercially available reversed-phase liquid chromatographic columns using principal component analysis. J Chromatogr A 994(1–2):13–36
Intelmann D, Haseleu G, Dunkel A, Lagemann A, Stephan A, Hofmann T (2011) Comprehensive sensomics analysis of hop-derived bitter compounds during storage of beer. J Agric Food Chem 59(5):1939–1953
Sandler N, Wilson D (2010) Prediction of granule packing and flow behavior based on particle size and shape analysis. J Pharm Sci 99(2):958–968
Pan Z, Christopher JD, Lyapustina S, Chou E (2004) Statistical techniques used in simulation of cascade impactor particle size distribution profiles. In: Dalby RN, Byron PR, Peart J, Suman JD, Farr SJ (eds) Respiratory drug delivery-IX. Davis HealthCare International, River Grove, IL, pp 669–672
Christopher D, Pan Z, Lyapustina S (2005) Aerodynamic particle size distribution profile comparisons: considerations for assessing statistical properties of profile comparisons tests. Am Pharm Rev 8(1):68–72
Hotelling H (1931) The generalization of Student’s ratio. Ann Math Stat 2(3):360–378
Hauck WW, DeStefano AJ, Cecil TL, Abernethy DR, Koch WF, Williams RL (2009) Acceptable, equivalent, or better: approaches for alternatives to official compendial procedures. Pharma Forum 35(3):772–778
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Christopher, J.D. et al. (2013). Performance Characterization of EDA and Its Potential to Improve Decision Making in Product Batch Release. In: Tougas, T., Mitchell, J., Lyapustina, S. (eds) Good Cascade Impactor Practices, AIM and EDA for Orally Inhaled Products. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-6296-5_8
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