An Interlaboratory Comparison on the Characterization of a Sub-micrometer Polydisperse Particle Dispersion
Type
Journal article
Language
English
Date issued
2022
Author
Benkstein, Kurt D.
Balakrishnan, Gurusamy
Bhirde, Ashwinkumar
Chalus, Pascal
Das, Tapan K.
Do, Ngoc
Duewer, David L.
Filonov, Nazar
Cheong, Fook Chiong
Garidel, Patrick
Gill, Nicole S.
Grabarek, Adam D.
Grier, David G.
Hadley, Judith
Hollingsworth, Andrew D.
Howard, Wesley W.
Jiskoot, Wim
Kar, Sambit R.
Kestens, Vikram
Khasa, Harshit
Kim, Yoen Joo
Koulov, Atanas
Matter, Anja
Philips, Laura A.
Probst, Christine
Ramaye, Yannic
Randolph, Theodore W.
Ripple, Dean C.
Romeijn, Stefan
Saggu, Miguel
Schleinzer, Franziska
Snell, Jared R.
Tatarkiewicz, Jan “Kuba”
Wright, Heather Anne
Yang, Dennis T.
Faculty
Wydział Nauk o Żywności i Żywieniu
Journal
Journal of Pharmaceutical Sciences
ISSN
0022-3549
Volume
111
Number
3
Pages from-to
699-709
Abstract (EN)
The measurement of polydisperse protein aggregates and particles in biotherapeutics remains a challenge, especially for particles with diameters of ≈ 1 µm and below (sub-micrometer). This paper describes an interlaboratory comparison with the goal of assessing the measurement variability for the characterization of a sub-micrometer polydisperse particle dispersion composed of five sub-populations of poly(methyl methacrylate) (PMMA) and silica beads. The study included 20 participating laboratories from industry, academia, and government, and a variety of state-of-the-art particle-counting instruments. The received datasets were organized by instrument class to enable comparison of intralaboratory and interlaboratory performance. The main findings included high variability between datasets from different laboratories, with coefficients of variation from 13 % to 189 %. Intralaboratory variability was, on average, 37 % of the interlaboratory variability for an instrument class and particle sub-population. Drop-offs at either end of the size range and poor agreement on maximum counts of particle sub-populations were noted. The mean distributions from an instrument class, however, showed the size-coverage range for that class. The study shows that a polydisperse sample can be used to assess performance capabilities of an instrument set-up (including hardware, software, and user settings) and provides guidance for the development of polydisperse reference materials.
License
Closed Access