LINK software is being utilized by Pfizer for S-factor optimization and application of particle classification by distinction of proteinaceous particulate vs. silicone oil.

Pfizer presented their research and collaboration with Lumetics in 2018 at the annual Protein Aggregation and Immunogenicity Conference, Breckenridge, Colorado (poster available below). At the 2019 Protein Stability Conference, Pfizer has built on their previous work with a co-authored presentation; “Aspects of silicone separation in protein-silicone mixtures using S-factor-style electronic filter”.  The new research explores the effect of refractive index upon the effectiveness of S-factor style electronic filters. Pfizer highlights the requirement for consideration of newly optimized S-factor cutoff functions not only when using different microscopy optical configurations, but also with differences in the optical properties of the particle/fluid system.

LINK was utilized for rapid data processing during the S Factor cut-off function optimization process, including application of new S Factor cut-off functions and evaluation of their effectiveness. LINK also helped the author’s achieve research results quicker by providing an automated importing, analysis, and reporting environment. The new abstract is available below and the 2018 & 2019 posters are available for download.

ABSTRACT: Aspects of silicone separation in protein-silicone mixtures using S-factor-style electronic filter
AUTHORS: E. Torres 1, A. Mehta 1 M. Lisowski 1, L. Rosner 1, P. Kolhe 1, C. Merchant 2, D. Thomas 2
1 Pfizer Biotherapeutics Pharmaceutical R & D;   2 Lumetics Inc.

Distinguishing between silicone oil vs. non-silicone oil particulates in protein formulations is important both in terms of accurately detecting protein aggregation during stress/stability, as well as for studying the protein-silicone oil interactions.

Strehl et al first reported a multi-parametric S-factor function capable of electronically filtering particles from data generated using ProteinSimple MFI 4100 flow microscopy system with a 400 µm flow cell. However, any function permitting distinction between silicone oil and proteinaceous particulates is dependent both on the optics and image processing of the flow microscopy system utilized, as well as the optical properties of the sample (i.e. difference in refractive Index between fluid and particulate).  Therefore, time-consuming offline data processing may be needed for S-factor optimization in each instance. To simplify the time consuming assessment and address optical properties challenges, we took an approach of understanding refractive properties of silicone oil/protein mixtures and used this to create an effective silicone oil filter using the Lumetics LINK software package.

In this poster an S-factor style filter was generated and applied to silicone oil and protein mixtures from data collected with a MFI 4200/5200 system and a 100 µm flow cell. A discussion on silicone oil quantification limitations due to a shift in solution refractive properties and linearity observed within silicone oil/protein mixtures as a function of specific particulate size ranges, will be presented.

S-Factor optimization for MFI using
Lumetics LINK™ 

2018 Pfizer and Lumetics co-publication

2018 Poster Download

Aspects of silicone separation in protein-silicone mixtures using S-factor-style electronic filter

2019 Pfizer and Lumetics co-publication

2019 Poster Download

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