Abstract
In this report we demonstrate a practical multivariate design of experiment (DoE) approach for asymmetric flow field-flow fractionation (AF4) method optimization using separation of lipoprotein subclasses as an example. First, with the aid of commercially available software, we built a full factorial screening design where the theoretical outcomes were calculated by applying established formulas that govern AF4 channel performance for a 5–35 nm particle size range of interest for lipid particles. Second, using the desirable ranges of instrumental parameters established from theoretical optimization, we performed fractional factorial DoE for AF4 separation of pure albumin and ferritin with UV detection to narrow the range of instrumental parameters and allow optimum size resolution while minimizing losses from membrane immobilization. Third, the optimal range of conditions were tested using response surface DoE for sub-fractionation of high and low density lipoproteins (HDL and LDL) in human serum, where the recovery of the analytes were monitored by fraction collection and isotope-dilution LC-MS/MS analysis of each individual fraction for cholesterol and apolipoproteins (ApoA-1 and ApoB-100). Our results show that DoE is an effective tool in combining AF4 theoretical knowledge and experimental data in finding the most optimal set of AF4 instrumental parameters for quantitative coupling with LC-MS/MS measurements.
Highlights
Field-flow fractionation (FFF) is a group of separation techniques discovered in the 1970s by J
One of the unique power of the AF4 technique is that optimal separation can be achieved purely through adjustment of the instrumental parameters by the user, without relying on proprietary size exclusion column chromatography packing
We believe that the design of experiment (DoE) approach empowers users to exploit the full potential of AF4 and to be able fine tune their methods with an efficient systematic manner to a specific size range and analyte group of interest, for their specific qualitative or quantitative analytical needs
Summary
Field-flow fractionation (FFF) is a group of separation techniques discovered in the 1970s by J. Asymmetric flow FFF (AF4), has become a frequently used commercially available pre-analytical technique for measuring macromolecules, polymers and metal nanoparticles [2,3,4,5]. In this report we demonstrate a design of experiment (DoE) workflow for optimization of AF4 methods. We adapted DoE (or quality-by-design, QbD) approaches used by numerous software products (Drylab, ChromSwordAuto, ICOS, Osiris, Diamond, and PESOS), that are currently used for optimization of chromatographic separations. We demonstrate a similar approach, using a generic commercial statistical design software, JMP (SAS Institute). Applying DoE with a combination of the theoretical models and experimental data should help to make AF4 as an analytical separation technique more accessible to new users who want to develop and optimize their methods to specific analytes in the particle size range and resolution of interest
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