Taylor Dispersion Analysis for Peptide and Protein Characterization monomer and one containing 96.8%. Possible contributory factors for this difference may include the fact that the samples were diluted for the HP-SEC analysis, whereas the TDA and DLS samples were run without dilution. Stress studies can form part of the drug development process but would generally use lower temperatures than that employed above. A comparison of the ability of TDA and DLS to identify size changes after a longer isothermal temperature hold was undertaken. During a one-week stability study of etanercept performed at 50°C, a comparable observation to those obtained in the previous paragraph was made: the rzave (DLS) increased to a higher level, i.e. from 6.7 nm to 20.6 nm after 7 days at 50°C, than the rh (TDA), which increased from 7.0 to 7.5 nm. However, for both DLS and TDA the increases in rzave (DLS) and rh (TDA) were found to be significant at day 3 of the stability study. The differences between DLS and TDA in their apparent sensitivity to detect aggregation can be explained by the different underlying measurement principles of the two techniques. DLS is biased to larger sizes, because the intensity of the scattered light is proportional to the sixth power of the radius (6). In particular, larger aggregates will contribute more to the overall scattering intensity, and the rzave is shifted to larger sizes. In TDA, the diffusion coefficient is derived from the band broadening measured by UV absorbance. For a molar concentration-based detector system, it can be assumed that monomeric and aggregated protein molecules are detected equally (neglecting the contribution of light scattering to the optical density at this point) and thus averaging of the hydrodynamic radii of mixtures is a number average (13). The inference is that TDA is more weighted and suited to studies where the focus is protein-protein interactions and DLS will more readily identify the larger sized aggregates that their scattering by intensity produces. CONCLUSIONS This work has explored the use of TDA in its new format linked to a pixilated area detector and compared it with DLS to determine the hydrodynamic radius of an extensive range of peptide and protein sizes in therapeutic formulations over a wide concentration range and after stress testing. Our findings suggest that DLS and TDA have some applications of overlap but that their different physical basis for the determination of size gives rise to different strengths for the sizing of biopharmaceuticals and their aggregates. For relatively pure unstressed protein formulations (BSA, etancercept and mono- clonal antibodies), TDA and DLS resulted in comparable results for the hydrodynamic radius in the concentration range from 0.5 to 50 mg/ml. Lower protein concentrations (0.05 mg/ml), as well as the small peptide oxytocin, could only 2309 be sized correctly by TDA, whereas DLS resulted in much larger values for the radius than theoretically expected. Another advantage of TDA is that it can be selectively tuned to detect the protein at low concentration and obviate the strong contributory factors that some excipients can make to DLS results. When focusing on the detection of aggregation after stress testing, both DLS and TDA identified significant size change for three protein systems after stressing. TDA compared to DLS was less sensitive in a fourth case. An explanation lies in the fact that the underlying principle of DLS is weighted to the detection of larger particles, and as a consequence also explains the differences in the absolute values obtained for the two methods. ACKNOWLEDGMENTS This research was supported, in part, by the Dutch Technology Foundation STW, Applied Science Division of NWO and the Technology Program of the Ministry of Economic Affairs. The authors also acknowledge the EPSRC grant (DT/F002564/1) for funding as part of a TSB collaborative research project. Open Access This article is distributed under the terms of the Creative Commons Attribution Noncommercial Li- cense which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. REFERENCES 1. Fraunhofer W, Winter G. The use of asymmetrical flow field-flow fractionation in pharmaceutics and biopharmaceutics. Eur J Pharm Biopharm. 2004;58:369–83. 2. Philo JS. Is any measurement method optimal for all aggregate sizes and types? AAPS J. 2006;8:E564–71. 3. Philo JS. A critical review of methods for size characterization of non-particulate protein aggregates. Curr Pharm Biotechnol. 2009;10:359–72. 4. 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