Multidimensional Liquid Chromatography Is Breaking Through

Dwight R. Stoll

I recently attended the 45th International Symposium on High Performance Liquid Phase Separations and Related Techniques (HPLC 2017) conference in Prague, Czech Republic, in June. As usual it was a great meeting with excellent talks and poster presentations describing recent research in the field of liquid-phase separations. I was struck, though, by the level of attention paid to multidimensional separations that simply was not as evident in past meetings. Indeed, in the plenary talks by Professors Gert Desmet and Pat Sandra, they both discussed the point that to significantly improve the performance of liquid chromatography (LC) from where we are now, we need to move from one-dimensional (1D) to two-dimensional (2D) separations. This concept is not new of course (1), but advances in theory and instrumentation have put nonexperts in a position to use 2D-LC, in particular, more routinely and to solve a wide variety of analytical challenges (2).

So then, where do we go from here? Although some experienced scientists using 2D-LC in industry are convinced that it is “here to stay” and will have a role larger than that of a niche technique (3), it is not yet clear what share of all LC separations will be 2D separations in say, five years from now. Questions about cost, ease of use, robustness, and so on are important to many potential users who are considering 2D-LC, but have not committed yet. A few years ago one of the most important questions we talked about as affecting the scope of application of 2D-LC had to do with whether or not 2D-LC methods would find their way into use in regulated environments (that is, in quality control [QC] labs). Now, it seems we have at least a tentative answer to that question. In just the past year, two publications have described the development of 2D-LC methods intended for use in QC environments. The first, described by Largy, Delobel, and coworkers describes a heartcutting 2D-LC–mass spectrometry (MS) method for analysis of a protein therapeutic drug (4). The second, described by Yang, Zhang, and colleagues involves a heartcutting 2D-LC method for analysis of a small-molecule drug. Very importantly, this group demonstrated that their 2D method could be validated by adapting the existing validation framework normally used for 1D methods (5).

In my view, the most important questions that will affect further development and adoption of 2D-LC in the next few years have to do with method development. At this point I think it is fair to say that users new to 2D-LC find the number of method development variables a bit overwhelming. The question is, how can we develop concepts, strategies, and perhaps instrument components that help to simplify and streamline method development without sacrificing the performance potential of the technique? We are starting to see the building blocks of such strategies develop. For example, a number of groups have picked up on the idea of Pareto optimality to maximize peak capacity of 2D separations as a function of analysis time (6,7). Peter Schoenmakers’s group has also demonstrated the application of software developed for the purpose of maximizing the resolution of a particular sample by 2D-LC (8). At the HPLC 2017 meeting, Dr. Kelly Zhang described efforts by her group at Genentech to simplify column selection in 2D-LC method development (9). This is a very important and exciting development, which will undoubtedly have a big impact on the field.

While I agree with Dr. Venkatramani that 2D-LC is “here to stay” (3), it is of course difficult to predict just how much growth we will see in the next few years. I believe a compelling case can be made from recently published literature that 2D-LC can be used to both provide significantly more resolving power than 1D-LC, but in the same analysis time, and to significantly improve the speed of separation relative to 1D-LC, but without sacrificing resolution (for example, see references 10 and 11). Now, it is up to users to realize this performance potential, and the extent to which they do so will depend on how easily it can be done. At the moment there is tremendous growth in the use of 2D-LC for characterization of biopharmaceutical materials (12), which are becoming more complex by the day. I believe scientists working in this space and others will increasingly find “two-for-one” analyses like that described recently by a group from the U.S. Food and Drug Administration for the characterization of therapeutic antibodies in crude bioreactor supernatant (13) too good to refuse. Stay tuned!

References

1. J.C. Giddings, Anal. Chem.56, 1258A–1270A, doi:10.1021/ac00276a003 (1984).
2. D.R. Stoll and P.W. Carr, Anal. Chem.89, 519–531, doi:10.1021/acs.analchem.6b03506 (2017).
3. C.J. Venkatramani, “High Resolution Analysis of Linker Drugs Used in Antibody Drug Conjugates (ADCs) by 2D-LC-MS: Transition of 2D-LC-MS from Research to Main Stream Pharmaceutical Analysis,” presented at the 45th International Symposium on High Performance Liquid Phase Separations and Related Techniques (HPLC 2017), Prague, Czech Republic, 2017.
4. E. Largy, A. Catrain, G. Van Vyncht, and A. Delobel, Current Trends in Mass Spectrometry14(2), 29–35 (2016).
5. S.H. Yang, J. Wang, and K. Zhang, J. Chrom. A 1492, 89–97, doi:10.1016/j.chroma.2017.02.074 (2017).
6. M. Sarrut, A. D’Attoma, and S. Heinisch, J. Chrom. A1421, 48–59, doi:10.1016/j.chroma.2015.08.052 (2015).
7. G. Vivó-Truyols, S. van der Wal, and P.J. Schoenmakers, Anal. Chem.82, 8525–8536, doi:10.1021/ac101420f (2010).
8. B.W.J. Pirok, S. Pous-Torres, C. Ortiz-Bolsico, G. Vivó-Truyols, and P.J. Schoenmakers, J. Chrom. A1450, 29–37, doi:10.1016/j.chroma.2016.04.061 (2016).
9. K. Zhang, “Multiplexed mLC-nLC for Comprehensive Impurity Profiling: A Method Development ‘Free’ Platform,” presented at the 45th International Symposium on High Performance Liquid Phase Separations and Related Techniques (HPLC 2017), Prague, Czech Republic, 2017.
10. M. Sarrut, F. Rouvière, and S. Heinisch, J. Chrom. A1498, 183–195, doi:10.1016/j.chroma.2017.01.054 (2017).
11. L.W. Potts and P.W. Carr, J. Chromatogr. A1310, 37–44, doi:10.1016/j.chroma.2013.07.102 (2013).
12. D. Stoll, J. Danforth, K. Zhang, and A. Beck, J. Chrom. B1032, 51-60, doi:10.1016/j.jchromb.2016.05.029 (2016).
13. A. Williams, E.K. Read, C.D. Agarabi, S. Lute, and K.A. Brorson, J. Chrom. B 1046, 122–130, doi:10.1016/j.jchromb.2017.01.021 (2017).

Dwight Stoll is an associate professor and co-chair of chemistry at Gustavus Adolphus College in St. Peter, Minnesota.