Aristotle University of Thessaloniki

1. Aristotle University of Thessaloniki Retention Prediction and separation optimization under multilinear gradient elution in HPLC with Microsoft Excel Macros S.FasoulaA,*, H. GikaB, A. Pappa-LouisiA, P. NikitasA ADepartment of Chemistry, Aristotle University of Thessaloniki B Department of Chemical Engineering, Aristotle University of Thessaloniki

2. The aim The exploration of Excel 2010 or 2013 capabilities in the whole procedure of separation optimizations under multilinear gradient elution in HPLC application of systematic optimization strategies much easier for the majority of chromatographers Microsoft Excel : friendly computational environment Fasoula Stella, Aegean Analytical Chemistry Days 2014, Chios TheExcel versions up to 2007 did not equip with the proper optimization tool. In the new versions, 2010 and 2013, the Solver add-in provides optimization capabilities when the cost function is not differential, like those adopted in liquid chromatography.

3. The steps… of a computer-assisted separation optimization under multilinear organic modifier gradient elution based on gradient retention data 1 2 Fasoula Stella, Aegean Analytical Chemistry Days 2014, Chios 3

4. The retention models examined 1. 3. 2. • ksoluteretention factor,k=(tR-t0)/t0 • tRsolute retention time t0column dead time • φis the organic modifier volume fraction • c0,c1, c2are the adjustable parameters Fasoula Stella, Aegean Analytical Chemistry Days 2014, Chios 4. 5. 6.

5. Determination of retention model by initial gradient data … The optimization procedure demands the solution of the fundamental gradient elution equation has an analytical solution only in case of multilinear organic modifier gradient occurs AND P.Nikitas, A. Pappa-Louisi, A. Papageorgiou, J. Chromatogr. A 1157(2007)178-186 Fasoula Stella, Aegean Analytical Chemistry Days 2014, Chios The solute retention is described by • Retention models 1-5 • Retention model 6 -Nikitas-Pappa's (NP) approach was adopted for the solution of the fundamental equation.

6.  6 5 4 3 2 1 in 2  1 0t1t2 t3t4 t5 t6 t Our approach… The multilineargradient profile is divided into subsections, so that at each φ range the dependence of ln k vs. φ to be linear, although the total retention model is not linear Fasoula Stella, Aegean Analytical Chemistry Days 2014, Chios

7. Example of the whole optimization procedure Step 1 Fitting procedure Retention data Fasoula Stella, Aegean Analytical Chemistry Days 2014, Chios 12 solutes (purines, pyrimidines, nucleosides) Under 5 different gradient conditions

8. Results… Fasoula Stella, Aegean Analytical Chemistry Days 2014, Chios • Even in case an analytical solution exists, sometimes the solver is trapped in local minima and gives unreliable adjustable parameters, and then our approach to solve the fundamental gradient elution equation is a good alternative method. • M5 and M6 exhibit the best fitting performance among the 4 models with three adjustable parameters. • Our approach is a very satisfactory method to solve the fundamental gradient elution equation, especially in case there is no analytical solution. • M3 exhibits the best fitting performance between the 2 models with two adjustable parameters

9. Step 2 The prediction ability of the retention models derived in the fitting procedure is detected on the prediction spreadsheets using the experimental retention data obtained under7 mono-linear and 4 bilinear gradient profiles Fasoula Stella, Aegean Analytical Chemistry Days 2014, Chios Prediction procedure

10. Results… Fasoula Stella, Aegean Analytical Chemistry Days 2014, Chios the M6 model seems to be the proper choice to be used in the optimization procedure.

11. Step 3 Once the proper retention model is adopted the optimal gradient profile is determined on the proper optimization spreadsheet using the corresponding adjustable parameters Optimization procedure Fasoula Stella, Aegean Analytical Chemistry Days 2014, Chios

12. Conclusions • We created Excel spreadsheets that can be adopted both for a computer-assisted optimization of chromatographic separations and for metabolite identification by the majority of chromatographers without some experience or knowledge of programming • Microsoft Excel is a user-friendly environment due to its unique features in organizing, storing and manipulating data using basic and complex mathematical operations, graphing tools, and programming. Fasoula Stella, Aegean Analytical Chemistry Days 2014, Chios

13. Acknowledgement The project is implemented under the Operational Program “Education and Lifelong learning" and is co-funded by the European Union (European Social Fund) and National Resources (Excellence II: Metabostandards 5204) Fasoula Stella, Aegean Analytical Chemistry Days 2014, Chios

14. THANK YOU FOR YOUR ATTENTION! QUESTIONS? Fasoula Stella PhD studentDepartment of Chemistry Aristotle University of Thessaloniki