Multi-objective optimization and Design of Experiments as tools to tailor molecularly imprinted polymers specific for glucuronic acid Stephanie Kunath1), Nataliya Marchyk2), Karsten Haupt2), Karl-Heinz Feller1) 1)University of Applied Sciences Jena, Department of Medical Engineering and Biotechnology, Jena, Germany 2)Enzyme and Cell Engineering Laboratory, UMR CNRS 6022, Compiègne University of Technology, Compiègne, France INTRODUCTION DoE Molecularly imprinted polymers (MIPs) are tailor-made biomimetic receptors showing high affinity and selectivity for target molecules.  Block diagram: influencing factors (x1 - x3) objective parameters (y1 - y4) O They are obtained by polymerization of functional and cross-linking monomers in the presence of molecular templates, and contain binding sites with "memory" for the size, shape and chemical functionality of the template molecule. NH HN NH H O H C OH H O O O OH OH O NH2 •Bmax – maximal absorption of GA at its saturating concentration (measure of capacity) •K50 – polymer concentration at half maximum absorption of GA (measure of affinity) •B2 – relative absorption of GA at 2 mg/mL of polymer •IF – imprinting factor Figure 1. Schematic Representation of the Molecular Imprinting Procedure MIP = COMPLEX SYSTEM  3 influencong factors with 2 factor levels = Compositional / operational factors dependency Influencing factors Factor levels MAM, eq to analyte 3 7 CL, % 60 83 AIBN, mol% of double bonds 0,56 1  Multi-objective optimization based on Derringer and Suich (Derringer, G. et al. 1980) - Optimization of MIP improving parameters via desirability functions; - Surface response plots; MIP performance is a function of : - Monomers [nature, distribution, amount] - Initiator [nature, amount] - Porogenic solvent - Physical form - Type of initiation [UV/VIS/ ∆] RESULTS = Important to understand factors interaction and dependancy GOOD BAD Objectives We present a multi-objective optimization of binding properties of MIPs based on a Design of Experiments (DoE) plan. The power of the applied optimization methods is illustrated using a polymer imprinted withthe template glucuronic acid as a model. Model template glucuronic acid As a model target a biologically important molecule was used, glucuronic aid, an important building block of glycoconjugates such as e.g. hualuronan and chondroitin sulfate which represent parts of proteoglycons in the intercellular matrix (glycocalix) (Kobata, A. et al. 2005) and of cartilage. Glucuronic acid is also part of many glycoconjugate drug metabolites (Baillie, T.A. ey al. 2002) EXPERIMENTAL To optimize the MIP : MIP synthesis Target template HO Functional monomers NH O O NH2 OH HN OH OH Β-D-glucuronic acid (GA) Cross-linking monomer O O O Methacrylamide (MAM) Porogen O S O Acrylamido benzamidine (AAB) Radical initiator CN CN N N O Ethyleneglycol dimethacrylate Anhydrous DMSO Predicted best polymer: 83% CL, 3eq MAM, 0.65 mol% AIBN NH2 OH O  Lower GA MAM equivalent, Increase cross-linking degree (A)  Use 0.65 mol% of initiator with low MAM concentration (B) and high cross-linking degree (C) Comparison of optimized polymer with the starting point polymer: ‘Affinity’ : 6 times ↗ ‘Capacity’ : 40% ↗ IF : 1.3 times ↗ Equilibrium binding isotherms of the predicted polymer (M-MIP, R-reference polymer) in methanol:water (9:1 vol) AIBN - The ratio GA : AAB = 1:1 was kept constant; - Polymerization by precipitation, 50°C, overnight - Polymers were synthesized according to a full factorial experimental design plan based on 3 influencing factors (crosslinking degree (CL), monomer (MAM) and initiator (AIBN) concentrations); MIP evaluation - Equilibrium binding experiments with radioligand GA[14C] in methanol:water (9:1); - Analysis of binding parameters with ANOVA, regression analysis and multi-objective optimization method based on a desirability approach. CONCLUSIONS • Comprehensive multi-objective optimization of the binding properties of MIPs has been performed; •Cause-effect-correlations of factors were determined. • In addition, an optimal glucuronic acid binding polymer composition was also found for use in pure water as the solvent (not shown) ; Acknowledgements The authors thank EFRE (TNA VI-1/2009) and the region of Picardy, France (Glycosense project) for financial support.