Multiparameter optimization

Table IV. Combinations ot Experimental Variables for Simplex or Other Multiparameter Optimization in SFC ...

In contrast to the minor difference in the minimum resolution, however, the difference in the analysis time for the two optimized separations (Figures 6 and 10) was significant The 30% shorter analysis time of 27 min for the optimized density/temperature method compared to 37 min for the density-only optimization clearly demonstrates the superiority of multiparameter optimization strategies. Had the arbitrarily selected temperature of 80°C (2.83 10 3 K l) not been relatively close to the true optimum temperature of 104 °C (2.65 10 3 K"l), the difference would have been even more dramatic ... 

Siclovan, O., Fluorescence spectroscopy and multivariate spectral descriptor analysis for high-throughput multiparameter optimization of polymerization conditions of combinatorial 96-microreactor arrays, J. Comb. Chem. 2003, 5, 8-17. 

Riester et al. [103] presented a series of thrombin inhibitors that were generated by using powerful computer-assisted multiparameter optimization process, which was organized in design cycles starting with a set of 170 ran-... 

Process development is a multiparameter optimization problem. It is not surprising, therefore, that notv that the technology is available to parallelize and automate organic synthesis, it is applied in this field. 

Preceding the first 29Si ENDOR measurement22,94, its feasibility had to be estimated for the correlation rotation time, the most essential condition in the multiparameter optimization experiment, a irot range 0.2 to 3 ns22,94 was correctly predicted both from molecular and from theoretical considerations. 

Another method for synthesis of useful derivatives of L-acosamine and L-daunosamine from rhamnal 23 was based on addition of chlorosulfonyl isocyanate to 2,3-unsaturated pyranosides 73 [66,67]. Since the anomeric alkyl substituent in this reaction ends up as the carbamate ester, aUyl glycoside securing easy deprotection was chosen for elaborating this reaction into large laboratory scale technical process. Method development for acosam-inal derivative 74 involved multiparameter optimization of the isocyanate addition step by exploration of the reaction response surface. The final daunosaminyl glycosylation synthon 76 was obtained in overall 35% yield (Scheme 12) [68]. 

Table 5.3. Variable Input Parameters (Process Conditions) for High-Tbrou put Multiparameter Optimization of Polymerization Conditions of Combinatorial 96-Microreactor Arrays ...

Bioisosteric replacement is often considered when tbe aims are to maintain enzyme potency wbUe optimizing additional properties, sudi as cellular penetration, solubility, metabolism, toxidty, and so on. This prindple is often referred to as multiobjective optimization (MOOP) or multiparameter optimization (MPO) [12]. There are many ways in which one can address multiple objectives, but it is important to understand the landscape of the trade-off surface between each of the important... 

Iterative methods are interpretive methods in which new experiments can be added to the small number of starting experiments in order to refine the surface retention for all the solutes, and to predict more accurately the optimum location in the parameter space. For single-parameter optimization both graphical and mathematical methods can be used, but for multiparameter optimization computerized methods are necessary. 

The Tophss Tree is an enduring tool for the iterative optimization of a chemical series where it is not possible to synthesize aU close analogs (i.e., for all medicinal chemistry projects) Figure 8.2 illustrates the practical application of the method. The continued popularity of the Tophss Tree (although, in the authors view, the tool is shU underused by medicinal chemists) is perhaps explained by the simplicity and visual applicatiou of the approach. However, the method is without a strong mathematical framework, which limits its apphcabihty to more complex problems, such as multiparameter optimization (MPO). 

We use MMP approaches to analyze primary SAR, selectivities, and anti-target S ARs. Results of an MMP analysis are presented in the form of HTML or PDF reports, which show the constant region of the molecular series on the left-hand side followed by the variable region of each individual compound (cf Figure 13.6) sorted by the property of interest. Activity can be substituted by any other property that is part of the multiparameter optimization problem, for example, solubility or ADMET endpoints. Data interpretation is facilitated by color coding. 

Some parameters may show synergistic effects on separation. In this case, simultaneous optimization of two or more parameters can provide better results than their sequential optimization. Simple methods can be used for sequential multiparameter optimization in HPLC. 

Wager, T.T., Hou, X., Verhoest, P.R., and Villalobos, A. (2010) Moving beyond rules the development of a central nervous system multiparameter optimization (CNS MPO) approach to enable alignment of druglike properties. ACS Chemical Neuroscience, 16,435-449. 

Multiparameter Optimization Identifying High-Quality Compounds... 

Multiparameter Optimization identifying High-Quaiity Compounds 435... 

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