Selectivity optimization

Current research in LHASA is focused on developing new methods assisting users in choosing the most appropriate strategy for their target structures. Furthermore, the development of criteria for the evaluation of synthesis routes and/or algorithms for selecting optimal synthesis routes within the tree are discussed [34]. 

When or if the reservoir is successfully simulated, the engineer can turn to optimizing petroleum recovery, and theoretical ideas can be applied to models for various enhanced recovery methods to select optimal procedures and schedules (see Chapter 7). 

A number of manual and computer-aided strategies available as a guide to selectivity optimization. The relat merits of these approaches are discussed in section 4.6.2. 

The remainder of this section deals primarily with selectivity optimization in isocratic liquid chromatography and with gradient elution Before entering these subjects proper, however, a discussion of the relevant chromatographic properties of solvents is in order as a framework for the intuitive selection of the preferred solvent or solvent mixtures for selectivity optimization. 

If the selectivity optimization is carried out manually, then the quality of the separation may be compared by visual Inspection of the chroautograms. This approach, however, is inadequate for automated cptimizatlon procedures, and the quality of a chromatogram must be expressed by a single-valued and easily calculated miathematical fiinction [478,479,484,525,53. 33]. This... 

Once the selectivity is optimized, a system optimization can be performed to Improve resolution or to minimize the separation time. Unlike selectivity optimization, system cqptimization is usually highly predictable, since only kinetic parameters are generally considered (see section 1.7). Typical experimental variables include column length, particle size, flow rate, instrument configuration, sample injection size, etc. Hany of these parameters can be. Interrelated mathematically and, therefore, computer simulation and e]q>ert systems have been successful in providing a structured approach to this problem (480,482,491-493). 

For the / ARK PH domain example considered here, the rc estimate using Eq. (15) gave 8.22 ns, while the model-selection optimization yielded rc = 8.27 ns, both values in good agreement with those derived using a more accurate fit (Fig. 12.3). 

Chemometrics is the chemical discipline that uses mathematical and statistical methods measurement procedures and experiments, and (b) to provide maximum chemical information by analyzing chemical data."(I)... 

The nature of combinatorial chemistry can present a considerable challenge because these libraries are generally produced as arrays of compounds and it is often inconvenient to synthesize individual compounds in order to achieve an optimal design. Two methods have been described that attempt to select optimal subset of reagents from a virtual library that has been partitioned into favorable and unfavorable compounds by some method of filtering. The PLUMS algorithm [97] was designed to simultaneously optimize the size of the library based on effectiveness and efEciency . 

Wermuth CG. (2004) Selective optimization of side activities Another way for drug discovery. /. Med. Chem. 47 1303-1314. 

In 1997, D.L. Massart suggested the following definition "Chemometrics is a chemical discipline that uses mathematics, statistics and formal logic (a) to design or select optimal experimental procedures (b) to provide maximum relevant chemical information by analyzing chemical data and (c) to obtain knowledge about chemical systems" (Massart et ah, 1997). 

A systematic procedure can select optimal solvent blends for nonreactive, multi-component absorption processes accounting for plant-wide point source environmental interactions. This approach, based on the optimal design technique for pure solvents, involves the identification of all agent-based operations (such as gas absorption and... 

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