Computer-based experiment design

Radiofrequency spectroscopy (NMR) was introduced in 1946 [158,159]. The development of the NMR method over the last 30 years has been characterised by evolution in magnet design and cryotechnology, the introduction of computer-based operating systems and pulsed Fourier transform methods, which permit the performance of new types of experiment that control production, acquisition and processing of the experimental data. New pulse sequences, double-resonance techniques and gradient spectroscopy allow different experiments and have opened up the area of multidimensional NMR and NMRI. 

Unlike most static design procedures, dynamic design requires a trial and error approach. Only in the verification of shear capacities and in the design of support connections can member proportions be directly determined. For the dynamic analysis, the needed nonlinear response properties are determined from a trial section. The analysis results then indicate the adequacy of the trial section. Experience on the part of the designer will help in reducing the number of iterations. The use of simple computer based design approaches help to reduce the time required for each analysis iteration. 

Both in the pharmaceutical industry and software companies specialized in computer-aided molecular design the demand for experts in the field interfacing medicinal chemistry and computer sciences will increase within the next decade. There is no doubt that we will experience an exciting period of substantial progress in pharmacophore-based VS technologies in the near future. 

Until recently, receptors were hypothetical macromolecules whose existence was postulated on the basis of pharmacological experiments. Although recent advances in molecular biology have led to cloning and expression of maity of those receptors whose existence was postulated as well as a plethora of subtypes, progress in most cases in defining their three-dimensional structure has yet to provide the medicinal chemist with the necessary atomic detail to design novel compounds. Without detailed information about the three-dimensional nature of the receptor, conventional computationally based approaches, such as... 

Chemical Reactor Design and Technology, Martinus Nijhoff, 1985, pp. 69-105] are also very useful. As indicated above, the acquisition of kinetic data and parameter estimation can be a complex endeavor. It includes statistical design of experiments, laboratory equipment, computer-based data acquisition, complex analytical methods, and statistical evaluation of the data. 

Model development (also called system identification) involves several critical activities including design of experiments and collection of data, data pretreatment, model fitting, model validation and acceptability of the model for its use. A vast literature has been developed over the last 50 years in various aspects of model identification [99, 170, 174, 246, 278]. A schematic diagram in Figure 4.2 where the ovals represent human activities and decision making steps and the rectangles represent computer-based computations and decisions illustrates the links between critical activities. 

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