Developing models for predicting

While the intrinsic activity and selectivity of a catalyst establish its performance in the absence of mass transfer effects, it is well known that the placement of the active components and access to these components by reactants can play a major role in the performance of practical catalysts. One of the challenges for reaction engineers is to develop models for predicting the distribution of active components in a catalyst and the effects of this distribution, together with the pore size distribution and particle size and shape, on the performance of a catalyst. 

We employed two popularly used machine learning methods, SVM and RF, to develop models for prediction and screening of the potential FXa inhibitors. A brief introduction to each of these two machine learning methods is summarized as below. 

The challenges in developing models for predicting solubility can arise from a number of experimental factors. The aqueous solubility of a compound can vary depending on a number of factors including ... 

Tutorial Developing Models for Solubility Prediction with 18 Topological Descriptors... 

UNIFAC andASOG Development. Pertinent equations of the UNIQUAC functional-group activity coefficient (UNIFAC) model for prediction of activity coefficients including example calculations are available (162). Much of the background of UNIFAC involves another QSAR technique, the analytical solution of groups (ASOG) method (163). 

The method for estimating point efficiency, outhned here, is not the only approach available for sieve plates, and more mechanistic methods are under development. For example, Prado and Fair [Ind. Eng. Chem. Re.s., 29, 1031 (1990)] have proposed a method whereby bubbling and jetting are taken into account however the method has not been vahdated tor nonaqueous systems. Chen and Chuang [Ind. Eng. Chem. Re.s., 32, 701 (1993)] have proposed a more mechanistic model for predicting point efficiency, but it needs evaluation against a commercial scale distillation data bank. One can expect more development in this area of plate efficiency prediction. 

A combination of thermodynamic analysis and experimental data on the deposition rates, efficiencies and deposit morphologies as a function of CVD variables may be used to develop models for the deposition processes. In the case of CVD of borides such a predictive model has been created so far only for a CVD system in which TiBj is obtained by reduction of TiCl4 and BCI3 with... 

A challenge particularly suited to chemical engineers is the development of process models for predicting the microstiucture and surface stiucture of catalysts as a function of the conditions of their preparation Such models could be used not only to guide the preparation of existing materials, but also to explore possibihties for making novel catalysts. 

Pelander et al. [81] developed a computer program for optimization of the mobile phase composition in TLC. They used the desirability function technique combined with the PRISMA model to enhance the quahty of TLC separation. They apphed the statistical models for prediction of retardation and band broadening at different mobile phase compositions they obtained using the PRISMA method the optimum mobile phase mixtures and a good separation for cyanobacterial hepatotoxins on a normal phase TLC plate and for phenolic compound on reversed-phase layers. 

A low accuracy of models for prediction of log D at any pH would not encourage the use of these models for practical applications in industry. Thus, it is likely that the methods for log D prediction at fixed pH that are developed in house by pharmaceutical companies will dominate in industry. However, log D measurements... 

Johnson and Swindell [77] developed a method for evaluating the complete particle distribution and its effect on dissolution. This method divided the distribution into discrete, noncontinuous partitions, from which Johnson and Swindell determined the dissolution of each partition under sink conditions. The dissolution results from each partition value were then summed to give the total dissolution. Oh et al. [82] and Crison and Amidon [83] performed similar calculations using an expression for non-sink conditions based on a macroscopic mass balance model for predicting oral absorption. The dissolution results from this approach could then be tied to the mass balance of the solution phase to predict oral absorption. 

A model for predicting oral bioavailability is an important tool, both in the early phases of drug discovery to select the most promising leads for further optimization, and in the later stages to select candidates for clinical development. The... 

The Langmuir model for competitive adsorption can be used as a common model for predicting adsorption equilibria in multicomponent systems. This was first developed by Butler and Ockrent [77] and is based on the same assumptions as the Langmuir model for single adsorbates. It assumes, as in the case of the Langmuir model, that the rate of adsorption of a species at equilibrium is equal to its desorption rate. This is expressed by Eq. (18) ... 

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