Compound selection factorial design

Factorial design methods cannot always be applied to QSAR-type studies. For example, i may not be practically possible to make any compounds at all with certain combination of factor values (in contrast to the situation where the factojs are physical properties sucl as temperature or pH, which can be easily varied). Under these circumstances, one woul( like to know which compounds from those that are available should be chosen to give well-balanced set with a wide spread of values in the variable space. D-optimal design i one technique that can be used for such a selection. This technique chooses subsets o... 

Figure 3. The substituents Rl, R2 and R3 can be selected using a fractional factorial design (FFD). Firsts, the eight substituents candidates were plotted on a 2D space of PPs (p, and p2) and four representatives (A, ++ B, —t F, — H + -) were extracted. Then, these were combined according to the FFD scheme to obtain a series of eight compounds.

Winter, D., M. Cashmore, M. Coleman, G. Errington, and P. White The apphcation of a two level factorial design to the selective reduction of phenohc compounds in mainstream smoke using ceUulose acetate filters 60th Tobacco Science Research Conference, Program Booklet and Abstracts, Vol. 60, Paper No. 46,2006, p. 45. 

The philosophy of the factorial approach is attractive, so are there related techniques which are more appropriate to the special requirements of chemistry There is a number of other methods for experimental design but one that is becoming applied in several chemical applications is known as D-optimal design . The origin of the expression D-optimal is a bit of statistical jargon based on the determinant of the variance-covariance matrix. As will be seen in the next section on compound selection, a well-chosen set of experiments (or compounds) will have a wide spread in the... 

Experimental design—compound and parameter selection Table 2.9 Factorial design for three parameters... 

A set of compounds substituted in the 5 -position was designed to explore the physiochemical parameter space represented by 7C, F, R and MR. This initial compound set was restricted to cover these minimum parameters in the interest of efficiency. Later, if the level of activity warranted it, the initial set could be expanded to more fully explore parameter space. In order to adequately cover the chosen parameter space, a 2 factorial design was utilized. ( 5) The 16 required compounds were selected via cluster analysis from our substituent physical-chemical database. ( ) Marker points which represented the factorial design were included in the data set prior to clustering. (2) In this way substituents which best represented the factorial design were those that were... 

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