The statistican must apply experimental designs for mixtures of ingredients, taste testing using hedonic scales, and numerical and graphical optimization techniques. Build response surface models to describe the performance of a chemical formulation in terms of its component levels. This may begin as a classic factorial study, then blend chemical knowledge with empiricism to develop meaningful models. Ultimately, nonlinear mechanistic models may be identified to describe the chemical kinetics. Predict the properties of compounds which have not yet been synthesized in any lab , by supporting computer aided molecular design based on molecular property descriptors.
Statisticians develop optimum design strategies which minimize the number of syntheses required.
Innovative modeling techniques enable continuous refinement of the molecular models to provide better predictions of the most promising compounds. High-throughput testing generates unprecedented volumes of data on both the synthesis conditions and the evaluated performance of each compound . High-dimensional data visualization and mining techniques ensure that the valuable information in these data will be discovered. Analytical chemists often generate spectra instead of single-number results. Chemometric techniques draw upon multivariate statistics to reduce large sets of numbers to a meaningful few.