Design and Optimization in Organic Synthesis

The methodologies are based upon multivariate mathematical and statistical methods which make it possible to consider all pertinent factors simultaneously: Such methods also make it possible to establish quantitative models which relate variations of the reaction system and experimental conditions to the observed result. Examples of multivariate methods used in the project are: Response surface modelling, principal component analysis and partial least squares (PLS) correlations in latent variables. It is investigated how such methods in connection with statistical principles for experimental design should be adopted for solving problems encountered in organic synthesis so that the desired information can be obtained from a limited number of experime ntal runs. Strategies are developed for answering the following type of questions: Which experimental factors and which properties of the reaction system have a significant influence on the result? How do these factors exert their influence? Why are they important? A new method for analyzing reaction kinetics is explored. The use of quantum chemical computation for obtaining relevant descriptors for multivariate modelling is studied. To develop the methodology, a strategy for optimizing multistep one-pot batch processes is developed. New synthetic reactions are explored: The preparative use of halogenated vinyl ketones for producing synthons is analyzed. New synthetic bulding blocks based upon donor-substituted cyclic ketones are investigated. The main focus is to develop methods for regio- and steroselective conjugat addition and Diels-Alder reaction with <.alfa.>-donor-<.alfa.>, <.beta.>-unsaturated ketones as dienophils. A gener al strategy for optimizing critical steps in multistep synthesis is developed.