Informatics

Using a priori biological knowledge and preselected SNPs within a finite set of xenobiotic metabolizing and transport genes, assist in the development of clinical decision support algorithms which classify and predict pharmacokinetic and pharmacodynamic response to a panel of commonly prescribed psychotropic and analgesic medications by reducing the dimensionality inherent to permutations and combinations of drug-drug, drug-gene, and gene-gene interactions.

Co-developed a novel data reduction method which facilitates pairwise comparisons across single enzyme phenotypes and a composite (5 enzyme) phenotype.

Co-developed a methodologically consistent approach for the augmentation of a budget impact model.

Co-developed a methodology to evaluate the performance of several versions of the same clinical decision support algorithm via simulation.

Head of automation and statistical analyses of the above simulation using SAS & R.