Fuzzy analysis of pharmaceutical effects in vascular dementia

Large pharmaceutical trials are now underway to assess the effectiveness of cholinesterase drugs in slowing the cognitive decline in vascular dementia. Current trials use probability based statistics in which mean values of cognitive measures are compared between treatment and placebo groups. Several limitations exist in traditional drug study designs that impact patient selection criteria, preclude identification of potentially high efficacy subpopulations, and constrain the applicability of study results in treating the individual. We propose that fuzzy logic based mathematical methods can augment conventional methods of data analysis in pharmaceutical trials to overcome existing limitations and provide more effective treatment algorithms in drug therapy. To illustrate this possibility, we intend to analyze data from a group of patients with vascular dementia given cholinesterase drug therapy using both fuzzy and probability based methods.