Patent ID: 8150629
Filing Date: 2012-04-03
Classification: G09B,G16H

Abstract:
1. A method for predicting clinical effects of a proposed pharmacological therapy for treating a known neurological disease associated with neuronal circuits within and among cortical and sub-cortical brain regions, comprising the steps: simulating a plurality of interconnected neuronal circuits within and among different regions of a human brain afflicted with said neurological disease, each of the simulated circuits being separately modeled with the use of actual data about the neurological disease, wherein said different regions include the cortex, and at least one of the striatum, hippocampus, amygdala, ventral tegmentum area, locus coeruleus, dorsal raphe and substantia nigra, and the simulated circuits include simulating the functional effects of each of a plurality of known pharmacological therapies on the receptors in said simulated circuits to thereby produce corresponding simulated biological effects on the interconnected neuronal circuits; deriving a regression equation quantitatively correlating said simulated biological effects of said known therapies with the known clinical effects of said therapies on a clinical scale related to said neurological disease; adjusting at least some parameters associated with said simulated circuits in order to develop modified simulated circuits resulting in a regression equation output having increased confidence measures of correlation between said simulated biological effects and said known clinical effects; simulating the functional effects of a proposed pharmacological therapy on the receptors in said modified simulated circuits to thereby produce corresponding simulated biological effects on the interconnected neuronal circuits and inputting said simulated biological effects of said proposed pharmacological therapy into said regression equation; and outputting from the regression equation a predicted quantitative clinical effect of the proposed pharmacological therapy on said clinical scale, together with a corresponding confidence measure for said predicted quantitative clinical effect, wherein the steps are performed in a programmed computer.