A method for developing a computer model of diseased interactions between and among cortical and sub-cortical brain areas, comprising: a) forming a receptor competition model comprising receiving a plurality of user-selected therapeutic interventions to modulate a plurality of biological processes, each biological process from the plurality of biological processes being based on data that relates changes in activation state of the neuronal receptor to the activation state of a neuronal network the receptor competition model comprising a series of ordinary differential equations which regulate the receptor activation state in different situations and accounts for: pre-synaptic autoreceptor regulation of neurotransmitter release; specific presynaptic firing patterns; facilitation and depression of presynaptic vesicle release; the presence of endogenous neurotransmitter; and two agents competing for the same site with appropriate k on and k off values (agonist or antagonist); the receptors comprising dopamine D1; serotonin 5HT1A, 5HT2A and 5-HT3, norepinephrine alpha2A; muscarinic M1 and M2; and nicotinic a4b2 and a7, wherein the outcome of the receptor competition model modulates conductance in a pre-frontal cortex neuronal network comprising 20 pyramidal cells and 10 interneurons by changes to the ion channels of these neurons associated with these receptors; b) producing a simulated neuronal model output associated with at least one neuronal model output of the diseased interactions between and among cortical and sub-cortical brain areas based on the combined plurality of biology processes and the user-defined input in a), and c) translating the simulated neuronal model output to an effect on a clinical scale with appropriate confidence and prediction intervals, based upon statistical analysis, d) whereupon upon execution of the model for a number of drugs with a specific dose, a simulated neuronal model output for the biological state of the diseased interactions between and among cortical and sub-cortical brain areas is produced, the neuronal model output being substantially consistent with the effect of that number of drugs at that specific dose in at least one clinical scale currently used for assessing the clinical benefits in that disease, the degree of correlation quantified using regression analysis with the production of a regression equation. a) forming a receptor competition model comprising receiving a plurality of user-selected therapeutic interventions to modulate a plurality of biological processes, each biological process from the plurality of biological processes being based on data that relates changes in activation state of the neuronal receptor to the activation state of a neuronal network the receptor competition model comprising a series of ordinary differential equations which regulate the receptor activation state in different situations and accounts for: pre-synaptic autoreceptor regulation of neurotransmitter release; specific presynaptic firing patterns; facilitation and depression of presynaptic vesicle release; the presence of endogenous neurotransmitter; and two agents competing for the same site with appropriate k on and k off values (agonist or antagonist); the receptors comprising dopamine D1; serotonin 5HT1A, 5HT2A and 5-HT3, norepinephrine alpha2A; muscarinic M1 and M2; and nicotinic a4b2 and a7, wherein the outcome of the receptor competition model modulates conductance in a pre-frontal cortex neuronal network comprising 20 pyramidal cells and 10 interneurons by changes to the ion channels of these neurons associated with these receptors; b) producing a simulated neuronal model output associated with at least one neuronal model output of the diseased interactions between and among cortical and sub-cortical brain areas based on the combined plurality of biology processes and the user-defined input in a), and c) translating the simulated neuronal model output to an effect on a clinical scale with appropriate confidence and prediction intervals, based upon statistical analysis, d) whereupon upon execution of the model for a number of drugs with a specific dose, a simulated neuronal model output for the biological state of the diseased interactions between and among cortical and sub-cortical brain areas is produced, the neuronal model output being substantially consistent with the effect of that number of drugs at that specific dose in at least one clinical scale currently used for assessing the clinical benefits in that disease, the degree of correlation quantified using regression analysis with the production of a regression equation.