Method of identifying and treating dopamine-related disorders and 5-HT 2c- related disorders

Abstract

This invention relates to a method of treating a dopamine-related disorder (such as a dopamine deficit-related disorder or excess dopamine-related disorder) or a 5-HT2C-related disorder (such as a 5-HT2C-hyperactivity disorder or 5-HT2C-hypoactivity disorder) in a patient in need thereof comprising administering a therapeutically effective amount of a dopamine-modulating agent (e.g., a dopamine increasing agent or dopamine decreasing agent) or a 5-HT2C-modulating agent (e.g., a 5-HT2C antagonist or 5-HT2C agonist), where the patient prior to treatment exhibits high or low EEG sample entropy using low gamma frequency range (30-40 Hz) electroencephalography.

Description

[0001] METHOD OF IDENTIFYING AND TREATING DOPAMINE-RELATED DISORDERS AND 5-HT2C-RELATED DISORDERS

[0002] CROSS-REFERENCE TO RELATED APPLICATION

[0003] [1] This application claims the benefit of U. S. Provisional Application Nos. 63 / 728,053, filed December 4, 2024, 63 / 753,298, filed February 3, 2025, 63 / 753,366, filed February 3, 2025, and 63 / 815,640, filed May 31, 2025, the contents of each are hereby incorporated in their entirety.

[0004] FIELD OF THE INVENTION

[0005] [2] This invention relates to a method of treating a dopamine-related disorder (such as a dopamine deficit-related disorder or excess dopamine-related disorder) or a 5-HT2C-related disorder (such as a 5-HT2c-hyperactivity disorder or 5-HT2C-hypoactivity disorder) in a patient in need thereof comprising administering a therapeutically effective amount of a dopamine-modulating agent (e.g., a dopamine increasing agent or dopamine decreasing agent) or a 5-HT2c-modulating agent (e.g., a 5-HT2C antagonist or 5-HT2C agonist), where the patient prior to treatment exhibits high or low EEG sample entropy using low gamma frequency range (30-40 Hz) on electroencephalography.

[0006] BACKGROUND OF THE INVENTION

[0007] [3] Clinical care for depression involves assessment and diagnosis based on a set of clinician-assessed and patient-reported symptoms such as depressed mood, anhedonia, appetite changes, sleep and psychomotor changes but notably no biological or quantitative behavioral variables. When an assessment such as a magnetic resonance imaging (MRI) scan or a blood test is performed, it is to rule out non-psychiatric causes of depression which may necessitate treatments other than an antidepressant medication, including causes such a hypothyroidism, dementia or metabolic disruptions. After diagnosing a patient with depression, a clinician may then prescribe one of multiple antidepressant treatments, which primarily includes drugs such as selective serotonin reuptake inhibitors (SSRIs), serotonin norepinephrine reuptake inhibitors (SNRIs), and norepinephrine dopamine reuptake inhibitors (NDRIs), or atypical antidepressants. Notably, however, selection of antidepressant medication is done purely by trial -and-error, with no biological or quantitative behavioral measures to inform medication choice. Typically, SSRIs are selected as the first line treatment based on their general tolerability, but not because they are known to be more effective for the broader patient population, nor more effective for that particular patient. Most patients, however, fail to respond adequately to the first medication (Trivedi et al., Am J Psychiatry, 2006, 163(l):28-4, doi:10.1176 / appi.ajp.l63.1.2, PMID 16390886), at which point selection of the next medication again follows a trial-and-error process. Indeed, it has been found that on average, failing one SSRI does not necessarily predict a different response to another SSRI versus an SNRI or NDRI (Rush et al., N Engl J Med. 2006, 354:1231-1242). Further there is no clear guidance if one should augment an antidepressant with an insufficient response or switch to a different antidepressant since both options have similar outcomes. As such, clinical assessments typical of clinical care interactions do not provide information sufficiently useful for selection of subsequent medication trials, and therefore external information required by the clinician to improve medication selection is not available. [4] The economic, societal and personal cost of depression is very large, with depression being the leading cause of disability worldwide. This is even more pronounced for treatment-resistant depression (Amos et al., J Clin Psychiatry, 2018, 79:2, PMID 29474009), thus suggesting that finding the best medication for an individual early in the course of treatment would provide many downstream benefits to the patient and society at large.

[0008] SUMMARY OF THE INVENTION

[0009] [5] Surprisingly, it has now been found that high or low EEG sample entropy (as determined by electroencephalogram (EEG)) in a patient is indicative of a dopamine-deficit or dopamine-excess which can be treated with a dopamine increasing agent (e.g., a 5-HT2C antagonist) or a dopamine decreasing agent (e.g., 5-HT2C agonist), respectively.

[0010] [6] One embodiment is a method of treating a method of treating a dopamine deficit-related disorder in need thereof comprising administering a therapeutically effective amount of a dopamine increasing agent (e.g., 5-HT2C antagonist), where the patient prior to treatment exhibits high EEG sample entropy using low gamma frequency range (30-40 Hz) electroencephalography. The dopamine deficit-related disorders may be, for instance, major depressive disorder, the depressive phase of bipolar disorder, depressive symptoms associated with post-traumatic stress disorder (PTSD), anhedonia, attention deficit hyperactivity disorder, Parkinson’s disease, restless legs syndrome, negative or cognitive symptoms of schizophrenia, psychosis, or substance dependence. The dopamine deficit-related disorder may be any 5-HT2c-hyperactivity disorder. [7] Another embodiment is a method of treating a 5-HT2c-hyperactivity disorder in a patient in need thereof comprising administering a therapeutically effective amount of a 5-HT2C antagonist, where the patient prior to treatment exhibits high EEG sample entropy using low gamma frequency range (30-40 Hz) electroencephalography. The 5-HT2c-hyperactivity disorder may be, for instance, major depressive disorder, the depressive phase of bipolar disorder, depressive symptoms associated with post-traumatic stress disorder (PTSD), anhedonia, attention deficit hyperactivity disorder, Parkinson’s disease, negative or cognitive symptoms of schizophrenia, psychosis, restless legs syndrome or substance dependence.

[0011] [8] The patient may additionally be treated with an antidepressant. In one embodiment, the antidepressant is selected from a selective serotonin reuptake inhibitor, serotonin norepinephrine reuptake inhibitor, bupropion or a pharmaceutically acceptable salt thereof, and any combination of any of the foregoing.

[0012] [9] Yet another embodiment is a method of treating major depressive disorder, the depressive phase of bipolar disorder, depressive symptoms associated with PTSD, anhedonia, attention deficit hyperactivity disorder, Parkinson’s disease, negative or cognitive symptoms of schizophrenia, psychosis, restless legs syndrome, or substance dependence in a patient in need thereof comprising administering to the patient a therapeutically effective amount of a dopamine increasing agent (e.g., a 5-HT2C antagonist), where the patient prior to treatment exhibits high EEG sample entropy using low gamma frequency range (30-40 Hz) electroencephalography.

[0013]

[0010] Yet another embodiment is a method of treating a dopamine deficit-related disorder (e g., major depressive disorder, the depressive phase of bipolar disorder, depressive symptoms associated with PTSD, anhedonia, attention deficit hyperactivity disorder, Parkinson’s disease, negative or cognitive symptoms of schizophrenia, psychosis, restless legs syndrome, or substance dependence) in a patient in need thereof comprising:

[0014] (a) measuring EEG sample entropy in the patient; and

[0015] (b) administering to the patient an effective amount of a dopamine increasing agent (e.g., 5-HT2C antagonist), where the patient is determined to be responsive to a dopamine increasing agent, based on exhibiting a high EEG sample entropy. In one embodiment, the method further comprises step (c) not initiating treatment with a dopamine increasing agent, where the patient does not exhibit a high EEG sample entropy using low gamma frequency range (30-40 Hz) electroencephalography.

[0016]

[0011] Yet another embodiment is a method of treating a 5-HT2C-hyperactivity disorder (e.g., major depressive disorder, the depressive phase of bipolar disorder, depressive symptoms associated with PTSD, anhedonia, attention deficit hyperactivity disorder, Parkinson’s disease, negative or cognitive symptoms of schizophrenia, psychosis, restless legs syndrome, or substance dependence) in a patient in need thereof in a patient comprising:

[0017] (a) measuring EEG sample entropy in the patient; and

[0018] (b) administering to the patient an effective amount of a 5-HT2C antagonist, where the patient is determined to be responsive to a 5-HT2Cantagonist, based on exhibiting a high EEG sample entropy. In one embodiment, the method further comprises step (c) not initiating treatment with a 5-HT2C antagonist, where the patient does not exhibit a high EEG sample entropy using low gamma frequency range (30-40 Hz) electroencephalography.

[0012] In one embodiment of any of the methods described herein involving administration of a dopamine increasing agent or a 5-HT2C antagonist, the patient exhibits high EEG sample entropy at the Pz electrode (according to the 10-20 system of electrode placement).

[0019]

[0013] In one embodiment of any of the methods described herein involving administration of a dopamine increasing agent or 5-HT2C antagonist, the EEG sample entropy in step (a) is analyzed with stored historical subject data containing data from a plurality of subjects having major depressive disorder or the depressive phase of bipolar disorder, who received treatment with a dopamine increasing agent or 5-HT2Cantagonist, where the data include for a plurality of the subjects, the efficacy of the dopamine increasing agent or 5-HT2C antagonist treatment and EEG sample entropy used to analyze the patient. In one embodiment, step (a) comprises determining a dopamine increasing agent or 5-HT2C antagonist likelihood score for the patient based on the stored historical subject data; and step (b) comprises administering to the patient an effective amount of the dopamine increasing agent or 5-HT2C antagonist, where the patient is determined to be responsive to the dopamine increasing agent or 5-HT2C antagonist, based on the likelihood score.

[0020]

[0014] In one embodiment, step (a) includes determining a dopamine increasing agent or 5-HT2C antagonist efficacy likelihood score (e.g., z-score) for the patient based on the stored historical subject data, and step (b) comprises administering to the patient an effective amount of the dopamine increasing agent or 5-HT2C antagonist, where the patient is determined to be responsive to the dopamine increasing agent or 5-HT2C antagonist based on the likelihood score. The likelihood score may be binary (that is, either 0 or 1 (categorical)) or continuous. In one embodiment, the likelihood score is bounded, for example, any value from 0.0 to 1.0.

[0015] Yet another embodiment is a method of treating anhedonia in a patient in need thereof comprising administering a therapeutically effective amount of a dopamine increasing agent or 5-HT2Cantagonist, where the patient prior to treatment exhibits high EEG sample entropy using low gamma frequency range (30-40 Hz) electroencephalography.

[0021]

[0016] Suitable dopamine-increasing agents include, but are not limited to, levodopa, a combination of levodopa and carbidopa, serotonin antagonists (e.g., 5-HT2Cantagonists such as mirtazapine, agomelatine, olanzapine, and fluoxetine), dopamine agonists, monoamine oxidase B (MAO-B) inhibitors (e.g., selegiline, rasagiline, and safinamide), COMT inhibitors (e.g., entacapone and tolcapone), bupropion, pharmaceutically acceptable salts thereof, prodrugs thereof, and any combination of any of the foregoing. Suitable dopamine agonists include, but are not limited to, ergot-based dopamine agonists (e g., bromocriptine and cabergoline), non-ergot- based dopamine agonists (e.g., amantadine, apomorphine, fenoldopam, pramipexole, ropinirole, and rotigotine), pharmaceutically acceptable salts thereof, prodrugs thereof, and any combination of any of the foregoing.

[0022]

[0017] In certain embodiments the dopamine increasing agent is pramipexole, or a pharmaceutically acceptable salt thereof. In some embodiments the dopamine increasing agent is pramipexole dihydrochloride.

[0023]

[0018] Suitable 5-HT2C antagonists include, but are not limited to, ziprasidone, olanzapine, mirtazapine, promazine, clozapine, sertindole, asenapine, paliperidone, loxapine, aripiprazole, flupenthixol, cariprazine, iloperidone, metysergide, cyclobenzaprine, tramadol, pizotifen, mianserin, agomelatine, clomipramine, doxepin, nefazodone, imipramine, amoxapine, nortryptiline, amitriptyline, cyproheptadine, captodiame, pharmaceutically acceptable salts thereof, prodrugs thereof, and any combination of any of the foregoing.

[0024]

[0019] In one embodiment of any of the methods described herein involving administration of a dopamine increasing agent or 5-HT2C antagonist, the patient suffers from major depressive disorder and previously failed to respond to the one or more antidepressants. In one embodiment, the patient continues treatment with the one or more antidepressants, upon initiation of the dopamine increasing agent or 5-HT2C antagonist.

[0025]

[0020] In one embodiment, the patient (e.g., a patient suffering from major depressive disorder) has previously been treated with one or more antidepressants but failed to achieve an adequate response to them and continues to be treated with the one or more antidepressants even after initiation of a dopamine increasing agent or 5-HT2C antagonist. In other words, a dopamine increasing agent or 5-HT2C antagonist is provided as a monotherapy, an adjunctive therapy to the one or more antidepressants, or a co-therapy with one or more antidepressants different from that previously administered to the patient. In one embodiment, the one or more antidepressants do not include a monoamine oxidase inhibitor (MAOI) or a tricyclic antidepressant. In another embodiment, the one or more antidepressants are selected from (i) serotonin reuptake inhibitors, (ii) serotonin norepinephrine reuptake inhibitors, (iii) bupropion (or a pharmaceutically acceptable salt thereof, such as bupropion hydrochloride) optionally with other medications (such as dextromethorphan), and (iv) any combination of any of the foregoing.

[0026]

[0021] In one embodiment of any of the methods described herein involving administration of a dopamine increasing agent or 5-HT2C antagonist, the patient suffers from major depressive disorder. In another embodiment of any of the methods described herein, the patient suffers from PTSD. In yet another embodiment of any of the methods described herein, the patient suffers from major depressive disorder and PTSD. In yet another embodiment, the patient was not previously treated with one or more antidepressants, and upon initiation of the dopamine increasing agent or 5-HT2C antagonist, treatment with one or more antidepressants is also initiated.

[0027]

[0022] In yet another embodiment of any of the methods described herein involving administration of a dopamine increasing agent or 5-HT2C antagonist, the patient suffers from bipolar disorder (such as bipolar I disorder or bipolar II disorder). In one embodiment, prior to initiating treatment with a dopamine increasing agent or 5-HT2C antagonist, the patient has failed to adequately respond to one or more mood stabilizers and / or antidepressants.

[0028]

[0023] In one embodiment of any of the methods described herein involving administration of a dopamine increasing agent or 5-HT2C antagonist, the patient suffers from the depressive phase of bipolar disorder and is concurrently treated with one or more mood stabilizers and / or one or more antidepressants. In one embodiment, prior to initiating treatment with a dopamine increasing agent or 5-HT2C antagonist, the patient has failed to adequately respond to the one or more mood stabilizers and / or antidepressants. In yet another embodiment, the patient was not previously treated with one or more antidepressants and / or mood stabilizers, and upon initiation of the dopamine increasing agent or 5-HT2C antagonist, treatment with one or more antidepressants and / or mood stabilizers is also initiated.

[0029]

[0024] In one embodiment of any of the methods described herein involving administration of a dopamine increasing agent or 5-HT2Cantagonist, the one or more antidepressants are selected from a selective serotonin reuptake inhibitor (SSRI), serotonin norepinephrine reuptake inhibitor (SNRI), bupropion or a pharmaceutically acceptable salt thereof, or any combination of any of the foregoing.

[0030]

[0025] In one embodiment of any of the methods described herein involving administration of a dopamine increasing agent or 5-HT2C antagonist, the method comprises orally administering a dopamine increasing agent or 5-HT2C antagonist (e.g., once daily).

[0031]

[0026] ?\ny embodiment of any method described herein involving administration of a dopamine increasing agent or 5-HT2C antagonist can be performed on a patient newly diagnosed with major depressive disorder, PTSD, bipolar disorder (such as bipolar I disorder or bipolar II disorder), anhedonia, attention deficit hyperactivity disorder, Parkinson’s disease, negative or cognitive symptoms of schizophrenia, psychosis, restless legs syndrome, psychosis, or migraine.

[0032]

[0027] Yet another embodiment is a method of treating an excess dopamine-related disorder in a patient in need thereof comprising administering a therapeutically effective amount of a dopamine decreasing agent, wherein the patient prior to treatment exhibits low EEG sample entropy using low gamma frequency range (30-40 Hz) electroencephalography. The excess dopamine-related disorder may be, for instance, psychosis, migraine, positive symptoms of schizophrenia, bipolar disorder (manic episodes), or a 5-HT2c-hypoactivity disorder.

[0033]

[0028] Yet another embodiment is a method of treating a 5-HT2c-hypoactivity disorder in a patient in need thereof comprising administering a therapeutically effective amount of a 5-HT2C agonist, wherein the patient prior to treatment exhibits low EEG sample entropy using low gamma frequency range (30-40 Hz) electroencephalography. The 5-HT2c-hypoactivity disorder may be, for instance, psychosis, positive symptoms of schizophrenia, or bipolar disorder (manic episodes).

[0034]

[0029] Yet another embodiment is a method of treating psychosis, migraine, positive symptoms of schizophrenia, or bipolar disorder (manic episodes) in a patient in need thereof comprising administering to the patient a therapeutically effective amount of a dopamine decreasing agent or 5-HT2C agonist, wherein the patient prior to treatment exhibits low EEG sample entropy using low gamma frequency range (30-40 Hz) electroencephalography.

[0035]

[0030] Yet another embodiment is a method of treating an excess dopamine-related disorder (e.g., psychosis, migraine, positive symptoms of schizophrenia, or bipolar disorder (manic episodes)) in a patient in need thereof in a patient comprising:

[0036] (a) measuring EEG sample entropy in the patient; and

[0037] (b) administering to the patient an effective amount of a dopamine decreasing agent, where the patient is determined to be responsive to a dopamine decreasing agent, based on exhibiting a low EEG sample entropy. In one embodiment, the method further comprises step (c) not initiating treatment with a dopamine decreasing agent, where the patient does not exhibit a low EEG sample entropy using low gamma frequency range (30-40 Hz) electroencephalography.

[0038]

[0031] Yet another embodiment is a method of treating a 5-HT2c-hypoactivity disorder (e.g., psychosis, migraine, positive symptoms of schizophrenia, or bipolar disorder (manic episodes)) in a patient in need thereof in a patient comprising:

[0039] (a) measuring EEG sample entropy in the patient; and (b) administering to the patient an effective amount of a 5-HT2C agonist, where the patient is determined to be responsive to a 5-HT2C agonist, based on exhibiting a low EEG sample entropy. In one embodiment, the method further comprises step (c) not initiating treatment with a 5-HT2C agonist, where the patient does not exhibit a low EEG sample entropy using low gamma frequency range (30-40 Hz) electroencephalography.

[0040]

[0032] In one embodiment, the EEG sample entropy in step (a) is analyzed with stored historical subject data containing data from a plurality of subjects having psychosis, migraine, positive symptoms of schizophrenia, or bipolar disorder (manic episodes), who received treatment with a dopamine decreasing agent or 5-HT2C agonist, wherein the data include for a plurality of the subjects, the efficacy of the dopamine decreasing agent or 5-HT2C agonist treatment and EEG sample entropy used to analyze the patient. In another embodiment, step (a) comprises determining a dopamine decreasing agent or 5-HT2C agonist likelihood score for the patient based on the stored historical subject data; and step (b) comprises administering to the patient an effective amount of the dopamine decreasing agent or 5-HT2C agonist, where the patient is determined to be responsive to the dopamine decreasing agent or 5-HT2C agonist, based on the likelihood score.

[0041]

[0033] In one embodiment of any of the methods described herein involving administration of a dopamine decreasing agent or 5-HT2C agonist, the dopamine decreasing agent or 5-HT2C agonist is selected from vabicaserin, lorcaserin, pharmaceutically acceptable salts thereof, prodrugs thereof, and any combination of any of the foregoing.

[0042]

[0034] In one embodiment of any of the methods described herein involving administration of a dopamine decreasing agent, the dopamine decreasing agent is selected from vabicaserin, lorcaserin, VMAT2 inhibitors (such as tetrabenazine, deutetrabenazine and valbenazine), antipsychotics, pharmaceutically acceptable salts thereof, prodrugs thereof, and any combination of any of the foregoing.

[0043]

[0035] In one embodiment of any of the methods described herein involving administration of a dopamine decreasing agent or 5-HT2C agonist, the patient exhibits low EEG sample entropy at the Pz electrode (according to the 10-20 system of electrode placement).

[0044]

[0036] In one embodiment of any of the methods described herein, the EEG measures are taken at resting-state. In another embodiment of any of the methods described herein, the EEG measures are taken with resting eyes closed.

[0045]

[0037] In one embodiment of any of the methods described herein, an antiemetic is concomitantly administered with the dopamine-modulating agent. The antiemetic may treat adverse events, such as nausea or vomiting, induced by the dopamine-modulating agent. In one embodiment, an antiemetic effective amount of the antiemetic is concomitantly administered with the dopamine- modulating agent. In another embodiment, the dopamine-increasing agent is pramipexole or a pharmaceutically acceptable salt thereof, and an antiemetic (such as ondansetron or a pharmaceutically acceptable salt thereof) is concomitantly administered with the pramipexole.

[0046]

[0038] In one embodiment of any of the methods described herein, the antiemetic is in the same pharmaceutical composition (such as oral dosage form) as the dopamine-modulating agent. In one embodiment, the pharmaceutical composition comprises (a) pramipexole or a pharmaceutically acceptable salt thereof and (b) an antiemetic (e.g., ondansetron or a pharmaceutically acceptable salt thereof). The pharmaceutical composition may be an oral dosage form. BRIEF DESCRIPTION OF THE DRAWINGS

[0047]

[0039] For a more complete understanding of the present invention, including features and advantages, reference is now made to the detailed description of the invention along with the accompanying figures:

[0048]

[0040] FIGS. 1A, 1B and 1C show a p<0.05 thresholded topographical map of channel-level correlations between sample entropy and percentage change in ADRS scores from baseline to week 4, 6, or 8 (subsections A, B, and C, respectively), of treatment with agomelatine. REC=resting eyes closed, REO=resting eyes open. Frequency bands are: delta (2-4Hz), theta (4- 7Hz), lower alpha (8-10Hz), upper alpha (10-12Hz), lower beta (13-20Hz), upper beta (20-30Hz), lower gamma (30-40Hz), upper gamma (40-50Hz).

[0049]

[0041] FIG. 2A shows a mixed model repeated measures (MMRM) analysis of change in MADRS scores in response to agomelatine between patients predicted by the EEG sample entropy machine learning model to respond to agomelatine. Data are plotted for patients left out of each round of model training during cross-validation. Also shown are one-sided p-values and Cohen’s d effect sizes for the contrast between predicted responders and predicted non -responders.

[0050]

[0042] FIG. 2B shows a mixed model repeated measures (MMRM) analysis of change in MADRS scores in response to agomelatine between patients predicted by the EEG sample entropy machine learning model to respond to agomelatine. Data are plotted for the holdout test dataset, which contains participants not included in the training dataset and thus an independent test of replication. Also shown are one-sided p-values and Cohen’s d effect sizes for the contrast between predicted responders and predicted non-responders.

[0051]

[0043] FIG. 2C shows a mixed model repeated measures (MMRM) analysis of change in MADRS scores in response to agomelatine between patients with high sample entropy at the Pz. electrode using low gamma frequency range EEG. Data are plotted for the full sample, combining patients left out of each round of model training during cross-validation and those in the holdout dataset. Also shown are one-sided p-values and Cohen’s d effect sizes for the contrast between predicted responders and predicted non-responders.

[0052]

[0044] FIG. 3A shows a mixed model repeated measures (MMRM) analysis of change in MADRS scores in patients in the placebo arm of a randomized trial based on their predicted agomelatine response using the agomelatine EEG sample entropy machine learning model. Also shown are p- values and Cohen’s d effect sizes for the contrast between predicted agomelatine responders and predicted non-responders with respect to observed response to placebo.

[0053]

[0045] FIG. 3B shows a mixed model repeated measures (MMRM) analysis of change in MADRS scores in patients receiving a new SSRI or SNRI based on their predicted agomelatine response using the agomelatine EEG sample entropy machine learning model. Also shown are p-values and Cohen’s d effect sizes for the contrast between predicted agomelatine responders and predicted non-responders with respect to observed response to SSRI / SNRIs.

[0054]

[0046] FIG. 4 shows a p<0.05 thresholded topographical map of channel-level correlations between Pz low gamma sample entropy and low gamma power envelope connectivity between Pz and each other electrode (REC). Datasets shown are baseline EEG data from the agomelatine trial (left-most, N=117), as well as baseline data from three other studies in depression (from second from the left to the right: dataset 1 N=894, dataset 2 N=793, dataset 3 N=215).

[0055]

[0047] Figure 5 is a bar graph showing the treatment dosage of the 5-HT2C agonist Ro 60-0175 in mice versus the measured sample entropy (40-100 Hz), as described in Example 2,

[0056]

[0048] Figure 6 is a bar graph showing the treatment dosage of the 5-HT2C agonist YM348 in mice versus the measured sample entropy (40-100 Hz), as described in Example 3.

[0057]

[0049] Figure 7 is a graph of Pz low gamma sample entropy in subj ects under the dietary dopamine depletion condition versus a control non-depletion condition.

[0058]

[0050] Figures 8A and 8B illustrate bar graphs depicting gamma sample entropy levels from EEG recordings (A) in rodents after acute dopamine depletion using varying doses (50, 100, or 150 mg / kg) of alpha-methyl -p-tyrosine ( AMPT) which inhibits the enzyme tyrosine hydroxylase, or a vehicle; and (B) in rodents after acute stimulation of D3 / D2 dopamine receptors with 0.1, 0.3, or 1 mg / kg pramipexole, or a vehicle.

[0059] DETAILED DESCRIPTION OF THE INVENTION

[0060]

[0051] The terms major depressive disorder, bipolar disorder, bipolar I disorder, and bipolar II disorder are intended to be as defined in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), which is hereby incorporated by reference. The severity of depression can be measured by the Montgomery-Asberg Depression Rating Scale (MADRS), Patient Health Questionnaire-9 (PHQ-9), Clinical Global Impression - severity Scale (CGI-S), Hamilton Depression Rating Scale (HDRS), or any combination of any of the foregoing.

[0052] The terms "treat," "treatment," and "treating" in the context of the administration of a therapy to a patient refers to the reduction or inhibition of the progression and / or duration of a disease or condition, the reduction or amelioration of the severity of a disease or condition, and / or the amelioration of one or more symptoms thereof resulting from the administration of one or more therapies.

[0061]

[0053] In certain embodiments, the patient had an inadequate response to other antidepressant therapy (i.e., one or more antidepressants other than a 5-HT2C antagonist or a dopamine increasing agent). In one embodiment, “inadequate response” as used herein refers to a patient experiencing a less than 50% reduction in depressive symptom severity from the start of initiating treatment. Typically, the inadequate response is during a current / active episode of the depression. In some embodiments, an inadequate response refers to a patient experiencing 0 to less than about 50% reduction in depressive symptom severity from the start of initiating treatment. In some embodiment, an inadequate response refers to a patient experiencing (a) less than about 50% reduction in depressive symptom severity from the start of initiating treatment and (b) at least a certain level of symptoms, such as a PHQ9 of at least 10. A patient's response may be measured by one or more scales described herein and / or by physician / clinical judgment. In some embodiments, an inadequate response is measured by ATRQ (the antidepressant treatment response questionnaire), MADRS, PHQ-9, CGI-S, orHDRS.

[0062]

[0054] The term “dopamine deficit-related disorder” includes, but is not limited to, major depressive disorder, the depressive phase of bipolar disorder, depressive symptoms associated with PTSD, anhedonia, attention deficit hyperactivity disorder, Parkinson’s disease, negative or cognitive symptoms of schizophrenia, psychosis, substance dependence, restless legs syndrome, myalgic encephalomyelitis, and 5-HT2C -hyperactivity disorders.

[0063]

[0055] The term “5-HT2c-hyperactivity disorder” includes, but is not limited to, major depressive disorder, the depressive phase of bipolar disorder, depressive symptoms associated with PTSD, anhedonia, attention deficit hyperactivity disorder, Parkinson’s disease, negative or cognitive symptoms of schizophrenia, and restless legs syndrome. Enhancing 5-HT2C receptor function has been linked to reduction in appetitive behaviors in rodents (Dremencov et al., Neuropharmacology 2005, 48:34-42; Hurren & Bertie, Am J Health Syst Pharm 2011, 68:2029-2037), and specifically to anhedonia-like behaviors such as reduced sucrose consumption (Han etal., Neuropharmacology 2015 93:68-79). Furthermore, drugs that antagonize 5-HT2C receptors reverse anhedonia-like behaviors in rodent models (Ring & Regan, J. Psychopharmacology 27:930-939; Dekeyne et al., Psychopharmacol 2008, 199:549-568)

[0064]

[0056] The term “excess dopamine related disorder” includes, but is not limited to, psychosis, migraine, positive symptoms of schizophrenia, bipolar disorder (manic episodes), and 5-HT2C- hypoactivity disorders.

[0065]

[0057] The term “5-HT2c-hypoactivity disorder” includes, but is not limited to, psychosis, migraine, positive symptoms of schizophrenia, or bipolar disorder (manic episodes).

[0066]

[0058] “Dopamine increasing agents” include but are not limited to, levodopa, a combination of levodopa and carbidopa, serotonin antagonists (e.g., 5-HT2c antagonists such as mirtazapine, agomelatine, olanzapine, and fluoxetine), dopamine agonists, MAO-B inhibitors (e.g., selegiline, rasagiline, and safinamide), COMT inhibitors (e.g., entacapone and tolcapone), bupropion, pharmaceutically acceptable salts thereof, prodrugs thereof, and any combination of any of the foregoing. Suitable dopamine agonists include, but are not limited to, ergot-based dopamine agonists (e.g., bromocriptine and cabergoline), non-ergot-based dopamine agonists (e.g., amantadine, apomorphine, fenoldopam, pramipexole, ropinirole, and rotigotine), pharmaceutically acceptable salts thereof, prodrugs thereof, and any combination of any of the foregoing.

[0067]

[0059] “5-HT c antagonists” include, but are not limited to, ziprasidone, olanzapine, mirtazapine, promazine, clozapine, sertindole, asenapine, paliperidone, loxapine, aripiprazole, flupenthixol, cariprazine, iloperidone, metysergide, cyclobenzaprine, tramadol, pizotifen, mianserin, agomelatine, clomipramine, doxepin, nefazodone, imipramine, amoxapine, nortryptiline, amitriptyline, cyproheptadine, captodiame, pharmaceutically acceptable salts thereof, prodrugs thereof, and any combination of any of the foregoing.

[0068]

[0060] ‘’Dopamine decreasing agents” include but are not limited to, vabicaserin, lorcaserin, VMAT2 inhibitors (such as tetrabenazine, deutetrabenazine and valbenazine), antipsychotics, pharmaceutically acceptable salts thereof, prodrugs thereof, and any combination of any of the foregoing.

[0069]

[0061] “5-HT2C agonists” include, but are not limited to, vabicaserin, lorcaserin, pharmaceutically acceptable salts thereof, prodrugs thereof, and any combination of any of the foregoing.

[0070]

[0062] The term “antidepressant” unless indicated otherwise includes selective serotonin reuptake inhibitors (SSRIs) (e.g., fluoxetine, escitalopram, citalopram, and sertraline), selective serotonin and norepinephrine reuptake inhibitors (SNRIs) (e.g., venlafaxine, duloxetine, and milnacipran), norepinephrine and dopamine reuptake inhibitors (e.g., bupropion), atypical antidepressants, and any combination of any of the foregoing. In one embodiment, the antidepressant is selected from an SSRI, SNRI, or bupropion. In another embodiment, antidepressant is selected from an SSRI (other than fluvoxamine), SNRI, or bupropion.

[0071]

[0063] The “mood stabilizer” referenced herein may be lithium carbonate, lithium orotate, lithium salt, valproic acid, divalproex sodium, propranolol, clonazepam, sodium valproate, lamotrigine, carbamazepine, gabapentin, oxcarbazepine, topiramate, a pharmaceutically acceptable salt thereof, or any combination of any of the foregoing.

[0072]

[0064] In one embodiment, the antiemetic is a 5-HTs receptor antagonist. In some embodiments, the 5-HT3 receptor antagonist is ondansetron, granisetron, palonosetron, dolasetron, alosetron, azasetron, bemesetron, cilansetron, fabesetron, itasetron, lerisetron, lurosetron, ramosetron, ricasetron, tropisetron, zatosetron, or a pharmaceutically acceptable salt thereof. In one preferred embodiment, the 5-HT3 receptor antagonist is ondansetron or a pharmaceutically acceptable salt thereof (such as ondansetron free base or ondansetron hydrochloride). Ondansetron is a selective serotonin 5-HT3 receptor antagonist. In some embodiments, the antiemetic is an NK-I antagonist. In some embodiments, the NK-I antagonist is aprepitant, fosaprepitant, netupitant, rolapitant, tradipitant, or a pharmaceutically acceptable salt thereof. In some embodiments, the antiemetic is a H1 receptor antagonist. In some embodiments, the H1 receptor antagonist is dimenhydrinate, diphenhydramine, meclizine, hydroxyzine, or a pharmaceutically acceptable salt thereof. In some embodiments, the antiemetic is a peripheral dopamine antagonist. In embodiments, the peripheral dopamine antagonist is domperidone or a pharmaceutically acceptable salt thereof. In some embodiments, the antiemetic is an anticholinergic. In some embodiments, the anticholinergic is scopolamine, dronabinol, nabilone, lorazepam, diazepam, or a pharmaceutically acceptable salt thereof,

[0073]

[0065] As used herein, the term “high EEG sample entropy” refers to an EEG signal in which sample entropy is in the higher range of the distribution in patients, e.g., relative to the mean entropy value in a healthy population. In one embodiment, EEG sample entropy is calculated as a standardized score (e.g., z-scores, T-scores, Standard Scores, Scaled Scores, Percentile rank, or Stanine scores) normalizing the patient against a healthy population (e.g., with respect to age, gender, or education). For example, the subject may have EEG sample entropy more than the mean of a similar healthy subject with a z-score more than zero, more than z=0.25, z = 0.5, z =0.75, z = 1, z = 1.5, or z = 2 (e.g., with a z-score of from about 0.5 or 0.75 to about 1 or 2, or a z-score of from about 0.75 or 1 to about 2). In one embodiment, a patient is considered to have higher entropy when the z-score is at least 0, 0.5, 1.0, 1.5, or 2.0 (e.g., at least 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, or 2.0). In one embodiment, the raw EEG data from a patient is first loaded and subjected to preprocessing steps including resampling, applying notch and bandpass filtering. Subsequently, the data undergoes bad-channel interpolation and artifact rejection, and is then re-referenced, quality-checked, and stored for analysis.

[0074]

[0066] As used herein, the term “low EEG sample entropy” refers to an EEG signal in which sample entropy is in the lower range of the distribution in patients, e.g., relative to the mean entropy value in a healthy population. In one embodiment, EEG sample entropy is calculated as a standardized score (e.g., z-scores, T-scores, Standard Scores, Scaled Scores, Percentile rank, or Stanine scores) normalizing the patient against a healthy population (e.g., with respect to age, gender, or education). For example, the subject may have EEG sample entropy less than the mean of a similar healthy subject with a z-score less than zero, less than z= -0.25, z = -0.5, z = -0.75, z = -1, z = -1.5, or z = -2 (e.g., with a z-score of from about -0.5 or -0.75 to about -1 or -2, or a z- score of from about -0.75 or -1 to about -2). In one embodiment, a patient is considered to have lower entropy when the z-score is no more than 0, -0.5, -1.0, -1.5, or -2.0 (e.g., no more than -0.1, -0.2, -0.3, -0.4, -0.5, -0.6, -0.7, -0.8, -0.9, -1.0, -1.1, -1.2, -1.3, -1.4, -1.5, -1.6, -1.7, -1.8, -1.9, or - 2.0). In one embodiment, the raw EEG data from a patient is first loaded and subjected to preprocessing steps including resampling, applying notch and bandpass filtering. Subsequently, the data undergoes bad-channel interpolation and artifact rejection, and is then re-referenced, quality-checked, and stored for analysis.

[0075]

[0067] As used herein, the terms "subject" and "patient" are used interchangeably and refer to a human patient unless indicated otherwise. In one embodiment, the patient has moderate to severe major depressive disorder. In another embodiment, the patient has moderate to severe major depressive disorder and is currently being treated with a SSRI, SNRI, or bupropion (e.g., bupropion or a pharmaceutically acceptable salt thereof in combination with another medication, such as dextromethorphan). In yet another embodiment, the patient has moderate to severe major depressive disorder and has failed to adequately respond to the current antidepressant medication which includes a SSRI, SNRI, or bupropion (e.g., bupropion or a pharmaceutically acceptable salt thereof in combination with another medication, such as dextromethorphan).

[0076]

[0068] The dopamine decreasing agent, 5-HT2C antagonist, dopamine increasing agent, or 5-HTsc agonist may be administered by any route, such as orally, rectally, percutaneously or by parenteral injection. A preferred route of administration is oral. The dopamine decreasing agent, 5-HT2C antagonist, dopamine increasing agent, or 5-HT2C agonist may be administered in the form of a tablet, capsule, granules, or oral liquid. In one embodiment, the dopamine decreasing agent, 5- HT2C antagonist, dopamine increasing agent, or 5-HT2C agonist is administered once daily (for example, in the form of a tablet).

[0077]

[0069] In one embodiment, the 5-HT2C antagonist is administered at the daily dosage range in Table 1

[0078] Table 1

[0079] 5-HT2C antagonist Daily oral dosage range(s) Ziprasidone 40-160 mg

[0080] Olanzapine 5-20 mg

[0081] Mirtazapine 15-45 mg

[0082] Promazine 50-600 mg

[0083] Clozapine 300-600 mg

[0084] Sertindole 12-24 mg

[0085] Asenapine 10-20 mg

[0086] Paliperidone 3-12 mg

[0087] Loxapine 20-100 mg

[0088] Aripiprazole 10-30 mg

[0089] Flupenthixol 1-3 mg

[0090] Cariprazine 1.5-6 mg

[0091] Iloperidone 12-24 mg

[0092] Metysergide 4-12 mg

[0093] Cyclobenzaprine 15-30 mg

[0094] Tramadol 50-400 mg

[0095] Pizotifen 1.5-3 mg

[0096] Mianserin 30-90 mg

[0097]

[0098] Agomelatine 25-50 mg

[0099] Clomipramine 25-250 mg

[0100] Doxepin 25-300 mg

[0101] Nefazodone 200-600 mg

[0102] Imipramine 75-300 mg

[0103] Amoxapine 200-300 mg

[0104] Nortriptyline 50-150 mg

[0105] Amitriptyline 150-300 mg Cyproheptadine 4-20 mg

[0106] Captodiame 60-120 mg

[0107]

[0108]

[0070] In one embodiment, the 5-HT2C agonist is administered at the daily dosage range in Table 2.

[0109] Table 2

[0110] 5-HT2C agonist Daily oral dosage range(s) Vabicaserin 50-600 mg

[0111] Lorcaserin 10-30 mg (e.g., 20 mg)

[0112]

[0113]

[0071] In one embodiment, the EEG measurements are performed with electrodes placed according to the 10-20 system.

[0114]

[0072] In one embodiment, the dopamine increasing agent is pramipexole, administered as pramipexole dihydrochloride monohydrate at a daily dose of 0.125 - 20 mg, or an equivalent amount of a different pharmaceutically acceptable salt of pramipexole or pramipexole free base. In one embodiment the pramipexole is administered as pramipexole dihydrochloride monohydrate at a daily dose of 0.125 - 6 mg, or an equivalent amount of a different pharmaceutically acceptable salt of pramipexole or pramipexole free base. In one embodiment the pramipexole is administered as pramipexole dihydrochloride monohydrate at a daily dose of 0.375 - 6 mg, or an equivalent amount of a different pharmaceutically acceptable salt of pramipexole or pramipexole free base. In one embodiment the pramipexole is administered as pramipexole dihydrochloride monohydrate at a daily dose of 1 - 6 mg, or an equivalent amount of a different pharmaceutically acceptable salt of pramipexole or pramipexole free base.

[0073] In one embodiment, the dopamine increasing agent is pramipexole administered as pramipexole dihydrochloride monohydrate at a daily dose of 0.125 - 20 mg, or an equivalent amount of a different pharmaceutically acceptable salt of pramipexole or pramipexole free base, in combination with 6 - 64 mg of ondansetron, or equivalent amount of a pharmaceutically acceptable salt of ondansetron. In one embodiment the pramipexole is administered as pramipexole dihydrochloride monohydrate at a daily dose of 0.125 - 6 mg, or an equivalent amount of a different pharmaceutically acceptable salt of pramipexole or pramipexole free base, in combination with 6 - 64 mg of ondansetron, or equivalent amount of a pharmaceutically acceptable salt of ondansetron. In one embodiment the pramipexole is administered as pramipexole dihydrochloride monohydrate at a daily dose of 0.375 - 6 mg, or an equivalent amount of a different pharmaceutically acceptable salt of pramipexole or pramipexole free base, in combination with 6 - 64 mg of ondansetron, or equivalent amount of a pharmaceutically acceptable salt of ondansetron. In one embodiment the pramipexole is administered as pramipexole dihydrochloride monohydrate at a daily dose of 1 - 6 mg, or an equivalent amount of a different pharmaceutically acceptable salt of pramipexole or pramipexole free base, in combination with 6 - 64 mg of ondansetron, or equivalent amount of a pharmaceutically acceptable salt of ondansetron. In other embodiments, the pramipexole or pharmaceutically acceptable salt thereof (e.g., pramipexole dihydrochloride monohydrate), is administered in combination with 6 - 32 mg ondansetron, or equivalent amount of a pharmaceutically acceptable salt of ondansetron. In other embodiments, the pramipexole or pharmaceutically acceptable salt thereof (e.g., pramipexole dihydrochloride monohydrate), is administered in combination with 8 - 16 mg ondansetron, or equivalent amount of a pharmaceutically acceptable salt of ondansetron. In some embodiments the pramipexole, or pharmaceutically acceptable salt thereof, is administered in combination with ondansetron hydrochloride. In some embodiments pramipexole di hydrochloride monohydrate is administered in combination with ondansetron hydrochloride.

[0115]

[0074] In some embodiments, the pramipexole, or pharmaceutically acceptable salt thereof, is administered once a day. In some embodiments, the pramipexole, or pharmaceutically acceptable salt thereof, is administered twice a day. In some embodiments, the pramipexole, or pharmaceutically acceptable salt thereof, is administered three times a day.

[0116] Exam le 1

[0117]

[0075] The inventors conducted two parallel open-label clinical trials of agomelatine, a 5-HT2C antagonist, at 25 mg once at bedtime in patients with major depressive disorder (NCT05118750 and NCT05157945, whose data was pooled in these analyses). These patients were required to have moderate to severe depression and be on a stable and adequate dose of an antidepressant (in particular, an SSRI, SNRI, or bupropion) to which they had an inadequate treatment response (i.e., agomelatine treatment was an adjunct to the antidepressant). Patients were evaluated over the course of eight weeks of treatment.

[0118]

[0076] EEG data were collected at rest (encompassing both eyes open and eyes closed conditions) prior to treatment using a 19-channel EEG system covering the conventional 10-20 electrode locations. A total of 107 patients with moderate to severe depression (MADRS>20 andPHQ-9>10) had EEG data (107 with eyes open (REO) EEG, 105 with eyes closed (REC) EEG). Quality control assessments were conducted, yielding 105 REO patient datasets and 103 REC patient datasets. These data were divided into a training dataset for identifying predictive signals, and a separate holdout dataset on which predictive signals could be additionally tested. The training dataset consisted of 60 REO patient datasets and 60 REC patient datasets. The holdout set consisted of 49 REO patient datasets and 46 REC patient datasets.

[0119]

[0077] The brain is a dynamic system that is inherently nonlinear and complex. Statistical features derived from information theory and chaos theory, such as sample entropy and the Lyapunov exponent, may capture nonlinear aspects of systems that standard linear features fail to capture. This, in turn, can improve our ability to characterize EEG recordings and potentially differentiate disease-relevant brain patterns (Lau et al., Eur J Neurosci, 2022, 56(7):5047-5069, doi: 10.1111 / ejn.15800, PMID 35985344; Rodriguez -Bermudez and Garcia-Laencina, Appl. Math Inf. Sei. 9(5):2309-2321, 2015). Sample entropy, in particular, measures the irregularity of a system. Low sample entropy indicates low randomness, high regularity (i.e. repeating patterns), and implies high dependence between data points. High sample entropy, conversely, indicates high randomness, low regularity, and low dependence between data points (Delgado-Bonal and Marshak, Entropy (Basel), 2019, 21 (6):541, doi: 10.3390 / e21060541, PMID: 33267255).

[0120]

[0078] Sample entropy is a modified version of approximate entropy, which is a modification of the Kolmogorov- Sinai (KS) entropy (Delgado-Bonal and Marshak, 2019, supra). KS entropy directly relates to the “entropy rate” of a dynamic system, which measures how much information over time (on average) is needed to describe a process. However, KS entropy can only be practically calculated for well-defined systems without any measurement noise and vast amounts of data. Approximate entropy solves this problem with a basis in the same principles as KS entropy, but usable with real data (Pincus, PNAS, 1991, 88(6):2297-301, doi: 10.1073 / pnas.88.6.2297, PMID: 11607165). Approximate entropy measures the frequency rate that a snippet of data of fixed length is approximately repeated and then also remains similar for the next sample. Approximate entropy is known to be biased measurement, especially with small amounts of data. Sample entropy is a very similar measure to approximate entropy but modified to solve this problem (Delgado-Bonal and Marshak, 2019, supra). Channel-wise EEG sample entropy was therefore calculated in the following analyses.

[0121]

[0079] As seen in FIGs. 1 A-1C (subsections A, B, and C), channel level sample entropy measures correlate at p<0.05 with percentage change in MADRS scores from baseline (to weeks 4, 6 and 8) across multiple frequency ranges and multiple scalp locations in the training dataset. In order to compile these individual signals into a single EEG composite entropy model for prediction of treatment outcome, the inventors conducted 10-fold cross-validated machine learning using elastic net regularization against an outcome of high versus low response to agomelatine. Cross-validation divides the training dataset iteratively into 9 / 10 for training the machine learning model and 1 / 10 for evaluating the predictive utility of the model (i.e., participants left out of the training itself, though part of the aforementioned training dataset). The training sample is then divided in this way until each participant has been left out of the training subset.

[0122]

[0080] FIG. 2A shows these cross-validation results for the left-out data within the training dataset, demonstrating statistically significant prediction of agomelatine outcome at all weeks of treatment. The Cohen’s d effect sizes at these weeks are all >0.4, indicating a substantial effect size for the prediction, especially considering that the m eta-anal yti cal ly calculated all-comer (i.e., unselected depression patients) effect size for the difference in treatment response to agomelatine (as monotherapy) versus placebo is d=0.26 (Cipriani et al., Lancet., 2018, 391(10128): 1357-1366, PMID: 29477251). A similar pattern of effect sizes was seen in the holdout dataset, wherein the difference in predicted agomelatine responders versus non-responders with respect to observed change in MADRS scores was d>0.4 at weeks 4, 6 and 8. Statistical significance was achieved in the holdout test set for weeks 6 and 8 (see FIG. 2B), indicating replication of the prediction of agomelatine outcome by EEG sample entropy in an independent group of patients. Thus, it has been surprisingly discovered that an EEG complexity measure, in this case sample entropy, can predict which patient receiving adjunctive treatment with 25 mg of agomelatine, a 5-HT2C antagonist, will be more likely to see a reduction in depression symptoms. Notably, other measurements, such as chronobiology, sleep, and cognition, were not found predictive of whether adjunctive treatment with agomelatine would be effective at reducing depressive symptoms.

[0123]

[0081] The inventors examined the weights ascribed by the machine learning model for each electrode, which revealed a prominent role for EEG sample entropy calculated at the Pz electrode on low gamma range frequency data (30-40Hz). Plotted in FIG. 2C is the MADRS change of patients with high Pz-computed low-gamma sample entropy (z > 0.27 was used here) compared to those with low Pz low-gamma sample entropy in the full study sample, demonstrating strong and statistically significant prediction of treatment outcome across all weeks.

[0124]

[0082] In order to understand whether thi s machine learning model identifies patients who respond better to agomelatine as compared to either placebo or standard-of-care SSRIs or SNRIs, the inventors applied the EEG sample entropy machine learning model to EEG data from patients who went on to receive placebo treatment for 8 weeks as part of a randomized trial in depression (Trivedi et al., J Psychiatr Res., 2016, 78:11-23, PMID: 27038550). As shown in FIG. 3 A, there is no significant difference between patients predicted by the EEG model to respond better or worse to agomelatine with respect to how they responded to placebo. In fact, these data demonstrate a slight effect in the opposite direction, whereby predicted agomelatine responders did numerically more poorly when given placebo. In a similar manner, patients who were given a new SSRI or SNRI showed no difference in outcome over 8 weeks when divided based on the agomelatine EEG model (FIG. 3B). Highly similar results were seen if using Pz signal only instead of the full machine learning model, also with a numerical superiority for low entropy patients (i.e., predicted agomelatine non-responders) in terms of response to placebo or SSRI / SNRIs. Thus, these data demonstrate the specificity of the EEG sample entropy model for predicting outcome with agomelatine, yielding therefore a novel and non-obvious tool for identifying who should and who should not receive agomelatine for the treatment of depression. Surprisingly, sample entropy at a single electrode in the low gamma frequency range (i.e., Pz) was able to robustly and specifically predict agomelatine outcome.

[0125]

[0083] Given the approximate 50% prevalence of positivity on the EEG machine learning model, one can estimate the agomelatine-placebo difference in EEG-predicted agomelatine responders by adding the all-comer effect size (d=0.26) to the enrichment in EEG-predicted responders over the all-comer population. This enrichment is calculated by halving the effect size between EEG- predicted responders and non-responders, since the average of these two groups is the all-comer population. No difference in placebo response as a function of EEG-predicted agomelatine response was assumed in the calculation (a conservative assumption in light of the results in FIG.

[0126] 3 A). Doing the calculations above, using the full sample effect size shown in FIG. 2B implies an agomelatine-placebo response in EEG-predicted responders of d=0.58 at week 8, which is more than double the all-comer effect size previously observed with agomelatine monotherapy in depression (i.e. all comer without the benefit of a treatment-predictive signal). Likewise, the implied agomelatine-placebo difference for EEG-predicted non-responders is d=-0.06, suggesting no difference at all between agomelatine monotherapy and placebo in patients predicted not to respond based on EEG sample entropy. Very similar results were obtained using Pz low gamma sample entropy alone (d=0.51 in high entropy patients and d=0.0 in low entropy patients based on the full sample results). Thus, there is clear clinical utility of EEG agomelatine-predictive signals, with benefit of the drug only accruing to patients predicted to respond to agomelatine and no benefit for patients predicted to not respond based on EEG.

[0127]

[0084] In addition to sample entropy, the inventors developed similar machine learning models to test the predictive utility of a range of other EEG complexity measures, as well as other common EEG indices. As seen in Tables IA and IB below (significant results are bolded; uncorrected p- values are provided), significant prediction of agomelatine outcome was achieved by use of several other measures of complexity (approximate entropy, detrended fluctuation analysis, Higuchi fractal dimension, Katz fractal dimension, largest Lyapunov exponent, modified multiscale entropy, multiscale entropy, and aperiodic exponent). No significant prediction of agomelatine outcome was achieved with several complexity measures that were used, including Lempel-Ziv complexity, permutation entropy and Tsallis entropy. Thus, certain complexity measures appear to carry consistent and strong prediction of agomelatine outcome. Another measure, the aperiodic exponent, which is sensitive to the balance between excitation and inhibition and may have some relationship to complexity (Park et al.. Front Comput Neurosci., 2023, 17:1169288, PMID: 37122995; Deco et al., J Neurosci., 2014, 34(23):7886-98, PMID: 24899711; Donoghue et al., Nat Neurosci., 2020, 23(12): 1655-1665, PMID: 33230329), is also predictive (significant at week 4). However, a common EEG index such as relative power is not predictive.

[0128] Table LA Week! Week 2 Week 4 ^.eModel Type Frequency

[0129] condition d p d p d p / Approximate lower

[0130] REO Entropy gamma -0.15 0.555 -0.05 0.782 0.09 0.630

[0131] Approximate lower

[0132] REC Entropy gamma 0.23 0.362 0.29 0.172 0.46 0.027

[0133] Detrended

[0134] REO Fluctuation Analysis lowerbeta 0.03 0.916 0.06 0.777 0.12 0.520

[0135] Detrended

[0136] REO Fluctuation Analysis delta 0.07 0.793 0.10 0.621 0.18 0.346

[0137] Detrended

[0138] REC Fluctuation Analysis upper beta 0.19 0.427 0,20 0.331 0.25 0.216

[0139] Detrended upper

[0140] REO Fluctuation Analysis gamma 0.37 0.137 0.33 0.099 0.32 0.079

[0141] Detrended

[0142] REC Fluctuation Analysis lower beta 0.49 0.047 0.44 0.035 0.41 0.038

[0143] Higuchi Fractal

[0144] REC Dimension upper beta -0.29 0.244 -0.20 0.349 -0.05 0.785

[0145] Higuchi Fractal

[0146] REO Dimension lowerbeta 0.03 0.898 0.03 0.860 0.05 0.797

[0147] Higuchi Fractal upper

[0148] REO Dimension gamma 0.04 0.885 0.06 0.767 0.11 0.551

[0149] Higuchi Fractal

[0150] REO Dimension delta -0.15 0.541 -0.05 0.809 0.12 0.527

[0151] Higuchi Fractal upper

[0152] REC Dimension gamma 0.16 0.529 0.16 0.433 0.21 0.307

[0153] Higuchi Fractal

[0154] REC Dimension lowerbeta 0.44 0.073 0.36 0.080 0.28 0.161

[0155] Higuchi Fractal lower

[0156] REC Dimension gamma 0.64 0.012 0.58 0.006 0.57 0.005

[0157] Katz Fractal

[0158] REO Dimension lowerbeta 0.28 0.249 0.18 0.351 0.06 0.769

[0159] Katz Fractal

[0160] REO Dimension delta 0.04 0.867 0.07 0.733 0.13 0.494

[0161] Katz Fractal lower

[0162] REC Dimension gamma 0.25 0.312 0.23 0.272 0.23 0.256

[0163] Katz Fractal upper

[0164] REC Dimension gamma 0.04 0.864 0.10 0.631 0.23 0.262

[0165]

[0166] Week! Week 2 Week 4 ^.eModel Type Frequency

[0167] condition d p d p d p Katz. Fractal

[0168] REO Dimension upper beta 0.24 0.313 0.24 0.219 0.29 0.123

[0169] Katz Fractal

[0170] REC Dimension lower beta 0.47 0.057 0.42 0.049 0.37 0.067

[0171] Katz Fractal

[0172] REC Dimension upper beta 0.42 0.082 0.40 0.054 0.42 0.039

[0173] Largest Lyapunov upper

[0174] REO Exponent gamma -0.24 0.323 -0.11 0.569 0.08 0.651

[0175] Largest Lyapunov upper

[0176] REO Exponent" alpha 0.03 0.893 0.08 0.690 0.17 0.347

[0177] Largest Lyapunov upper

[0178] REC Exponent alpha 0.10 0.692 0.12 0.566 0.18 0.371

[0179] Largest Lyapunov upper

[0180] REC Exponent gamma -0.02 0.932 0.08 0.698 0.29 0.159

[0181] Lempel-Ziv lower

[0182] REO Complexity gamma -0.24 0.324 -0.13 0.501 0.02 0.894

[0183] Lempel-Ziv upper

[0184] REC Complexity alpha 0.21 0.389 0.17 0.408 0.13 0.532

[0185] Lempel-Ziv lower

[0186] REC Complexity gamma -0.06 0.806 0.01 0.955 0.15 0.462

[0187] Lempel-Ziv

[0188] REO Complexity theta 0.13 0.587 0.14 0.494 0.17 0.367

[0189] Lempel-Ziv

[0190] REO Complexity upper beta 0.19 0.426 0.21 0.283 0.30 0.126

[0191] Modified Multiscale lower

[0192] REC Entropy alpha 0.08 0.743 0.11 0.591 0.19 0.349

[0193] Modified Multiscale lower

[0194] REC Entropy gamma -0.09 0.711 0.01 0.958 0.21 0.313

[0195] Modified Multiscale

[0196] REO Entropy upper beta 0.08 0.736 0.15 0.435 0.31 0.093

[0197] Modified Multiscale upper

[0198] REC Entropy alpha 0.19 0.428 0.25 0.225 0.39 0.045

[0199] lower

[0200] REO Multi scale Entropy gamma -0.41 0.096 -0.21 0.263 0.05 0.797 upper

[0201] REC Multi scale Entropy alpha 0.05 0.833 0.08 0.701 0.15 0.472 REO Multi scale Entropy upper beta -0.09 0.729 0.02 0.924 0.20 0.277 Week! Week 2 Week 4 ^.eModel Type Frequency

[0202] condition d p d p d p lower

[0203] REC Multi scale Entropy gamma 0.18 0.488 0.24 0.287 0.39 0.080 lower

[0204] REC Permutation Entropy gamma 0.38 0.119 0.35 0.098 0.33 0.105 REO Tsallis Entropy lower beta -0.18 0.490 -0.09 0.642 0.02 0.909 upper

[0205] REC Tsallis Entropy alpha 0.03 0.904 0.04 0.848 0.06 0.745 lower

[0206] REO Tsallis Entropy gamma 0.21 0.441 0.18 0.413 0.16 0.421

[0207] Table IB

[0208] Week 6 Week 8 Model Type Frequency¬ condition - d p d p Approximate lower

[0209] REO Entropy gamma 0.22 0.284 0.35 0.171

[0210] Approximate lower

[0211] REC Entropy gamma 0.54 0.010 0.69 0.011

[0212] Detrended

[0213] REO Fluctuation Analysis lower beta 0.18 0.397 0.23 0.367

[0214] Detrended

[0215] REO Fluctuation Analysis delta 0.26 0.244 0.32 0.229

[0216] Detrended

[0217] REC Fluctuation Analysis upper beta 0.27 0.211 0.29 0.257

[0218] Detrended upper

[0219] REO Fluctuation Analysis gamma 0.32 0.126 0.31 0.220

[0220] Detrended

[0221] REC Fluctuation Analysis lower beta 0.35 0.099 0.31 0.232

[0222] Higuchi Fractal

[0223] REC Dimension upper beta 0.08 0.707 0.20 0.433

[0224] Higuchi Fractal

[0225] REO Dimension lower beta 0.06 0.778 0.07 0.786

[0226] Higuchi Fractal upper

[0227] REO Dimension gamma 0.16 0.451 0.20 0.431

[0228]

[0229] Week 6 Week 8 Eye....,T.

[0230] ... Model Type Frequency

[0231] condition - d p d p Higuchi Fractal

[0232] REO Dimension delta 0.26 0.195 0.41 0.105

[0233] Higuchi Fractal upper

[0234] REC Dimension gamma 0.22 0.293 0.25 0,334

[0235] Higuchi Fractal

[0236] REC Dimension lower beta 0.17 0.407 0,09 0.721

[0237] Higuchi Fractal lower

[0238] REC Dimension gamma 0,50 0.019 0.47 0,076

[0239] Katz Fractal REO Dimension lower beta -0.07 0.742 -0.18 0.469

[0240] Katz Fractal

[0241]

[0242] REO Dimension delta 0.18 0.387 0.23 0.366

[0243] Katz Fractal lower

[0244] REC Dimension gamma 0.20 0.338 0.19 0.458

[0245] Katz Fractal upper

[0246] REC Dimension gamma 0.32 0.134 0.43 0.108

[0247] Katz Fractal

[0248] REO Dimension upper beta 0.32 0.124 0.35 0,165

[0249] Katz Fractal

[0250] REC Dimension lower beta 0.29 0.172 0.24 0.362

[0251] Katz Fractal

[0252] REC Dimension upper beta 0.39 0.072 0.36 0.150

[0253] Largest Lyapunov upper

[0254] REO Exponent gamma 0.26 0.208 0.43 0.092

[0255] Largest Lyapunov upper

[0256] REO Exponent alpha 0.26 0.210 0.34 0.179

[0257] Largest Lyapunov upper

[0258] REC Exponent alpha 0.22 0.307 0.26 0.314

[0259] Largest Lyapunov upper

[0260] REC Exponent gamma 0.46 0.037 0.62 0.019

[0261] Lempel-Ziv lower

[0262] REO Complexity gamma 0.17 0.411 0.31 0.225

[0263] Lempel-Ziv upper

[0264] REC Complexity alpha 0.07 0.743 0.02 0.927

[0265] Lempel-Ziv lower

[0266] REC Complexity gamma 0.26 0.226 0.37 0.156 Week 6 Week 8

[0267] Eye....,T.

[0268] ... Model Type Frequency

[0269] condition - d p d p Lempel-Ziv

[0270] REO Complexity theta 0.19 0.352 0.22 0.389

[0271] Lempel-Ziv

[0272] REO Complexity upper beta 0.35 0.098 0.40 0.113

[0273] Modified Multiscale lower

[0274] REC Entropy alpha 0.24 0.260 0.30 0.253

[0275] Modified Multiscale lower

[0276] REC Entropy gamma 0.37 0.089 0.54 0.044

[0277] Modified Multiscale

[0278] REO Entropy upper beta 0.43 0.028 0.61 0.020

[0279] Modified Multiscale upper

[0280] REC Entropy alpha 0.51 0.018 0.62 0.018

[0281] lower

[0282] REO Multiscale Entropy gamma 0.30 0.160 0.52 0.040

[0283] upper

[0284] REC Multiscale Entropy alpha 0.20 0.375 0.24 0.360 REO Multiscale Entropy upper beta 0.36 0.075 0.54 0.037

[0285] lower

[0286] REC Multiscale Entropy gamma 0.49 0.040 0.57 0.039

[0287] lower

[0288] REC Permutation Entropy gamma 0.27 0.197 0.24 0.351 REO Tsallis Entropy lower beta 0.13 0.542 0.23 0.375

[0289] upper

[0290] REC Tsallis Entropy alpha 0.08 0.699 0.10 0.696

[0291] lower

[0292] REO Tsallis Entropy gamma 0.15 0.518 0.13 0.634

[0293]

[0085] Having found that higher EEG sample entropy predicts better agomelatine response, the inventors reasoned that EEG signal that is more erratic, unpredictable and irregular (i.e. higher entropy) may result in poorer information transfer between a brain region with these attributes and other brain regions. Information transfer in EEG can be tested using measures of connectivity, such as orthogonalized power envelope connectivity (Hipp etal. Nat Neurosci., 2012, 15(6):884- 90, PMID: 22561454). The inventors therefore examined whether higher Pz low gamma frequency entropy could predict lower power envelope connectivity from Pz, As seen in FIG. 4, higher low gamma Pz sample entropy predicted lower Pz connectivity in particular to midline frontal regions (e.g., at electrode Fz). The location of this electrode suggests that the decrease in connectivity impacts the default mode network in the brain, a neural network identified as having a central role in depression (Runia et al., Neruosci Biobehav Rev., 2022, 132:433-438, PMID: 34890601; Tozzi et al., Neuroimage Clin., 2021, 30:102570; PMID: 33540370). Thus, measures of connectivity, inasmuch as they reflect the correlates of entropy, can also be used to identify agomelatine responders versus non-responders.

[0294] Example 2

[0295]

[0086] Mice (n = 14, 13 included in analysis) were subjected to a cross-over study with four dosages of a 5-HT2C agonist, Ro 60-0175 ((aS)-6-chloro-5-fluoro-a-methyl-lH-indole-l- ethanamine, (2E)-2-butenedioate, CAS No. 169675-09-6) (0.75, 1.25, 2.5, 4 mg / kg) and vehicle, with a washout period of at least 72 hours after each dosing. Mice were dosed at 10 am. Two rsEEG channels (frontal and parietal) were used. Gamma sample entropy (40-100 Hz) over a period of 0.5 to 1.5 hours post-dosing with Ro 60-0175 was compared with vehicle. High gamma EEG measurements in mice correlate to low gamma EEG measurements in humans.

[0296]

[0087] The results are shown in Figure 5. As shown, gamma band sample entropy significantly increased (compared to the vehicle group) after administration of the two highest doses of Ro 60- 0175. According to a t-test, p = 0.010 for 2.5 mg / kg Ro 60-0175 and p = 0.003 for 4.0 mg / kg Ro 60-0175.

[0297] Example 3

[0298]

[0088] Mice (n=l 1) were subjected to a cross-over study with five dosages of another 5-HT2Cagonist, YM348 ((S)-2-(7-ethyl-lH-furo[2,3-g]indazol-l-yl)-l-methylethylamine, CAS No.

[0299] 372163-84-3) (0.05, 0.1, 0.2, 0.3, and 0.6 mg / kg) and vehicle, with a washout period of at least 72 hours after each dosing. Mice were dosed at 10 am. Two rsEEG channels (frontal and parietal) were used. Gamma sample entropy (40-100 Hz) over a period of 0.5 to 1.5 hours post-dosing with YM348 was compared with vehicle.

[0300]

[0089] The results are shown in Figure 6. As shown, gamma band sample entropy significantly increased (compared to the vehicle group) after administration of the two highest doses of YM348. An Analysis of Variance (ANOVA) revealed a significant dose-dependent increase in gamma band sample entropy with YM348 (p=0.007).

[0301] Example 4

[0302]

[0090] A double-blind clinical trial was performed with twelve male subjects who were administered a dietary' dopamine depletion or placebo mixture. Treatment administration was separated by 1 week and randomly assigned to allow full recovery' in between. An amino acid mixture deficient in phenylalanine and tyrosine (precursors for dopamine) was administered to induce dopamine depletion. A nutritionally balanced amino acid mixture was administered as a placebo. The day prior to each testing session participants were provided a low-protein diet and fasted from midnight until arriving for the study in the morning. The subjects performed a color naming visual oddball task. Low gamma band sample entropy at the Pz electrode was calculated across the oddball task recording, and found not to be affected by evoked responses related to the task itself (i.e. functioned like a resting-state EEG run with respect to ability to calculate sample entropy).

[0303]

[0091] The results are provided in Figure 7, showing that dopamine depletion led to a significant increase in low gamma sample entropy (p=0.01, Cohen’s d=0.93) relative to the control condition. These data suggest that individuals with higher levels of low gamma sample entropy may have decreased dopamine levels or activity.

[0304] Example 5

[0305]

[0092] To determine whether gamma band sample entropy is a consistent index of dopaminergic activity, a translational study was then conducted in rodents, recording EEG from the parietal cortex. Animals were given different doses (50, 100, or 150 mg / kg) of alpha-methyl-p-tyrosine (AMPT), which inhibits dopamine synthesis by inhibiting the tyrosine hydroylase enzyme. As seen in Fig, 8A, this led to an increase in gamma sample entropy in a dose-dependent manner. Conversely, stimulating D3 / D2 receptors, by administration of the agonist pramipexole (as pramipexole dihydrochloride monohydrate), resulted in a dose-dependent decrease in gamma sample entropy (Fig. 8B). Thus, gamma band sample entropy indexes dopaminergic activity - it is elevated in situations of low dopaminergic activity, and decreased in situations of high dopaminergic activity. These data further suggest that individuals with high gamma sample entropy may respond particularly well to treatment with a D3 / D2 agonist such as pramipexole.

[0306] ADDITIONAL EMBODIMENTS

[0307] 1. A method of treating a dopamine deficit-related disorder in a patient in need thereof comprising administering a therapeutically effective amount of a dopamine increasing agent, wherein the patient prior to treatment exhibits high EEG sample entropy using low gamma frequency range (30-40 Hz) electroencephalography.

[0308] 2. The method of embodiment 1, wherein the dopamine increasing agent is selected from levodopa, a combination of levodopa and carbidopa, serotonin antagonists (e.g., 5-HT2Cantagonists such as mirtazapine, agomelatine, olanzapine, and fluoxetine), dopamine agonists, monoamine oxidase B (MAO-B) inhibitors (e.g., selegiline, rasagiline, and safinamide), COMT inhibitors (e.g., entacapone and tolcapone), bupropion, pharmaceutically acceptable salts thereof, prodrugs thereof, and any combination of any of the foregoing.

[0309] 3. The method of embodiment 1 or 2, wherein the dopamine deficit-related disorder is selected from major depressive disorder, the depressive phase of bipolar disorder, or depressive symptoms associated with post-traumatic stress disorder (PTSD), anhedonia, attention deficit hyperactivity disorder, Parkinson’s disease, negative or cognitive symptoms of schizophrenia, psychosis, restless legs syndrome, or substance dependence.

[0310] 4. The method of embodiment 1 or 2, wherein the dopamine deficit-related disorder is major depressive disorder. 5. A method of treating a 5-HT2c-related disorder in a patient in need thereof comprising administering a therapeutically effective amount of a 5-HT2c-modulating agent, wherein the patient prior to treatment exhibits high or low EEG sample entropy using low gamma frequency range (30-40 Hz) electroencephalography.

[0311] 6. A method of treating a 5-HT2c-hyperactivity disorder in a patient in need thereof comprising administering a therapeutically effective amount of a 5-HT2C antagonist, wherein the patient prior to treatment exhibits high EEG sample entropy using low gamma frequency range (30-40 Hz.) electroencephalography.

[0312] 7. The method of embodiment 6, wherein the 5-HT2c-hyperactivity disorder is major depressive disorder.

[0313] 8. The method of embodiment 4 or 7, wherein the method further comprises treating the patient with an antidepressant.

[0314] 9. The method of embodiment 8, wherein the antidepressant is selected from a selective serotonin reuptake inhibitor, serotonin norepinephrine reuptake inhibitor, bupropion or a pharmaceutically acceptable salt thereof, and any combination of any of the foregoing.

[0315] 10. A method of treating major depressive disorder, the depressive phase of bipolar disorder, depressive symptoms associated with post-traumatic stress disorder (PTSD), anhedonia, attention deficit hyperactivity disorder, Parkinson’s disease, negative or cognitive symptoms of schizophrenia, psychosis, restless legs syndrome, or substance dependence in a patient in need thereof comprising administering to the patient a therapeutically effective amount of a dopamine increasing agent (e.g., a 5-HT2C antagonist), wherein the patient prior to treatment exhibits high EEG sample entropy using low gamma frequency range (30-40 Hz) electroencephalography.

[0316] 11. A method of treating a dopamine deficit-related disorder (e.g., a 5-HT2C-hyperactivity disorder) (e.g., major depressive disorder, the depressive phase of bipolar disorder, or depressive symptoms associated with post- traumatic stress disorder (PTSD), anhedonia, attention deficit hyperactivity disorder, Parkinson’s disease, negative or cognitive symptoms of schizophrenia, psychosis, restless legs syndrome, or substance dependence) in a patient in need thereof in a patient comprising:

[0317] (a) measuring EEG sample entropy in the patient; and

[0318] (b) administering to the patient an effective amount of a dopamine increasing agent (e.g., 5-HT2Cantagonist), where the patient is determined to be responsive to a dopamine increasing agent (e.g., 5-HT2Cantagonist) based on exhibiting a high EEG sample entropy.

[0319] 12. The method of embodiment 12, further comprising the step (c) not initiating treatment with a dopamine increasing agent (e.g., 5-HT2C antagonist), where the patient does not exhibit a high EEG sample entropy.

[0320] 13. The method of embodiment 11 or 12, wherein the EEG sample entropy in step (a) is analyzed with stored historical subject data containing data from a plurality of subjects having major depressive disorder or the depressive phase of bipolar disorder, who received treatment with a dopamine increasing agent (e.g., 5-HT2C antagonist), wherein the data include for a plurality of the subjects, the efficacy of the dopamine increasing agent (e.g., 5-HT2C antagonist) treatment and EEG sample entropy used to analyze the patient. 14. The method of embodiment 13, wherein step (a) comprises determining a dopamine increasing agent (e.g., 5-HT2C antagonist) likelihood score for the patient based on the stored historical subject data; and step (b) comprises administering to the patient an effective amount of the dopamine increasing agent (e.g., 5-HT2C antagonist), where the patient is determined to be responsive to the dopamine increasing agent (e.g., 5-HT2C antagonist), based on the likelihood score.

[0321] 15. A method of treating anhedonia in a patient in need thereof comprising administering a therapeutically effective amount of a dopamine increasing agent (e.g., 5-HT2Cantagonist), wherein the patient prior to treatment exhibits high EEG sample entropy using low gamma frequency range (30-40 Hz) electroencephalography.

[0322] 16. The method of any one of the preceding embodiments, wherein the patient exhibits high EEG sample entropy at the Pz electrode (according to the 10-20 system of electrode placement).

[0323] 17. A method of treating an excess dopamine-related disorder (e.g., 5-HT2C-hypoactivity disorder) in a patient in need thereof comprising administering a therapeutically effective amount of a dopamine decreasing agent (e.g., 5-HT2Cagonist), wherein the patient prior to treatment exhibits low EEG sample entropy using low gamma frequency range (30-40 Hz) electroencephalography.

[0324] 18. The method of embodiment 16, wherein the excess dopamine-related disorder is psychosis, migraine, positive symptoms of schizophrenia, or bipolar disorder (manic episodes). 19. A method of treating psychosis, migraine, positive symptoms of schizophrenia, or bipolar disorder (manic episodes) in a patient in need thereof comprising administering to the patient a therapeutically effective amount of a dopamine decreasing agent (e.g., 5-HT2Cagonist), wherein the patient prior to treatment exhibits low EEG sample entropy using low gamma frequency range (30-40 Hz) electroencephalography.

[0325] 20. A method of treating an excess dopamine-related disorder (e.g., 5-HT2C-hypoactivity disorder) (e.g., psychosis, migraine, positive symptoms of schizophrenia, or bipolar disorder (manic episodes)) in a patient in need thereof in a patient comprising:

[0326] (a) measuring EEG sample entropy in the patient; and

[0327] (b) administering to the patient an effective amount of a dopamine decreasing agent (e.g., 5-HT2C agonist), where the patient is determined to be responsive to a dopamine decreasing agent (e.g., 5-HT2Cagonist) based on exhibiting a low EEG sample entropy.

[0328] 21. The method of embodiment 19, further comprising the step (c) not initiating treatment with a dopamine decreasing agent (e.g., 5-HT2cagonist), where the patient does not exhibit a low EEG sample entropy.

[0329] 22. The method of embodiment 20 or 21, wherein the EEG sample entropy in step (a) is analyzed with stored historical subject data containing data from a plurality of subjects having psychosis, positive symptoms of schizophrenia, or bipolar disorder (manic episodes), who received treatment with a dopamine decreasing agent (e.g., 5-HT2Cagonist), wherein the data include for a plurality of the subjects, the efficacy of the dopamine decreasing agent (e.g., 5-HT2cagonist) treatment and EEG sample entropy used to analyze the patient. 23. The method of embodiment 22, wherein step (a) comprises determining a dopamine decreasing agent (e.g., 5-HT2C agonist) likelihood score for the patient based on the stored historical subject data; and step (b) comprises administering to the patient an effective amount of the dopamine decreasing agent (e.g., 5-HT2C agonist), where the patient is determined to be responsive to the dopamine decreasing agent (e.g., 5-HT2C agonist), based on the likelihood score.

[0330] 24. The method of any one of embodiments 17-23, wherein the patient exhibits low EEG sample entropy at the Pz electrode (according to the 10-20 system of electrode placement).

[0331] 25. The method of any of the preceding embodiments, wherein the EEG measures are taken with resting eyes closed.

[0332]

[0093] All publications, patents and patent applications cited herein are hereby incorporated by reference as if set forth in their entirety herein. While this invention has been described with reference to illustrative embodiments, this description is not intended to be construed in a limiting sense. Various modifications and combinations of illustrative embodiments, as well as other embodiments of the invention, will be apparent to persons skilled in the art upon reference to the description. It is therefore intended that the appended claims encompass such modifications and enhancements.

Claims

CLAIMS1. A method of treating a dopamine deficit-related disorder in a patient in need thereof comprising identifying a patient having high EEG sample entropy prior to treatment, and administering to the patient a therapeutically effective amount of a dopamine increasing agent.

2. The method of claim 1, wherein the dopamine increasing agent is selected from levodopa, a combination of levodopa and carbidopa, serotonin antagonists (e.g., 5-HT2C antagonists such as mirtazapine, agomelatine, olanzapine, and fluoxetine), dopamine agonists, monoamine oxidase B (MAO-B) inhibitors (e.g., selegiline, rasagiline, and safinamide), COMT inhibitors (e.g., entacapone and tolcapone), bupropion, non-ergot-based dopamine agonists (e.g., amantadine, apomorphine, fenoldopam, pramipexole, ropinirole, and rotigotine), pharmaceutically acceptable salts thereof, prodrugs thereof, and any combination of any of the foregoing.

3. The method of claim 1, wherein the high EEG sample entropy is measured using low gamma frequency range (30-40 Hz) electroencephalography.

4. The method of claim 1, wherein the dopamine increasing agent is pramipexole, or a pharmaceutically acceptable salt thereof.

5. The method of claim 1, wherein the dopamine increasing agent is pramipexole dihydrochloride.

6. The method of any of claims 1-5, further comprising administering to the patient ondansetron, or a pharmaceutically acceptable salt thereof.

7. The method of any of claims 1-5, wherein the dopamine deficit-related disorder is selected from major depressive disorder, the depressive phase of bipolar disorder, or depressive symptoms associated with post-traumatic stress disorder (PTSD), anhedonia, attention deficit hyperactivity disorder, Parkinson’s disease, negative or cognitive symptoms of schizophrenia, psychosis, restless legs syndrome, or substance dependence.

8. The method of any of claims 1-5, wherein the dopamine deficit-related disorder is major depressive disorder.

9. A method of treating a 5-HT2c-related disorder in a patient in need thereof comprising identifying a patient with high or low EEG sample entropy and administering a therapeutically effective amount of a 5-HT2c-modulating agent.

10. A method of treating a 5-HT2c-hyperactivity disorder in a patient in need thereof comprising identifying a patient with high EEG sample entropy prior to treatment and administering a therapeutically effective amount of a 5-HT2Cantagonist.

11. The method of claim 10, wherein the 5-HT2c-hyperactivity disorder is major depressive disorder.

12. The method of any of claims 1-5 or 8-11, wherein the method further comprises administering to the patient an antidepressant.

13. The method of claim 12, wherein the antidepressant is selected from a selective serotonin reuptake inhibitor, serotonin norepinephrine reuptake inhibitor, bupropion, or a pharmaceutically acceptable salt thereof, or a combination thereof.

14. A method of treating major depressive disorder, the depressive phase of bipolar disorder, depressive symptoms associated with post-traumatic stress disorder (PTSD), anhedonia, attention deficit hyperactivity disorder, Parkinson’s disease, negative or cognitive symptoms of schizophrenia, psychosis, restless legs syndrome, or substance dependence in a patient in need thereof comprising identifying a patient with high EEG sample entropy prior to treatment and administering to the patient a therapeutically effective amount of a dopamine increasing agent.

15. A method of treating a dopamine deficit-related disorder in a patient in need thereof in a patient comprising:(a) measuring EEG sample entropy in the patient; and(b) administering to the patient an effective amount of a dopamine increasing agent, where the patient is determined to be responsive to a dopamine increasing agent based on exhibiting a high EEG sample entropy.

16. The method of claim 15, further comprising the step (c) not initiating treatment with a dopamine increasing agent, where the patient does not exhibit a high EEG sample entropy.

17. The method of claim 15 or 16, wherein the high EEG sample entropy is measured using low gamma frequency range (30-40 Hz) electroencephalography.

18. The method of any of claims 14-17, wherein the dopamine increasing agent is pramipexole, or a pharmaceutically acceptable salt thereof.

19. The method of any of claims 14-18 wherein the dopamine increasing agent is pramipexole dihydrochloride.

20. The method of any of claims 14-19, further comprising administering to the patient ondansetron, or a pharmaceutically acceptable salt thereof.

21. The method of any of claims 14-20, wherein the EEG sample entropy in step (a) is analyzed with stored historical subject data containing data from a plurality of subjects having major depressive disorder or the depressive phase of bipolar disorder, who received treatment with a dopamine increasing agent, wherein the data include for a plurality of the subjects, the efficacy of the dopamine increasing agent treatment and EEG sample entropy used to analyze the patient.

22. The method of any of claims 15-17, wherein step (a) comprises determining a dopamine increasing agent likelihood score for the patient based on the stored historical subject data; and step (b) comprises administering to the patient an effective amount of the dopamine increasing agent, where the patient is determined to be responsive to the dopamine increasing agent, based on the likelihood score.

23. A method of treating anhedonia in a patient in need thereof comprising identifying a patient with high EEG sample entropy prior to treatment and administering a therapeutically effective amount of a dopamine increasing agent.

24. The method of any preceding claim, wherein the patient exhibits high EEG sample entropy at the Pz electrode (according to the 10-20 system of electrode placement).

25. A method of treating an excess dopamine-related disorder in a patient in need thereof comprising identifying a patient with high EEG sample entropy prior to treatment and administering a therapeutically effective amount of a dopamine decreasing agent.

26. The method of claim 25, wherein the excess dopamine-related disorder is psychosis, migraine, positive symptoms of schizophrenia, or bipolar disorder (manic episodes).

27. A method of treating psychosis, migraine, positive symptoms of schizophrenia, or bipolar di sorder (manic episodes) in a patient in need thereof comprising identifying a patient with low EEG sample entropy prior to treatment and administering to the patient a therapeutically effective amount of a dopamine decreasing agent.

28. A method of treating an excess dopamine-related disorder in a patient in need thereof in a patient comprising:(a) measuring EEG sample entropy in the patient; and(b) administering to the patient an effective amount of a dopamine decreasing agent, where the patient is determined to be responsive to a dopamine decreasing agent based on exhibiting a low EEG sample entropy.

29. The method of claim 28, further comprising the step (c) not initiating treatment with a dopamine decreasing agent, where the patient does not exhibit a low EEG sample entropy.

30. The method of claim 28 or 29, wherein the EEG sample entropy in step (a) is analyzed with stored historical subject data containing data from a plurality of subjects having psychosis, positive symptoms of schizophrenia, or bipolar disorder (manic episodes), who received treatment with a dopamine decreasing agent, wherein the data include for a plurality of the subjects, the efficacy of the dopamine decreasing agent treatment and EEG sample entropy used to analyze the patient.

31. The method of any of claims 28-30, wherein step (a) comprises determining a dopamine decreasing agent likelihood score for the patient based on the stored historical subject data; and step (b) comprises administering to the patient an effective amount of the dopamine decreasing agent, where the patient is determined to be responsive to the dopamine decreasing agent, based on the likelihood score.

32. The method of any one of claims 25-31, wherein the patient exhibits low EEG sample entropy at the Pz electrode (according to the 10-20 system of electrode placement).

33. The method of any preceding claim, wherein the EEG measures are taken with resting eyes closed.

34. The method of any of claims 23-33, wherein the EEG sample entropy is measured using low gamma frequency range (30-40 Hz) electroencephalography.

35. A composition for use in the treatment of a dopamine deficit-related disorder in a patient having high EEG sample entropy, wherein the use comprises identifying a patient with high EEG sample entropy, and the composition comprises a dopamine increasing agent.

36. The composition of claim 35, wherein the high EEG sample entropy is measured using low gamma frequency range (30-40 Hz.) electroencephalography.

37. The composition of claim 35 or 36, wherein the dopamine deficit-related disorder comprises major depressive disorder, the depressive phase of bipolar disorder, or depressive symptoms associated with post-traumatic stress disorder (PTSD), anhedonia, attention deficithyperactivity disorder, Parkinson’s disease, negative or cognitive symptoms of schizophrenia, psychosis, restless legs syndrome, or substance dependence.

38. The composition of any of claims 35-37, wherein the dopamine increasing agent is pramipexole, or a pharmaceutically acceptable salt thereof.

39. The composition of any of claims 35-38, wherein the dopamine increasing agent is pramipexole dihydrochloride.

40. The composition of any of claims 35-39, wherein the composition comprises 0.125-20 mg pramipexole, or the equivalent amount of a pharmaceutically acceptable salt.

41. The composition of any of claims 35-39, wherein the composition comprises 0.125-6 mg pramipexole, or the equivalent amount of a pharmaceutically acceptable salt.

42. The composition of any of claims 35-39, wherein the composition comprises 0.375-6 mg pramipexole, or the equivalent amount of a pharmaceutically acceptable salt.

43. The composition of any of claims 35-39, wherein the composition comprises 1-6 mg pramipexole, or the equivalent amount of a pharmaceutically acceptable salt44. The composition of any of claims 35-43, wherein the composition comprises ondansetron, or a pharmaceutically acceptable salt thereof.

45. The composition of any of claims 35-44, wherein the dopamine deficit-related disorder comprises major depressive disorder.

46. The composition of any of claims 35-44, wherein the dopamine deficit-related disorder comprises the depressive phase of bipolar disorder.

47. The composition of any of claims 35-44, wherein the dopamine deficit-related disorder comprises depressive symptoms associated with post-traumatic stress disorder (PTSD).

48. The composition of any of claims 35-44, wherein the dopamine deficit-related disorder comprises anhedonia.

49. The composition of any of claims 35-44, wherein the dopamine deficit-related disorder comprises attention deficit hyperactivity disorder.

50. The composition of any of claims 35-44, wherein the dopamine deficit-related disorder comprises Parkinson’s disease.

51. The composition of any of claims 35-44, wherein the dopamine deficit-related disorder comprises negative or cognitive symptoms of schizophrenia.

52. The composition of any of claims 35-44, wherein the dopamine deficit-related disorder comprises psychosis.

53. The composition of any of claims 35-44, wherein the dopamine deficit-related disorder comprises restless legs syndrome.

54. The composition of any of claims 35-44, wherein the dopamine deficit-related disorder comprises substance dependence.

55. The method of any of claims 25-34, wherein the dopamine decreasing agent is a 5HTC2 agonist.

56. The method of any of claims 1-3, 6-8, 12-17, 20-24, or 33, or the composition of any of claims 35-37 or 45-54, wherein the dopamine increasing agent is a 5HTc2 antagonist.

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