Method of recommending neurophysiological therapies

• US 7,962,204 B2
• Filed: 11/18/2008
• Issued: 06/14/2011
• Est. Priority Date: 07/11/2001
• Status: Expired due to Fees

• Current Assignee: MYnd Analytics, Inc. (Emmaus Life Sciences, Inc.)
• Original Assignee: CNS Response Inc.
• Inventors: Emory, W. Hamlin, Suffin, Stephen C., Brandt, Leonard J.
• Primary Examiner(s): Mallari; Patricia C
• Application Number:
  US12/273,383
• Publication Number:
  US 20090137923A1
• Time in Patent Office: 938 Days
• Field of Search: 600/544, 600/545
• US Class Current: 600/544
• CPC Class Codes: A61B 5/0006 ECG or EEG signals
• CPC Class Codes: A61B 5/369 Electroencephalography [EEG] devices for psychotechnics A61B5/16
• CPC Class Codes: A61B 5/372 Analysis of electroencephalograms
• CPC Class Codes: A61B 5/386 Accessories or supplementary instruments therefor
• CPC Class Codes: A61B 5/4076 Diagnosing or monitoring particular conditions of the nervous system A61B5/4821, A61B5/4824 take precedence
• CPC Class Codes: A61B 5/411 Detecting or monitoring allergy or intolerance reactions to an allergenic agent or substance
• CPC Class Codes: A61B 5/4833 Assessment of subject's compliance to treatment
• CPC Class Codes: A61B 5/7257 using Fourier transforms
• CPC Class Codes: A61B 5/7264 Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems neural networks per se G06N3/00; expert systems per se G06N5/00
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof
• CPC Class Codes: G16H 20/10 relating to drugs or medications, e.g. for ensuring correct administration to patients
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/70 for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: G16H 70/60 relating to pathologies

Abstract

A method and system for utilizing neurophysiologic information obtained by techniques such as quantitative electroencephalography (QEEG), electrode recordings, MRI in appropriately matching patients with therapeutic entities is disclosed. The present invention enables utilization of neurophysiologic information, notwithstanding its weak correlation with extant diagnostic schemes for mental disorders, for safer and expeditious treatment for mental disorders, discovering new applications for therapeutic entities, improved testing of candidate therapeutic entities, inferring the presence or absence of a desirable response to a treatment, and deducing the mode of action of one or more therapeutic entities. In particular, methods for effectively comparing neurophysiologic information relative to a reference set are disclosed along with database-based tools for deducing therapeutic entity actions on particular patients such that these tools are readily accessible to remote users.

Claims

1. A method for recommending treatment, comprising:

a) providing;

i) a first set of quantified neurophysiologic information obtained from a patient having a behaviorally diagnosed psychiatric disorder;

ii) a second set of quantified neurophysiologic information obtained from at least one reference population of individuals, wherein said second information set comprises at least one therapy responsivity profile, wherein said profile includes a first treatment modality, wherein said first treatment modality is recommended independently of said diagnosed psychiatric disorder and associated symptoms;

b) comparing said first set of quantified neurophysiologic information with said second set of quantified neurophysiologic information by cluster analysis, under conditions such that a correlation between said patient and said at least one therapy responsivity profile is indicated, wherein said comparing is performed by a computer;

c) recommending said first treatment modality for said patient based upon said indicated correlation.

2. The method of claim 1, wherein said therapy responsivity profile comprises determined effects of said at least one treatment modality.

3. The method of claim 1, wherein said indicated correlation comprises a relatively high correlation such that said at least one reference population was relatively effectively treated with said at least one treatment modality.

4. The method of claim 1, wherein said indicated correlation comprises a relatively low correlation such that said at least one reference population was relatively ineffectively treated with said at least one treatment modality.

5. The method of claim 1, further comprising repeating step (b) and step (c) after administering said first treatment modality to said patient, wherein said repeated step (c) recommends a second treatment modality.

6. The method of claim 1, wherein said first and second sets of quantified neurophysiological information comprise electroencephalographic information.

7. The method of claim 6, wherein said electroencephalographic information was recorded by electrodes placed in accordance with the International 10/20 system.

8. The method of claim 1, wherein said behaviorally diagnosed psychiatric disorder is selected from the group consisting of a major depressive disorder, a psychosomatic disorder, an atypical asthma disorder, an anxiety disorder, infancy disorders, childhood disorders, adolescence disorders, eating disorders, delirium disorders, dementia disorders, amnestic disorders, general cognitive disorders, impulse control disorders, mood disorders, personality disorders, hypoactive sexual desire disorders, sleep disorders, somatoform disorders, and substance-related disorders.

9. The method of claim 1, wherein said treatment modality is selected from the group consisting of psychiatric therapy, including for example therapeutic entity therapy, medicinal therapy, psychotherapy, verbal therapy, convulsive therapy, neuromodulation therapy, electromagnetic therapy, and photo therapy.

10. The method of claim 1, wherein said recommending comprises a report identifying said least one treatment modality as a plurality of agent classes and a list of specific agents within each of said classes.

11. The method of claim 10, wherein said agent classes are in order of significance.

12. The method of claim 10, wherein said specific agents are in order of responsivity.