Integrated biosensor and simulation system for diagnosis and therapy

• US 20060253259A1
• Filed: 11/23/2005
• Published: 11/09/2006
• Est. Priority Date: 08/22/2003
• Status: Active Grant

• Current Assignee: Dennis Fernandez
• Original Assignee: Dennis Fernandez
• Inventors: Fernandez, Dennis S.
• Granted Patent: US 8,370,078 B2
• Time in Patent Office: Days
• US Class Current: 702/19
• CPC Class Codes: A61B 2562/028 Microscale sensors, e.g. electromechanical sensors [MEMS]
• CPC Class Codes: A61B 5/0002 Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network A61B5/07 takes precedence; transmission systems for measured values G08C; transmission H04B; transmission of digital information H04L; wireless communication networks H04W
• CPC Class Codes: A61B 5/02028 Determining haemodynamic parameters not otherwise provided for, e.g. cardiac contractility or left ventricular ejection fraction
• CPC Class Codes: A61B 5/0215 by means inserted into the body catheters A61M25/00
• CPC Class Codes: A61B 5/024 Detecting, measuring or recording pulse rate or heart rate A61B5/0205, A61B5/021 take precedence
• CPC Class Codes: A61B 5/026 Measuring blood flow A61B3/1233, A61B3/1241 take precedence
• CPC Class Codes: A61B 5/076 Permanent implantations telemetry using implanted circuitry A61B5/0031; implanted stimulators for therapy A61N1/3605, A61N1/362, A61N1/372
• CPC Class Codes: A61B 5/145 Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissuemeasuring of blood pressure or blood flow A61B5/02; non-radiation detecting or locating of foreign bodies in blood A61B5/06
• CPC Class Codes: A61B 5/14539 for measuring pH
• CPC Class Codes: A61B 5/14542 for measuring blood gases A61B5/14551 takes precedence
• CPC Class Codes: A61B 5/14546 for measuring analytes not otherwise provided for, e.g. ions, cytochromes
• CPC Class Codes: A61B 5/411 Detecting or monitoring allergy or intolerance reactions to an allergenic agent or substance
• CPC Class Codes: A61B 5/413 Monitoring transplanted tissue or organ, e.g. for possible rejection reactions after a transplant
• CPC Class Codes: A61B 5/415 the glands, e.g. tonsils, adenoids or thymus
• CPC Class Codes: A61B 5/418 lymph vessels, ducts or nodes
• CPC Class Codes: A61B 5/4839 combined with drug delivery
• CPC Class Codes: A61B 5/486 Bio-feedback A61B5/375 takes precedence
• CPC Class Codes: A61B 5/686 Permanently implanted devices, e.g. pacemakers, other stimulators, biochips A61B5/6861 takes precedence
• 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: A61P 9/00 Drugs for disorders of the cardiovascular system
• CPC Class Codes: C12Q 1/04 : Determining presence or kind of microorganism; Use of selective media for testing antibiotics or bacteriocides; Compositions containing a chemical indicator therefor C12Q1/6897 takes precedence
• CPC Class Codes: C12Q 1/68 : involving nucleic acids
• CPC Class Codes: C12Q 1/6886 : for cancer immunoassay for cancer G01N33/574
• CPC Class Codes: C12Q 1/70 : involving virus or bacteriophage immunoassay for viruses G01N33/56983
• CPC Class Codes: C12Q 2600/156 : Polymorphic or mutational markers
• CPC Class Codes: G01N 33/53 : Immunoassay; Biospecific binding assay; Materials therefor
• CPC Class Codes: G06Q 40/08 : Insurance
• CPC Class Codes: G06Q 50/22 : Social work or social welfare, e.g. community support activities or counselling services
• CPC Class Codes: G16B 5/00 : ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
• CPC Class Codes: G16B 5/20 : Probabilistic models
• CPC Class Codes: G16B 5/30 : Dynamic-time models
• CPC Class Codes: G16H 10/60 : for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 40/63 : for local operation
• CPC Class Codes: G16H 50/50 : for simulation or modelling of medical disorders
• CPC Class Codes: G16H 70/60 : relating to pathologies
• CPC Class Codes: Y02A 90/10 : Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

BioMEMS/NEMS appliance biologically monitors an individual, using biosensors to detect cellular components. Data is simulated or analyzed using systems-biology software, which provides diagnostic or therapeutic guidance.

Claims

1-20. -20. (canceled)

21. A system for detecting a genetic predisposition of a patient for metabolizing a drug comprising:

a microarray comprising one or more oligonucleotide probes for detecting by hybridization a presence of one or more DNA polymorphisms of CYP2D6 labeled with a fluorescent dye;

a laser scanner for detecting a hybridization pattern produced on the microarray labeled by the fluorescent dye; and

a data analysis module for determining a phenotype of a patient, such that a dosage of one or more drugs comprising β

-adrenergic receptor antagonists, neuroleptics, or tricyclic antidepressants is personalizable according to the patient phenotype.

23. A system according to claim 21, wherein the data analysis module further comprises a database comprising information such that a suggested therapy comprising a specific drug to treat the patient is accessible to medical professionals.

24. A system according to claim 21, further comprising a storage device wherein the phenotype of the patient can be accessed and displayed to medical professionals using an on-screen search.

22. A method for detecting a genetic predisposition of a patient for metabolizing a drug comprising the steps of:

hybridizing DNA acquired from a patient and labeled with a fluorescent dye to a microarray comprising one or more oligonucleotide probes for detecting a presence of one or more DNA polymorphisms of CYP2D6;

scanning the microarray with a laser for detecting a hybridization pattern produced on the microarray by sensing the fluorescent dye; and

determining a phenotype of the patient using a data analysis module such that a dosage of one or more drugs comprising β

-adrenergic receptor antagonists, neuroleptics, or tricyclic antidepressants is personalizable according to the patient phenotype.

25. A method for diagnosing an infectious disease or infection comprising the steps of:

hybridizing biotinylated biological samples acquired from a patient to a site on a microarray comprising biotinylated reporter probes bound to a streptavidin gel;

scanning the microarray with a laser for detecting one or more fluorescence ratios by sensing the fluorescent dye; and

reporting the presence or absence of one or more nucleic acid sequences for specific organisms or genetic mutations associated with disease such that an infection comprising influenza, herpes, chlamydia, pneumonia, or cytomegalic inclusion disease is diagnosable.

26. A method according to claim 25, wherein the reporting step further comprises creating and displaying one or more suggested therapies based on a patient'"'"'s medical history or insurance coverage.

27. The method of claim 26, further comprising the step of repeating the diagnosis such that a selected therapy can be evaluated and is adaptable to the patient.

29. An apparatus according to claim 25, wherein the user interface further comprises creates and displays one or more suggested therapies based on a patient'"'"'s medical history or insurance coverage or FDA approval status.

30. The apparatus of claim 29, further comprising a second microarray for repeating the diagnosis such that a selected therapy can be evaluated and is adaptable to the patient.

28. An apparatus for diagnosing an infectious disease or infection comprising:

microarray comprising biotinylated reporter probes bound to a streptavidin gel for hybridizing biotinylated biological samples acquired from a patient;

a laser scanner for scanning the microarray to detect one or more fluorescence ratios by sensing the hybridized biotinylated biological samples; and

a user interface for reporting the presence or absence of one or more nucleic acid sequences for specific organisms or genetic mutations associated with disease such that an infection comprising influenza, herpes, chlamydia, pneumonia, or cytomegalic inclusion disease is diagnosable.

31. An apparatus for diagnosing an infectious disease or infection comprising:

a microarray for hybridizing biotinylated biological samples acquired from a patient to a site comprising biotinylated reporter probes bound to a streptavidin gel;

an automated platform for scanning the microarray with a laser for detecting fluorescence ratios by sensing the fluorescent dye; and

a user interface for reporting the presence or absence of nucleic acid sequences for specific organisms or genetic mutations associated with disease such that an infection comprising influenza, herpes, chlamydia, pneumonia, or cytomegalic inclusion disease is diagnosable.

32. The apparatus of claim 31, further comprising a sensor manufacture to dictate the manufacture using a software program for binding probes in an array for hybridizing biotinylated biological samples acquired from a patient.

33. A method for diagnosing an infectious disease or infection comprising the steps of:

hybridizing biotinylated biological samples acquired from a patient to a microarray site comprising biotinylated reporter probes bound to a streptavidin gel;

scanning the microarray with a laser for detecting fluorescence ratios by sensing the fluorescent dye; and

reporting the presence or absence of nucleic acid sequences for specific organisms or genetic mutations associated with disease such that an infection comprising influenza, herpes, chlamydia, pneumonia, or cytomegalic inclusion disease is diagnosable on a user interface.

34. The method of claim 33, further comprising the step of manufacturing nucleic acids to be bound to microarrays using software for hybridizing biotinylated biological samples acquired from a patient.

35. A method for diagnosing a patient or making therapy recommendations comprising the steps of:

storing information in a database such that patient records comprising reports indicating gene expression, a history of diagnoses, patient age, height, weight, symptoms, allergies, diet, previous or present medications, medical or family history of disease, sickness or infection, results of previous blood or urine tests, or environmental or immunological factors is accessible using an on-screen search of a patient record;

using mathematical methods comprising neural networks, artificial intelligence, fuzzy systems, or probabilities on the patient records to simulate one or more conditions of a patient; and

reporting one or more diagnoses or therapy recommendations based on the conditions of the patient to a medical professional on a user interface.

36. The method of claim 35 wherein the patient records further comprise information about the insurance coverage of the patient.

37. The method of claim 36 wherein the therapy recommendations are based on the insurance coverage of the patient.

38. The method of claim 35 comprising the additional step of assuring that the therapy recommendations comply with Food and Drug Administration (FDA) regulations.

39. An apparatus for diagnosing a patient or making therapy recommendations comprising:

a database for storing patient records such that reports comprising gene expression analysis, a history of diagnoses, patient age, height, weight, symptoms, allergies, diet, previous or present medications, medical or family history of disease, sickness or infection, results of previous blood or urine tests, or environmental or immunological factors is accessible using an on-screen search of a patient record;

a data analyzer using mathematical methods comprising neural networks, artificial intelligence, fuzzy systems, or probabilities on the patient records to simulate one or more conditions of a patient; and

a user interface for reporting one or more diagnoses or therapy recommendations based on the conditions of the patient to a medical professional on a user interface.

40. The apparatus of claim 39 wherein the patient records further comprise information about the insurance coverage of the patient.

41. The method of claim 40 wherein the therapy recommendations are based on the insurance coverage of the patient.

42. The method of claim 39 comprising a regulatory overlay for assuring that the therapy recommendations comply with Food and Drug Administration (FDA) regulations.

43. A method for treating a patient with HIV comprising the steps of:

using an HIV diagnostic system to diagnose a patient as HIV positive;

storing the HIV positive diagnosis in a database such that patient records comprising reports indicating gene expression, a history of diagnoses, patient age, height, weight, symptoms, allergies, diet, previous or present medications, medical or family history of disease, sickness or infection, results of previous blood or urine tests, or environmental or immunological factors is accessible using an on-screen search of a patient record; and

using mathematical methods comprising neural networks, artificial intelligence, fuzzy systems, or probabilities on the patient records to simulate one or more conditions of a patient; and

reporting one or more therapy recommendations based on the conditions of the patient to a medical professional on a user interface.

44. An apparatus for treating a patient with HIV comprising:

an HIV diagnostic system to diagnose a patient as HIV positive;

a database for storing the HIV positive diagnosis such that patient records comprising reports indicating gene expression, a history of diagnoses, patient age, height, weight, symptoms, allergies, diet, previous or present medications, medical or family history of disease, sickness or infection, results of previous blood or urine tests, or environmental or immunological factors is accessible using an on-screen search of a patient record;

a data analyzer using mathematical methods comprising neural networks, artificial intelligence, fuzzy systems, or probabilities on the patient records to simulate one or more conditions of a patient; and

a user interface for reporting one or more therapy recommendations based on the conditions of the patient to a medical professional on a user interface.

45. An apparatus for analyzing a patient'"'"'s metabolic profile comprising:

a sensor comprising microfluidics to mix reagents and a biological sample from a patient to chemically react;

a processor for monitoring chemical reactions by optical communication such that the concentrations of ions comprising H+, Ca²⁺, K⁺, Na⁺, Mg²⁺, Zn²⁺, Cl⁻

, NO₂⁻

, O₂, NO or glucose molecoles are determined such that metabolic conditions are diagnosable; and

a user interface connected to a network for accessing the concentrations of ions from a database coupled to the processor.

46. A method for analyzing a patient'"'"'s metabolic profile comprising the steps of:

mixing reagents and a biological sample from a patient to chemically react using microfluidics;

monitoring chemical reactions by optical communication such that concentrations of one or more ions comprising H+, Ca²⁺, K⁺, Na⁺, Mg²⁺, Zn²⁺, Cl⁻

, NO₂⁻

, O₂, NO or glucose molecules are determined such that metabolic conditions are diagnosable; and

accessing the concentrations from a database coupled to the processor over a network using a user interface.

47. A method for diagnosing immunity diseases comprising the steps of:

sensing levels of HLA (human leukocyte antigen) complex by amplifying and sequencing a patient'"'"'s genomic DNA;

generating a report accessible via a user interface wherein the report is customizable by the user such that a diagnosis is determinable.

48. An apparatus for diagnosing hormonal changes, cancer, infectious diseases or diabetes comprising:

a chip-based ELISA platform for binding a target antigene obtained from a patient to an adsorbed antibody;

an electrochemical detector using current to detect a concentration of the target antigens; and

a user interface for generating a report such that one or more diagnoses or therapy recommendations can be made based on the conditions of the patient to a medical professional.