SYSTEM AND METHODS FOR THE PRODUCTION OF PERSONALIZED DRUG PRODUCTS

• US 20120041778A1
• Filed: 08/15/2011
• Published: 02/16/2012
• Est. Priority Date: 08/13/2010
• Status: Active Grant

• Current Assignee: Daniel L. Kraft
• Original Assignee: Daniel L. Kraft
• Inventors: Kraft, Daniel L.
• Granted Patent: US 10,189,616 B2
• Time in Patent Office: Days
• US Class Current: 705/2
• CPC Class Codes: A61J 1/03 for pills or tablets containers for pills or tablets with special dispensing means therefor B65D83/04
• CPC Class Codes: A61J 2200/30 Compliance analysis for taking medication
• CPC Class Codes: A61J 2205/60 using magnetic or electronic identifications, e.g. chips, RFID, electronic tags
• CPC Class Codes: A61J 3/074 Filling capsules; Related operations
• CPC Class Codes: A61M 2205/52 with memories providing a history of measured variating parameters of apparatus or patient
• CPC Class Codes: A61M 2205/6009 for matching patient with his treatment, e.g. to improve transfusion security
• CPC Class Codes: A61M 2205/6054 Magnetic identification systems
• CPC Class Codes: A61M 35/00 Devices for applying media, e.g. remedies, on the human body devices for handling toiletry or cosmetic substances A45D; absorbent pads, e.g. swabs, A61F13/15
• CPC Class Codes: B65D 51/2828 said element being a film or a foil B65D51/2821, B65D51/2842 take precedence
• CPC Class Codes: G16H 20/10 relating to drugs or medications, e.g. for ensuring correct administration to patients
• CPC Class Codes: G16Z 99/00 Subject matter not provided for in other main groups of this subclass
• 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

A system and method for determining an optimal combination drug product for a particular patient includes a processor that receives patient information and determines an optimal combination drug product based on the received information. A system which can provide information regarding predicted events or pathologies based on received patient information and guidance on subsequent steps to ameliorate, treat or intervent. A drug production device includes a plurality of drug containers, each of which are coupled to a drug dispensing channel. A controller controls the dispensing of drug through each channel, and a combination drug product is produced from the dispensed drugs. A combination drug product includes a plurality of discrete units of a first drug, and a plurality of discrete units of a second drug. A transdermal patch includes a plurality of drug compartments, each containing a quantity of drug product, and a controller for controlling the release of drugs from each compartment. Feedback loop elements can enable iterations to optimized personalized doses.

Claims

1. A system for producing a drug product for an individual patient, comprising:

a computer processor configured to receive information relating to the patient and to predict, based on the received patient information, an optimal drug selection, combination and dosage for the patient; and

a drug production device, in communication with the processor, for producing the drug product based on the predicted optimal drug selection, combination and dosage.

2. The system of claim 1 wherein the patient information includes information selected from at least one of the group consisting of:

weight;

age;

sex;

BSA (body surface area);

body mass index;

lean body mass, percentage body fat, metabolism;

renal function;

liver enzymes;

proteomics/biomarkers, blood chemistries, pharmacokinetics;

risk factors for disease;

current medications;

other medications/supplements;

history of prior side effects to one or more medications;

partial or full genome SNP screening data;

analysis of pharmacogenomic and/or pharmacogenetic profile;

drug-drug interaction information;

drug-diet interaction information;

whole or partial genome analysis;

vitamin deficiencies;

vitamin and micronutrient levels;

diet;

drug allergies and/or sensitivities;

environmental, toxin or other allergy history;

the patient'"'"'s medical history;

diagnostic information;

exercise activity;

sleep activities;

tissue expression profiling;

hormonal cycles, biomarker information;

radiologic/imaging information, demographic information;

patient'"'"'s medical history;

diagnostic information;

exercise activity;

monthly reproductive cycle;

sleep activities;

tissue expression profiling, geolocation, social network, consumer information, habits, physiologic data, electroencephalogram (EEG) recordings, behavioral history, geographic history, exposures or potential exposures to toxins and other environmental factors including exposure to radiation, compliance history and personality testing from body measurement devices.

3. The system of claim 2, wherein the biomarker information comprises information obtained from the at least one of the group consisting of the patient'"'"'s blood, urine, sweat, saliva, body tissue, biopsy or bodily fluid.

4. The system of claim 1, wherein the processor further receives reference information and predicts the optimal drug selection, combination and dosage for the patient based on the received patient information and reference information.

5. The system of claim 1, further comprising an external measurement device, said external measurement device being configured to measure at least one element of patient information, and to transmit said measured element of patient information to the processor.

6. The system of claim 1, further comprising a database configured to store a plurality of categories of information that relates patient information to optimal dosages of different drugs, and said processor predicts an optimal drug selection, combination and dosage for the patient by comparing the received patient information with the information stored in the database.

7. The system of claim 1, wherein the predicted optimal drug selection, combination and dosage is output to a display.

8. The system of claim 1, wherein the processor is housed within the drug production device.

9. The system of claim 1, wherein the predicted optimal drug selection, combination and dosage is transmitted to the patient'"'"'s electronic medical record.

10. The system of claim 1, wherein the predicted optimal drug selection, combination and dosage is transmitted to a pharmacy.

11. The system of claim 1, wherein the processor is configured to communicate with the drug production device over a wireless network.

12. The system of claim 1, wherein the processor further receives patient feedback information and predicts the optimal drug selection, combination and dosage for the patient based on the received patient information and the patient feedback information.

13. The system of claim 1, wherein the drug production device comprises:

a plurality of drug containers, each configured to hold a quantity of a drug;

a plurality of drug dispensers, each of said drug dispensers coupled to one of said drug containers; and

a controller, which controls the dispensing of drug by each drug dispenser, wherein a combination drug product is produced from the dispensed drugs.

14. A drug production device, comprising:

a plurality of drug containers, each configured to hold a quantity of a drug;

a plurality of drug dispensers, each of said drug dispensers coupled to one of said drug containers; and

a controller, which controls the dispensing of drug by each drug dispenser, wherein a combination drug product is produced from the dispensed drugs.

15. The drug production device of claim 14, wherein said combination drug product is produced based on information received from a processor relating to a predicted optimal drug selection, combination and dosage.

16. The drug production device of claim 14, wherein each of said drug dispensers are coupled to one another.

17. The drug production device of claim 14, further comprising a conveyor for moving a drug carrier to successive drug dispensers, wherein a determined quantity of each drug is dispensed onto the drug carrier from each drug dispensers.

18. The drug production device of claim 14, further comprising a verification element for verifying qualities of the produced combination drug product.

19. The drug production device of claim 14, further comprising a scanner for scanning identifying indicia provided on the drug containers.

20. A bottle cap for containing one or more drugs, comprising:

a cap configured to fit onto a bottle, said cap containing one or more drugs within a space formed between a frangible seal and under the cap, wherein, in use, said frangible seal is configured to be punctured upon activating the cap whereby to empty drugs contained under the cap into liquid contained in the bottle.

21. The bottle cap of claim 20, further including a bottle for holding a liquid, wherein said bottle cap is configured to fit onto the bottle.

22. A cartridge for holding a bulk quantity of drug, said cartridge comprising a unique coupling element, said coupling element configured to couple to a drug production device having an element to accommodate the coupling element of the drug cartridge.

23. The cartridge of claim 22, wherein said unique coupling element comprises a unique machine-readable indicia for identifying the drug contained within the cartridge.

24. The cartridge of claim 23, wherein said indicia comprises an RFID tag.

25. The cartridge of claim 23, wherein said indicia comprises a barcode.

26. A method of predicting an optimal combination drug product for an individual patient, comprising:

receiving, by a processor, information relating to the patient; and

predicting, by the processor, an optimal drug selection, combination and dosage for the particular patient, based on said received patient information.

27. The method of claim 26, wherein the patient information includes information selected from at least one of the group consisting of:

weight;

age;

sex;

BSA (body surface area);

body mass index;

metabolism;

renal function;

liver enzymes;

pharmacokinetics;

risk factors for disease;

current medications;

other medications;

history of prior side effects to one or more medications;

partial or full genome SNP screening data;

analysis of pharmacogenomic and/or pharmacogenetic profile;

drug-drug interaction information;

drug-diet interaction information;

whole or partial genome analysis;

vitamin deficiencies;

vitamin and micronutrient levels;

diet;

drug allergies and/or sensitivities;

environmental, toxin or other allergy history;

the patient'"'"'s medical history;

diagnostic information;

exercise activity;

sleep activities;

tissue expression profiling;

hormonal cycles, biomarker information;

radiologic/imaging information, demographic information;

patient'"'"'s medical history;

diagnostic information;

exercise activity;

monthly reproductive cycle;

sleep activities;

tissue expression profiling, geolocation, social network, consumer information, habits, physiologic data, electroencephalogram data, behavioral history, geographic history, exposures or potential exposures to toxins and other environmental factors including exposure to radiation, compliance history and personality testing from body measurement devices.

28. The method of claim 27, wherein the biomarker information comprises information obtained from the at least one of the patient'"'"'s blood, urine, sweat, saliva, body tissue, biopsy or bodily fluid.

29. The method of claim 26, wherein at least a portion of said received patient information is received from an external measurement device, said device being configured to measure at least one element of patient information, and to transmit said measured element of patient information to the processor.

30. The method of claim 26, wherein at least a portion of said received patient information includes patient-reported information relating to the severity of symptoms and/or side effects.

31. The method of claim 26, wherein said processor predicts the optimal drug selection, combination and dosage by comparing the received patient information with information stored in a database that relates patient information to optimal dosages of different drugs.

32. The method of claim 26, further comprising:

outputting the predicted optimal drug selection, combination and dosage to a display.

33. The method of claim 26, wherein the processor is housed within the drug production device.

34. The method of claim 26, further comprising:

transmitting the predicted optimal drug selection, combination and dosage to the patient'"'"'s electronic medical record.

35. The method of claim 26, wherein the processor is configured to communicate with the drug production device over a wireless network.

36. A non-transitory computer readable medium encoding a computer program for predicting an optimal combination drug product for an individual patient, comprising first program instructions usable on a processor, for receiving information relating to the patient, and for predicting, by the processor, an optimal drug selection, combination and dosage for the particular patient, based on said received patient information and patient prescription information.

37. The computer readable medium of claim 36, wherein the patient information includes information selected from at least one of the group consisting of:

weight;

age;

sex;

BSA (body surface area);

body mass index;

metabolism;

renal function;

liver enzymes;

pharmacokinetics;

risk factors for disease;

current medications;

other medications;

history of prior side effects to one or more medications;

partial or full genome SNP screening data;

analysis of pharmacogenomic and/or pharmacogenetic profile;

drug-drug interaction information;

the patient'"'"'s medical history;

diagnostic information;

exercise activity;

sleep activities;

tissue expression profiling;

hormonal cycles, biomarker information;

radiologic/imaging information, demographic information;

patient'"'"'s medical history;

diagnostic information;

exercise activity;

monthly reproductive cycle;

sleep activities;

tissue expression profiling, geolocation, social network, consumer information, habits, physiologic data, electroencephalogram data, behavioral history, geographic history, exposures or potential exposures to toxins and other environmental factors including exposure to radiation, compliance history and personality testing from body measurement devices.

38. The computer readable medium of claim 37, wherein the biomarker information comprises information obtained from the at least one of the patient'"'"'s blood, urine, sweat, saliva, body tissue, biopsy or bodily fluid.

39. The computer readable medium of claim 36, wherein at least a portion of said received patient information is received from an external measurement device, said device being configured to measure at least one element of patient information, and to transmit said measured element of patient information to the processor.

40. The computer readable medium of claim 36, further comprising second program instructions, wherein said processor predicts the optimal drug selection, combination and dosage by comparing the received patient information with information stored in a database that relates patient information to optimal dosages of different drugs.

41. The computer readable medium of claim 36, further comprising third program instructions for outputting the predicted optimal drug selection, combination and dosage to a display.

42. The computer readable medium of claim 36, wherein the processor is housed within the drug production device.

43. The computer readable medium of claim 36, further comprising fourth program instructions for transmitting the predicted optimal drug selection, combination and dosage to the patient'"'"'s electronic medical record.

44. The computer readable medium of claim 36, wherein the processor is configured to communicate with the drug production device over a wireless network.

45. A combination drug product comprising a plurality of discrete units of a first drug, and a plurality of discrete units of a second drug.

46. The combination drug product of claim 45, wherein said first drug and said second drug are optimally selected for a patient.

47. The combination drug product of claim 45, wherein said plurality of discrete units of a first drug each comprise substantially equally sized doses, and said plurality of discrete units of a second drug each comprise a second substantially equally sized doses.

48. A cartridge including a plurality of combination drug products of claim 45.

49. The cartridge of claim 48, wherein said cartridge is configured to fit in to a chamber in a drug dispenser, said drug dispenser further having a dispensing mechanism for dispensing one or more of the plurality of combination drug products upon activation of the dispensing mechanism.

50. A method of predicting an optimal treatment protocol for an individual patient, comprising:

receiving, by a processor, information relating to the patient; and

predicting, by the processor, an optimal treatment protocol for the particular patient, based on said received patient information.

51. The method of claim 50, wherein said predicted optimal treatment protocol is selected from the group consisting of a particular diet or exercise regimen, a suggested physical therapy program, a suggested implant, a suggested medical procedure, operation or surgery, one or more drugs, and a combination of one or more of said treatment protocols.

52. A patch for transdermal delivery of a drug product, comprising:

a plurality of drug compartments, each containing a quantity of drug product; and

a controller for controlling the release of drugs from each of said drug compartments, wherein said drug products are optimally selected for a patient.

53. A method for monitoring an individual patient, comprising

receiving, by a processor, information relating to the patient;

and

predicting, by the processor, an early warning and an appropriate response to chronic, deteriorating and/or potentially acute situations for the particular patient, based on said received patient information.

54. The method of claim 53, wherein the patient information includes information selected from at least one of the group consisting of:

weight;

age;

sex;

BSA (body surface area);

body mass index;

metabolism;

renal function;

liver enzymes;

pharmacokinetics;

risk factors for disease;

current medications;

other medications;

history of prior side effects to one or more medications;

partial or full genome SNP screening data;

analysis of pharmacogenomic and/or pharmacogenetic profile;

drug-drug interaction information;

drug-diet interaction information;

whole or partial genome analysis;

vitamin deficiencies;

vitamin and micronutrient levels;

diet;

drug allergies and/or sensitivities;

environmental, toxin or other allergy history;

the patient'"'"'s medical history;

diagnostic information;

exercise activity;

sleep activities;

tissue expression profiling;

hormonal cycles, biomarker information;

radiologic/imaging information, demographic information;

patient'"'"'s medical history;

diagnostic information;

exercise activity;

monthly reproductive cycle;

sleep activities;

tissue expression profiling, geolocation, social network, consumer information, habits, physiologic data, electroencephalogram data, behavioral history, geographic history, exposures or potential exposures to toxins and other environmental factors including exposure to radiation, compliance history and personality testing from body measurement devices.