INHALATION MONITORING SYSTEM AND METHOD

Abstract

An inhalation monitoring system includes an inhaler having a medicament delivery apparatus configured to deliver medicament to a user during an inhalation of the user; inhalation monitoring apparatus, configured to, during the inhalation, gather data for determining a measure of the user's lung function and/or lung health; and a processor configured to receive the data from the inhalation monitoring apparatus and, using the data, determine a measure of the user's lung function and/or lung health.

Claims

1-20. (canceled)

21. An inhalation monitoring system comprising: a processor configured to: receive inhalation data gathered during a plurality of inhalations of a plurality of different users; identify occurrences of exacerbations of a lung condition for the plurality of different users based on the inhalation data; identify a pattern in changes to the inhalation data that precede the occurrences of exacerbations; and determine that inhalation data of a patient matches the pattern; and a user interface configured to provide an alert for the patient or their medical practitioner based on the determination that the inhalation data matches the pattern.

22. The inhalation monitoring system of claim 21, wherein the alert indicates a suggested change to a treatment regimen of the patient.

23. The inhalation monitoring system of claim 21, wherein the alert indicates an efficacy of the treatment regimen of the patient.

24. The inhalation monitoring system of claim 21, wherein the alert indicates an increased likelihood of an exacerbation of the lung condition for the patient.

25. The inhalation monitoring system of claim 21, wherein the processor is configured to receive additional inhalation data of additional inhalations, and refine the identification of the pattern using a self-learning algorithm.

26. The inhalation monitoring system of claim 21, wherein the processor is configured to predict future changes to the user's lung function or lung health based on the determination that the inhalation data of the patient matches the pattern.

27. The inhalation monitoring system of claim 21, wherein the future changes comprise exacerbations of an existing respiratory condition, and wherein the existing respiratory condition is asthma, chronic obstructive pulmonary disease, respiratory syncytial virus, cystic fibrosis, idiopathic pulmonary fibrosis or pulmonary embolism.

28. An inhalation monitoring system of claim 21, wherein the processor is further configured to: determine inspiratory measures based on the inhalation data; determine expiratory measures based on the inspiratory measures; identify the occurrences of exacerbations of the lung condition for the plurality of different users; identify a pattern in changes to the expiratory measures that precede the occurrences of exacerbations; and determine that expiratory measures for a patient match the pattern; and wherein the user interface is configured to provide the alert for the patient or their medical practitioner that indicates an increased likelihood of an exacerbation of the lung condition based on the determination that the expiratory measures matches the pattern; wherein the alert indicates a change to a treatment regimen of the patient, an efficacy of a treatment regimen of the patient, or an increased likelihood of an exacerbation of the lung condition for the patient.

29. A method comprising: determining a plurality of inspiratory measures, wherein each inspiratory measure is based on data gathered during an inhalation of a user; determining an expiratory measure based on each of the plurality of inspiratory measures, wherein each of the expiratory measures is indicative of a lung function of the user; identifying a pattern in the expiratory measures or the plurality of inspiratory measures; and generating an alert, via a user interface, for the user or their medical practitioner that is indicative of a progression of a lung related condition over time based on the identified pattern.

30. The method of claim 29, wherein the alert indicates an efficacy of a treatment regimen of the user or a change to the treatment regimen of the user.

31. The method of claim 29, wherein the pattern relates to an exacerbation.

32. The method of claim 31, wherein the pattern precedes the exacerbation.

33. The method of claim 29, further comprising: identifying occurrences of exacerbations of a lung condition for the user based on the expiratory measures or the plurality of inspiratory measures; identifying the pattern based on changes to the expiratory measures or the plurality of inspiratory measures that precede the occurrences of exacerbations.

34. The method of claim 29, further comprising: predicting a future lung function of the user based on the identified pattern, wherein the future lung function of the user comprises an exacerbation of the lung related condition of the user; and providing an alert to the user that indicates the future lung function prediction.

35. An inhalation monitoring system comprising: a processor configured to: determine a plurality of inspiratory measures, wherein each inspiratory measure is based on data gathered during an inhalation of a user; determine an expiratory measure based on each of the plurality of inspiratory measures, wherein each of the expiratory measures is indicative of a lung function of the user; and identify a pattern in the expiratory measures or the plurality of inspiratory measures; and a user interface configured to provide an alert for the user or their medical practitioner that is indicative of a progression of a lung related condition over time based on the identified pattern.

36. The inhalation monitoring system of claim 35, wherein the alert indicates an efficacy of a treatment regimen of the user or a change to the treatment regimen of the user.

37. The inhalation monitoring system of claim 35, wherein the pattern relates to an exacerbation.

38. The inhalation monitoring system of claim 37, wherein the pattern precedes the exacerbation.

39. The inhalation monitoring system of claim 35, wherein the processor is further configured to: identify occurrences of exacerbations of a lung condition for the plurality of different users based on the expiratory measures or the plurality of inspiratory measures; and identify the pattern based on changes to the expiratory measures and/or the plurality of inspiratory measures that precede the occurrences of exacerbations.

40. The inhalation monitoring system of claim 35, wherein the processor is further configured to predict a future lung function of the user based on the identified pattern, wherein the future lung function of the user comprises an exacerbation of the lung related condition of the user; and wherein the user interface configured to provide an alert to the user that indicates the future lung function prediction.

Description

BRIEF DESCRIPTION OF THE DRAWING FIGURES

[0084] Aspects of the present invention will now be described by way of example with reference to the accompanying figures. In the figures:

[0085] FIG. 1a illustrates a correlation between PEF and the maximum flow measured during inhalation;

[0086] FIG. 1b illustrates a correlation between FEV1 and total inhaled volume;

[0087] FIG. 2 schematically illustrates an example inhalation monitoring system; and

[0088] FIG. 3 is a flowchart of an example inhalation monitoring method.

DETAILED DESCRIPTION OF THE INVENTION

[0089] The following description is presented to enable any person skilled in the art to make and use the system, and is provided in the context of a particular application. Various modifications to the disclosed embodiments will be readily apparent to those skilled in the art.

[0090] The general principles defined herein may be applied to other embodiments and applications without departing from the spirit and scope of the present invention. Thus, the present invention is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.

[0091] Many lung patients are prescribed inhalers so that they or a caregiver can administer medicament to them as a routine preventative measure, to ease an exacerbation, or both. Such patients and caregivers are trained in the use of these inhalers and become very familiar with them. It is therefore proposed to monitor patients' lung function using their inhalers. Monitoring lung health while administering medication reduces the time and effort required from patients, caregivers and medical professionals to manage lung conditions.

[0092] This has not been previously considered since, as explained above, lung function is generally assessed using expiratory measures and dry powder inhalers, for example, are not generally designed to permit exhalation. In some cases, for example some dry powder inhalers, exhalation into inhalers can impair their function (e.g. if moisture from an exhalation causes powdered medicament to form clumps, making even administration more difficult).

[0093] However, the applicant has established that there are correlations between some expiratory measures of lung function and some inspiratory measures. For example, see FIG. 1a, showing a correlation between PEF and the maximum flow measured during inhalation (peak inspiratory flow, PIF), and FIG. 1b, showing a correlation between FEV1 and total inhaled volume. Regression lines and their equations are indicated on the plots, where:

x.sub.1=gender (male=0; female=1)
x.sub.2=age/years
x.sub.3=height/cm
x.sub.4=weight/kg
x.sub.5=PEF/l.Math.min.sup.−1
x.sub.6=FEV1/l.Math.min.sup.−1
y.sub.1=inhaled volume/l
y.sub.2=PIF/l

[0094] It is therefore proposed to process inhalation data gathered while administering medicament with an inhaler in order to determine lung function and/or health.

[0095] FIG. 2 schematically illustrates an example inhalation monitoring system 200. An inhaler 210 comprises medicament delivery apparatus 211. This could for example be as per the dry powder inhalers described in any of PCT patent application publication numbers WO 01/97889, WO 02/00281, WO 2005/034833 or WO 2011/054527, which are incorporated in their entirety herein. Inhalation monitoring systems could also comprise other types of inhalers/nebulisers, e.g. pressurised metred dose inhalers (pMDIs) or wet nebulisers. The inhalers could require forced inspiratory manoeuvres or only tidal breathing.

[0096] Inhalation monitoring apparatus 220 may also be comprised in the inhaler as shown, or may be comprised in a separate unit connected to it. The inhalation monitoring apparatus could for example comprise a miniature (e.g. microelectromechanical, MEMS, or nanoelectromechanical, NEMS) pressure sensor as described in any of U.S. patent application No. 62/043,126 to Morrison, 62/043,120 to Morrison, and 62/043,114 to Morrison, which are incorporated in their entirety herein. Other suitable arrangements could be envisaged. For those making use of a pressure sensor, said sensor should be in pneumatic communication with an airflow channel of the inhaler through which the user inhales.

[0097] A processor 230 communicates with the inhalation monitoring apparatus in order to process data collected by the inhalation monitoring apparatus to determine a measure of the user's lung function and/or health. The processor could be comprised in the inhaler as shown, or if the inhalation monitoring apparatus is comprised in a separate accessory unit, the processor could also be comprised in said accessory unit. Alternatively, if the inhalation monitoring apparatus is equipped with a wired or wireless transmitter 221, the processor could be in a separate device, for example a user device such as a smartphone, tablet, laptop or PC. If the inhalation monitoring apparatus is equipped with a transmitter capable of communicating with a network such as the internet, the processing could be done remotely, for example at a medical professional's PC or on a health service, inhaler manufacturer or cloud server. (Any of the abovementioned devices or servers could also be used for data storage.) Optionally, processor 230 could be made up of multiple processors in any of the abovementioned locations, for example some basic processing may be done on board the inhaler, while more detailed analysis is offloaded to a remote device or server.

[0098] The inhaler could optionally comprise a user interface 240 for providing information relating to use of the inhaler and/or determined lung function and/or lung health. This could, for example, be a screen, indicator light, indicator buzzer, speaker, traditional dose counter tape, vibrating alert etc. or any combination of these or similar. Alternatively, such information could be provided via one or more user interfaces of a user device of the patient or a caregiver or medical professional.

[0099] The system could also comprise a memory 250 for storing the collected data, calculation results and computer code instructions for execution by the processor. As with the processor, the memory could be located in the inhaler or an external device or server.

[0100] The electronic component of the inhaler could be powered by a battery 212 so that the inhaler can be portable.

[0101] The inhaler could further comprise switching means for putting the medicament delivery apparatus in or out of operation. When the medicament delivery apparatus is not functioning, the inhaler can be used as a spirometer. As one example, electronic switching means could be provided if the medicament delivery apparatus is under electronic (e.g. push-button) control. As another example, PCT patent application publication number WO 2005/034833, which is incorporated by reference herein in its entirety, describes a mechanism for a metered dose dry powder inhaler in which a metering cup measures out a dose of medicament from a hopper and is moved to a dosing position by action of a yoke linked to a mouthpiece cover. Thus, opening the mouthpiece cover primes the inhaler for use and once a dose has been inhaled, further dosing is not possible until the cover has been closed and opened again. Using such an inhaler with the inhalation monitoring apparatus proposed herein, a patient could take their dose of medicament and, before closing the mouthpiece cover, make one or more further inhalations through the mouthpiece for the purposes of further data collection. This allows greater volumes of data to be collected without risking the patient over-dosing. As yet another example, a spirometer cartridge could be connected to a replaceable cartridge tidal inhaler, and a patient could make one or more further inhalations through the spirometer cartridge for the purpose of further data collection.

[0102] Alternatively, the inhaler described above could be provided in a kit with a placebo or dummy inhaler which has a similar flow resistance to the real inhaler, but which either does not comprise medicament delivery apparatus, is empty or is loaded with a placebo substance such as lactose. The placebo inhaler could comprise similar inhalation monitoring apparatus to that described above, or could be connectable to such apparatus.

[0103] If inhaler 210 were a wet nebulizer, for example, then all of the electronic components could be located in a module that is removably connected to the inhalation port in order to protect the electronics from exposure to fluid. The module could be configured to be connected to different wet nebulizers of varying shape and size. The module could include a flow channel having a defined inhalation flow resistance that is higher than the inhalation flow resistance of the wet nebulizer alone (i.e., without the module).

[0104] FIG. 3 is a flowchart of an example inhalation monitoring method 300. At 310, inhalation (through an inhaler) commences. At 320, medicament is delivered via the inhaler. At 330, data concerning said inhalation is collected. At 340, inhalation ends. At 350, the data is processed to make a determination of a measure of lung function and/or lung health. The order of steps 320 and 330 could be reversed or they could be carried out partially or fully in parallel. Step 350 could occur before, during or after 340 and before, after, or fully or partially in parallel with 320.

[0105] The data could also be used for adherence monitoring by a medical practitioner, i.e., to ensure that the inhaler is being used properly by the user.

[0106] The processing could comprise use of a mathematical model such as the regression models illustrated in FIG. 1.

[0107] Method 300 could be repeated each time the inhaler is used, which could for example be daily. Data gathered from multiple uses of the inhaler and/or determinations made from the data could be stored and compared to provide an indication of the progression of a condition over time. This information could be used to determine efficacy of the current treatment regime and inform any changes which may be required. The processor may also be capable of using the data and/or determinations to predict future changes in lung function and/or lung health. This prediction could be based only on data collected from the patient in question, or could incorporate data collected from other patients too. For example, data from users of many inhalers as described above could be collated and used to identify patterns in inhalation data changes preceding exacerbations of particular lung conditions. The processing logic could thus be self-learning. If a particular patient's data is then seen to match the beginning of such a pattern, they or their caregiver or medical practitioner could be alerted so that any required changes to a treatment regime (for example increased dosage, additional medications or therapies) can be made to help avoid an exacerbation.

[0108] The data collected by the inhalation monitoring apparatus could be, for example, a time series of pressure differential measurements or absolute pressure measurements. Measurements could be made periodically, for example every 10 ms, 50 ms or 100 ms over e.g. 2, 5 or 10 seconds. Data collection may be reset between uses of the inhalation monitoring apparatus.

[0109] The user interface could provide a numerical value, for example of measured PIF, calculated total inhaled volume, calculated PEF, calculated FEV1 or a fraction or percentage of one of these relative to an ideal value for the particular patient (said ideal value could be chosen based on biometric data such as age, gender, height, weight etc.). Alternatively it could provide a binary indicator as to whether or not the measured value is within a healthy range, or a tertiary indicator as to whether the measured value is below, above or within a healthy range. Boundaries of such a healthy range could again depend on biometric data stored for the particular patient. The user interface could alternatively or additionally be used to indicate number of doses taken or number of doses remaining in a disposable inhaler, refillable hopper or disposable cartridge. Another alternative or additional indication could be whether the inhaler has been used correctly, for example so that the patient or a caregiver or medical professional is alerted to missed doses, inhalations that are too short or weak for effective drug administration, or that medication has otherwise been taken incorrectly, and/or receives confirmation that medication has been taken correctly.

[0110] The applicant hereby discloses in isolation each individual feature described herein and any combination of two or more such features, to the extent that such features or combinations are capable of being carried out based on the present specification as a whole in the light of the common general knowledge of a person skilled in the art, irrespective of whether such features or combinations of features solve any problems disclosed herein, and without limitation to the scope of the claims. The applicant indicates that aspects of the present invention may consist of any such individual feature or combination of features. In view of the foregoing description it will be evident to a person skilled in the art that various modifications may be made within the scope of the invention.