Method and system for determining operating state

Abstract

The present specification provides a method and system for monitoring a drug delivery process, such as a process for delivering a drug, a therapeutic agent, or a medication. The present specification also provides a method and system for determining the operating state of a drug delivery device.

Description

Technology Field

[0001] Cross-reference

[0002] This application claims the benefit of U.S. Provisional Application No. 63 / 615,429 filed on December 28, 2023, the entirety of which is incorporated herein by reference.

[0003] The subject matter of this patent application relates to the subject matter of Patent Cooperation Treaty application number PCT / US2019 / 069142, U.S. Patent number 11,109,800, U.S. Patent number 11,571,164, and U.S. Patent number 11,786,173, each of which is incorporated herein by reference in its entirety. Background Technology

[0004] Self-administered injection devices have been the subject of continuous development to better provide advantages such as ease of use while delivering effective subcutaneous injections. However, determining the injection status and ensuring compliance and adherence to injection schedules or protocols can be challenging. Therefore, improvements are required.

[0005] The present specification provides a system and method for guiding and monitoring a drug delivery process to ensure the successful delivery of a drug to a target.

[0006] One aspect provided herein is a method for determining the operating state of a drug delivery device, comprising: a) instructing a user to capture one or more images of at least a portion of the drug delivery device using an image sensor; and b) determining the operating state of the drug delivery device by analyzing one or more images—the determining step includes evaluating the location of at least a portion of the drug delivery device. In some embodiments, the method further comprises the step of transmitting one or more images to a cloud-based server.

[0007] In some embodiments, the drug is delivered by advancing a movable component within the drug delivery device. In some embodiments, the movable component advances along a trajectory that is not a straight line. In some embodiments, the amount of drug delivered is linearly related to the distance the movable component advances. In some embodiments, the amount of drug delivered is non-linearly related to the distance the movable component advances.

[0008] In some embodiments, the determining step includes determining the position of a button cap of a drug delivery device. In some embodiments, the position of the button cap includes a ready-to-inject position, an inject position, a pause position, or a lockout position. In some embodiments, the determining step includes determining the position of a needle of a drug delivery device. In some embodiments, the position of the needle includes a retracted position or an extended position. In some embodiments, the determining step includes determining the position of a gas gauge of a drug delivery device. In some embodiments, the position of the gas gauge includes a ready-to-inject position, an inject position, a pause position, a lockout position, or a completion position.

[0009] In some embodiments, the method further comprises the steps of assigning a first operation state at the time a first image is captured, assigning a second operation state at the time a second image is captured, and determining a delivered capacity between the time the first image is captured and the time the second image is captured. In some embodiments, the operation state includes a scan start state, a scan pause state, a scan in progress state, or a scan complete state. In some embodiments, the operation state includes a delivered capacity state, a remaining capacity state, and / or a remaining time to completion state. In some embodiments, the image sensor is a digital camera or a digital video camera.

[0010] In some embodiments, the analysis is performed by comparing one or more images with a predetermined image. In some embodiments, the analysis is performed using a mobile phone. In some embodiments, the analysis is performed using a software application.

[0011] In some embodiments, the method further includes the step of displaying an operating state. In some embodiments, the method further includes the step of receiving input information from a user and calculating a dosage amount of a drug to be administered in a subsequent delivery. In some embodiments, the image sensor includes instructions for a user to guide the positioning of the image sensor with respect to a part of the drug delivery device while capturing one or more images. In some embodiments, the method further includes the step of instructing a user to match a device outline displayed on the image sensor with a part of the drug delivery device while capturing one or more images. In some embodiments, the method further includes the step of storing one or more images. In some embodiments, the method further includes the step of storing information of the operating state. In some embodiments, the method further includes the step of warning a user if the operating state deviates from a predetermined state.

[0012] Another aspect provided in this specification is a system for determining the operating state of a drug delivery device, comprising: an image sensor for capturing one or more images of at least a portion of the drug delivery device; a data transmission interface for transmitting one or more images to an electronic device; and a processor for analyzing one or more images and communicating with the electronic device to determine the operating state.

[0013] In some embodiments, the image sensor includes a digital camera or a digital video camera. In some embodiments, the drug delivery device includes a patch and an injector. In some embodiments, the patch and the injector are detachably coupled. In some embodiments, at least a portion of the drug delivery device includes a button. In some embodiments, at least a portion of the drug delivery device includes a needle. In some embodiments, at least a portion of the drug delivery device includes a gas gauge. In some embodiments, at least a portion of the drug delivery device is configured to change the position indicating the operating status. In some embodiments, the processor is configured to operate a software application.

[0014] In some embodiments, the system further includes a non-transient computer-readable storage medium encoded in a computer program containing instructions executable by a processor. In some embodiments, the system further includes a data reporting accessory for providing information to a user. In some embodiments, the system further includes a data display accessory for displaying an operating state. In some embodiments, an image sensor, a data transmission interface, and a processor are within a common housing. In some embodiments, the common housing is a smartphone.

[0015] Another aspect provided herein is a computer-implemented onboarding method for monitoring drug delivery, the method comprising: a) receiving account information from a user to create a new user account; b) displaying an overview of the application, safety information, an educational video, or any combination thereof; c) receiving confirmation from the user for data consent, acceptance of notifications, symptom tracking information, or any combination thereof; d) creating a patient profile and an injection schedule; and e) establishing a connection with the user's drug delivery device.

[0016] In some embodiments, the step of displaying an overview of the application includes displaying infographics regarding methods for recording and tracking injections, methods for setting reminders for taking medication, methods for generating schedules and reminders for treatment appointments, methods for tracking and identifying symptoms to the user's medical team, methods for accessing support programs, or any combination thereof. In some embodiments, the step of displaying safety information includes displaying drug prescription information. In some embodiments, the step of creating a patient profile includes receiving the user's date of birth, user gender, user name, user age, user weight, user height, user ethnicity, user nationality, user residential address, user zip code, user email, user phone number, user contact information, or any combination thereof. In some embodiments, the step of creating an injection schedule includes receiving the administration frequency, infusion date, infusion time, or any combination thereof. In some embodiments, the step of establishing a connection with the user's drug delivery device is performed via a wireless communication protocol, a machine-readable barcode, or both. In some embodiments, the wireless communication protocol includes near-field communication (NFC), Bluetooth, Bluetooth LE, Wi-Fi, radio frequency identification (RFID), iBeacon, ZigBee, Z-Wave, or any combination thereof.

[0017] In some embodiments, the step of establishing a connection with a user's drug delivery device comprises instructing the user to: a) activate a wireless communication protocol for the drug delivery device; b) position the user's mobile computing device in close proximity to the drug delivery device, the packaging of the drug delivery device, or both—the mobile computing device is positioned close enough to activate wireless communication between the mobile computing device and the drug delivery device—; c) remove a battery insulation tab to activate the drug delivery device; or d) perform any combination thereof.

[0018] In some embodiments, the method further includes the step of bonding the drug delivery device to the application. In some embodiments, bonding is performed when the application is in the background of the user's mobile computing device. In some embodiments, bonding is performed when the application is not opened on the mobile computing device. In some embodiments, the drug delivery device or packaging material includes a bonding stimulus. In some embodiments, the bonding stimulus is provided by a wireless communication protocol, a machine-readable barcode, or both.

[0019] In some embodiments, the method further includes the step of providing a notification to the user when the drug delivery device establishes a connection with the application.

[0020] In some embodiments, the drug delivery device includes a syringe, a wearable autoinjector, a wearable infusion pump, a device attached directly for subcutaneous delivery, a device attached indirectly for subcutaneous delivery, or an autoinjector pen.

[0021] Another aspect provided herein is a non-transient computer-readable storage medium coupled to a processor and storing instructions, wherein the instructions, when executed by the processor, cause the processor to implement an application, and the application comprises: a) an injection module that instructs a user to take a supply, scan a drug, warm a drug, deliver a drug to a delivery base and press down, select an injection site, remove an injection device from a delivery base, attach an injection device to a user with a view window facing upward, or perform any combination thereof; and b) a progress monitor module that displays an injection status, an on / off body status of the injector, injection progress, remaining injection time, or any combination thereof.

[0022] In some embodiments, the application further includes a home module that displays a next infusion time view, a missed infusion notification view, or any combination thereof. In some embodiments, the home module displays a notification when it is determined that a scanned medication has expired, is incorrect, or both. In some embodiments, the infusion module is configured to receive a stomach quadrant selection indicating the location where the injection device is attached. In some embodiments, the application further includes a log module that displays an overview of the user's adherence to the injection schedule and / or indications of symptom progression. In some embodiments, the log module is configured to receive indications for completed injections. In some embodiments, the log module is configured to determine the user's adherence to the injection schedule based on indications for completed injections. In some embodiments, the application further includes a settings module that displays the user's patient profile, infusion schedule, notification settings, or any combination thereof. In some embodiments, the settings module is configured to receive edits from the user regarding the user's patient profile, infusion schedule, notification settings, or any combination thereof. In some embodiments, the user's patient profile includes the user's name, user's date of birth, user's age, user's weight, user's height, user's ethnicity, user's nationality, user's residential address, user's zip code, user's email, user's phone number, or any combination thereof. In some embodiments, the application further includes a login module that receives symptom notifications and injection notifications, and the login module is accessible through the home module. In some embodiments, the application further includes an injection completion module that displays a notification indicating that an injection has been completed. In some embodiments, the progress monitor module includes the injection completion module.In some embodiments, the application further includes a scheduling module that receives user responses to a symptom questionnaire. In some embodiments, the application further includes a resource module that displays an instructions for use document, a demo video, a terms of use document, a privacy policy document, or any combination thereof.

[0023] Inclusion by reference

[0024] All disclosures, patents, and patent applications mentioned in this specification are incorporated by reference into this specification to the same extent that each individual disclosure, patent, or patent application was specifically and individually indicated to be incorporated by reference. Where a disclosure, patent, or patent application incorporated by reference contradicts a disclosure included in this specification, the specification is intended to replace and / or supersede any such contradictory content. Brief explanation of the drawing

[0025] Novel features of the present disclosure are specifically set forth in the appended claims. A better understanding of the features and advantages of the present disclosure will be obtained by referring to the following detailed description presenting exemplary embodiments in which the principles of the disclosure are utilized, and the attached drawings, which are as follows: Fig. 1 ...illustrates an exemplary flowchart of a method for guiding and monitoring the injection of a drug according to some embodiments; Fig. 2 ...shows an exemplary screenshot of a pre-validation instruction provided in a mobile application according to some embodiments; Fig. 3 ...shows additional exemplary screenshots of pre-validation instructions provided in a mobile application according to some embodiments; Fig. 4...schematically illustrates a plurality of devices or systems that can be integrated with the mobile application(s) described herein according to some embodiments, and an educational video for using the plurality of drug delivery devices or systems described herein; Fig. 5 ...illustrates exemplary displays and instructions provided in a mobile application according to some embodiments; Fig. 6a ... illustrates an exemplary step of placing / connecting a syringe to a syringe delivery or filling base of an injector according to some embodiments of the method described herein, and Fig. 6b It illustrates exemplary steps for pressing a syringe plunger to deliver a drug from a syringe to an injector; Fig. 7a ... illustrates an exemplary step of placing or connecting a vial to a vial delivery or filling base of an injector according to some embodiment of the method described herein, and Fig. 7b illustrates an exemplary step of delivering a drug from a vial to an injector; Fig. 8 ...illustrates an exemplary state of an injector according to some embodiments; Fig. 9 ...illustrates an exemplary step of removing a fixing strap on a drug delivery device according to some embodiment of the method described herein; According to some embodiments described in this specification, Fig. 10a It illustrates exemplary graphic instructions for removing the injector from the delivery or charging base and placing it in the body, Fig. 10b It illustrates an exemplary step of removing an injector from a vial delivery or filling base, and Fig. 10c It illustrates an exemplary step of removing an injector from a syringe delivery or filling base; According to some embodiments , Fig. 11a ... illustrates an exemplary target area for the user to attach an injector, and Fig. 11b It illustrates exemplary steps for attaching an injector to a user's body, and Fig. 11c ... illustrates an exemplary side view of an attached injector, and Fig. 11d It illustrates exemplary graphic instructions for removing the safety strip, Fig. 11e ... illustrates an exemplary step of removing a safety strip from an injector; According to some embodiments, Fig. 12a ... illustrates exemplary graphic instructions for pressing a button to start an injection, Fig. 12b ... illustrates an exemplary side view of pressing a button; Fig. 13 ...illustrates an exemplary flowchart for determining the operating state of a drug delivery device according to some embodiments; According to some embodiments, Fig. 14a ... illustrates an exemplary button position in an injector, and Fig. 14b illustrates another exemplary button position in the injector; Fig. 15 is illustrating an exemplary needle position in an injector according to some embodiments; According to some embodiments, Fig. 16a It illustrates an exemplary status indicator for an injector indicating that the drug delivery device is ready to be injected, and Fig. 16b It illustrates an exemplary status indicator for an injector indicating that a drug is being delivered, and Fig. 16c It illustrates an exemplary status indicator for an injector indicating that drug delivery is complete; Fig. 17 ...illustrates an exemplary operating state of a drug delivery device according to some embodiments; According to some embodiments, Fig. 18a ... illustrates an exemplary display of the progression of scanning over time, Fig. 18b It illustrates an exemplary display of the progression of an on-body injection over time; Fig. 19 ... illustrates a computer system programmed or otherwise configured to implement the method provided in this specification; Fig. 20...illustrates components and data flows in an exemplary digital ecosystem for application(s) and drug delivery devices described herein, according to some embodiments; Fig. 21 ...illustrates a flowchart of digital components interacting in an exemplary drug delivery device ecosystem according to some embodiments; Fig. 22 ...illustrates a flowchart of an exemplary digital offering evolution according to some embodiments; Fig. 23 ...illustrates a flowchart of an exemplary digital ecosystem for the application(s) and drug delivery devices described herein, according to some embodiments; Fig. 24 ...shows an image of an exemplary injector according to some embodiments; Fig. 25 [It] illustrates a diagram of an exemplary onboarding method for monitoring drug delivery according to some embodiments; Fig. 26 ...illustrates a diagram of an exemplary application for repeated monitoring of drug delivery according to some embodiments; According to some embodiments, Fig. 27a ... illustrates a graphical user interface of an exemplary login module, Fig. 27b It illustrates a graphical user interface of an exemplary module for instructing a user to select a guidance mode, and Fig. 27c It illustrates a graphical user interface of an exemplary module for instructing a user to take supplies, Fig. 27d It illustrates a graphical user interface of an exemplary module for instructing a user to open packaging, and Fig. 27e It illustrates a graphical user interface of an exemplary module for instructing a user to tap to pair, and Fig. 27f It illustrates a graphical user interface of an exemplary module for instructing a user to maintain a mobile device within a certain distance from a scanning device in order to scan the scanning device, and 27gIt illustrates an exemplary screen when the scanning device is recognized and the scanning device and the application are paired, Fig. 27h It illustrates a graphical user interface of an exemplary module for instructing a user to check a drug (medication), and Fig. 27i It illustrates a graphical user interface of an exemplary module for instructing a user to scan the barcode of a drug container (e.g., a vial), and Fig. 27j It illustrates an exemplary screen showing that the drug has been identified, and Figure 27k It illustrates a graphical user interface of an exemplary module for instructing a user to select an injection site, Fig. 27l ... illustrates an exemplary screen displaying a selected injection site, and Figure 27m It illustrates an exemplary screen that displays a warning or caution when the user selects the last scan area; According to some embodiments, Fig. 28a It illustrates a graphical user interface of exemplary instructions having replayable animations for users to prepare their drug vials, and Fig. 28b It illustrates a graphical user interface of exemplary instructions having a replayable animation for a user to remove the injector and the surrounding filling base from the packaging and to place the injector on a clean, flat surface, Fig. 28c It illustrates a graphical user interface of exemplary instructions having a replayable animation for a user to insert a vial into an injector, and Fig. 28d It illustrates a first graphical user interface of exemplary instructions for a user to prepare an injection site; According to some embodiments, Fig. 29a It illustrates a graphical user interface of exemplary instructions having a replayable animation for a user to prepare an injection site, and Fig. 29bIt illustrates a graphical user interface of exemplary instructions having a replayable animation for removing an injector from a charging base, and Fig. 29c It illustrates a graphical user interface of exemplary instructions having a replayable animation for attaching an injector, and Fig. 29d It illustrates a graphical user interface of exemplary instructions having a replayable animation for removing a safety tab on an injector; According to some embodiments, Fig. 30a It illustrates a graphical user interface of exemplary instructions having a replayable animation for a user to initiate delivery, and Fig. 30b It illustrates an exemplary screen displaying the delivery status, Fig. 30c It illustrates exemplary instructions for use (Instructions for Use: IFU) for delivery, and Fig. 30d It illustrates an exemplary screen displaying that delivery is paused, and Fig. 30e It illustrates an exemplary screen displaying that delivery is complete, and Fig. 30f It illustrates a graphical user interface of exemplary instructions having a replayable animation for a user to remove an injector, and 30g It illustrates an exemplary screen displaying a monitoring patch, Figure 30h It illustrates a graphical user interface of exemplary instructions having a replayable animation for a user to discard an injector; According to some embodiments, Fig. 31a ... illustrates an exemplary extended notification graphical user interface on the lock screen, and Fig. 31b illustrates a graphical user interface of an exemplary collapsed notification on the lock screen, and Fig. 31c illustrates an exemplary graphical user interface of an extended notification on the home screen, and Fig. 31dillustrates an exemplary graphical user interface of a collapsed notification on the home screen; According to some embodiments, Fig. 32a ... illustrates a graphical user interface of an exemplary iconographic notification on a home screen indicating that a device has been recognized, and Fig. 32b It illustrates a graphical user interface of an exemplary icon-type notification on the home screen indicating that a device is being paired, and Fig. 32c It illustrates a graphical user interface of an exemplary icon-type notification on the home screen indicating that the device is paired, and Fig. 32d It illustrates a graphical user interface of an exemplary icon-type notification on the home screen indicating that injection has started; According to some embodiments, Fig. 33a It illustrates a graphical user interface of an exemplary icon-type notification on the home screen indicating that injection has been paused, and Fig. 33b It illustrates a graphical user interface of an exemplary icon-type notification on the home screen indicating an injection error, and Fig. 33c It illustrates a graphical user interface of an exemplary icon-type notification on the home screen indicating that injection is complete, and Fig. 33d It illustrates a graphical user interface of an exemplary icon-type notification on a lock screen indicating that a device has been recognized; According to some embodiments, Fig. 34a ... illustrates a graphical user interface of an exemplary icon-type notification on a lock screen indicating that a device is being paired, and Fig. 34b It illustrates a graphical user interface of an exemplary icon-type notification on the lock screen indicating that injection has started, and Fig. 34c It illustrates a graphical user interface of an exemplary icon-type notification on the lock screen indicating that injection is in progress, and Fig. 34dIt illustrates a graphical user interface of an exemplary icon-type notification on the lock screen indicating that injection has been paused; According to some embodiments, Fig. 35a [Illustrated] illustrates a graphical user interface of an exemplary icon-type notification on a lock screen indicating an injection error, according to some embodiments, and Fig. 35b It illustrates a graphical user interface of an exemplary icon-type notification on the lock screen indicating that injection is complete, and Fig. 35c It illustrates a graphical user interface of another exemplary icon-type notification on the lock screen indicating that an injection is being delivered, and Fig. 35d It illustrates a graphical user interface of another exemplary icon-type notification on the lock screen indicating that injection is paused, and Fig. 35e It illustrates a graphical user interface of another exemplary icon-type notification on the lock screen indicating that injection is complete, and Fig. 35f , 35g , and Fig. 35h It illustrates icon-type notifications on a compact dynamic island for injection statuses of delivering, paused, and completed, and Fig. 35i , Fig. 35j , and 35k It illustrates icon-type notifications in an extended dynamic island for the injection statuses of delivering, paused, and completed, and Fig. 35l , 35m , and Fig. 35n It illustrates icon-type notifications in Minimal Dynamic Island for the injection statuses of delivering, paused, and completed, Fig. 35o illustrates a graphical user interface of an exemplary icon-type notification on a lock screen indicating skin temperature, and 35p illustrates a graphical user interface of an exemplary icon-type notification on a lock screen representing the number of steps, and Figure 35qIt illustrates icon-type notifications in an extended dynamic island for monitoring patch data, and Fig. 35r It illustrates a graphical user interface of an exemplary icon-type notification on the lock screen indicating a broken connection with a patch; Fig. 36 ...illustrates a graphical user interface of an exemplary tap-to-bond pairing process according to some embodiments; According to some embodiments, Fig. 37a It illustrates an exemplary graphical user interface for a user to select "Delete Account" from the application settings, and Fig. 37b It illustrates an exemplary graphical user interface for a user to choose to confirm "account deletion" and / or export data from the application, and Fig. 37c It illustrates an exemplary graphical user interface for a user to confirm "account deletion" after data has been exported, and Fig. 37d It illustrates an exemplary graphical user interface for confirming account deletion after a user taps the "Delete Account" button, and Fig. 37e It illustrates an exemplary graphical user interface for a user to create a new account or sign into an existing account; According to some embodiments, Fig. 38a ... illustrates an exemplary graphical user interface for a user to manage a medicine schedule, and Fig. 38b It illustrates an exemplary graphical user interface for a user to add a medicine name, and Fig. 38c It illustrates an exemplary graphical user interface for a user to add frequencies, and Fig. 38d It illustrates an exemplary graphical user interface for a user to select different information to add, and Fig. 38eIt illustrates an exemplary screen displaying that a drug (e.g., Aleve) is scheduled to be administered daily at 8:00 AM and 8:00 PM, and Fig. 38f It illustrates an exemplary graphical user interface for a user to select an icon and color for a medicine, and 38g It illustrates an exemplary graphical user interface for a user to set a starter dose schedule and administration time for a drug (e.g., Enfusimab), and Fig. 38h According to some embodiments, it illustrates an exemplary screen displaying that, according to some embodiments, a drug (e.g., Enfusimab) is scheduled to be administered by an injector (e.g., enFuse injector) every two weeks at 9:00 a.m. at a dose of 150 mg / mL, starting February 1, 2023; According to some embodiments, Fig. 39a ... illustrates an exemplary screen showing a drug schedule, and the screen shows the drug name, dosage, and administration schedule, Fig. 39b It illustrates an exemplary graphical user interface for a user to choose to skip or complete an administration, and Fig. 39c It illustrates an exemplary screen showing that the administration of the drug (e.g., Enfusimab) is completed and Aleve is scheduled for 11:00 AM, and Fig. 39d It illustrates an exemplary screen showing that the administration of a drug (e.g., Enfusimab) is skipped and Aleve is scheduled for 11:00 AM, and Fig. 39e It illustrates an exemplary screen of the application's home screen during the injection of a drug (e.g., Enfusimab), and Fig. 39f It illustrates an exemplary screen of the application's home screen when the scan is paused, and 39g It illustrates an exemplary screen of the application's home screen when the injection is complete and the monitoring patch is still in use, and Fig. 39h... illustrates an exemplary screen of the application's home screen when the monitoring patch is removed; According to some embodiments, Fig. 40a It illustrates an exemplary screen of the statistics module, and Fig. 40b It illustrates an exemplary screen displaying the average scores of quality of life and disease symptoms based on user input in each survey, Fig. 40c It illustrates an exemplary screen displaying the distribution and number of injection sites during a selected duration, and Fig. 40d It illustrates an exemplary screen displaying regimen compliance, Fig. 40e It illustrates an exemplary screen displaying monitoring patch data from a recent injection, and Fig. 40f It illustrates an exemplary screen displaying monitoring patch data from a recent injection in which an elevated temperature was detected, and 40g inside Figure 40h It illustrates an exemplary screen displaying a summary of monitoring patch data for a selected duration (a single drawing is divided into two drawings for presentation purposes). Specific details for implementing the invention

[0026] The present specification recognizes the need for new and / or improved methods and systems for initiating, guiding, and monitoring a drug delivery process and determining the operating status of a drug delivery device. Such methods or systems can provide a consistent, accurate, and reliable method for monitoring drug delivery schedules and / or protocols, warning the user of any non-compliance with usage, and ensuring compliance with drug delivery schedules and / or protocols.

[0027] Whenever the terms “at least,” “greater than,” or “greater than or equal to” precede the first numeric value in a series of two or more numeric values, the terms “at least,” “greater than,” or “greater than or equal to” apply to each numeric value in that series of numeric values. For example, greater than or equal to 1, 2, or 3 is equivalent to greater than 1, greater than 2, or greater than 3.

[0028] Whenever the terms “no more than,” “less than,” or “less than or equal to” precede the first numeric value in a series of two or more numeric values, the terms “no more than,” “less than,” or “less than or equal to” apply to each numeric value in that series of numeric values. For example, less than or equal to 3, 2, or 1 is equivalent to less than or equal to 3, less than or equal to 2, or less than or equal to 1.

[0029] As used herein, the term “subject” generally refers to a user of the device, system, or method of the present disclosure, or an individual on whom the device, system, or method of the present disclosure is being used. The subject may be a patient (e.g., a patient being treated or monitored by a physician or healthcare provider). Alternatively, the subject may not be a patient. The subject may have or be suspected of having a disease or disability. Alternatively, the subject may be asymptomatic for a disease or disability. The subject may be a vertebrate, a mammal (e.g., a human or animal), a non-human primate, etc. The subject may be an animal such as a rodent (e.g., a rat or a mouse), a canid (e.g., a dog), a feline (e.g., a cat), a bovine, or other animals.

[0030] As used interchangeably herein, the terms “medicament,” “medicine,” “drug,” or “medication” generally refer to a substance used to treat (e.g., medical treatment) a health or physiological condition or condition of a subject. A medicament may be a drug or a therapeutic agent. A medicament may be a solid, liquid, gas, or a combination thereof. A medicament may be an aerosol, pill, tablet, capsule, pastile, elixir, emulsion, effervescent powder, solution, suspension, tincture, liquid, gel, dry powder, vapor, droplet, ointment, or a combination or modification thereof. A medicament may be used to treat an illness, ailment, or disease, or may be used as a health supplement (e.g., vitamins, minerals, probiotics, etc.).

[0031] As used interchangeably herein, the terms “drug delivery device,” “delivery device,” “injector,” or “infusion device” generally refer to a device used to deliver, inject, or infuse a drug to a subject.

[0032] As used interchangeably herein, the terms “injection,” “delivery,” or “infusion” generally refer to the process of injecting a drug into a subject.

[0033] Pre-injection verification and injector operation

[0034] To use an on-body drug delivery device, such as an injector, the user may require feedback regarding the operation of the injector, such as confirmation of the successful initiation of an injection. The user may also need to learn how to use the injector, successfully deliver the drug, position the injector, and initiate the injection.

[0035] In one aspect, the present disclosure provides a system and method capable of guiding a user through the steps of using an injector and its companion delivery system, and providing the user with feedback regarding pre-injection verification and delivery processes.

[0036] Fig. 1 A method for guiding and monitoring an injection, according to some embodiments ( 100 An exemplary flowchart of ) is illustrated. In some embodiments, the method ( 100) is performed by an injection system. In some embodiments, the system includes a mobile device. In some embodiments, the mobile device includes a mobile application. In some embodiments, the mobile application includes a user interface for providing written instructions, images, graphics, animations, audio, and similar things. In some embodiments, the user interface includes a screen that guides the user through the following steps: pre-injection verification, drug delivery, device placement and initiation of injection, and injection progress.

[0037] method( 100 ) is, action( 101 In ), it may include instructing the user to perform pre-injection verification. Fig. 2 Referring to, the menu screen of the mobile application ( 200 function( from ) 201 When you select )(e.g., starting a new injection / infusion), the screen( 202 ) may appear. In some embodiments, a barcode, quick response code (QR code), or near field target may be embedded in the drug vial, syringe packaging, or labeling. In some embodiments, a mobile application provides a user with a barcode or QR code on the vial ( 203 (Reference) or barcode or QR code on the delivery device ( 204 It can be instructed to scan (see reference). The mobile application can be integrated with another application on the mobile device, such as a camera. screen( 205) illustrates an exemplary screen of a scanned QR code, which may present information about a drug or injector. In some embodiments, the mobile application may instruct the user to bring the mobile device containing the mobile application very close to a vial, syringe, or injector. Information about the drug or delivery device may appear on the screen of the mobile application.

[0038] The mobile application can subsequently verify the compatibility of the drug and the injector and / or other parameters of the drug / injector, such as expiration date, dosage, etc. If the drug or device is inappropriate for the user (e.g., an expired drug), the screen ( 301 or 302 )( Fig. 3 (Reference) may appear, which informs the user of the inappropriateness of the drug or injector. If the drug or injector is appropriate for the user, the screen ( 303 ) may appear, which may provide guidance, instructions, or guidelines to the user. Instructions are, screen( 303 As exemplified in ). It may be presented in a continuous scroll format. Then, the mobile application may be paired with an injector or registered with an injector. For example, the injector may include a unique identifier or other indicia that the mobile application can read and register to a user, a user profile, or both.

[0039] After verification before injection, method ( 100 ) is an action( 102It may include instructing the user to deliver a drug to the injector. In some embodiments, the mobile application may instruct the user to follow a demonstration on the mobile application's screen. In some embodiments, the mobile application may display a specific dose to be drawn with the syringe on the screen. Fig. 6a and Fig. 6b Referring to, the mobile application is a syringe ( 601 ) injector( 603 ) syringe delivery / filling base( 602 Place / connect to ), and syringe( 601 from ) injector( 603 To deliver drugs to ), a syringe plunger ( 611 The step of pressing ) can be displayed on the screen. In some embodiments, the mobile application may instruct the user to capture one or more images of at least a portion of the syringe and injector after connection. The mobile application may analyze one or more images (e.g., using a computer vision program or module) and determine whether the syringe is correctly placed / connected. If the syringe is correctly placed / connected, the mobile application may display on the screen that the user can proceed to the next step. If the syringe is incorrectly placed / connected, the mobile application may display on the screen that the user needs to adjust the placement / connection of the syringe.

[0040] Fig. 7a and Fig. 7b Referring to, the mobile application is a vial ( 701 ) injector( 703 ) vial delivery / filling base( 702 Place / connect to ), and from the vial to the injector ( 703 To deliver drugs to the vial ( 702The step of pressing ) can be displayed on the screen. In some embodiments, the mobile application may instruct the user to capture one or more images of at least a portion of the vial and injector after connection. The mobile application may analyze one or more images and determine whether the vial is correctly placed or connected. If the vial is correctly placed / connected, the mobile application may display on the screen that the user can proceed to the next step. If the vial is incorrectly placed or connected, the mobile application may display on the screen that the user needs to adjust the placement / connection of the vial. In some embodiments, the mobile application may display on the screen the dose of the drug to be delivered to the injector.

[0041] Fig. 8 Referring to, after the drug is delivered to the injector, the mobile application displays a gas gauge ( 802 An injector having an exemplary position of ) 801 An exemplary image of ) can be displayed on the screen.

[0042] Fig. 9 Referring to, after the drug is delivered to the injector, the mobile application [delivers] the injector ( 901 Fixing strap ( from ) 902A step for removing the fixing strap can be displayed on the screen. In some embodiments, the mobile application may instruct the user to capture one or more images of at least a portion of the injector. In some embodiments, the mobile application may analyze one or more images (e.g., using a computer vision program or module) and determine whether the fixing strap has been removed correctly. If the fixing strap has been removed correctly, the mobile application may display on the screen that the user can proceed to the next step. If the fixing strap has been removed incorrectly, the mobile application may display on the screen that the user needs to make corrections.

[0043] After the fixing strap is removed, method ( 100 ) is an action( 103 It may include instructing the user to place the injector on the body and begin the injection.

[0044] Fig. 10a inside Fig. 10c Referring to, the fixed strap ( 1002 After ) is removed, the mobile application is the delivery or charging base ( 1003 from ) injector( 1001 The steps of removing ) and placing the injector in the body can be displayed on the screen. Fig. 10b is vial delivery or filling base ( 702 from ) injector( 703 Illuminate an exemplary method for removing ), Fig. 10c is syringe delivery or filling base ( 602 from ) injector( 603 Illustrate an exemplary method for removing ).

[0045] Fig. 11a is an exemplary target area for the user to attach the injector ( 1101 ) illustrates. The target area may include the trunk, torso, or arm of the target. Fig. 11bis the target area of ​​the target's body ( 1101 injector( 1102 An exemplary method of attaching ) is illustrated. In some embodiments, the undersurface of the injector is the injector ( until injection is completed 1102 An adhesive tape may be provided to temporarily secure the ) to the subject's body (e.g., skin). After attaching the injector to the subject, Fig. 11c Referring to, the mobile application has an attached injector ( 1102 An exemplary side view of the injector may be displayed on the screen. In some embodiments, the mobile application may instruct the user to capture one or more images of at least a portion of the injector. In some embodiments, the mobile application may analyze one or more images and determine whether the injector is correctly attached to the target. If the injector is correctly attached to the target, the mobile application may display on the screen that the user can proceed to the next step. If the injector is incorrectly attached to the target, the mobile application may display on the screen information indicating that the user needs to make corrections and the steps for attaching the injector.

[0046] After the injector is accurately attached to the target, Fig. 11d Referring to, the mobile application is a safety strip ( 1103 Remove ) and button( 1104 You can display instructions on the screen to start the injection by pressing ). Fig. 11e is a safety strip ( 1103 ) to the side and the injector( 1102 By pulling substantially parallel to the surface of the injector ( 1102 Safety strip from ) 1103An exemplary method for removing ) is illustrated. In some embodiments, the mobile application may instruct the user to capture one or more images of at least a portion of the injector. In some embodiments, the mobile application may analyze one or more images and determine whether the safety strip has been removed correctly. If the safety strip has been removed correctly, the mobile application may display on the screen that the user can proceed to the next step. If the safety strip has been removed incorrectly, the mobile application may display on the screen information indicating that the user needs to make corrections and steps for removing the safety strip.

[0047] After the safety strip is accurately removed, 12a Referring to, the mobile application has a button ( 1201 You can display instructions on the screen to start the injection by pressing ). Fig. 12b is an injector ( 1202 )'s button( 1201 An exemplary side view of pressing ) is illustrated. The button position may be injection preparation, injection, pause, and lock. Fig. 14a The button is the injection preparation position ( 1401 Illustrates exemplary button locations in ). Fig. 14b The button is the injection position ( 1402 Illuminates another exemplary button location in ). In some embodiments, the mobile application may instruct the user to capture one or more images of at least a portion of the injector. In some embodiments, the mobile application may analyze one or more images (e.g., using a computer vision program or module) and determine whether the button is in the correct position. If the button is not in the correct position, the mobile application may display on the screen information indicating that the user needs to make corrections and steps to press the button in the correct position.

[0048] Fig. 15 Referring to, the mobile application has different positions of the needle, for example, pause ( 1501 ), delivering( 1502 ), or completion( 1503 You can display a photo or animation showing ) on the screen.

[0049] In some embodiments, the mobile application may provide additional guidelines to the user. Fig. 2 If you refer to , the menu screen ( 200 function( from ) 211 When you select )(e.g., an educational video), the screen( 400 ) may appear ( Fig. 4 (Reference). Mobile applications may include various tutorials or educational information for the target audience. Fig. 4 ... schematically illustrates multiple devices or systems that can be integrated with a mobile application. Devices or systems (e.g., a syringe delivery system ( 401 ), handheld system( 402 ), vial delivery system( 403 ), reconstruction system( 404 If you select )), the screen( 401 , 402 , 403 , or 404 ) may appear, and this may include a tutorial or video showing how to use the device or system. Fig. 5 ... outlines an exemplary workflow of a mobile application that can be used with one or more workflows of a mobile application. Menu screen ( 200 )( Fig. 2 From the function (reference) 221 )(e.g., additional information, Fig. 2 If you select (reference), the screen ( 500) may appear, which may include a menu displaying one or more health or physiological parameters or one or more device parameters. Additional information may be available to the subject (e.g., prescription information, device information, etc.). When a function is selected from the menu, the screen ( 502 )(e.g., prescription information) or screen( 504 )(e.g., device information) may appear, which includes additional information, such as safety information (e.g., screen ( 502 or 505 )) or questions and answers (e.g., screen( 503 or 506 It may include additional options for displaying )). The mobile application may include options for the subject to view and / or input patient information (e.g., age, gender, height, weight, activity level). Additional settings such as alarms, alerts, emails, notifications, etc., may be implemented in the mobile application.

[0050] Safety features may be included in the mobile application, and, for example, if a safety measure (e.g., a safety tab) is not performed by the user, the mobile application may notify the user. The mobile application may display one or more injector parameters on the screen (e.g., injection status, injection of the cannula into the target's body, etc.). An incomplete injection may be presented on the screen, which may display the status of the injection and include other indications of device parameters (e.g., “Injection Pause”).

[0051] In some embodiments, the mobile application may present the user with an option to rank the injection experience. Multiple steps of the process may also include communication steps to a separate device, cloud computing, a clinician's server, etc. (e.g., via Bluetooth, Wi-Fi).

[0052] method( 100 ) is, action( 104 In ), it may include instructing the user to monitor the injection process. In some embodiments, monitoring the injection process includes determining the operating status of the injector.

[0053] Method for monitoring the drug delivery process

[0054] In another aspect, the present disclosure provides a method for monitoring a drug delivery process and providing feedback to a user regarding the operating status of an injector.

[0055] Fig. 13 is a method for determining the operating state of an injector ( 1300 Illustrates an exemplary flowchart of ).

[0056] Fig. 13 If you refer to , operation( 1301 In ), method( 1300 ...instructs the user to capture one or more images of at least a portion of the drug delivery device. In some embodiments, the drug delivery device may be a syringe, a wearable autoinjector, or an autoinjector pen. In some embodiments, the drug delivery device may be a wearable infusion pump. In some embodiments, the drug delivery device may be a device attached directly for the subcutaneous delivery of a medicinal product (or drug). In some embodiments, the drug delivery device may be a device attached indirectly for the subcutaneous delivery of a medicinal product (or drug), for example, through a cannula or a set of tubes. In some embodiments, the drug delivery device may be any injector disclosed in PCT / US2019 / 069142, PCT / US2021 / 039545, or PCT / US2018 / 034486, all of which are incorporated herein by reference in their entirety.

[0057] A drug delivery device includes a reservoir for holding a drug. In some embodiments, the drug is delivered by advancing a movable component within the drug delivery device. As the movable component advances within the drug delivery device, the drug is pushed out of the reservoir and delivered to a target through a needle or cannula. In some embodiments, the movable component advances along a non-straight trajectory. In some embodiments, the movable component advances along a straight trajectory. The movable component may be a plunger, i.e., the plunger of a syringe. The movable component may be a gas gauge, i.e., the gas gauge of an injector as described in PCT / US2019 / 069142, PCT / US2021 / 039545, or PCT / US2018 / 034486.

[0058] In some embodiments, the amount of drug delivered is linearly related to the distance the movable component advances. In some embodiments, the amount of drug delivered is non-linearly related to the distance the movable component advances.

[0059] In some embodiments, one or more images may be taken from at least a portion of the drug delivery device. In some embodiments, at least a portion may include a needle. In some embodiments, at least a portion may include a button. In some embodiments, at least a portion may include a movable component, such as a plunger or a gas gauge. In some embodiments, at least a portion of the drug delivery device may be the entire drug delivery device.

[0060] In some embodiments, one or more images may be captured using an image sensor. Non-limiting examples of image sensors include cameras, e.g., digital cameras, mobile phones, video cameras, e.g., digital video cameras, or video recorders. The method may instruct the user to capture images at different times or stages during the delivery process. In some embodiments, the method may instruct the user to capture images before the delivery begins, which may be considered an initial state. In some embodiments, the method may calculate the length of the delivery process and instruct the user to periodically capture images at various intervals spanning from the initial state to completion. For example, if it takes one hour to complete the delivery, the method may instruct the user to capture images at 1 minute, 2 minutes, 5 minutes, 10 minutes, 20 minutes, 30 minutes, 40 minutes, 50 minutes, and 60 minutes. In some embodiments, the method may instruct the user to capture images at shorter intervals during the early stages of the delivery. In some embodiments, the method may instruct the user to capture images at shorter intervals during the later stages of the delivery. The method may allow the user to set a time schedule before delivery begins. In some embodiments, the method may allow the user to modify the schedule at any point in the delivery process.

[0061] In some embodiments, the image sensor may include instructions for guiding the positioning of the image sensor relative to at least a portion of a delivery device while capturing one or more images. In some embodiments, the instructions may include the placement distance and angle of the image sensor relative to at least a portion of the delivery device. When the image sensor is at an appropriate distance and in an appropriate orientation, the image sensor can automate image capture.

[0062] In some embodiments, the image sensor may display the device outline on a screen, and the mobile application may instruct the user to match the device outline with at least a portion of the drug delivery device while capturing one or more images. In some embodiments, the method may include storing one or more images. In some embodiments, one or more images may be stored in the image sensor. In some embodiments, one or more images may be transmitted to another mobile device.

[0063] Fig. 13 If you refer to , operation( 1302 In ), method( 1300 ) may include analyzing one or more images. In some embodiments, the analysis may be performed by a software application. In some embodiments, the analysis may be performed by an algorithm embedded in the software application. In some embodiments, the analysis may be performed by a mobile phone. In some embodiments, one or more images may be transmitted to a cloud-based server and analyzed by a program within the server.

[0064] In some embodiments, the analysis may further include assigning a first operating state at the time when the first image is captured, assigning a second operating state at the time when the second image is captured, and determining the capacity transferred between the time when the first image is captured and the time when the second image is captured.

[0065] In some embodiments, the analysis may be performed, for example, by a computer vision program or module, by comparing one or more images with a predetermined image. In some embodiments, the analysis may be performed by comparing one or more images with a baseline. In some embodiments, the analysis may be performed by comparing a point array within a given relationship to account for scale or image capture variations. In some embodiments, an algorithm may be used for the analysis. In some embodiments, machine learning may be used for the analysis. Any suitable algorithm and / or AI / ML training disclosed in this disclosure may be used for the analysis.

[0066] In some embodiments, the analysis may be performed by a trained model, such as a computer vision model. In some embodiments, the trained model may include a machine learning algorithm.

[0067] Fig. 13 If you refer to , operation( 1303 In ), method( 1300 ) may further include determining the operating state of the drug delivery device. In some embodiments, determining may include evaluating the location of at least a portion of the drug delivery device.

[0068] In some embodiments, determining may include determining the button cap position. Fig. 17 Referring to the button cap position, it may include injection preparation (1702), injection (1703), pause (1704), or lock / complete (1701).

[0069] In some embodiments, determining may include determining the needle position. Fig. 15 Referring to [the image], the needle position may include a retracted position (1501 and 1503) or an extended position (1502).

[0070] In some embodiments, determining may include determining a gas gauge position. The gas gauge position may include an injection preparation position, an injection position, a pause position, or a lock or completion position. Fig. 16a is a gas gauge for the operating status of “injection preparation” ( 1601 Illuminates the exemplary location of ). Fig. 16b is a gas gauge for the operating status of the “injection” ( 1611 Illuminates the exemplary location of ). Fig. 16c is a gas gauge for the “completed” operating status ( 1621 Illuminates the exemplary location of ). The injector lid marking( 1602 Can have ).

[0071] In some embodiments, the operation state may include an injection start state, an injection pause state, an injection in progress state, or an injection completion state. In some embodiments, the operation state may include or provide information regarding the delivered dose, the remaining dose, and / or the remaining time until completion.

[0072] In some embodiments, the method may compare the operating state with a predetermined state. If the operating state deviates from the predetermined state, the method may include warning the user of the deviation. In some embodiments, the method may include steps for troubleshooting.

[0073] After the operation status is determined, the operation status can be displayed on a display device. The display device may be a mobile phone or a cloud-based server. The operation status may be stored on a mobile phone or a cloud-based server.

[0074] In some embodiments, the method ( 1300 ) may include receiving input information from the user and calculating the dosage of the drug to be administered in subsequent delivery.

[0075] Fig. 25The diagram illustrates an exemplary onboarding method for monitoring drug delivery. In some embodiments, the method may include the steps of downloading an application for monitoring drug delivery (2501), creating an account (2502), performing an application overview (2503), receiving data consent (2504), displaying safety information (2505), creating a patient profile (2506), setting an injection schedule (2507), receiving confirmation from the user to accept notifications (2508), receiving symptom tracking information (2509), establishing a connection with the user's device (2510), and displaying an educational video (2512). In some embodiments, the step of creating an account (2502) may include receiving the user's email. In some embodiments, the step of performing an application overview (2503) may include showing the user methods for recording and tracking injections, methods for setting reminders for taking medication, methods for creating schedules and reminders for treatment appointments, methods for tracking and identifying symptoms to the user's medical team, methods for accessing support programs, or any combination thereof. In some embodiments, the step of displaying safety information (2505) may include displaying medication prescription information. In some embodiments, a patient profile may be created by receiving the user's date of birth, user's gender, user's name, user's age, user's weight, user's height, user's ethnicity, user's nationality, user's residential address, user's address / zip code, user's email, user's phone number, user's contact information, or any combination thereof. In some embodiments, the step of setting an injection schedule (2507) may include receiving the administration frequency, injection date, injection time, or any combination thereof.In some embodiments, the step (2510) of establishing a connection with the user's device may be performed via a wireless communication protocol, a machine-readable barcode, or both. In some embodiments, the wireless communication protocol includes near-field communication (NFC), Bluetooth, Bluetooth LE, Wi-Fi, radio frequency identification (RFID), iBeacon, ZigBee, Z-Wave, or any combination thereof.

[0076] In some embodiments, the step (2510) of establishing a connection with a user's device may be performed by instructing the user to turn on Bluetooth, Wi-Fi, RFID, or any combination thereof; instructing the user to tap their mobile device on a drug delivery device (e.g., an injection device), its packaging, or both; instructing the user to remove a battery insulation tab to turn on the injection device; or instructing any combination thereof.

[0077] In some embodiments, establishing a connection with a drug delivery device may include instructing a user to: enable a wireless communication protocol for the drug delivery device; and instructing the user's mobile device (or mobile computing device) to be positioned in close proximity to the drug delivery device, the packaging of the drug delivery device, or both. In some embodiments, the mobile computing device may be positioned close enough to enable wireless communication between the mobile computing device and the drug delivery device. In some embodiments, the method may further include instructing the user to remove a battery insulation tab to enable the drug delivery device.

[0078] In some embodiments, the method may further include providing a notification to the user when the drug delivery device establishes a connection with a mobile device (e.g., an application on the mobile device).

[0079] Fig. 27a inside Figure 30h This illustrates a graphical user interface (GUI) of an exemplary application for setting up, performing, and monitoring drug delivery. In some embodiments, the graphical user interface may be presented to the user in the order illustrated. In some embodiments, two or more consecutive graphical user interfaces may be presented to the user in the order illustrated. Fig. 27a The graphical user interface of an exemplary login module is illustrated, and the user can (i) provide a login email address and password to log in to the application for monitoring drug delivery, or (ii) create an account for the application for monitoring drug delivery. Fig. 27b [It] illustrates a graphical user interface of an exemplary module for instructing a user to select a guidance mode. The guidance mode may include a full guidance mode that includes step-by-step instructions. The guidance mode may include a quick guidance mode that includes summarized instructions. In some embodiments, the application may further include notifications for the user to record their symptoms, perform an injection, and / or refill their prescription. The user can tap Home to return to the Home module. The user can tap stats to move to the statistics module. In some embodiments, the graphical user interface may separate notifications to be processed today from notifications to be processed in the future. Fig. 27c It illustrates a graphical user interface of an exemplary module for instructing a user to take supplies, in which the supplies include a drug vial, a delivery device, and an alcohol wipe. Fig. 27d inside Figure 27k It illustrates a graphical user interface of an exemplary module for instructing a user to set up an injection. Fig. 27d It illustrates a graphical user interface of an exemplary module for instructing a user to open a package. The module may display step-by-step animations to guide the user to open the package. Instructions may include removing the injector and the surrounding filling base from the package and placing the injector on a clean, flat surface. Fig. 27e [Illustrate] illustrates a graphical user interface of an exemplary module for instructing a user to tap to pair. The module may include a replayable animation and may instruct the user to bring the mobile device close to the box of the injection device (or injector) to start the pairing process. At this stage, the box of the injector may remain closed. The user can pair the mobile device with the injection device by tapping Start Pairing. Fig. 27f It illustrates a graphical user interface of an exemplary module for instructing a user to keep a mobile device within a certain distance (e.g., 2 inches) of a scanning device in order to scan the scanning device. When a successful scan is detected, the application may automatically move to the next screen. The user may tap Cancel in the modal to return to the previous screen. 27g It illustrates an exemplary screen when a scanning device is recognized and the scanning device is paired with an application. The screen may include a replayable animation. Fig. 27hIt illustrates a graphical user interface of an exemplary module for instructing a user to check a drug (medication). The application may display a replayable animation of the instruction. The user may open the camera by tapping the Next button. In some embodiments, the application may request access to the camera from the mobile device. Fig. 27i It illustrates a graphical user interface of an exemplary module for instructing a user to scan a barcode (or QR code) of a drug container (e.g., a vial). The module may instruct the user to position the barcode of the container in the center of a frame on the screen. Fig. 27j It illustrates an exemplary screen displaying that the drug is identified (e.g., the drug is correct and has not expired). If the drug is incorrect or has expired, the application may send a warning to the user to replace it with the correct drug. Figure 27k[The document] illustrates a graphical user interface of an exemplary module for instructing a user to select an injection site. The application may instruct the user to determine where to place the injection device. Instructions may include selecting an injection site only on the abdomen. Instructions may include selecting an injection site at least 1 inch from the navel. Instructions may include avoiding areas that are tender, bruised, red, hard, irritated, scarred, tattooed, or have stretch marks. Instructions may include not applying the injector along the belt line. The screen may display four areas corresponding to four regions on the abdomen. For the first injection, the application may instruct the user to select any of the four areas according to instructions. The application may record the injection site for the injection. For subsequent injections, the screen may display the injection site of the previous injection with a different notation (e.g., a different color) and suggest that the user select a different area. Fig. 27l The example screen illustrates an exemplary screen displaying a selected injection site. In some embodiments, the application may instruct the user to record information regarding symptoms and sensations during the injection process (e.g., any discomfort, pain, or irritation). In some embodiments, the application may process user input information and detected information (e.g., health or physiological data from one or more sensors) to determine whether the area is unsuitable for injection or should be avoided. Figure 27mThe device illustrates an exemplary screen that displays a warning or caution when the user selects the area for the last injection. The display may include a recommendation for the user to rotate injection sites to avoid bruising, pain, and / or changes in skin properties that may affect future injections. The user may continue to select the same injection site or select different injection sites.

[0080] Fig. 28a inside Fig. 29d It illustrates a graphical user interface of exemplary instructions for a user to prepare an injection. Fig. 28a It illustrates a graphical user interface of exemplary instructions with replayable animations for a user to prepare their drug vials, including an image of a cap being removed from a vial and the following instructions: remove the plastic cap from the vial; wash the rubber stopper of the vial with an alcohol swab; and dry it. Fig. 28b It illustrates a graphical user interface of exemplary instructions with replayable animations for a user to remove the injector and the surrounding filling base from the packaging and place the injector on a clean, flat surface. Fig. 28c [It] illustrates a graphical user interface of exemplary instructions with replayable animations for a user to insert a vial into an injector. The instructions may include: inserting the vial into the port of the filling base; not lifting or moving the device during filling; pressing the vial down firmly until a steady stream of bubbles is seen indicating that filling has started; the gauge will move as the device fills; filling may take up to 10 minutes and is complete when the retainer strap opens automatically; and placing it on a flat surface until filling is complete. Fig. 28dThe first graphical user interface of exemplary instructions for a user to prepare an injection site may include cleaning the injection site before placing the device. The screen may display an image of the location selected for injection. Fig. 29a The graphical user interface of exemplary instructions with replayable animations for a user to prepare an injection site includes the following instructions: clean the site with an alcohol swab; dry it; ensure that clothing does not come into contact with the cleaned site. Fig. 29b [It] illustrates a graphical user interface of exemplary instructions having a replayable animation for removing an injector from a charging base, and includes the following instructions: charging is completed when the retaining strap opens automatically; when the infuser is lifted from the charging base, the clear adhesive liner will remain attached to the charging base; do not touch the adhesive on the bottom of the infuser; do not remove the safety tab until the infuser is attached to the body. In some embodiments, the module may instruct the user to capture an image of the drug delivery device after the drug delivery device is placed (or attached) to the user's body. In some embodiments, the module may analyze the image to determine the placement (or attachment) location on the user's body. In some embodiments, the module may record and store the attachment location. In some embodiments, the image may be captured by a camera or a digital device. Fig. 29c It illustrates a graphical user interface of exemplary instructions having a replayable animation for attaching an injector. The instructions may include positioning the injector so that the charging window points upward toward the user's face, and pressing the injector firmly to attach the injector to the abdomen. Fig. 29dIt illustrates a graphical user interface of exemplary instructions having a replayable animation for removing a safety tab on an injector. The instructions may include holding the injector with one hand and using the other hand to pull the safety tab to remove it. Delivery may not begin until the safety tab is removed.

[0081] Fig. 30a inside Figure 30h It illustrates a graphical user interface of exemplary instructions for a user to perform an injection. Fig. 30a The graphical user interface illustrates an exemplary instruction having a replayable animation for a user to initiate delivery. The instruction may include initiating delivery by pressing a button firmly until the button is held in place. After the button is pressed, the injection may begin and the status of the injection may be automatically displayed on the screen. Fig. 30b It illustrates an exemplary screen that displays the delivery status. The screen may display that delivery is in progress. An injection status window and a monitoring patch data window may be displayed on the screen. The injection status window may display the start time and the estimated injection time. Patch data may include skin temperature, activity level, step count, and start date. The screen may include a View important IFU button for the user to view instructions. Fig. 30c... illustrates an exemplary IFU for delivery. The IFU may include the following: delivery continues while the button is inserted; to estimate progress, watch the charge gauge as it moves across the charge window toward the empty side; the gauge moves slowly and may take 15 minutes to start moving; the gauge is only an estimate of progress; the injector is not removed until the button pops out; delivery is completed when the button pops out; the gauge is only an estimate of progress; when the button pops out, the needle exits the skin and re-enters the injector without pricking the user. Fig. 30d It illustrates an exemplary screen displaying that delivery is paused. Fig. 30e It illustrates an exemplary screen displaying that delivery is complete. Fig. 30f It illustrates a graphical user interface of exemplary instructions having a replayable animation for a user to remove an injector. The instructions may include using a thumb to lift the adhesive tab, holding the tab against the injector, and slowly peeling the injector away from the skin. 30g It illustrates an exemplary screen displaying a monitoring patch. After the injector is removed, the monitoring patch may remain on the body to continue tracking activity levels and skin temperature. The monitoring patch may function for up to 5 days, and the application may notify the user when it is time to remove the monitoring patch from the abdomen. Replayable animations and instructions may include using a thumb to lift the adhesive tab, holding the tab against the injector, and slowly peeling the injector away from the skin. Fig. 30fIt illustrates a graphical user interface of exemplary instructions having a replayable animation for a user to dispose of an injector. The instructions may include placing the used filling base and injector in an FDA-approved sharp-toothed waste container after use and not disposing of them in household waste.

[0082] In some embodiments, the user may select a quick guidance mode. The quick guidance mode is pairing with a device ( Fig. 27e and 27f ), scanning to check for drugs ( Fig. 27i and Fig. 27j ), recording the injection site ( Fig. 27l ), and performing injections ( Fig. 30a inside Figure 30h It may include ).

[0083] In some embodiments, the system provided herein may enable bonding of an application (e.g., a mobile application) with a drug delivery device and / or packaging material of the drug delivery device. In some embodiments, bonding may be performed while the application is in the background of the mobile device and its operating system. In some embodiments, bonding may be performed without opening the application on the mobile device, that is, without making the application an active window or screen. In some embodiments, the drug delivery device may include any drug delivery device disclosed herein. In some embodiments, the drug delivery device may be a syringe, a wearable autoinjector, or an autoinjector pen. In some embodiments, the drug delivery device may be a wearable infusion pump. In some embodiments, the drug delivery device may be a device directly attached for the subcutaneous delivery of a medicine (or drug). In some embodiments, the drug delivery device may be a device indirectly attached for the subcutaneous delivery of a medicine (or drug), for example, through a cannula or a set of tubes. In some embodiments, the packaging of the drug delivery device may be any suitable packaging that may contain the drug delivery device. In some embodiments, the drug delivery device or packaging may include a bonding, pairing, or registration stimulus or mechanism for initiating and implementing bonding with an application of a mobile device. In some embodiments, the bonding stimulus or mechanism may include a reading of a wireless communication protocol or a computer-readable barcode, e.g., Near Field Communication (NFC), Radio Frequency Identification (RFID), Bluetooth, Bluetooth LE, Wi-Fi, iBeacon, ZigBee, Z-Wave, QR code, or a combination thereof.In some embodiments, when a drug delivery device or packaging material is brought close to a mobile device (e.g., close enough to establish wireless communication and / or accurately read a barcode), an application on the mobile device is activated and a notification pops up on the mobile device screen, thereby enabling a bonding process. Following the bonding process, the application may guide the user through a pairing process to pair the mobile device with the drug delivery device for a subsequent delivery process. In some embodiments, the pairing process may be completed via an application notification function or a live activity function. In some embodiments, the pairing process may be completed by opening the application. Such an automated bonding process can simplify the pairing process, for example, without the need to open the application on the mobile device.

[0084] Fig. 36Figure [] illustrates a graphical user interface of an exemplary tab-to-bond pairing process. As illustrated, in one example, the pairing process may include instructing the user to “bring your phone close to the box of the device to start the pairing process.” When the user performs this action, a notification may be shown indicating that the infusion device is ready to scan, and the user may be instructed to “keep the smartphone near the packaging label to start pairing,” and the user’s mobile device may recognize a tag or code, such as an NFC tag or QR code, within the packaging and / or the infusion device, and a notification may be provided indicating that the device has been recognized. In some embodiments, the user may be further instructed to activate the infusion device. In some embodiments, the user may be further instructed to activate the infusion device by removing the battery tab to allow the battery to supply power to the infusion device. In some embodiments, the user may be further instructed to turn on the infusion device by removing the infusion device from its base. In some embodiments, the user may be further instructed to turn on the infusion device by inserting a vial and / or syringe. In some embodiments, tapping a mobile device on a packaging material can activate a pairing application. In some embodiments, pairing enables communication between an injection device and a mobile device.

[0085] System for monitoring the drug delivery process

[0086] In another aspect, the present disclosure provides a system for monitoring a drug delivery process and providing feedback to a user regarding the operating status of a drug delivery device.

[0087] The system may include an image sensor for capturing one or more images of at least a portion of a drug delivery device, a data transmission interface for transmitting one or more images to an electronic device, and a processor for analyzing one or more images and determining an operating state.

[0088] In some embodiments, the system may include a drug delivery device. In some embodiments, the drug delivery device may be any injector disclosed in PCT / US2019 / 069142, PCT / US2021 / 039545, or PCT / US2018 / 034486. In some embodiments, the drug delivery device may include a patch and an injection unit. In some embodiments, the patch and the injection unit may be removablely coupled.

[0089] In some embodiments, at least part of the drug delivery device may include a button, a needle, or a gas gauge. In some embodiments, at least part of the drug delivery device may be the entire drug delivery device. In some embodiments, at least part of the drug delivery device may be configured to change a location indicating an operating state or a change in the operating state.

[0090] The image sensor may be any suitable image sensor capable of capturing an image. In some embodiments, the image sensor may be a digital camera or a digital video camera. In some embodiments, the image sensor may be a digital camera integrated into a mobile device. In some embodiments, the mobile device may be a laptop, tablet, phone (e.g., a smartphone), or other electronic device (e.g., a portable electronic device).

[0091] In some embodiments, the processor may include a software application. In some embodiments, the software application may be integrated into a mobile device. In some embodiments, the mobile device may include a mobile phone. In some embodiments, the system may include a non-transient computer-readable storage medium encoded in a computer program containing instructions executable by the processor. In some embodiments, the system may include a data reporting accessory for providing information to a user.

[0092] In some embodiments, the system may include a data display accessory for displaying an operating status. In some embodiments, the operating status may include injection start, injection pause, injection in progress, or injection completed. In some embodiments, the operating status may include the delivered dose, the remaining dose, and / or the remaining time until completion. The display may be text, an image, a graph, or an animation.

[0093] Fig. 18a illustrates an exemplary display of the injection progress over time. During the injection, the gas gauge ( 1801 ) is an arrow( 1803 As schematically shown by ), the injector ( 1802 It can advance along a trajectory inside. The trajectory can be non-linear. Fig. 18b is an injector in a state of body attachment over time ( 1812 Illustrate an exemplary display of the injection progress of ). The gas gauge is the arrow ( 1813 As schematically shown by ), the injector ( 1812 It can advance along the trajectory inside.

[0094] Fig. 16a It illustrates an exemplary display indicating that drug delivery is ready for injection, and Fig. 16bIt illustrates an exemplary display indicating that drug delivery is in progress, Fig. 16c It illustrates an exemplary display indicating that drug delivery is complete.

[0095] In some embodiments, the image sensor, the data transmission interface, and the processor may be within a common housing. In some embodiments, the common housing may be a mobile phone.

[0096] Fig. 20 The figure illustrates components and data flow in an exemplary digital ecosystem. As illustrated, a body-attached delivery device (2010) transmits injection data to a mobile application (2020). In some embodiments, the body-attached delivery device (2010) transmits injection data to the mobile application (2020) via Bluetooth. In some embodiments, the mobile application (2020) provides a digital interface for education, reminders, instructions, and resources, and transmits data to the cloud (2030). In some embodiments, the cloud (2030) acts as a database and performs analysis to determine meaningful information from the injection data and stored patient data. In some embodiments, the cloud (2030) transmits data to a dashboard (2040), and the dashboard (2040) acts as an interface for remote stakeholders to utilize the meaningful information determined by the cloud (2030).

[0097] Fig. 21Figure 2 illustrates an exemplary flowchart of digital components within a drug delivery device ecosystem. As illustrated, in some embodiments, drug product information (2111), device information (2112), and patient / caregiver information (2113) are provided to the mobile application (2020). In some embodiments, the drug product information (2111) includes the drug type and drug expiration information. In some embodiments, the device information (2112) includes the infusion date, infusion start time, infusion stop time, infusion duration, dosage, body attachment / detachment status, patient vital signs, or any combination thereof. In some embodiments, the patient or caregiver information (2113) includes patient reported outcomes. In some embodiments, the mobile application (2020) also provides the patient or caregiver with usage instructions, infusion reminders, prescription reminders, symptom guidance, and adherence tracking as user feedback (2114). Additionally, as described, in some embodiments, a mobile application (2020) is communically coupled to a cloud storage (2030). In some embodiments, the cloud storage (2030) provides a clinical trial dashboard (2041) and a provider dashboard (2042) including remote monitoring related to compliance, endpoints, symptoms, or any combination thereof. In some embodiments, the cloud storage (2030) also provides a patient dashboard (2043) based on remote device performance data.

[0098] Fig. 22This illustrates a flowchart of an exemplary digital offering evolution. As illustrated, a mobile application (2020) receives manual input (2050) from a user and receives performance and usage data and biometric data (2011) from a body-attached delivery device (2010). In some embodiments, the mobile application (2020) transmits data to a cloud (2030), and the cloud (2030) is communically coupled to a dashboard (2040). Additionally, as illustrated, the manual input (2050), the mobile application (2020), the cloud (2030), and the dashboard exist in a digital ecosystem offering (2210), the body-attached delivery device (2010) is in a device monitoring offering (2220), and the biometric data (2011) is received in a patient monitoring offering (2230). Fig. 24 It illustrates an image of an exemplary body-attached delivery device (2010).

[0099] Fig. 23 The flowchart illustrates a four-tiered exemplary digital ecosystem for collaboration with a pharma companion. In the first tier (2310), security, analytics, and user experience may be managed by the pharma companion, and the pharma companion utilizes the pharma companion application (2021), the pharma companion cloud (2031), and the pharma companion dashboard (2041). In the second tier (2320), the pharma companion may utilize the mobile application (2020) of this specification, the cloud (2030) includes the pharma companion cloud, and the dashboard (2040) includes the pharma companion dashboard. In the third tier (2330), the pharma companion may utilize the mobile application (2020) and the cloud (2030) of this specification, the cloud (2030) communicates, and the dashboard (2040) includes the pharma companion dashboard.

[0100] Applications for monitoring drug delivery

[0101] The present specification provides a non-transient computer-readable storage medium coupled to a processor and storing instructions, wherein the instructions enable the processor to provide an application when executed by the processor.

[0102] In some embodiments, the application may instruct the user to create an injection schedule and receive reminders. In some embodiments, the application may instruct the user to use step-by-step injection instructions. In some embodiments, the application may monitor the progress of the injection. In some embodiments, the application may record the injection.

[0103] In some embodiments, the application may include a home module. In some embodiments, the home module may display a next infusion time view, a missed infusion notification view, or any combination thereof. In some embodiments, the application may include a login module. In some embodiments, the login module may receive symptom notifications and injection notifications. In some embodiments, the login module may include a function for creating an account or logging in. In some embodiments, the login module may be accessible through the home module. In some embodiments, the application may include an infusion module. In some embodiments, the infusion module may instruct the user to take supplies, scan for medication, warm medication, deliver medication to a delivery base and press down, select an injection site, remove the injection device from the delivery base, attach the injection device to the user with the view window facing upward, or perform any combination thereof. In some embodiments, the application may include a progress monitor module. In some embodiments, the progress monitor module may display the injection status, the body attachment / disattachment status of the injector, the injection progress, or the remaining injection time, or any combination thereof. In some embodiments, the application may include an injection completion module. In some embodiments, the injection completion module may display a notification indicating that the injection has been completed. In some embodiments, a progress monitor module may include the injection completion module. In some embodiments, the application may include a schedule module. In some embodiments, the schedule module may receive user responses to a symptom questionnaire or survey. In some embodiments, the application may include a log module. In some embodiments, the log module may display an overview of the user's compliance with the injection schedule and / or an indication of symptom progression. In some embodiments, the application may include a settings module.In some embodiments, the settings module may display the user's patient profile, infusion schedule, notification settings, or any combination thereof. In some embodiments, the application may include a resource module. In some embodiments, the resource module may display a user manual, a demo video, a terms of use document, or a privacy policy document, or any combination thereof.

[0104] Fig. 26The diagram illustrates an exemplary application for the repeated monitoring of drug delivery. A login module (2620) may receive symptom notifications (2611) and injection notifications (2612) and may be communicatively coupled to a home module (2610). The home module may allow the user to navigate the modules of this specification, view the next injection time, view a missed injection notification, or perform any combination thereof. In some embodiments, from the home module (2610), the user may choose to enter a module (2630) for performing an injection, and the user may be instructed to take supplies (2631), scan the drugs (2632), warm the drugs (2633), deliver the drugs to a delivery base (2634), press down, select an injection site (2635), remove the injection device from the delivery base (2636), place the device at the selected injection site (e.g., abdomen), and start the injection (2637). When an injection is initiated, in some embodiments, a progress monitor module (2638) may display the injection status, the body attachment / detachment status of the injector, the progress of the injection, the remaining injection time, or any combination thereof. In some embodiments, when the injection is completed, an injection completion module (2639) may provide a notification. In some embodiments, if the scanned drug (2632) is determined to be expired and / or incorrect, a notification may be provided to the user. In some embodiments, if the scanned drug (2632) is determined to be accurate or compliant, a notification may be provided to the user. In some embodiments, when the user is instructed to place the device at a selected injection site (e.g., their abdomen with the window facing upward) (2637), a quadrant selection (e.g., abdominal quadrant selection) indicating the location where the device was placed may be received.In some embodiments, from the home module (2610), the user may choose to enter the schedule module (2640) to receive user responses to a symptom questionnaire or survey. In some embodiments, from the home module (2610), the user may choose to enter the record module (2650), which displays an overview of the user's adherence (2651) to their injection schedule and / or indications (2652) of symptom progression. In some embodiments, the record module (2650) may also receive indications for all completed injections, and adherence (2651) may be based on the indications. In some embodiments, from the home module (2610), the user may choose to enter the settings module (2660), and the user may display and / or edit patient profiles (2661) (e.g., name, date of birth, email address, address, password, and / or zip code), display and / or edit their infusion schedules (2662), and / or display and / or edit their notifications (2663) related to injection reminders and symptom tracking. In some embodiments, from the home module (2610), the user may choose to enter the resources module (2670), and the user may view the instruction manual (IFU) (2671) (e.g., a PDF copy of the IFU), demo videos (2672), terms of use (2673), and privacy policy (2674).

[0105] Fig. 31a illustrates an exemplary graphical user interface of an extended notification on a lock screen, with four notification icons arranged to be visible. In some cases, at least one, at least two, at least three, at least four, at least five, or more notification icons may be displayed. Fig. 31billustrates a graphical user interface of an exemplary collapsed notification on a lock screen, wherein one or more notifications are nested, and dismissing one notification displays the subsequent notification below it. In some embodiments, the notification may include an injection in progress (e.g., initiated, in progress, paused, completed, injector removed, and / or monitoring patch removed). In some embodiments, the notification may include a caution. In some embodiments, the caution may include an elevated skin temperature (detected by a monitoring patch). In some embodiments, the caution may include a high or intense activity level. In some embodiments, the caution may include a static activity level (e.g., an activity level close to zero). Fig. 31c It illustrates an exemplary graphical user interface of an extended notification on the home screen, with four notification icons arranged to be visible. Fig. 31d illustrates an exemplary graphical user interface of collapsed notifications on the home screen, where one or more notifications are nested, and dismissing one notification displays the subsequent notification below it.

[0106] Fig. 32a It illustrates a graphical user interface of an exemplary icon-type notification on the home screen that indicates that the device has been recognized and provides an estimated injection time. Fig. 32b It illustrates a graphical user interface of an exemplary icon-type notification on the home screen that indicates that the device is being paired and provides an estimated injection time. Fig. 32c It illustrates a graphical user interface of an exemplary icon-type notification on the home screen that indicates that the device is paired and provides an estimated injection time. Fig. 32d It illustrates a graphical user interface of an exemplary icon-type notification on the home screen that indicates that injection has started in a color different from the pairing notification (e.g., green) and has an estimated injection time. Fig. 33aIt illustrates a graphical user interface of an exemplary icon-type notification on the home screen that indicates that the injection has been paused in a color different from the injection start notification (e.g., yellow) and has an estimated injection time. Fig. 33b It illustrates a graphical user interface of an exemplary icon-type notification on a home screen that indicates an injection error in a color (e.g., red) different from the pairing notification and / or injection start notification and has an estimated injection time. Fig. 33c It illustrates a graphical user interface of an exemplary icon-type notification on the home screen that indicates that injection is complete in a color different from error notifications and / or pause notifications (e.g., green). Fig. 33d It illustrates a graphical user interface of an exemplary icon-type notification on the lock screen indicating that the device has been recognized and the estimated injection time.

[0107] Fig. 34a It illustrates a graphical user interface of an exemplary icon-type notification on the lock screen indicating that the device is being paired and the estimated injection time. Fig. 34b It illustrates a graphical user interface of an exemplary icon-type notification on the lock screen indicating that injection has started and the estimated injection time. Fig. 34c It illustrates a graphical user interface of an exemplary icon-type notification on the lock screen that indicates that injection is in progress, along with a progress bar and an estimated injection time. Fig. 34d It illustrates a graphical user interface of an exemplary icon-type notification on a lock screen that indicates that injection has been paused, along with a progress bar having a color different from the color of the injection progress bar (i.e., yellow) and an estimated injection time. Fig. 35a It illustrates a graphical user interface of an exemplary icon-type notification on the lock screen for an injection error, along with a progress bar having a color different from (i.e., red) of the injection progress bar and an estimated injection time. Fig. 35b It illustrates a graphical user interface of an exemplary icon-type notification on the lock screen indicating that injection is complete. Fig. 35c It illustrates a graphical user interface of another exemplary icon-type notification on the lock screen indicating that an injection is being delivered. Fig. 35d It illustrates a graphical user interface of another exemplary icon-type notification on the lock screen indicating that injection is paused. Fig. 35e illustrates a graphical user interface of another exemplary icon-type notification on the lock screen indicating that injection is complete. In some embodiments, the icon-type notification may be on the compact dynamic island or the expanded dynamic island of the unlocked home screen. Fig. 35f , 35g and Fig. 35h is being delivered ( Fig. 35f ), paused( 35g ), and completed( Fig. 35h Illuminates an icon-type notification in a compact dynamic island regarding the injection status of ). Fig. 35i , Fig. 35j and 35k is being delivered ( Fig. 35i ), paused( Fig. 35j ) and completed( 35k Illuminates icon-type notifications in an extended dynamic island regarding the injection status of ). Fig. 35l , 35m and Fig. 35n ...is being delivered ( Fig. 35l ), paused( 35m ) and completed( Fig. 35n Illuminates icon-type notifications in Minimal Dynamic Island regarding the injection status of ). In some embodiments, monitoring patch data may be displayed on the lock screen. Fig. 35o It illustrates a graphical user interface of an exemplary icon-type notification on the lock screen regarding skin temperature. Figure 35pillustrates a graphical user interface of an exemplary icon-type notification on the lock screen for the number of steps. In some embodiments, monitoring patch data may be displayed in an extended mode, a compact mode, or a minimal mode on a dynamic island of the unlocked screen. Figure 35q It illustrates an icon-type notification in an extended dynamic island for monitoring patch data. In some embodiments, additional notifications may be displayed on the lock screen. Fig. 35r It illustrates a graphical user interface of an exemplary icon-type notification on the lock screen regarding a disconnection from the patch. In some embodiments, additional notifications may be displayed in an extended mode, a compact mode, or a minimal mode on the dynamic island of the unlocked screen.

[0108] In some embodiments, the configuration module may include a submodule for the user to delete the account. In some embodiments, the deletion of the account may occur after the user has completed the prescribed treatment. In some embodiments, the deletion of the account may occur when the user decides to stop treatment (e.g., when no further injections are needed or desired).

[0109] Fig. 37a inside Fig. 37e It illustrates an exemplary graphical user interface for deleting an account. Fig. 37a It illustrates an exemplary graphical user interface for a user to select “Delete Account” from the application settings. Fig. 37bIt illustrates an exemplary graphical user interface for a user to confirm “Delete Account” and / or choose to export data from the application. The user can export data by tapping “Export Data,” and the data may be exported to the email address associated with the account or any email address provided by the user. Fig. 37c It illustrates an exemplary graphical user interface for a user to confirm “Delete Account” after data has been exported. Before the user proceeds with deleting the account, the screen may display a notification, for example, “data successfully exported.” The user may check their email to ensure that the exported data has been successfully received. Fig. 37d It illustrates an exemplary graphical user interface for the user to confirm account deletion after tapping the “Delete Account” button. The application may ask the user if they are sure they want to delete the account. The user can tap Cancel to close the dialog and return to the previous screen. If account deletion is confirmed, the user can tap Delete to delete the account. After the account is deleted, the application moves to the First Time Welcome Screen, where the user can set up a new account. Fig. 37e It illustrates an exemplary graphical user interface for a user to create a new account or log in to an existing account.

[0110] In some embodiments, the application may include a submodule for the user to manage a medication schedule. In some embodiments, the user may manage a schedule for one or more medications. In some embodiments, the application may serve as an integrated medication management system for the user to manage a schedule for one or more medications that the user or another person may take, to administer injections, and to monitor symptoms. In some embodiments, one or more medications may include medications injected by a drug delivery device. In some embodiments, one or more medications may include medications administered orally. In some embodiments, one or more medications may include medications administered topically.

[0111] Fig. 38a [The image] illustrates an exemplary graphical user interface for a user to manage a medication schedule. The screen shows that the user can add Medicine A, Medicine B, and / or Medicine C in the Medicine Cabinet settings. The user can tap the Add A medicine button to add a medication schedule. In some embodiments, the user can tap the Add medicine (e.g., Enfusimab) button to add the medicine Enfusimab (a subcutaneous medication). The user can select a method of administration. Fig. 38b It illustrates an exemplary graphical user interface for a user to add a medicine name. Fig. 38c It illustrates an exemplary graphical user interface for a user to add the frequency of administering the drug (e.g., as needed or how many times a day, at what time each administration is scheduled, on which specific day the administration is scheduled, e.g., every Monday or every 5 days). Fig. 38dIt illustrates an exemplary graphical user interface for the user to select different information to add (e.g., drug name, frequency, dosage, duration, and notes & photos). The user can populate the information by tapping their respective buttons. Once completed, the user can save the information by tapping Save Medicine. The user can enable the reminder function so that the application sends notifications and / or reminders to the user when it is time to administer the drug. Fig. 38e This illustrates an exemplary screen showing that the drug Aleve is scheduled to be administered daily at 8:00 AM and 8:00 PM. In the duration section, the user can add a start date and an end date. The user can edit the default icon and color for the added drug by tapping the edit icon. Fig. 38f It illustrates an exemplary graphical user interface for a user to select icons and colors for medicine. In "Notes & Photos," the user can add notes and photos of the medicine. When a reminder is turned off, the application can send a warning. The application can send a reminder that the user must take the medicine as prescribed and should not rely solely on the application for reminders. 38g It illustrates an exemplary graphical user interface for a user to set a starting dose schedule and administration time for a drug (e.g., Enfusimab). Fig. 38h It illustrates an exemplary screen showing that a drug (e.g., Enfusimab) is scheduled to be administered by an injector (e.g., enFuse injector) every two weeks at 9:00 AM at a dose of 150 mg / mL starting February 1, 2023.

[0112] Fig. 39a[It] illustrates an exemplary screen showing a medication schedule. The screen displays the drug name, dosage, and administration schedule. The user can edit the dosage by tapping the dosage button. The user can tap the quality of life survey to provide feedback on feelings. The quality of life survey may include questions regarding 1) lack of energy, 2) pain, 3) nausea, 4) concern that the condition may worsen, 5) sleep well, 6) enjoyment of life, and 7) satisfaction with quality of life, along with ratings of not at all, somewhat, somewhat, significantly, and very much. After answers are provided, the application may calculate a quality of life score (e.g., ranging from 0 to 28, where a higher score indicates better quality of life). The questions listed herein are for illustrative purposes only and are not limited to the disclosed questions. Other questions may be added. The user can tap the disease symptom survey to provide feedback on symptoms. The symptom questionnaire may include questions regarding 1) having experienced pain in a specific part of the body, 2) weakness throughout the body, 3) fatigue easily, 4) difficulty concentrating, 5) worry about infection, 6) discouragement about the disease, 7) difficulty planning for the future, 8) worry about new symptoms developing, 9) mood swings, 10) bone pain, 11) needing assistance with daily activities, 12) difficulty walking due to pain, 13) feeling fatigued, and 14) weight gain, along with an evaluation of not at all, slightly, somewhat, significantly, or very much. After the answers are provided, the application may calculate a disease symptom score (e.g., ranging from 0 to 56, where a higher score indicates fewer experienced disease symptoms). The questions listed herein are for illustrative purposes only and are not limited to the disclosed questions.Other questions may be added.

[0113] When an administration is scheduled, the user can choose to perform the administration or skip it. Fig. 39b It illustrates an exemplary graphical user interface for a user to choose to skip or complete an administration. The user can select Skip to skip the administration. The user can select Complete to perform the administration and record the completed administration after it has been performed. Fig. 39c It illustrates an exemplary screen showing that the administration of the drug (e.g., Enfusimab) has been completed and Aleve is scheduled for 11:00 AM. Fig. 39d It illustrates an exemplary screen showing that the administration of the drug (e.g., Enfusimab) is skipped and Aleve is scheduled for 11:00 AM.

[0114] Fig. 39e This illustrates an exemplary screen of the application's home screen during an injection of a drug (e.g., Enfusimab). The screen shows the weekly schedule scheduled by Advil while the injection of the drug (e.g., Enfusimab) is in progress. When the injector and monitoring patch are in use, the injection status and monitoring patch data may be displayed at the top of the screen. Patch data may include skin temperature, activity level, and step count. Patch data may remain at the top of the screen while the patch is in use. The injection status may show the start time and the estimated injection time. When the injector is in use but the monitoring patch is not, only the injection status may be displayed at the top of the screen without patch data. Fig. 39f This illustrates an exemplary screen of the application's home screen when the injection is paused. The injection status and monitoring patch are displayed at the top of the screen. The injection status is paused with a notification that the injection is paused while the button is pressed and to release the button to continue. 39gThis illustrates an exemplary screen of the application's home screen when the scan is complete and the monitoring patch is still in use. The scan status window disappears, and the medication (e.g., Enfusimab) schedule changes to "Completed". The patch data window may remain until the patch is removed. Fig. 39h This illustrates an exemplary screen of the application's home screen when a monitoring patch is removed. The user can tap the patch removal banner to review patch data in the statistics.

[0115] In some embodiments, the application may further include a statistics or history module. Fig. 40a illustrates an exemplary screen of a statistics module. In some embodiments, the statistics module may include data on the user's feelings. Fig. 40b It illustrates an exemplary screen displaying average scores for quality of life and disease symptoms based on user input in each survey. The higher the score, the better the quality of life and the fewer disease symptoms experienced. The module can display statistics for a selected duration. In some embodiments, the statistics module may include data on injection site tracking. Fig. 40c It illustrates an exemplary screen displaying the distribution and number of injection sites for a selected duration. Fig. 40c It shows that in 2023, injections were performed in 30% of the upper right area, 30% of the upper left area, 10% of the lower right area, and 30% of the lower left area. Fig. 40c It also indicates that the most injections occurred in July, followed by March. In some embodiments, the statistics module may include data on injection compliance. Fig. 40d It illustrates an exemplary screen displaying injection therapy compliance, including on-time injections, early injections, delayed injections, skipped injections, and unrecorded injections. Fig. 40dIt also illustrates detailed compliance events for each month. In some embodiments, the statistics module may include monitoring patch data. Fig. 40e The screen illustrates an exemplary screen that displays monitoring patch data from a recent injection. The screen may display the wearing time, injection data, and removal date. The screen may display skin temperature, including average temperature and maximum temperature. If an elevated temperature is detected (e.g., a temperature exceeding 100 degrees Fahrenheit), the screen may display a notification. The screen may display activity levels as a pie chart showing the percentage of time the user is in a static state or has low, medium, high, or vigorous activity levels while wearing the patch. Fig. 40f It illustrates an exemplary screen displaying monitoring patch data from a recent injection in which an elevated temperature was detected. 40g inside Figure 40hIt illustrates an exemplary screen (one drawing divided into two drawings for presentation purposes) that displays a summary of monitoring patch data over a selected duration (e.g., 3 months, 6 months, 1 year). The screen may display the total number of patches worn, total number of steps, minimum temperature, maximum temperature, and average temperature. The screen may include a bar graph to visualize the number of steps for each patch worn. The screen may include a graph of skin temperature trends showing the average temperature and maximum temperature for each patch worn. The screen may include a graph showing the percentage of time at an activity level (static, low, medium, high, or vigorous) during each patch wear. In some embodiments, statistical data may display how the user adhered to the injection schedule and the presence or likelihood of any abnormal events the user may have experienced (e.g., low scores for quality of life and disease symptoms, elevated temperature). In some embodiments, statistical data may be used to extract the relationship between the user's activity and quality of life and disease symptoms. In some embodiments, statistical data may be used to provide injection recommendations to the user. Injection recommendations may include injection time, injection site, and / or injection frequency. Injection recommendations may include means for improving compliance (e.g., setting additional reminders, forming injection patterns). Injection recommendations may include means for adjusting activity levels during injection.

[0116] computer system

[0117] The present disclosure provides a computer system programmed to implement the method of the disclosure. Fig. 19

[1901] illustrates a computer system (1901) that is programmed or otherwise configured to transmit and / or receive data and process the data. The computer system (1901) may regulate various aspects of the present disclosure, such as, for example, a method for analyzing data, monitoring of a target and measurement of an operating state, and providing an output of an operating state. The computer system (1901) may be a user's electronic device or a computer system located remotely from the electronic device. The electronic device may be a mobile electronic device.

[0118] A computer system (1901) includes a central processing unit (CPU, also referred to herein as “processor” and “computer processor”) (1905), which may be a single-core or multi-core processor, or a plurality of processors for parallel processing. The computer system (1901) also includes memory or memory location (1910) (e.g., random access memory, read-only memory, flash memory), electronic storage unit (1915) (e.g., hard disk), a communication interface (1920) for communicating with one or more other systems (e.g., network adapter), and peripheral devices (1925) such as a cache, other memory, data storage and / or electronic display adapter. The memory (1910), storage unit (1915), interface (1920), and peripheral devices (1925) communicate with the CPU (1905) via a communication bus (solid line), such as a motherboard. The storage unit (1915) may be a data storage unit (or data storage) for storing data. The computer system (1901) may be operatively coupled to a computer network (“network”) (1930) with the help of a communication interface (1920). The network (1930) may be the Internet, the Internet and / or extranet, or an intranet and / or extranet communicating with the Internet. In some cases, the network (1930) is a communication and / or data network. The network (1930) may include one or more computer servers, which may enable distributed computing such as cloud computing. In some cases, the network (1930) may implement a peer-to-peer network with the help of the computer system (1901), which may enable a device coupled to the computer system (1901) to act as a client or a server.

[0119] The CPU (1905) may execute a sequence of machine-readable instructions that may be implemented as a program or software. The instructions may be stored in a memory location such as memory (1910). The instructions may be instructed to the CPU (1905), which may subsequently program or otherwise configure the CPU (1905) to implement the method of the present disclosure. Examples of operations performed by the CPU (1905) may include fetch, decode, execute, and writeback.

[0120] The CPU (1905) may be part of a circuit such as an integrated circuit. One or more other components of the system (1901) may be included in the circuit. In some cases, the circuit is an application-specific integrated circuit (ASIC).

[0121] The storage unit (1915) can store files such as drivers, libraries, and stored programs. The storage unit (1915) can store user data, such as user preferences and user programs. In some cases, the computer system (1901) may include one or more additional data storage units located outside the computer system (1901), such as those located on a remote server that communicates with the computer system (1901) via an intranet or the internet.

[0122] The computer system (1901) can communicate with one or more remote computer systems via the network (1930). For example, the computer system (1901) can communicate with a user's remote computer system (e.g., located in a doctor's office or on a doctor's mobile device). Examples of remote computer systems include a personal computer (e.g., a portable PC), a slate or tablet PC (e.g., an Apple® iPad, a Samsung® Galaxy Tab), a telephone, a smartphone (e.g., an Apple® iPhone, an Android-enabled device, a Blackberry®), or a personal digital assistant. The user can access the computer system (1901) via the network (1930).

[0123] The method described herein may be implemented by machine-executable code (e.g., computer processor) stored on an electronic storage location of a computer system (1901), such as memory (1910) or an electronic storage unit (1915). The machine-executable code or machine-readable code may be provided in the form of software. During use, the code may be executed by the processor (1905). In some cases, the code may be retrieved from the storage unit (1915) and stored in memory (1910) for immediate access by the processor (1905). In some situations, the electronic storage unit (1915) may be excluded, and the machine-executable instructions are stored in memory (1910).

[0124] The code may be pre-compiled and configured, or compiled during runtime, for use on a machine having a processor adapted to execute the code. The code may be supplied in a programming language that can be selected to enable the code to be executed in a pre-compiled or compiled manner.

[0125] Aspects of the systems and methods provided herein, for example, a computer system (1901), may be implemented by programming. Various aspects of the technology may generally be conceived as “products” or “manufactured articles” in the form of machine (or processor) executable code and / or associated data, which are carried on or implemented therein in a specific type of machine-readable medium. The machine-executable code may be stored in memory (e.g., read-only memory, random access memory, flash memory) or electronic storage units such as hard disks. The “storage” type medium may include any or all types of tangible memory of a computer, processor, or similar, or various semiconductor memory, tape drives, disk drives, and associated modules such as similar ones that can provide non-transient storage at any point in time for software programming. All or part of the software may be communicated from time to time via the Internet or various other communication networks. Such communication can, for example, enable software to be loaded from one computer or processor to another computer or processor, and, for example, enable it to be loaded from a management server or host computer to the computer platform of an application server. Accordingly, another type of medium capable of carrying software elements includes optical, electric, and electromagnetic waves, such as those used through physical interfaces between local devices, through wired and optical landline networks, and through various air links. Physical elements that transmit these waves, such as wired or wireless links, optical links, or similar ones, can also be considered as a medium carrying software.As used herein, terms such as computer or machine "readable medium" refer to any medium involved in providing instructions to a processor for execution, unless limited to non-transient, tangible "storage" media.

[0126] Accordingly, machine-readable media, such as computer-executable code, may take many forms, including but not limited to tangible storage media, carrier media, or physical transmission media. Non-volatile storage media include optical disks or magnetic disks, such as any of the storage devices within any computer(s) or similar, such as those that may be used to implement the database, etc., illustrated in the drawings. Volatile storage media include dynamic memory, such as the main memory of such computer platforms. Tangible transmission media include coaxial cables; copper wires and optical fibers, which include wires containing buses within a computer system. Carrier transmission media may take the form of electrical or electromagnetic signals, or acoustic or light waves, such as those generated during radio frequency (RF) and infrared (IR) data communication. Accordingly, general forms of computer-readable media include, for example, floppy disks, flexible disks, hard disks, magnetic tapes, any other magnetic media, CD-ROMs, DVDs or DVD-ROMs, any other optical media, punched cards, paper tapes, any other physical storage media having a hole pattern, RAM, ROM, PROM and EPROM, FLASH-EPROM, any other memory chips or cartridges, carriers carrying data or instructions, cables or links carrying such carriers, or any other media in which a computer can read programming code and / or data. Many of these forms of computer-readable media may be involved in delivering one or more sequences of one or more instructions to a processor for execution.

[0127] The computer system (1901) may include or communicate with an electronic display (1935) that includes a user interface (UI) (1940). Examples of the UI include, without limitation, a graphical user interface (GUI) and a web-based user interface.

[0128] The method and system of the present disclosure may be implemented by one or more algorithms. The algorithm may be implemented by software when executed by a central processing unit (1905). The algorithm may, for example, process data, perform statistical analysis, plot or graphically represent data, and provide feedback to one or more systems disclosed herein (e.g., patches and / or injectors).

[0129] The method and system of the present disclosure may be implemented by one or more digital processing devices. Non-limiting examples of digital processing devices may include a server computer, a desktop computer, a laptop computer, a notebook computer, a subnotebook computer, a netbook computer, a netpad computer, a set-top computer, a media streaming device, a handheld computer, an internet appliance, a mobile smartphone, a tablet computer, a personal digital assistive device, a video game console, and a vehicle.

[0130] In some embodiments, the digital processing device may include an operating system configured to execute executable instructions. The operating system is software that includes, for example, programs and data, manages the hardware of the device, and provides services for the execution of applications. Non-limiting examples of operating systems may include FreeBSD, OpenBSD, NetBSD®, Linux, Apple® Mac OS X Server®, Oracle® Solaris®, Windows Server®, and Novell® NetWare®. Non-limiting examples of mobile phone operating systems may include Nokia® Symbian® OS, Apple® iOS®, Research In Motion® BlackBerry OS®, Google® Android®, Microsoft® Windows Phone® OS, Microsoft® Windows Mobile® OS, Linux®, and Palm® WebOS®.

[0131] In some embodiments, the computer program may include a mobile application provided to a mobile digital processing device. In some embodiments, the mobile application is provided at the time the mobile digital processing device is manufactured. In other embodiments, the mobile application is provided to the mobile digital processing device via a computer network described herein. The mobile application may be written in several programming languages. Non-limiting examples of programming languages ​​may include C, C++, C#, Objective-C, Java™, JavaScript, Pascal, Object Pascal, Python™, Ruby, VB.NET, WML, and XHTML / HTML, with or without CSS, or a combination thereof.

[0132] Exemplary machine learning techniques

[0133] In some cases, the systems, methods, computer-readable media, and techniques disclosed herein may utilize various machine learning (ML) techniques. In some cases, ML may generally involve identifying and recognizing patterns in existing data to facilitate predictions regarding subsequent data. ML may include ML models (e.g., may include ML algorithms). Machine learning may provide deductive or abductive reasoning based on real or simulated data, regardless of whether it is of an analytical or statistical nature. An ML model may be a trained model. ML techniques may include one or more supervised, semi-supervised, self-supervised, or unsupervised ML techniques. For example, an ML model may be a trained model trained through supervised learning (e.g., various parameters are determined as weights or scaling factors). ML may include one or more of regression analysis, normalization, classification, dimensionality reduction, ensemble learning, meta-learning, association rule learning, cluster analysis, anomaly detection, deep learning, or super-deep learning.ML includes, but is not limited to, k-means, k-means clustering, k-nearest neighbors, training vector quantization, linear regression, nonlinear regression, least squares regression, partial least squares regression, logistic regression, stepwise regression, multivariate adaptive regression spline, ridge regression, principal component regression, least absolute shrinkage and selection operation (LASSO), minimum angle regression, canonical correlation, factor analysis, independent component analysis, linear discriminant analysis, multidimensional scaling, non-negative matrix factorization, principal component analysis, principal coordinate analysis, projection pursuit, Sammon mapping, t-distribution stochastic neighbor embeddings, AdaBoosting, boosting, gradient boosting, bootstrap aggregation, ensemble averaging, decision trees, conditional decision trees, boosted decision trees, gradient-boosted decision trees, random forests, stacked generalization, and Bayesian Network (Bayesian network), Bayesian belief network, Naive Bayes (na. ve Bayes), Gaussian Naive Bayes (Gaussian na ve Bayes), multinomial naive Bayes It may include Bayes), hidden Markov model, hierarchical hidden Markov model, support vector machine, encoder, decoder, auto-encoder, stacked auto-encoder, perceptron, multilayer perceptron, artificial neural network, feedforward neural network, convolutional neural network, recurrent neural network, long short-term memory, deep belief network, deep Boltzmann machine, deep convolutional neural network, deep recurrent neural network, generative adversarial network, vision transformer, long short-term memory network (LSTM), masked autoencoder, etc.

[0134] In some cases, training an ML model may involve selecting one or more untrained data models to be trained using a training data set. The selected untrained data models may include any type of untrained ML model for supervised, semi-supervised, self-supervised, or unsupervised machine learning. The selected untrained data models may be specified based on inputs (e.g., user input) that specify relevant parameters to be used as predicted variables or other variables to be used as potential explanatory variables. For example, the selected untrained data models may be specified to generate outputs (e.g., predictions) based on inputs. Conditions for training an ML model from the selected untrained data models may be selected, such as restrictions on ML model complexity or restrictions on refining the ML model past a specific point in time. The ML model may be trained using a training data set (e.g., through a computer system such as a server). In some cases, a first subset of the training data set may be selected to train the ML model. Next, the selected untrained data model may be trained on a first subset of the training data set using an appropriate ML technique, based on the type of selected ML model and any conditions specified for training the ML model. In some cases, due to the processing power requirements for training the ML model, the selected untrained data model may be trained using additional computing resources (e.g., cloud computing resources). In some cases, this training may continue until at least one aspect of the ML model is validated and meets the selection criteria for use as a predictive model.

[0135] In some cases, one or more aspects of an ML model may be validated using a second subset of the training dataset (e.g., distinct from a first subset of the training dataset) to determine the accuracy and robustness of the ML model. Such validation may involve applying the ML model to the second subset of the training dataset to perform predictions derived from the second subset of the training data. The ML model may then be evaluated to determine whether its performance is sufficient based on the derived predictions. The sufficiency criteria applied to the ML model may depend on the size of the training dataset available for training, the performance of previous iterations of the trained model, or user-specific performance requirements. If the ML model does not achieve sufficient performance, additional training may be performed. Additional training may include refining the ML model or retraining on a different first subset of the training dataset, after which the new ML model may be validated and evaluated again. In some cases, when the ML model achieves sufficient performance, the ML may be stored for current or future use. The ML model may be stored as a set of parameter values ​​or weights for the analysis of additional inputs (e.g., additional relevant parameters to be used as additional predictors, additional explanatory variables, additional user interaction data, etc.), which may also include analysis logic or indications of model validity in some cases. In some cases, multiple ML models may be stored to generate predictions under different sets of input data conditions. In some embodiments, the ML model may be stored in a database (e.g., associated with a server).

[0136] The systems, methods, computer-readable media, and techniques disclosed herein may implement one or more computer vision techniques. Computer vision is a field of artificial intelligence that interprets and understands the visual world using a computer, at least in part, by processing one or more digital images from cameras and video. In some cases, computer vision may use deep learning models (e.g., convolutional neural networks). Bounding box and tracking techniques may be used in object detection techniques within computer vision.

[0137] The systems, methods, computer-readable media, and techniques disclosed herein may implement one or more deep learning techniques. Deep learning is an example of ML that may be based on a set of algorithms that attempt to model high-level abstraction of data by using a number of processing layers having a complex structure composed of a number of non-linear transformations or a structure that is not. In some cases, a dropout method may be used to reduce overfitting. At each training step, individual nodes are "dropped out" from the network (e.g., ignored) with probability 1-p or retained with probability p, leaving a reduced network; input and output edges for the dropped-out nodes may also be removed. In some cases, the reduced network is trained on the data at that step. The removed nodes may then be reinserted into the network with their original weights.

[0138] The systems, methods, computer-readable media, and techniques disclosed herein may implement one or more vision transformer (ViT) techniques. A ViT is a transformer-like model that handles vision processing tasks. While CNNs use convolution, which is a "local" operation bounded by small neighborhoods of an image, ViTs use self-attention, which is a "global" operation, because they draw information from the entire image. This allows ViTs to effectively capture distant semantic relevance in an image. Advantageously, ViTs can be highly suitable for capturing long-term dependencies. In some cases, ViTs can be a competitive alternative to convolutional neural networks because they can perform nearly four times better than current state-of-the-art CNNs in terms of computational efficiency and accuracy. ViTs can be highly suitable for object detection, image segmentation, image classification, and motion recognition. Furthermore, ViT can be applied to generative modeling and multi-model tasks, including visual grounding, visual question answering, and visual inference. In some cases, ViT can represent images as sequences and predict class labels for the images, which allows the model to learn the image structure independently. Input images can be treated as a sequence of patches, where each patch is flattened into a single vector by concatenating the channels of all pixels within the patch, and then linearly projected onto the desired input dimension.For example, a ViT architecture may include the following operations: (A) segmenting images into patches; (B) flattening the patches; (C) generating low-dimensional linear embeddings from the flattened patches; (D) adding positional embeddings; (E) providing the sequence as input to a standard Transformer encoder; (F) pre-training the model using image labels (e.g., fully supervised learning on a large dataset); and (G) fine-tuning on a downstream dataset for image classification. In some cases, a ViT encoder may contain multiple blocks, each containing three main processing elements: (1) layer normalization; (2) a multi-head attention network; and (3) a multi-layer perceptron. Layer normalization can keep the training process on track and enable the model to adapt to variations between training images. The multi-head attention network may be a network responsible for generating attention maps from a given embedded visual token. These attention maps can help the network focus on the most important areas in an image, such as object(s). The multilayer perceptron can be a two-layer classification network with Gaussian Error Linear Units at the terminals. The final multilayer perceptron block can be used as the output of a transformer. The application of softmax to this output can provide classification labels (e.g., if the application is image classification).

[0139] The systems, methods, computer-readable media, and techniques disclosed herein may implement one or more masked autoencoder (MAE) techniques. An MAE is a scalable self-supervised learner for computer vision. MAE leverages the success of autoencoders for various imaging and natural language processing tasks. Some computer vision models can be trained using supervised learning, such as when humans view images and generate labels for them, thereby allowing the model to learn patterns of these labels (e.g., a human annotator will assign class labels to an image or draw bounding boxes around objects within the image). In contrast, self-supervised learning may not use any human-generated labels. One technique for training self-supervised image processing using MAE is to apply a specific set of masks to an image before the image is input into an encoder transformer. Due to the masks, pixels are removed from the image, and thus the model is provided with an incomplete image. At a higher level, the task of the model is now to learn how the entire original image looked before the masks were applied.

[0140] In other words, MAE can involve masking random patches of an input image and reconstructing missing pixels. MAE can be based on a two-core design. First, it is an asymmetric encoder-decoder architecture featuring an encoder that operates on a visible subset of patches (without mask tokens), alongside a lightweight decoder that reconstructs the original image from latent representations and mask tokens. Second, masking a high proportion of the input image, e.g., 75%, can yield significant and meaningful self-supervised tasks. Combining these two core designs enables the efficient and effective training of large models, thereby accelerating training (e.g., by more than three times) and improving accuracy. MAE techniques can be scalable, which can enable the training of high-capacity models with good generalization, such as vanilla ViT-Huge models. As mentioned, MAE can be effective for pre-training ViTs for natural image analysis. In some cases, MAE reconstructs the original image as a proxy operation by observing partial images using the redundancy of image information, and the MAE encoder can have the ability to infer the content of masked image regions by aggregating context information. This ability to aggregate context can be important in the field of image processing and analysis.

[0141] The systems, methods, computer-readable media, and techniques disclosed herein may implement one or more decision tree or random forest techniques. A decision tree may be a supervised ML algorithm applicable to both regression and classification problems. A decision tree may mimic the decision-making process of the human brain. For example, a decision tree may grow from a root (base condition) and may split into multiple branches when conditions (internal nodes / features) are met. The ends of branches that are no longer split may be results (leaves). A decision tree may be generated using a training dataset according to the following operations: (1) starting from a root node (entire dataset), the algorithm may split the dataset into two branches using a decision rule or branching criterion; (2) each of these two branches may generate a new child node; and (3) for each new child node, the branching process may be repeated until the dataset can no longer be split; (4) Each branching criterion can be selected to maximize information gain (e.g., quantification of how much the branching criterion reduces the quantification of how mixed the labels are in the child nodes). The labels can be data or classifications predicted by the decision tree.

[0142] Random Forest Regression is an extension of the Decision Tree model that tends to yield more robust predictions by expanding the use of training data partitions. While Decision Trees can perform a single pass on the data, Random Forest Regression can bootstrap 50% of the data (e.g., using replacement) and build many trees. Instead of using all explanatory variables as candidates for splitting, a random subset of candidate variables can be used for splitting, which can enable trees with completely different data and different variables (hence the term "random"). Predictions from the trees, collectively referred to as a "forest," can then be averaged together to generate the final prediction. Many trees (e.g., 100 trees) may be included in the random forest model, including the number of terms sampled per split (e.g., 3, 6, 10, etc.), the minimum number of splits per tree (e.g., 1, 2, 4, 10, etc.), and the minimum split size (e.g., 16, 32, 64, 128, 256, etc.). A random forest can be trained in a manner similar to a decision tree. Specifically, training a random forest may include the following operations: (1) randomly selecting k features from the total number of features; (2) generating a decision tree from these k features using the same operations as those used to generate the decision tree; and (3) repeating the previous two operations until a target number of trees is generated.

[0143] The systems, methods, computer-readable media, and techniques disclosed herein may implement one or more Long Short-Term Memory (LSTM) techniques. An LSTM may be an artificial neural network used in the fields of artificial intelligence and deep learning. Unlike standard feedforward neural networks, an LSTM may use feedback connections. An LSTM architecture may provide short-term memory to a recurrent neural network (RNN). Such RNNs can process not only single data points (e.g., images) but also entire sequences of data (e.g., speech or video). This characteristic may imply that LSTM networks are highly suitable for processing and predicting data. The term LSTM may refer to the analogy that a standard RNN possesses both "long-term memory" and "short-term memory." The connection weights and biases of an RNN may be changed once per training episode, which is similar to how physiological changes in synaptic strength store long-term memory; The activation pattern of a network can change once per time-step, which is similar to how moment-to-moment changes in the brain's electric firing pattern store short-term memory. LSTM architectures can provide short-term memory for RNNs capable of sustaining many (e.g., thousands) time-steps.

[0144] In some cases, an LSTM unit may include a cell, an input gate, an output gate, and a forget gate. The cell can remember a value over an arbitrary time interval, and the input gate, output gate, and forget gate can regulate the flow of information to and from the cell. The forget gate can be used to determine which information to discard from a previous state by assigning a value between 0 and 1 to the previous state in comparison to the current input (e.g., a (rounded) value of 1 may mean retaining the information, and a value of 0 may mean discarding the information). The input gate can use the same system as the forget gate to determine which part of the new information to store in the current state. The output gate can control which part of the information from the current state to output (e.g., by assigning a value between 0 and 1 to the information considering the previous and current states). Selectively outputting relevant information from the current state can allow the LSTM network to maintain long-term dependencies useful for performing predictions at both current and future time steps. LSTM networks can be highly suitable for classifying, processing, and predicting based on time series data, as there may be unknown duration delays between important events in a time series. LSTMs can solve the vanishing gradient problem that can be encountered when training traditional RNNs. The relative insensitivity to gap length can be an advantage of LSTMs over RNNs, Hidden Markov Models, and other sequence learning methods in many applications.

[0145] In some cases, LSTMs can be used in conjunction with one or more different types of neural networks (e.g., convolutional neural networks (CNNs), deep neural networks (DNNs), recurrent neural networks (RNNs), etc.). In some cases, CNNs, LSTMs, and DNNs are complementary in their modeling capabilities and can be combined into an integrated architecture. For example, in such an integrated architecture, CNNs may be highly suitable for reducing frequency fluctuations, LSTMs may be highly suitable for temporal modeling, and DNNs may be highly suitable for mapping features to a more separable space. For example, input features for an ML model using LSTM techniques in an integrated architecture may include segment features for each of multiple segments. To process the input features for each of multiple segments, the segment features for the segments may be processed using one or more CNN layers to generate first features for the segments; the first features may be processed using one or more LSTM layers to generate second features for the segments; The second feature can be processed using one or more fully connected neural network layers to generate a third feature for the segment, where the third feature can be used for classification operations. In some examples, to generate a second feature by processing the first feature using one or more LSTM layers, the first feature can be processed using linear layers to generate a reduced feature having a reduced dimension from the dimension of the first feature; and the reduced feature can be processed using one or more LSTM layers to generate a second feature.Short-term features having a first number of context frames may be generated based on input features, wherein features generated using one or more CNN layers may include long-term features having a second number of context frames, which is greater than the first number of context frames of the short-term features. In some cases, one or more CNN layers, one or more LSTM layers, and one or more fully connected neural network layers may be trained together to determine the trained values ​​of the parameters of one or more CNN layers, one or more LSTM layers, and one or more fully connected neural network layers. In some cases, input features may include log-mel features having multiple dimensions. Input features may include one or more context frames representing the temporal context of the signal (e.g., input data). Advantageously, an implementation of this integrated architecture can leverage the complementary advantages associated with CNN, LSTM, and DNN, respectively. For example, convolution layers can reduce spectral variability in the input, which can aid in the modeling of LSTM layers. Having a DNN layer after an LSTM layer can help reduce variability in the hidden state of the LSTM layer. Training a unified architecture together can provide better overall performance. Training in a unified architecture can also eliminate the need for separate CNN, LSTM, and DNN architectures, which can be costly (e.g., in terms of computational resources, network traffic, financial resources, energy consumption, etc.). By adding multiscale information to the unified architecture, information can be captured at different time scales.

[0146] The systems, methods, computer-readable media, and techniques disclosed herein may implement one or more support vector machine learning techniques. In machine learning, a support vector machine (SVM) may be a supervised learning model having an associated learning algorithm that analyzes data for classification and regression analysis. An SVM may be a robust prediction method based on statistical learning. An SVM may be highly suitable for domains characterized by the presence of large amounts of data, the presence of noisy patterns, or the absence of general theory.

[0147] In general, SVMs can map input vectors to a high-dimensional feature space using a priori-selected non-linear mapping function. In this high-dimensional feature space, optimal separating hyperplanes can be constructed. These optimal hyperplanes can then be used to determine accuracy in class separation, regression fitting, or density estimation. More formally, SVMs construct hyperplanes or sets of hyperplanes in high-dimensional or infinite-dimensional spaces, which can be used for other tasks such as classification, regression, or outlier detection.

[0148] Support vectors can be defined as data points located closest to a decision surface (or hyperplane). Therefore, support vectors can be the data points most difficult to classify and may have a direct bearing on the optimal location on the decision surface. Given a set of training examples, each marked as belonging to one of two categories, an SVM training algorithm can build a model that assigns new examples to one category or the other, making it a non-probabilistic binary linear classifier (however, methods such as Platt scaling exist for using SVMs in probabilistic classification settings). SVMs can map training examples to points within a space to maximize the width of the gap between the two categories. Then, new examples are mapped to the same space and can be predicted to belong to a category based on which side of the gap they fall on. In addition to performing linear classification, SVMs can efficiently perform non-linear classification using what is called the kernel trick, which can implicitly map their inputs to a high-dimensional feature space.

[0149] In Support Vector Machines, the dimensionality of the feature space can be large. For example, a fourth-order polynomial mapping function can map a 200-dimensional input space to a 1.6 billion-dimensional feature space. Kernel tricks and Vapnik-Chervonenkis dimensions can thwart the "curse of dimensionality" that limits other methods for SVMs, allowing them to effectively derive generalizable answers from these very high-dimensional feature spaces. Therefore, SVMs can help discover knowledge from vast amounts of input data.

[0150] The systems, methods, computer-readable media, and techniques disclosed herein may implement one or more gradient boosting techniques. Gradient boosting is a machine learning technique used, among other things, for regression and classification tasks. It provides a predictive model in the form of an ensemble of weak predictive models, which are generally decision trees. When the decision tree is a weak learner, the resulting algorithm is called a gradient-boosted tree; it generally performs better than a random forest. The gradient-boosted tree model is constructed in a stepwise manner, as in other boosting methods, but generalizes other methods by allowing the optimization of any differentiable loss function.

[0151] The systems, methods, computer-readable media, and techniques disclosed herein may implement one or more K-nearest neighbor (KNN) techniques. KNN is a non-parametric classification method. In KNN classification, the output is class membership. An object is classified by its neighbor's plurality vote, and the object is assigned to the most common class among its k nearest neighbors (k is a positive integer and is typically small). When k=1, the object is assigned to the class of its single nearest neighbor. In KNN regression, the output is an attribute value for the object. This value is the average of the values ​​of the k nearest neighbors. KNN is a type of classification where the function is locally approximated and computation is deferred until the function is evaluated. Because this algorithm relies on distance for classification, normalizing the training data can significantly improve its accuracy when features represent different physical units or are provided at very different scales.

[0152] The systems, methods, computer-readable media, and techniques disclosed herein may implement one or more Monte Carlo techniques. Monte Carlo is a broad class of computational algorithms that rely on iterative random sampling to obtain numerical results. The underlying concept is to use randomness to solve problems that may be deterministic in principle.

[0153] The systems, methods, computer-readable media, and techniques disclosed herein may implement one or more one-hot encoding techniques. One-hot encoding can be used to handle categorical data. For example, an ML model may use numeric input variables. In one example, categorical variables may be transformed in a preprocessing part. Categorical data may be nominal or ordinal. Ordinal data may have a ranked order for its values ​​and thus can be transformed into numeric data through ordinal encoding.

[0154] The systems, methods, computer-readable media, and techniques disclosed herein may implement one or more quadratic discriminant analysis (QDA) techniques. In some cases, QDA may assume that measurements from each class are normally distributed. In QDA, there is no assumption that the covariances for each class are equal. When the assumption of normality is true, the best possible test for the hypothesis that a given measurement comes from a given class is the likelihood ratio test.

[0155] The systems, methods, computer-readable media, and techniques disclosed herein may implement one or more response surface methodology (RSM) techniques. RSM may explore the relationship between several explanatory variables and one or more response variables. RSM may use a sequence of experiments designed to obtain the optimal response. RSM may use factorial experiments or fractional factorial designs. This may be sufficient to determine which explanatory variables influence the response variable(s) of interest. If it is assumed that only meaningful explanatory variables remain, more complex designs, such as a central composite design, may be implemented to estimate a second-order polynomial model, which is still, at best, only an approximation. However, the second-order model may be used to optimize the response variable(s) of interest (e.g., to maximize, minimize, or achieve a specific target).

[0156] The systems, methods, computer-readable media, and techniques disclosed herein may implement one or more Synthetic Minority Oversampling Techniques (SMOTE). SMOTE is a type of data augmentation for a minority class. SMOTE may select examples that are close to each other in feature space, draw lines between the examples in feature space, and derive new samples from points along the lines.

[0157] ***

[0158] Although preferred embodiments of the present disclosure have been illustrated and described herein, such embodiments are provided by way of example only. The present disclosure is not intended to be limited by the specific examples provided within the specification. Although the present disclosure has been described by reference to the aforementioned specification, the description and examples of embodiments within the present specification are not intended to be interpreted in a limiting sense. Numerous modifications, changes, and substitutions will now be made without departing from the present disclosure. Furthermore, it will be understood that not all aspects of the present disclosure are limited by the specific descriptions, configurations, or relative proportions presented herein, which depend on various conditions and variables. It should be understood that various alternatives to the embodiments of the present disclosure described herein may be used to practice the present disclosure. Accordingly, the present disclosure is also considered to cover any such alternatives, modifications, variations, or equivalents. The following claims define the scope of the present disclosure, and it is intended that methods and structures and their equivalents within the scope of these claims are covered by them.

Claims

Claim 1 A method for determining the operating state of a medication delivery device, comprising: a) instructing a user to capture one or more images of at least a portion of the medication delivery device using an image sensor; and b) determining the operating state of the medication delivery device by analyzing the one or more images, wherein the determining step includes evaluating the location of the at least portion of the medication delivery device. Claim 2 A method for determining the operating state of a drug delivery device according to claim 1, further comprising the step of transmitting one or more images to a cloud-based server. Claim 3 A method for determining the operating state of a drug delivery device according to claim 1 or 2, wherein a drug is delivered by advancing a movable component inside the drug delivery device. Claim 4 A method for determining the operating state of a drug delivery device, wherein, in paragraph 3, the movable component advances along a trajectory that is not a straight line. Claim 5 A method for determining the operating state of a drug delivery device, wherein, in paragraph 3, the amount of drug delivered is in a linear relationship with the distance the movable component advances. Claim 6 A method for determining the operating state of a drug delivery device, wherein, in paragraph 3, the amount of drug delivered has a non-linear relationship with the distance the movable component advances. Claim 7 A method for determining the operating state of a drug delivery device, wherein, in any one of claims 1 to 6, the determining step includes the step of determining the position of the button cap of the drug delivery device. Claim 8 A method for determining the operating state of a drug delivery device, wherein, in claim 7, the position of the button cap includes a ready to inject position, an inject position, a pause position, or a lockout position. Claim 9 A method for determining the operating state of a drug delivery device, wherein, in any one of claims 1 to 8, the determining step includes the step of determining the position of the needle of the drug delivery device. Claim 10 A method for determining the operating state of a drug delivery device according to claim 9, wherein the position of the needle includes a retracted position or an extended position. Claim 11 A method for determining the operating state of a drug delivery device, wherein, in any one of claims 1 to 10, the determining step includes the step of determining the position of a gas gauge of the drug delivery device. Claim 12 A method for determining the operating state of a drug delivery device according to claim 11, wherein the position of the gas gauge includes an injection preparation position, an injection position, a pause position, a lock position, or a completion position. Claim 13 A method for determining the operating state of a drug delivery device, wherein, in any one of claims 1 to 12, a first operating state is assigned at the time when a first image is captured, a second operating state is assigned at the time when a second image is captured, and a dose delivered between the time when the first image is captured and the time when the second image is captured. Claim 14 A method for determining the operating state of a drug delivery device, wherein, in any one of claims 1 to 13, the operating state includes an injection start state, an injection pause state, an injection in progress state, or an injection completion state. Claim 15 A method for determining the operating state of a drug delivery device, wherein, in any one of claims 1 to 14, the operating state includes a delivered dose state, a remaining dose state, and / or a remaining time state until completion. Claim 16 A method for determining the operating state of a drug delivery device, wherein, in any one of claims 1 to 15, the image sensor is a digital camera or a digital video camera. Claim 17 A method for determining the operating state of a drug delivery device, wherein, in any one of claims 1 to 16, the analysis is performed by comparing one or more images with a predetermined image. Claim 18 A method for determining the operating state of a drug delivery device, wherein, in any one of claims 1 to 17, the analysis is performed using a mobile phone. Claim 19 A method for determining the operating state of a drug delivery device, wherein, in any one of claims 1 to 18, the analysis is performed by a software application. Claim 20 A method for determining the operating state of a drug delivery device, comprising, in any one of claims 1 to 19, a step of displaying the operating state. Claim 21 A method for determining the operating state of a drug delivery device, wherein, in any one of claims 1 to 20, the method further comprises the step of receiving input information from the user and calculating the dosage amount of a drug to be administered in a subsequent delivery. Claim 22 A method for determining the operating state of a drug delivery device, wherein, in any one of claims 1 to 21, the image sensor includes instructions for the user to guide the positioning of the image sensor with respect to the at least part of the drug delivery device while capturing the one or more images. Claim 23 A method for determining the operating state of a drug delivery device according to claim 22, further comprising the step of instructing the user to match the device outline displayed on the image sensor with the at least part of the drug delivery device while capturing the one or more images. Claim 24 A method for determining the operating state of a drug delivery device, comprising, in any one of claims 1 to 23, further a step of storing one or more images. Claim 25 A method for determining the operating state of a drug delivery device, wherein, in any one of claims 1 to 24, the method further comprises the step of storing information of the operating state. Claim 26 A method for determining the operating state of a drug delivery device, wherein, in any one of claims 1 to 25, the method further comprises the step of warning the user when the operating state deviates from a predetermined state. Claim 27 A system for determining the operating state of a drug delivery device, comprising: (a) an image sensor for capturing one or more images of at least a portion of the drug delivery device; (b) a data transmission interface for transmitting the one or more images to an electronic device; and (c) a processor for analyzing the one or more images and communicating with the electronic device to determine the operating state. Claim 28 A system for determining the operating state of a drug delivery device, wherein, in paragraph 27, the image sensor comprises a digital camera or a digital video camera. Claim 29 A system for determining the operating state of a drug delivery device, wherein, in claim 27 or 28, the drug delivery device comprises a patch and an injector, and the patch and the injector are removablely coupled. Claim 30 A system for determining the operating state of a drug delivery device, wherein, in any one of claims 27 to 29, at least a portion of the drug delivery device comprises a button. Claim 31 A system for determining the operating state of a drug delivery device, wherein, in any one of claims 27 to 30, at least a portion of the drug delivery device comprises a needle. Claim 32 A system for determining the operating state of a drug delivery device, wherein, in any one of claims 27 to 31, at least a portion of the drug delivery device comprises a gas gauge. Claim 33 A system for determining the operating state of a drug delivery device, wherein, in any one of claims 27 to 32, the at least part of the drug delivery device is configured to change the position indicating the operating state. Claim 34 A system for determining the operating state of a drug delivery device, wherein, in any one of claims 27 to 33, the processor is configured to operate a software application. Claim 35 A system for determining the operating state of a drug delivery device, further comprising, in any one of claims 27 to 34, a non-transient computer-readable storage medium encoded in a computer program that includes instructions executable by the processor. Claim 36 A system for determining the operating state of a drug delivery device, further comprising a data reporting accessory for providing information to a user in any one of claims 27 to 35. Claim 37 A system for determining the operating state of a drug delivery device, further comprising a data display accessory for displaying the operating state in any one of claims 27 to 36. Claim 38 A system for determining the operating state of a drug delivery device, wherein, in any one of claims 27 to 37, the image sensor, the data transmission interface, and the processor are located within a common housing. Claim 39 A system for determining the operating state of a drug delivery device, wherein, in paragraph 38, the common housing is a smartphone. Claim 40 A computer-implemented onboarding method for monitoring drug delivery, comprising: a) receiving account information from a user to create a new user account; b) displaying an overview of an application, safety information, an educational video, or any combination thereof; c) receiving data consent, confirmation from the user to accept notifications, symptom tracking information, or any combination thereof; d) creating a patient profile and an injection schedule; and e) establishing a connection with the user's drug delivery device. Claim 41 A computer-implemented onboarding method according to claim 40, wherein the step of displaying an overview of the application comprises the step of displaying an infographic regarding a method for recording and tracking injections, a method for setting reminders for taking medication, a method for creating schedules and reminders for treatment appointments, a method for tracking and identifying symptoms to the user's medical team, a method for accessing support programs, or any combination thereof. Claim 42 A computer-implemented onboarding method according to claim 40 or 41, wherein the step of displaying safety information includes the step of displaying drug prescription information. Claim 43 A computer-implemented onboarding method according to any one of claims 40 to 42, wherein the step of generating the patient profile comprises receiving a user date of birth, user gender, user name, user age, user weight, user height, user ethnicity, user nationality, user residential address, user zip code, user email, user phone number, user contact information, or any combination thereof. Claim 44 A computer-implemented onboarding method according to any one of claims 40 to 43, wherein the step of generating the injection schedule comprises receiving the administration frequency, the infusion date, the infusion time, or any combination thereof. Claim 45 A computer-implemented onboarding method according to any one of claims 40 to 44, wherein the step of establishing a connection with the user’s drug delivery device is performed via a wireless communication protocol, a machine-readable barcode, or both. Claim 46 A computer-implemented onboarding method according to claim 45, wherein the wireless communication protocol comprises near-field communication (NFC), Bluetooth, Bluetooth LE, Wi-Fi, radio frequency identification (RFID), iBeacon, ZigBee, Z-Wave, or any combination thereof. Claim 47 A computer-implemented onboarding method according to any one of claims 40 through 46, wherein the step of establishing a connection with the user’s drug delivery device comprises: a) activating a wireless communication protocol for the drug delivery device; b) positioning the user’s mobile computing device in close proximity to the drug delivery device, the packaging of the drug delivery device, or both—the mobile computing device being positioned close enough to activate wireless communication between the mobile computing device and the drug delivery device—c) removing a battery insulation tab to activate the drug delivery device; or d) performing any combination thereof. Claim 48 A computer-implemented onboarding method according to claim 47, further comprising the step of bonding the drug delivery device to the application. Claim 49 A computer-implemented onboarding method according to claim 48, wherein the bonding is performed when the application is in the background of the user's mobile computing device. Claim 50 A computer-implemented onboarding method according to claim 48 or 49, wherein the bonding is performed without opening the application on the mobile computing device. Claim 51 A computer-implemented onboarding method according to any one of claims 48 to 50, wherein the drug delivery device or the packaging material comprises a bonding stimulus. Claim 52 A computer-implemented onboarding method according to any one of claims 48 to 51, wherein the bonding stimulus is provided by a wireless communication protocol, a machine-readable barcode, or both. Claim 53 A computer-implemented onboarding method according to any one of claims 47 to 52, further comprising the step of providing a notification to the user when the drug delivery device establishes a connection with the application. Claim 54 A computer-implemented onboarding method according to any one of claims 47 to 53, wherein the drug delivery device comprises a syringe, a wearable autoinjector, a wearable infusion pump, a device directly attached for subcutaneous delivery, a device indirectly attached for subcutaneous delivery, or an autoinjector pen. Claim 55 A non-transient computer-readable storage medium coupled to a processor and storing instructions, wherein the instructions, when executed by the processor, cause the processor to implement an application, and the application comprises: a) an injection module instructing a user to take supplies, scan for a drug, warm the drug, deliver the drug to a delivery base and press down, select an injection site, remove an injection device from the delivery base, attach the injection device to the user with a view window facing upward, or perform any combination thereof; and b) a progress monitor module displaying an injection status, an on / off body status of the injector, injection progress, remaining injection time, or any combination thereof. Claim 56 In paragraph 55, the application further comprises a home module that displays a next injection time view, a missing injection notification view, or any combination thereof, a non-transient computer-readable storage medium. Claim 57 In paragraph 56, the home module is a non-transient computer-readable storage medium that displays a notification when it is determined that the scanned drug has expired, is incorrect, or both. Claim 58 A non-transient computer-readable storage medium according to any one of claims 55 to 57, wherein the injection module is configured to receive a stomach quadrant selection indicating the location where the injection device is attached. Claim 59 A non-transient computer-readable storage medium according to any one of claims 55 through 58, wherein the application further comprises a recording module that displays an overview of the user’s adherence to an injection schedule and / or an indication of symptom progression. Claim 60 In paragraph 59, a non-transient computer-readable storage medium wherein the recording module is configured to receive an indication of a completed injection. Claim 61 In paragraph 59, a non-transient computer-readable storage medium wherein the recording module is configured to determine the user’s compliance with the injection schedule based on an indication of the completed injection. Claim 62 A non-transient computer-readable storage medium according to any one of claims 55 to 61, wherein the application further comprises a setting module for displaying the user's patient profile, infusion schedule, notification settings, or any combination thereof. Claim 63 A non-transient computer-readable storage medium according to claim 62, wherein the setting module is configured to receive an edit from the user regarding the user's patient profile, the infusion schedule, the notification settings, or any combination thereof. Claim 64 In paragraph 63, the user’s patient profile is a non-transient computer-readable storage medium comprising a user name, user date of birth, user gender, user age, user weight, user height, user ethnicity, user nationality, user residential address, user zip code, user email, user phone number, or any combination thereof. Claim 65 A non-transient computer-readable storage medium according to any one of claims 55 through 64, wherein the application further comprises a login module that receives symptom notifications and injection notifications, and the login module is accessible through a home module. Claim 66 A non-transient computer-readable storage medium according to any one of claims 55 to 65, wherein the application further comprises an injection completion module that displays a notification indicating that the injection is completed. Claim 67 In paragraph 66, a non-transient computer-readable storage medium wherein the progress monitor module comprises the scan completion module. Claim 68 A non-transient computer-readable storage medium according to any one of claims 55 through 67, wherein the application further comprises a scheduling module for receiving a user's response to a symptom questionnaire. Claim 69 A non-transient computer-readable storage medium, wherein, in any one of paragraphs 55 through 68, the application further comprises a resource module for displaying an instructions for use document, a demo video, a terms of use document, a privacy policy document, or any combination thereof.

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