Methods and systems for drug sensitivity determination and customized drug delivery

Abstract

A method of determining a patient's sensitivity to a drug delivered at a delivery frequency is disclosed, comprising: perturbing the delivery amount at a perturbation frequency, by a perturbation amount; constructing a perturbation signal; measuring a patient's response to the perturbation; and recovering the effect of the perturbation. A system for determining a patient's sensitivity to a drug is also disclosed, the system comprising a processor configured for the method.

Description

[0001] Cross-references to related applications

[0002] This application claims priority to U.S. Nonprovisional Application No. 18 / 594,176, filed March 4, 2024, entitled “Method of and System for Determining and Customizing Medication Delivery Based on Medication Sensitivity” (Attorney’s Case No. AB138), the entire contents of which are incorporated herein by reference. Technical Field

[0003] This application generally relates to drug infusion, and more specifically to the identification and customization of infusion control based on patient sensitivity to the drug. Background Technology

[0004] Subcutaneous delivery of therapeutic fluids is a common treatment for a variety of human diseases, such as diabetes. Diabetes is a condition in which the body cannot produce enough insulin to stimulate the uptake of glucose in the bloodstream. Treatment for diabetes involves delivering sufficient amounts of insulin into the body to promote the necessary uptake of glucose.

[0005] This delivery is achieved through one or more injections using a syringe. The components and concentrations of this injection are designed to suit the individual patient's physiology. Because physiology is dynamic, the patient must endure test episodes multiple times a day, such as drops of blood taken from a finger.

[0006] The development of patch-sized fluid delivery systems, such as those disclosed in U.S. Patent No. 8,585,377 to Kamen et al., issued November 19, 2013 (which is incorporated herein by reference), has revolutionized the ability to treat such chronic diseases, offering far greater convenience and comfort to patients. Typically, such devices have at least one reservoir for receiving fluids, not limited to insulin, and include a processor with a power supply and an execution controller. This controller causes a pump to dispense fluid at a quantity and rate based on a program or algorithm.

[0007] Typically, the rate at which an insulin pump releases or delivers insulin into a patient's body is input by the person with diabetes or their caregiver. Therefore, the patient or caregiver determines / instructs the amount of insulin to be delivered at any given time / period. This amount typically includes a "basal" or normal rate / volume and may include "push" or enhanced rates / volumes required to manage events such as meal intake. This rate / volume is determined by the patient / caregiver based on available information or factors such as blood glucose readings determined using a glucometer, past data from similar situations, anticipated or completed consumption, anticipated or completed exercise, and / or stress or illness.

[0008] Although patients determine the rate / volume based on one or more of these or additional factors, managing diabetes is not an exact science. There are many reasons for this, not limited to inaccurate methods of insulin delivery, inaccurate blood glucose meters, inability to properly count carbohydrate intake, inability to identify adjacent diseases, inability to predict the exact effects of exercise, and inability to predict or forecast the effects of many additional hormones or processes in the body.

[0009] The nature of diabetes management is further complicated and made more critical given the risks of hypoglycemia, which can lead to seizures / epilepsy, dementia, fainting, loss of consciousness, and even death. Therefore, over-calculating the required insulin levels can be life-threatening. While the short-term effects of hyperglycemia are not fatal, complications from long-term hyperglycemia are known and include shorter lifespan, increased risk of heart attack or stroke, kidney failure, adult blindness, nerve damage, and non-traumatic amputation. Therefore, long-term under-calculation of required insulin levels can significantly impact quality of life and lead to fatal complications.

[0010] The development of continuous analyte sensors for assessing blood glucosamine levels has significantly improved the ability to treat diabetes, offering greater convenience and comfort for patients. These sensors also unlock the potential for developing closed-loop systems where a processor in an infusion pump is notified by sensor data to configure and instruct the pump to deliver the appropriate amount of medication according to an algorithm. Such closed-loop systems will revolutionize diabetes care through improved glycemic control with reduced monitoring requirements.

[0011] Some control algorithms are limited to operating within small ranges of variation. Others, such as those proposed in U.S. Patent Application Publication 2021 / 0241876 by Eli Lilly and Co., published August 5, 2021, lack the ability to confirm and subsequently proactively incorporate patient sensitivity into determining the effective dose and frequency for treating the disease, avoiding long-term problems caused by inappropriate dosing, and improving the lives of those who must manage diabetes.

[0012] What is needed is a way to identify the patient’s sensitivity, namely, the time lag before the patient’s physiological response to the infused drug, and the degree to which the physiological response to the drug can be taken into account in the algorithm used to control the infusion pump, thus forming a closed-loop system in which the patient can live a normal life with minimal attention to the infusion system.

[0013] The foregoing background is intended to provide a contextual overview of some current issues and is not intended to be exhaustive. Summary of the Invention

[0014] This invention overcomes the shortcomings of existing response systems by utilizing methods and systems for determining a patient's sensitivity to a drug, the methods and systems including response time and degree of response to a given amount, the given amount being taken into account in the infusion control for effective closed-loop therapy.

[0015] A system of one or more computers may be configured to perform a specific operation or action by installing software, firmware, hardware, or a combination thereof on the system, which, in operation, causes the system to perform the action. One or more computer programs may be configured to perform a specific operation or action by including instructions that, when executed by a data processing device, cause the device to perform the action. An embodiment of a method for determining a patient's sensitivity to a drug delivered in a delivery amount at a delivery frequency, configured according to the principles of the invention, includes perturbing the delivery amount by a perturbation amount at a perturbation frequency to substantially constitute a perturbation signal. The embodiment further includes measuring the patient's response to the perturbation. The embodiment further includes recovering the effect of the perturbation, which determines the patient's sensitivity. Other embodiments of the invention include corresponding computer systems, devices, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the method.

[0016] An embodiment of a system configured according to the principles of the invention for determining a patient's sensitivity to a drug delivered at a delivery frequency and in a delivery amount includes a processor configured to communicate with a pump and a sensor. The pump is responsive to the processor. The sensor is configured to transmit signals corresponding to physiological functional parameters. The processor is configured to perform a method comprising perturbing the delivery amount at a perturbation frequency and a perturbation amount, measuring a patient response, and restoring the patient's response to the perturbation.

[0017] Details of one or more embodiments are set forth in the accompanying drawings and the following description. Other features and advantages will become apparent from the specification, drawings, and claims. Attached Figure Description

[0018] Non-limiting and non-exhaustive aspects of this disclosure are described with reference to the following figures, wherein, unless otherwise stated, the same reference numerals refer to the same parts in the various views.

[0019] Figure 1 This is an environmental perspective view of an embodiment of a system configured according to the principles of the present invention; Figure 2 and Figure 3 This is a schematic diagram illustrating an embodiment of a method configured according to the principles of the present invention; Figure 4 This is a schematic diagram illustrating the step and wave function of an embodiment of the method configured according to the principles of the present invention; Figure 5 It is affected by the method configured according to the principle of the present invention. Figure 2 and Figure 3 A schematic diagram of the model; Figure 6 It is the formula referenced in the instruction manual; Figure 7 This is a flowchart of the configuration method according to the principle of the present invention; Figure 8A and Figure 8B These are graphical views of insulin and glucose levels over time. Figures 9A-9C These are graphical views of the perturbation configured for FSK processing, the perturbed insulin level, and the perturbed glucose level over time. Figure 10A and 10B These are graphical views of the demodulated high-frequency and low-frequency glucose levels, and the time-shifted demodulated low-frequency glucose levels over time. Figure 11A and Figure 11B These are graphical views of insulin and glucose levels over time. Figures 12A-12C These are graphical views of the perturbation configured for heterodyne processing, the perturbed insulin level, and the perturbed glucose level over time. Figure 13A and Figure 13B These are graphical views of the demodulated high-frequency and low-frequency glucose levels, and the time-shifted demodulated high-frequency and low-frequency glucose levels over time. Figure 14A and Figure 14B These are graphical views of insulin and glucose levels over time. Figures 15A-15C These are graphical views of the perturbation configured for the Wiener filter, the perturbed insulin level, and the perturbed glucose level over time. Figure 16A and Figure 16B These are, respectively, superimposed Wiener-filtered glucose and insulin signals and a time-shifted Wiener-filtered glucose level graphical view in frequency; and Figure 17 This is a schematic diagram of an embodiment of a control configured according to the principles of the present invention. Detailed Implementation

[0020] Examples shown in the accompanying drawings are presented to illustrate aspects of this disclosure. The drawings are illustrative and not restrictive. In the drawings, for illustrative purposes, some elements may be enlarged and not drawn to scale. Additionally, depending on the context, elements with the same number shown in the figures may be the same element or may be similar elements.

[0021] When the term "comprising" is used in this specification and claims, it does not exclude other elements or steps. When an indefinite or definite article is used when referring to a singular noun (e.g., "a," "an," or "the"), this includes the plural of that noun, unless otherwise specified. Therefore, the term "comprising" should not be construed as limited to the items listed thereafter; it does not exclude other elements or steps, and thus the scope of "device comprising items A and B" should not be limited to a device consisting only of components A and B. Furthermore, with regard to the use of the terms "comprising," "having," "possessing," etc., in this specification and claims, these terms are intended to be open-ended in a manner similar to the term "including," as "including" is interpreted when used as a transitional word in the claims.

[0022] Furthermore, the terms “first,” “second,” “third,” etc., used both in the specification and in the claims, are provided to distinguish similar elements and do not necessarily describe an order or chronological sequence. It should be understood that such terms are interchangeable where appropriate (unless explicitly disclosed otherwise), and aspects of this disclosure described herein can be operated in a different order and / or arrangement than those described or shown herein.

[0023] In the following description, numerous specific details are set forth to provide a thorough understanding of the various aspects and arrangements. However, it will be appreciated that the techniques described herein can be practiced without one or more of these specific details, or using other methods, components, materials, etc. In other instances, well-known structures, materials, or operations may not have been shown or described in detail to avoid obscuring certain aspects.

[0024] Throughout this specification, references to “aspect,” “arrangement,” “configuration,” or “example” indicate that a particular feature, structure, or characteristic is described. Therefore, the appearance of phrases such as “in an aspect,” “in an arrangement,” “in a configuration,” or “in some instances” throughout this specification does not necessarily refer to the same aspect, feature, configuration, example, or arrangement. Furthermore, the specific features, structures, and / or characteristics described may be combined in any suitable manner.

[0025] Within the scope of this disclosure and the claims, the terms “component,” “system,” “platform,” “layer,” “selector,” “interface,” etc., are intended to refer to a computer-related entity or an entity associated with an operating device having one or more specific functions, wherein the entity may be hardware, a combination of hardware and software, software, or software in execution. As an example, a component may be, but is not limited to, a process running on a processor, a processor, an object, an executable file, an execution thread, a program, and / or a computer. By way of illustration and not limitation, an application running on a server and the server itself can both be a component. One or more components may reside within a process and / or an execution thread, and components may be located on a single computer and / or distributed among two or more computers. Furthermore, a component may be executable from various computer-readable media, device-readable storage devices, or machine-readable media on which various data structures are stored. The component may communicate via local and / or remote processes, such as according to signals having one or more data packets (e.g., data from a component interacting with a local system, another component in a distributed system, and / or interacting with other systems across a network such as the Internet via signals). As another example, a component can be a device having specific functions provided by mechanical parts operated by electrical or electronic circuitry, which can be operated by a software or firmware application executed by a processor, wherein the processor can be internal or external to the device and execute at least a portion of the software or firmware application. As yet another example, a component can be a device that provides specific functions through electronic parts without mechanical parts; the electronic parts may include a processor to execute software or firmware that at least partially imparts the functions to the electronic parts.

[0026] Within the scope of use in this specification, terms such as “storage,” “data storage,” “data data,” “database,” etc., refer to a memory component, an entity embodied in memory, or a component that includes memory. It should be understood that the memory component described herein may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory.

[0027] Furthermore, the term "or" is intended to mean an inclusive "or" rather than an exclusive "or." That is, unless otherwise stated or clearly indicated from the context, "X adopts A or B" is intended to mean any natural inclusive permutation. In other words, "X adopts A or B" is satisfied in any of the foregoing cases if X adopts A, X adopts B, or X adopts both A and B. Additionally, the articles "a" and "an" used in this disclosure and claims should generally be interpreted as meaning "one or more," unless otherwise stated or clearly indicated from the context to be in the singular form.

[0028] Within the scope of use herein, the terms “exemplary” and / or “illustrative” are intended to be used as examples, instances, or illustrations. For the avoidance of doubt, the subject matter disclosed herein is not limited to the disclosed examples. Furthermore, any aspect or design described herein as “exemplary” and / or “illustrative” is not necessarily to be construed as preferred or advantageous over other aspects or designs, nor does it exclude equivalent exemplary structures and techniques. Moreover, with regard to the use of the terms “comprising,” “having,” “including,” and other similar words in the detailed description or claims, such terms are intended to be open-ended in a manner similar to the term “comprising” as an open transition word, without excluding any additional or other elements.

[0029] As used herein, the term "inference" or "inference" generally refers to the process of reasoning or inferring the state of a system, environment, user, and / or intention based on a set of observations captured via events and / or data. Captured data and events can include user data, device data, environmental data, data from sensors, application data, implicit data, explicit data, etc. For example, inference can be used to identify specific contexts or actions, or it can be used to generate a probability distribution of states of interest based on considerations of data and events.

[0030] The disclosed subject matter can be implemented as a method, apparatus, or article of manufacture that uses standard programming and / or engineering techniques to produce software, firmware, hardware, or any combination thereof to control a computer to implement the disclosed subject matter. The term "article of manufacture," as used herein, is intended to encompass a computer program accessible from any computer-readable device, machine-readable device, computer-readable carrier, computer-readable medium, or machine-readable medium. For example, a computer-readable medium may include, but is not limited to, magnetic storage devices such as hard disks; floppy disks; magnetic stripes; optical discs (e.g., optical discs (CDs), digital video discs (DVDs), Blu-ray discs (BDs)); smart cards; flash memory devices (e.g., cards, sticks, key drives); virtual devices simulating storage devices; and / or any combination of the aforementioned computer-readable media.

[0031] Typically, program modules include routines, programs, components, data structures, etc., that perform specific tasks or implement specific abstract data types. The aspects disclosed in this subject can be practiced in distributed computing environments, where some tasks are performed by remote processing devices linked via a communication network. In distributed computing environments, program modules can reside in both local and remote memory storage devices.

[0032] A computing device may include at least a computer-readable storage medium, a machine-readable storage medium, and / or a communication medium. A computer-readable or machine-readable storage medium can be any available storage medium accessible by a computer, and includes volatile and non-volatile media, removable and non-removable media. By way of example and not limitation, a computer-readable or machine-readable storage medium can be implemented in conjunction with any method or technique for storing information such as computer-readable or machine-readable instructions, program modules, structured data, or unstructured data.

[0033] Computer-readable storage media may include, but are not limited to, random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, optical disc read-only memory (CDROM), digital versatile disc (DVD), Blu-ray disc (BD) or other optical disc storage devices, magnetic tape cassettes, magnetic tape, disk storage devices or other magnetic storage devices, solid-state drives or other solid-state storage devices, or other tangible and / or non-transitory media that can be used to store desired information. In this regard, the terms “tangible” or “non-transitory” used herein to describe storage devices, memories, or computer-readable media should be understood to exclude only the propagation of transient signals themselves as a modifier, and do not exclude any standard storage device, memory, or computer-readable medium that not only propagates transient signals themselves.

[0034] Computer-readable storage media can be accessed by one or more local or remote computing devices, for example via access requests, queries or other data retrieval protocols, for various operations concerning the information stored on the media.

[0035] The system bus, as used herein, can be any of several types of bus architectures, which can be further interconnected to a memory bus (with or without a memory controller), a peripheral bus, and a local bus using any of a variety of commercially available bus architectures. As used herein, the database can include a Basic Input / Output System (BIOS), which can be stored in non-volatile memory such as ROM, EPROM, or EEPROM, where the BIOS contains basic routines that facilitate, for example, the transfer of information between components within the computer during startup. RAM can also include high-speed RAM, such as static RAM for caching data.

[0036] As used herein, a computer can operate in a networked environment using a logical connection to one or more remote computers via wired and / or wireless communication. This remote computer can be a workstation, server, router, personal computer, laptop, microprocessor-based entertainment application, peer-to-peer device, or other public network node. The logical connection described herein can include wired / wireless connections to a local area network (LAN) and / or a larger network (e.g., a wide area network (WAN)). Such LAN and WAN networking environments are common in offices and companies and facilitate enterprise-wide computer networks, such as intranets, any of which can connect to global communications networks, such as the Internet.

[0037] When used in a LAN networking environment, a computer can connect to the LAN via a wired and / or wireless communication network interface or adapter. The adapter can facilitate wired or wireless communication to the LAN, which may also include wireless access points (APs) configured thereon for communication with the adapter in wireless mode.

[0038] When used in a WAN networking environment, the computer may include a modem or may be connected to a communication server on the WAN via other means for establishing communication over the WAN (such as via the Internet). Modems, whether internal or external, and wired or wireless devices may be connected to the system bus via input device interfaces. In a networking environment, program modules described herein with respect to a computer or parts thereof may be stored in remote memory / storage devices.

[0039] When used in a LAN or WAN networking environment, a computer can access cloud storage systems or other network-based storage systems in addition to or in place of external storage devices. Typically, the connection between the computer and the cloud storage system can be established via a LAN or WAN, for example, through an adapter or modem. When a computer is connected to an associated cloud storage system, the external storage interface can manage the storage provided by the cloud storage system with the help of the adapter and / or modem, just like other types of external storage. For example, the external storage interface can be configured to provide access to cloud storage sources as if these sources were physically connected to the computer.

[0040] As used herein, the term "processor" can refer to virtually any computing processing unit or device, including, but not limited to, single-core processors; single-core processors with software multithreading capabilities; multi-core processors; multi-core processors with software multithreading capabilities; multi-core processors with hardware multithreading technology; vector processors; pipelined processors; parallel platforms; and parallel platforms with distributed shared memory. Additionally, a processor can refer to an integrated circuit, application-specific integrated circuit (ASIC), digital signal processor (DSP), field-programmable gate array (FPGA), programmable logic controller (PLC), complex programmable logic device (CPLD), state machine, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. Processors can utilize nanoscale architectures, such as, but not limited to, molecular and quantum dot-based transistors, switches, and gates, to optimize space usage or enhance the performance of user devices. Processors can also be implemented as a combination of computing processing units. For example, processors can be implemented as one or more processors together, which are tightly coupled, loosely coupled, or remotely located relative to each other. Multiple processing chips or multiple devices can share the execution of one or more functions described herein, and similarly, storage can be implemented across multiple devices. The processor can be implemented to reside in a cloud-based network (e.g., the Internet).

[0041] The actions of the methods or algorithms described in conjunction with the arrangements disclosed herein can be directly embodied in hardware, software modules executed by a processor, or a combination of both. The software modules can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disks, removable disks, CD-ROMs, or any other known form of storage medium. The storage medium can be coupled to the processor, enabling the processor to read information from and write information to the storage medium. Alternatively, the storage medium can be integrated into the processor. The processor and the storage medium can reside in an ASIC. The ASIC can reside in a functional facility, such as a computer, robot, user terminal, mobile phone or tablet computer, automobile, or IP camera. Alternatively, the processor and the storage medium can reside as discrete components in such a functional facility. Additionally or alternatively, at least one of the processor and / or the storage medium can reside in a cloud-based network, such as, for example, the Internet.

[0042] The configuration described herein relates to a computer system for implementing the methods discussed herein, and to a computer-readable medium containing programs for implementing these methods. Raw data and results may be stored for future retrieval and processing, printing, displaying, transmission to another computer, and / or to other locations. Communication links may be wired or wireless, for example, using cellular communication systems, military communication systems, and satellite communication systems. Multiple parts of the system may operate on a computer with a variable number of CPUs. Other alternative computer platforms may be used.

[0043] This configuration also relates to software / firmware / hardware for implementing the methods discussed herein, and a computer-readable medium for storing the software for implementing these methods. The various modules described herein may be implemented on the same CPU or on different CPUs. This configuration has been described in language more or less specific to structural and methodological features in accordance with applicable regulations. However, it should be understood that this configuration is not limited to the specific features shown and described, as the apparatus disclosed herein includes preferred forms that enable this configuration.

[0044] The method may be implemented electronically, in whole or in part. Signals indicating actions taken by the system's components and other publicly disclosed configurations may travel over at least one real-time communication network. Control and data information may be executed electronically and stored on at least one computer-readable medium. The system may be implemented to execute on at least one computer node in at least one real-time communication network. Common forms of the at least one computer-readable medium may include, for example, but not limited to, floppy disks, flexible disks, hard disks, magnetic tape or any other magnetic media, optical disc read-only memory or any other optical media, punched cards, paper tape or any other physical media with a perforated pattern, random access memory, programmable read-only memory, and erasable programmable read-only memory (EPROM), flash memory EPROM, or any other memory chip or cartridge, or any other medium that a computer can read. Furthermore, the at least one computer-readable medium may contain graphics of any form, subject to appropriate licensing where necessary, including but not limited to Graphics Exchange Format (GIF), Joint Image Experts Group (JPEG), Portable Web Graphics (PNG), Scalable Vector Graphics (SVG), and Tagged Image File Format (TIFF).

[0045] This document describes various arrangements. For simplicity, the method or algorithm is depicted and described as a series of steps or actions. It should be understood and recognized that the various arrangements are not limited to the actions shown and / or the order of actions. For example, actions may occur in various orders and / or simultaneously, and together with other actions not presented or described herein. Furthermore, not all actions shown may be required to implement the method. Alternatively, the method may be represented as a series of interrelated states via a state diagram or events. Additionally, the methods described below can be stored on an article of manufacture as defined herein to facilitate the transfer and transmission of such methods to a computer.

[0046] This invention relates to a method for determining a patient's sensitivity to a drug and then adjusting drug delivery parameters based on that sensitivity. Sensitivity is identified from the patient's responsiveness to precise timing perturbations in the delivery amount.

[0047] Although insulin and diabetes have been discussed herein, the invention is not limited to the use of systems and methods for treating diabetes only. The disclosed methods and systems can be used to deliver any fluid, including any medical or therapeutic fluid, including but not limited to insulin, for the treatment of medical conditions not limited to diabetes.

[0048] This article describes methods and systems for closed-loop or partially closed-loop control of diabetes. As mentioned above, many factors influence the amount of insulin required for a patient or user to maintain appropriate blood glucose levels. The term "appropriate" is used herein to mean the blood glucose level that has been selected by the patient and / or their healthcare provider as being beneficial to the patient's health. Appropriate blood glucose levels can vary from patient to patient, and appropriate blood glucose levels can also vary for any given patient at any given time. Typically, many healthcare providers recommend maintaining blood glucose levels between 90 and 140 mg / dL. However, the range can vary depending on the circumstances. For example, a patient might consider a blood glucose level of 150 mg / dL appropriate before bedtime, but would consider the same reading inappropriate before mealtime.

[0049] refer to Figure 1A preferred system configured according to the principles of the invention includes a patient 12 wearing a medical fluid pump 14, a sensor device 16, and holding a controller 18. The sensor device 16 may include one or more continuous glucose monitors (“CGM”) and one or more additional sensors. The sensors transmit data to the controller 18. The medical fluid pump 14 shown in the figure is a patch pump, similar to any patch pump shown and described in the following documents: U.S. Publication No. US-2007-0219480 (published September 20, 2007, entitled "Patch-sized Liquid Delivery System and Method (E72)"); U.S. Publication No. US-2007-0228071 (published October 4, 2007, entitled "Liquid Delivery System and Method (E70)"); U.S. Publication No. US-2007-0219496 (published September 20, 2007, entitled "Pumping Liquid Delivery System and Method Using a Force Application Component (E71)"); U.S. Publication No. US-2007-0219597 (published September 20, 2007, entitled "Adhesive and Peripheral System and Method for Medical Devices (E73)"); U.S. Patent Application Serial No. 12 / 347,985 (200 U.S. Patent Application Serial No. 12 / 347,982 (filed December 31, 2008, entitled "Infusion Pump Assembly (G75)"); U.S. Patent Application Serial No. 12 / 347,982 (filed December 31, 2008, entitled "Wearable Pump Assembly (G76)"); U.S. Patent Application Serial No. 12 / 347,981 (filed December 31, 2008, entitled "Infusion Pump Assembly (G77)"); U.S. Patent Application Serial No. 12 / 347,984 (filed December 31, 2008, entitled "Infusion Pump Assembly (G77)"); U.S. Patent Application Serial No. 12 / 347,984 (filed December 31, 2008, entitled "Wearable Pump Assembly (G76)"); The entire contents of the following documents are incorporated herein by reference: U.S. Publication No. US-2009-0099522 (published April 16, 2009, entitled "Microneedle System and Device"); and U.S. Publication No. US-2009-0099523 (published April 16, 2009, entitled "Infusion Pump Assembly");

[0050] Preferably, pump 14 is controlled by controller 18 and transmits information to controller 18. Some embodiments may include a user interface that allows patient / user control. Controller 18 receives information related to the one or more sensors and the pump. The controller additionally receives input from the user, such as events, and may receive manual input for finger-prick blood readings or finger-prick blood data. Additionally, in some embodiments, the controller may wirelessly receive information related to food or glucose readings. In some embodiments, the controller includes voice recognition, so in these embodiments, the controller may receive commands via voice.

[0051] The system can use at least one CGM. The CGM includes a glucose sensor (referred to as a “sensor” or “analyte sensor”). In various embodiments, the CGM sensor is introduced and retained in the interstitial fluid located on the user’s body (e.g., on the abdomen). The CGM sends electrical signals to a receiver or controller at predetermined intervals. The receiver or controller correlates these electrical signals with glucose values. In some embodiments, for safety reasons, redundant CGMs are used to provide more than one interstitial glucose reading at any given reading time. In some embodiments, the redundant CGM can be one or more additional CGMs (the same CGM) located in different parts of the patient. In other embodiments, the redundancy can be provided by one or more sensors integrated into a single CGM device, where all sensors are introduced to similar locations on the patient, and in some embodiments, the same automated inserter is used. In some embodiments, the one or more redundant sensors can be sensors introduced to different depths in the patient; for example, if four redundant sensors are present, each sensor is introduced to a different depth in the patient.

[0052] Redundant sensors provide additional safety. Sensor readings can be sent to a processor that can use various methods to determine whether the system should accept the reading, or which reading the system should accept, for determining the amount of insulin to be delivered. For example, the processor can determine if the value varies by more than 6% (in other embodiments, the percentage difference can be different and can be determined and / or specified based on one or more calibration techniques), then the reading may not be used for delivery and recalibration (i.e., via finger-prick blood sampling) is required. If the processor does not receive a signal from a sensor, the processor can be programmed to ignore that sensor. If all redundant sensors read the same or similar values ​​(again, within a pre-programmable or predetermined percentage), the system can be more confident that the value is closer to correct.

[0053] In some embodiments, the redundant sensors can be calibrated differently. For example, one sensor can be calibrated to be more sensitive than the others. In some embodiments, the various sensors are tuned to different dynamic ranges. For example, in the case of using two sensors, each of the two sensors is tuned to a different range, one tuned to be highly sensitive to low blood glucose levels and the other tuned to high blood glucose levels. For example, if the tuned sensor reads 60 mg / dL, the system will recognize that the sensor is in the patient and is reading. If the tuned sensor reads 250 mg / dL, the system can confirm that the sensor is in the patient and is reading. In other embodiments, the redundant sensors can be tuned based on a time constant, i.e., one sensor reads faster than the next sensor, etc.

[0054] The controller serves as at least one user interface and also as a central user interface for the CGM / sensor, the pump, and the patient / user to the control system. For the purposes of this document, the controller may be programmed by a patient, a “user,” a caregiver, a healthcare provider, or any combination thereof. However, for the purposes of this specification, the terms “patient,” “patient / user,” or “user” refer to anyone who inputs information into the controller or uses the controller to provide care to a patient. In an exemplary embodiment, the system controller communicates with various system components wirelessly (e.g., radio frequency (“RF”) communication and / or other types of telecommunication). In an exemplary embodiment, the controller includes a graphical user interface (“GUI”) and one or more input devices, such as buttons, capacitive sliders, scroll wheels, touchscreens, keypads, electronic keypads, and any other input devices. The controller also includes at least one processor, although in an exemplary embodiment, the controller includes at least two processors: a control processor and a security processor. These processors may be redundant processors, or two different processors providing redundant processing or checking each other’s processing.

[0055] Some embodiments of the controller may include at least one “event” or designated button, such as a “food” button, a “workout” button, and a “pump” button. In some embodiments, the controller may include a single “event” button. Pressing or actuating this button takes the user to an event menu, which may include a list of potential events, one or more of which may be user-customizable.

[0056] Regarding all event buttons, when pressed, these buttons will lead the patient / user into a menu or processing logic that allows the patient / user to directly input information for, for example, exercise, food, or injection. The logic can then query the patient / user to input additional information, such as the expected duration and intensity of exercise, the amount of food (i.e., carbohydrates), glycemic index, fat content, and protein content of the food. Regarding injections, the patient / user will be able to input the requested insulin dosage, i.e., insulin units, by pressing a series of buttons or by using another input device (i.e., a scroll wheel, button, or slider). In some embodiments, this user interface includes many of the same features as insulin pumps and pump controllers known in the art.

[0057] In an exemplary embodiment, the controller further includes a "test strip reader," for example, a space for receiving glucose test strips for "finger stick" readings, whereby the patient pricks their finger and applies blood from the finger to the "finger stick." The "test strip reader" uses an electrochemical test to determine the blood's glucose level. The test strip reader can be used to calibrate the CGM (Cyclic Glucose Meter), to double-check for unexpected or abnormal readings, or as a backup for the CGM in case of failure. In some embodiments, the test strip reader can be a separate device, such as a glucose meter. In these embodiments, the glucose meter can wirelessly receive the finger stick reading, or the user can manually input the reading into the controller.

[0058] In some embodiments, the controller functions as a receiver for at least one sensor (including, but not limited to, at least one CGM). Therefore, the user will instruct the controller when to introduce a new sensor into the body. In some embodiments, the user can additionally input the location of the sensor on the user's body, for example, including but not limited to the right abdomen, left abdomen, right arm, left arm, right hip, left hip, right leg, left leg, etc. This may be desirable because the sensor can function differently in different areas of the body. As the controller records and processes this data, it can calibrate the sensor based on past archival information indicating "hysteresis" and / or "drift" from the same area of ​​the body.

[0059] To manage diabetes using at least a partially closed-loop approach, components of the described system can be used to deliver controlled doses of insulin according to various methods, and in some embodiments, to deliver counter-regulatory hormones, such as glucagon, some of which are described herein. In exemplary embodiments, the control method relies on the use of a system that includes the ability to actively measure the actual dose of insulin or other fluid delivered to the patient, rather than measuring a user-requested or user-preprogrammed dose of insulin to be delivered. At least one CGM and user interface, and a process containing instructions for at least a partially closed-loop algorithm, are included. Other sensors and data input models may also be included, as described in more detail above. However, in some embodiments, a pump that does not actively measure the actual dose of insulin or other fluid delivered to the patient may also be used. In these embodiments, the assumption is made that the dose delivered to the patient is the dose requested by the processor, unless or until a mechanical failure or blockage is detected.

[0060] Sensitivity to any of a variety of drugs can be confirmed using embodiments of a method for determining drug sensitivity configured according to the principles of the present invention. Sensitivity refers to: (1) the amount of time elapsed before the patient responds to the drug; and (2) the response correspondence or degree of the patient's response to the amount of drug. Here, methods for determining these important attributes are described in the context, but are not limited to insulin sensitivity.

[0061] refer to Figure 2 The insulin-related embodiments of the present invention are configured based on the Sturis metabolic model, a kinetic model developed to simulate human insulin-glucose metabolism, as described in the *Journal of Theoretical Biology*, 2000, Vol. 207, pp. 361-375, and in *Computer Models of the Intrinsic Mechanisms of Hypersolar Oscillations in Insulin and Glucose*, Sturis, Polonsky, Mosekilde, and Van Cauter, *American Journal of Physiology*, May 1991, 260(5 Pt 1):E801-9, Digital Object Identifier (doi): 10.1152 / ajpendo.1991.260.5.E801. Both of these references are incorporated herein by reference. The Sturis model is adapted to allow external sources of glucose and insulin. A detailed description of the model is beyond the scope of this document. It should be noted that this Sturis model uses interrelated time-differential equations to describe the concentrations of insulin and glucose in the body, and the functions relating to their increase, decrease, and utilization. The model comprises the following feedback loop: glucose stimulates pancreatic insulin secretion, insulin stimulates glucose uptake and inhibits hepatic glucose production, and glucose enhances its own uptake. This system contains two significant delays. One delay involves the correlation between the physiological effects of insulin on glucose utilization and the insulin concentration in the slowly equilibrium cellular compartments, rather than with the insulin concentration in the plasma. The other delay is associated with the time lag between the appearance of insulin in the plasma and its inhibitory effect on hepatic glucose production.

[0062] Figure 2 The expected relationship between glucose and insulin concentrations in non-diabetic humans is shown, where glucose levels lead to insulin levels. Introducing a certain dose of glucose D into the system results in a corresponding increase in the time delay of insulin production or release. This invention provides a method for supplying insulin in diabetic patients in a manner that mimics a non-diabetic system.

[0063] refer to Figure 3Consistent with this Sturis model, the amount of insulin available in the body over time, represented by curve 20, undergoes a known human physiological process 25 that reduces the amount of glucose found in the blood over time, represented by curve 30. Normally, the pancreas secretes insulin into the bloodstream throughout the day and night; this is known as basal insulin release. This basal amount is not fixed but varies according to perceived glucose concentration levels. Glucose levels rise and fall, for example, as the body develops glucose, such as from food, and absorbs glucose into cells that require insulin. In response to elevated blood glucose concentrations, the pancreas increases the amount of insulin released into the bloodstream beyond this basal amount. Generally, glucose and insulin concentrations correspond, with the former leading the latter by varying amounts from person to person.

[0064] refer to Figure 4 When the pancreas is not functioning sufficiently to produce enough insulin to lower glucose levels, insulin supplementation is typically achieved through injections administered by a syringe and / or infusion pump. A syringe injection introduces a single dose of insulin at a time. Infusion pump injections typically release discrete amounts of insulin in the body over discrete time intervals, as modeled by a positive range of a step curve 35 or a sine curve 40 with amplitude 42 and period 44. Preferably, on a longer timescale, discrete injections of curves 35 and 40 can be effectively modeled as a smooth curve 45, such as... Figure 5 As shown, this corresponds to the healthy, continuously releasing function of the human pancreas. Figure 3 The curve 20 in the middle is equivalent.

[0065] A patient's sensitivity to insulin—that is, the degree to which a patient responds to a given amount of insulin, and the lag time between the introduction of insulin and the body's response to it—is unique to each patient. Understanding this sensitivity is crucial for patient comfort, even if it doesn't directly affect the patient's survival, given the potentially disastrous consequences of untimely release or excessive or insufficient amounts of insulin.

[0066] One approach is to consider patient input, namely anticipated exercise and dietary intake, and infer sensitivity from the difference between predicted and measured glucose levels. However, the parameters of this control system must be kept constant or inferred from the assumed accuracy of glucose response and diet / exercise reports under control. Another drawback is that insulin / glucose control is slower and more conservative than parameters determined through active physiological stimulation, as per the principles of this invention.

[0067] Monotone perturbation

[0068] This invention improves upon the previous method by actively stimulating and monitoring the patient's physiological functions. This embodiment and subsequent embodiments of the invention employ signal processing principles to identify the degree and frequency of the patient's sensitivity to active stimulation.

[0069] Continue to refer to Figure 5 This method assumes that supplemental insulin is released using an infusion pump based on an algorithm or function that controls the amount and frequency of release, and describes the insulin release curve 45. (Compared to...) Figure 3 Consistent with the modeling, the algorithm or function used to achieve the insulin release curve 45 can be based on the following formula 1 and... Figure 6 To describe.

[0070] Formula 1:

[0071] Where i is the amount of insulin released, t is time, and x is the amount of insulin required according to changes in glucose concentration (c). It is the frequency of insulin release.

[0072] and Figure 3 Similar to the model described above, in response to the presence of insulin, known human physiological processes 25 reduce the amount of glucose found in the blood, as shown in glucose level curve 50. Preferably, in response to one or more of the aforementioned sensors, the algorithm controlling the pump responds and releases insulin like the human pancreas, such that glucose and insulin concentrations correspond, with the former leading the latter.

[0073] Also refer to Figure 7 A preferred embodiment of the present invention is method 200, which includes step 205 of perturbing the delivery amount 45 with a perturbation amount 60 at a perturbation frequency 67. Preferably, but not necessarily, the present invention employs a sinusoidal perturbation model, which perturbs the insulin release algorithm or function and analyzes the patient's response to the perturbation. The perturbation may be constant, as shown by curve 60, or varied to explore the degree of patient responsiveness, as described below. The amount of perturbation to the insulin release algorithm can be based on the following formula 2 and in Figure 6 As described in the text.

[0074] Formula 2:

[0075] Where p is the amount by which i(t) increases or decreases, t is time, and k is a disturbance that can be constant or time-varying. It is the frequency of the perturbation. The amount of perturbation curve 60 is used to perturb the insulin release curve 45 to produce a curve 45 with periodic spikes 55.

[0076] A preferred embodiment of method 200 includes step 210 of measuring the patient's response. For example... Figure 5 As shown, the patient can respond to this perturbation infusion and exhibits a perturbed response corresponding to the glucose level at curve 65 and the perturbed insulin release at curves 45 / 55. This release, perturbation, and response can be represented as follows: Figure 6 Formula 3 in the text.

[0077] Formula 3:

[0078] A preferred embodiment of method 200 includes a step 215 of recovering the effect of perturbation 75 from the perturbed patient response 65. Sensitivity is determined by the recovered effect. A preferred manner for recovering the effect of the perturbation is by demodulating the measured glucose level using a sine / cosine signal of the same frequency as the perturbation. This recovers the amplitude of the physiological response to the stimulus at that frequency. Preferably, the response is determined by an interpretation function applied to the convolution of the response and the perturbation signal, which may be derived from the following and Figure 6 Formula 4 in the text represents this.

[0079] Formula 4:

[0080] In one embodiment of the present invention, the perturbation signal is a sine wave. Furthermore, the perturbation curve 60 is interpreted as a carrier signal with encoded information (i.e., physiological response). The patient's unique physiological function 25 responds to this insulin release and develops a glucose level corresponding to curve 65. The perturbation signal of curve 60 removed from the glucose response signal 65 is interpreted as a demodulated signal 65. This demodulation 70 generates a sensitive signal 75 in the frequency domain with an amplitude related to the patient's individual responsive physiological function.

[0081] Consistent with the principles of signal processing, the frequency at which this disturbance occurs... Preferably less than the frequency at which the measurement occurs. And / or consistent with Nyquist sampling to allow for meaningful demodulation of the patient's response.

[0082] The advantage of this method is that it rapidly restores the patient's physiological sensitivity to insulin. One limitation is that the measurement time lag (the period of physiological response) must be less than the perturbation period.

[0083] Once a patient's sensitivity is understood, it can be used to enhance algorithms programmed to control the delivery of insulin to the patient. For example, if the sensitivity signal indicates that the patient needs a longer time to respond to insulin, the sensitivity function will adjust the algorithm to release insulin earlier in a given cycle. As another example, if the sensitivity signal indicates that the patient is responding to a small amount of insulin, the sensitivity function will adjust the algorithm to release a smaller amount of insulin that the algorithm typically has in a given cycle. Adjusting the pump delivery algorithm based on patient sensitivity flattens the patient's response curve, as... Figure 5 As shown, this leads to more normal bodily functions, greater comfort, and better health.

[0084] Frequency Shift Keying

[0085] refer to Figures 8A-8B and Figures 9A-9C Another embodiment of the method for identifying patient sensitivity according to the principles of the present invention perturbs and assesses insulin release based on the principles of frequency shift keying (FSK). The method involves perturbing a certain amount of insulin delivery at a certain frequency, forming a single-tone signal, and changing the amount and frequency according to a known timetable, such as after five cycles. The demodulation of this physiological response produces a sensitivity curve or function.

[0086] Figures 8A-8B This represents the undisturbed state, where the pump's control or algorithm corresponds to... Figure 8A The curve or signal 145 shown indicates the amount of insulin supplied. The patient's physiological response to this insulin infusion produces a glucose curve or signal 150, such as... Figure 8B As shown.

[0087] This embodiment of the method for configuring according to the principles of the present invention utilizes the description Figure 9A The disturbance curve 160 in the figure is used to describe the disturbance using the disturbance function. Figure 8A The insulin release function is represented by the insulin release curve 145. The perturbation signal is configured according to the principle of Frequency Shift Keying (FSK). The FSK signal 160 has a fixed amplitude or perturbation amount 170, which is added to the insulin release function over a fixed time period, with different frequency signals, a higher frequency 192 or a faster perturbation, and a lower frequency 194 or a slower perturbation, such as... Figure 9A As shown.

[0088] refer to Figure 9B The perturbation function / curve 160 is used to add to or modulate the insulin release function / curve 145 to generate the perturbed insulin release curve 165. The mathematics involved in modulating the insulin release function using this perturbation function is similar to that described above regarding the aforementioned perturbation model; the difference lies in the frequency of the perturbation in Equation 2. The signal changes in a known manner. Therefore, the perturbed insulin release signal 155 has different frequency components, which are physiologically recognizable and indicate different properties of drug sensitivity.

[0089] refer to Figure 9C In response to the perturbed insulin release signal 155, the patient's unique physiology will develop glucose levels corresponding to the glucose response signal / curve 165. It is expected that a high-frequency insulin signal will be carried to the glucose response 165. If the perturbation is small relative to the individual's physiology, a substantially linear response can be expected.

[0090] The glucose response signal / curve 165 contains valuable information about physiological function, namely: insulin sensitivity, the degree to which physiological function responds to insulin levels, and the response time or lag between insulin input and changes in glucose levels.

[0091] refer to Figure 10A This method provides a method for removing the perturbation signal of curve 160 from the glucose response signal 165, and demodulating signal 165 using signal 160. FSK demodulation consists of standard IQ demodulation, where I represents the in-phase component and Q represents the quadrature-phase component, performed at each component frequency. The IQ demodulator strips data from the modulated signal by creating I and Q (amplitude and phase) components that can be interpreted meaningfully, in this case, as drug sensitivity.

[0092] like Figure 10A As shown, corresponding to the higher frequency portion 192 and the lower frequency portion 194 of the perturbation insulin release function 160, two corresponding demodulated signals 180 and 185 alternate. When the demodulation 180 of the glucose response signal 165 is greater than the demodulation 185 of the slower frequency signal 194, demodulation 180 corresponds to the fast frequency portion 192 of the FSK signal, as... Figure 9A As shown, the opposite is also true. Changes in amplitude relative to the vertical axis indicate changes in insulin sensitivity or the degree to which the physiological function responds to insulin. Sensitivity changes between two frequencies can also be determined. Therefore, this method can reveal the dynamics of a patient's physiological function.

[0093] refer to Figure 10B The response time of a patient's physiological function can be determined by assessing the phase shift between the insulin signal and the glucose signal. For example, the slower component 194 of the FSK input signal 175 can be described by a sine function, such as in Equation 5 below. Figure 6 middle.

[0094] Formula 5:

[0095] Where t is time in seconds, and T is a constant. The input signal has a period of 2 minutes, therefore i(0) = i(120). The demodulated response signal 185 will be similar to the input signal with a similar periodicity, but shifted by an amount of time corresponding to the physiological response time of the body. Therefore, as Figure 10B As shown, the lower-frequency demodulated signal 185, shown as a non-time-shifted instance covering the lower-frequency demodulated signal 197, has a difference 190 between the actual signal and the time-shifted signal corresponding to the patient's time responsiveness or time lag. The actual and time-shifted high-frequency demodulated signals exhibit the same information.

[0096] The advantage of multi-tone FSK demodulation over single-tone perturbation is that it can determine the entire length 175 of the perturbation frequency signal, which is either the response time or the lag in the FSK waveform. Assuming the FSK waveform has a length 175 exceeding the physiological response time, because the faster portion 192 is smaller than the length 175, the effects of fast-frequency perturbations can be identified from the demodulation. These effects may occur within or outside the period of the fast-frequency perturbation.

[0097] Implementing this FSK model reveals insulin sensitivity at known frequencies, including a defined time lag up to the length of time spent at that frequency. The advantage of this approach is that it achieves a higher signal-to-noise ratio at specific frequencies. However, as described below, this technique is slower than heterodyne analysis.

[0098] Code division multiplexing

[0099] Another embodiment of the method for identifying patient sensitivity, configured according to the principles of the present invention, perturbs and assesses insulin release based on the principles of code division multiplexing (CDM). Similar to the FSK embodiment described above, the CDM signal includes codes of multiple code blocks in length, instead of just two as described above for FSK. This method extends the time lag between the measurable perturbation / response.

[0100] external

[0101] refer to Figure 11A and Figure 11B as well as Figures 12A-12C Another embodiment of the method for identifying patient sensitivity, configured according to the principles of the present invention, perturbs and assesses insulin release based on the principle of heterodyne. This embodiment is similar to the FSK embodiment, except that the perturbation signal 195 continuously employs two or more tones. In this non-limiting example, only two tones are shown.

[0102] Figures 11A-11B This represents the undisturbed state, where the pump's control or algorithm corresponds to, for example... Figure 11A The curve or signal 200 shown indicates the amount of insulin supplied. The patient's physiological response to this insulin input produces a glucose curve or signal 205, such as... Figure 11B As shown.

[0103] refer to Figure 13A and Figure 13B The heterodyne signal 195 is added to the pump controller command signal 200 to generate a heterodyne signal 210 with a higher frequency component.

[0104] refer to Figure 12CThe patient's physiological response is to insulin released according to the perturbation signal 210, and the glucose level is represented by curve 215. It is expected that the high-frequency insulin signal 210 will carry over to the glucose response 215. Smaller perturbations will tend to produce a more linear response.

[0105] refer to Figure 13A Heterodyne demodulation consists of standard IQ demodulation performed at each component frequency. Variations in amplitude indicate variations in insulin sensitivity. It can also determine the sensitivity variation between two frequencies.

[0106] refer to Figure 13B The patient's physiological response time or time lag can be inferred from the time lag observable in either signal. The low-frequency demodulated signal 220, shown as an example of a time shift covering the low-frequency demodulated signal 225, has a phase shifted by an amount 230 relative to the phase of the perturbed signal. The amount 230 between the actual signal and the time-shifted signal corresponds to the patient's time responsiveness or time lag. Phase shifts observable in the actual and time-shifted demodulated signals at other frequencies convey the same information. The "no lag" curves are essentially flat. The lower-frequency curves switch between near 0 degrees and near 360 degrees. This variation is due to noise in the signal.

[0107] In heterodyne, phase measurements at different frequencies allow for the determination of the time delay of this physiological function. The unique minimum time lag should correspond to the time difference between the two signals. For example, if the heterodyne includes a sine wave with a period of 7 minutes and a sine wave with a period of 11 minutes, and if the 7-minute sine wave has a 3-minute offset in glucose while the 11-minute sine wave has a 5-minute offset, since the offsets of both should be the same, the common time should give this combination of offsets: 1) At 10 minutes, the 7-minute sine wave has a 3-minute offset, and the 11-minute sine wave has a 10-minute offset; 2) At 17 minutes, the 7-minute sine wave has a 3-minute offset, and the 11-minute sine wave has a 6-minute offset; 3) At 24 minutes, the 7-minute sine wave has a 3-minute offset, and the 11-minute sine wave has a 2-minute offset; 4) At 31 minutes, the 7-minute sine wave has a 3-minute offset, and the 11-minute sine wave has a 9-minute offset; 5) At 38 minutes, the 7-minute sine wave has a 3-minute offset, and the 11-minute sine wave has a 5-minute offset. Therefore, the insulin time delay is 38 minutes because it is compatible with both phase measurements.

[0108] Signal processing in heterodynes is more complex than in FSK or CDM and is more sensitive to other signals leaking into the demodulation. Selecting sufficiently diverse frequencies for long-term measurements can be challenging depending on individual physiological capabilities. The measurable time range is essentially the period of the beat frequency. .

[0109] Wiener Filter

[0110] refer to Figure 14A and Figure 14B as well as Figures 15A-15C Another embodiment of the method for identifying patient sensitivity, configured according to the principles of the present invention, perturbs and assesses insulin release based on the principles of Wiener filtering. This embodiment is similar to heterodyne, but employs a continuous frequency band.

[0111] Figures 14A-14B This represents the undisturbed state, where the pump's control or algorithm corresponds to... Figure 14A The curve or signal 300 shown indicates the amount of insulin supplied. The patient's physiological response to this insulin infusion produces a glucose curve or signal 305, such as... Figure 14B As shown.

[0112] refer to Figure 15A and Figure 15B Preferably, the present invention adds a narrowband insulin perturbation signal 310 to the pump controller command signal 300 to achieve a signal 315 with a composite frequency component.

[0113] refer to Figure 15C The patient's physiological response is based on the release of insulin according to the perturbation signal 310, and presents as glucose levels as described by curve 320. It is desirable that various frequencies of the perturbation signal 310 be carried over to the glucose response 320.

[0114] refer to Figure 16A The Wiener filter is applied to the response signal 320 at all frequencies to generate the Wiener-filtered response signal 325, and applied to the input signal 315 to generate the Wiener-filtered input signal 330. The amplitude difference 335 between the Wiener-filtered response signal 325 and the Wiener-filtered input signal 330 indicates the change in insulin sensitivity depending on the amount of insulin.

[0115] refer to Figure 16B The patient's physiological response time or time lag can be inferred from the phase shift between the output signal and the input signal. This shift is observed by comparing a time-shifted instance 340 of the Wiener-filtered response signal to a non-time-shifted instance covering the Wiener-filtered response signal 325. A generally flat response curve (such as in segment 350) indicates a phase shift relative to the input signal (…). Figure 15BThe perturbed insulin signal 315 is in phase. A relatively skewed response curve (such as in segment 345) indicates a phase difference from the perturbed insulin signal 315. The phase shift between curves 340 and 325 indicates the patient's time responsiveness or time lag T. The response signal 325 with time lag T can be expressed by the following formula 6 and... Figure 6 As described in the text.

[0116] Formula 6:

[0117] The phase in radians is given by the following formula 7 and Figure 6 As described in the text.

[0118] Formula 7:

[0119] like Figure 16B As shown, the response signal 325 exhibits a change of approximately 200° at a frequency variation of 0.002Hz. Substituting the value of this variable into the following... Figure 6 Formula 8 in the text.

[0120] Formula 8:

[0121] This invention envisions the application of alternative signal processing techniques to determine a patient's sensitivity to medication, which would be appropriate. This sensitivity information improves current algorithms driving infusion pumps and allows them to be modified according to the patient's physiological functions. This individually customized self-calibrating capability enables the deployment of infusion pumps as closed-loop systems, allowing patients to perform their daily activities with minimal attention to the pump.

[0122] refer to Figure 17 An embodiment of the controller 100 configured according to the principles of the invention is preferably closed-loop and allows the patient to perform daily activities without having to manage the pump. For this purpose, the controller 100 is preferably a multiple-input multiple-output (MIMO) controller. Some inputs to the controller 100 are not limited to desired glucose levels 105; predicted or reported food intake 110; predicted or reported exercise events 110; and modulated glucose concentration levels 130. The outputs of the controller 100 may include insulin controller commands 135. The outputs of the controller 100 may include glucagon controller commands (not shown) for increasing the amount of glucose in the bloodstream, as may be necessary to avoid hypoglycemic events.

[0123] According to a preferred embodiment of the invention, insulin controller command 135 is perturbed by perturbation signal 115, wherein the perturbed insulin signal instructs the pump (not shown) to release an amount of insulin corresponding to the perturbed insulin signal.

[0124] The patient's physiological functions 125 respond to received insulin and actual food intake and movement events 120, and develop glucose levels, which are measured using sensor 140. Therefore, due to the physiological response to the perturbed insulin level, the output of sensor 140 is interpreted as the perturbed glucose concentration level 130.

[0125] Consistent with the method described above, controller 100 processes the perturbed glucose concentration signal 130 and identifies or updates the patient's drug sensitivity. Based on the patient's drug sensitivity, controller 100 adjusts the insulin controller command to customize the pump command algorithm to more appropriately adapt to the patient's physiological functions.

[0126] The aforementioned non-exclusive methods enable the identification of a patient's sensitivity to a drug, including response time, degree of response to a given dose, and duration of response. These methods outline the dosing algorithm and enable the deployment of closed-loop systems for drug infusion that allow users to live and thrive with minimal concern for pump maintenance.

[0127] While preferred embodiments of the invention aim to provide a closed-loop system that does not require attention to routine operations, another embodiment provides timing to assist patients in activities that may cause large fluctuations in glucose levels, such as exercise and meal intake. Based on the aforementioned methods for identifying patient sensitivity to medication, particularly lag time, the invention responds to patient predictions or reports of food / exercise and, given patient sensitivity, suggests when the patient will optimally manage such activities according to their physiological capabilities.

[0128] Several embodiments have been described. However, it should be understood that various modifications can be made. Therefore, other embodiments are within the scope of the appended claims.

[0129] While the principles of the invention have been described herein, it should be understood by those skilled in the art that this description is by way of example only and not as a limitation on the scope of the invention. Other embodiments are contemplated within the scope of the invention, in addition to the exemplary embodiments shown and described herein. Modifications and substitutions by those skilled in the art are considered to be within the scope of the invention.

Claims

1. A method for determining a patient's sensitivity to a drug delivered at a delivery frequency and in a delivery amount, the method comprising: The delivery quantity is perturbed by perturbation frequency and perturbation amount; Measure the patient's response to the disturbance; as well as The effects of the disturbance are restored based on the patient's response, and sensitivity is determined.

2. The method according to claim 1, wherein, The delivery quantity and / or the delivery frequency depend on the sensitivity.

3. The method according to claim 1, wherein, The perturbation and the recovery are configured according to signal processing principles.

4. The method according to claim 1, wherein, The perturbation and the recovery are configured according to principles selected from the following: single-tone perturbation; frequency shift keying; code division multiplexing; heterodyne; Wiener filtering; and combinations thereof.

5. The method according to claim 1, wherein, The perturbation frequency is less than the delivery frequency.

6. The method according to claim 1, wherein, The measurement has a measurement frequency that is lower than the delivery frequency.

7. The method according to claim 1, wherein, The perturbation frequency maximizes the signal-to-noise ratio of the sensitivity.

8. The method according to claim 1, wherein, The recovery includes demodulating the patient's response.

9. The method according to claim 1, wherein, The perturbation frequency is variable.

10. The method according to claim 1, wherein, The perturbation frequency is selected such that a correspondence with the sensitivity can be determined.

11. The method according to claim 1, wherein, The amount of disturbance can be varied.

12. The method according to claim 9, wherein, The amount of disturbance can be varied.

13. The method for customized drug delivery according to claim 1, comprising controlling the delivery amount and / or the delivery frequency based on the sensitivity.

14. A system for determining a patient’s sensitivity to a drug, comprising a processor configured for the method of claim 1.

15. The system according to claim 14, wherein, The processor is configured to communicate with a pump and a sensor, wherein the pump is configured to deliver the drug and the sensor is configured to transmit signals corresponding to the patient's physiological parameters.

16. The system of claim 15, further comprising one of the pump and the sensor.

17. The system of claim 16, further comprising another of the pump and the sensor.

18. The system of claim 15, further comprising one of the pump and the sensor.

19. A non-transient computer-readable medium configured for instructions configured for the method of claim 1.

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