DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-18 are rejected under 35 U.S.C. 103 as being unpatentable over Estes et al. (US 2009/0069787A1; hereinafter “Estes”) in view of Keenan et al. (US 20150217052A1; hereinafter “Keenan”), Khan et al. (US 20130018284A1; hereinafter “Khan”), Desborough et al. (US 2017/0203039A1; hereinafter “Desborough”) and Yang (US 2019/0307958A1).
In relation to independent claim 1, this claim recites a processor-implemented method comprising obtaining user status sensor data indicative of a sleeping status of a user of an insulin infusion device and controlling operation of the insulin infusion device in accordance with the sleeping status.
A processor-implemented method.
Estes discloses an infusion pump system with a controller and control circuitry, stating that “a wearable infusion pump system may include a disposable and non-reusable pump device having a drive system to dispense insulin” and “a reusable controller device removably attached to the pump device,” where “[t]he controller device can having control circuitry that communicates control signals to the drive system to dispense insulin at a dispensation rate.” (Estes ¶ [0008].) Estes further discloses that “the pump system 10 can store data ... in the computer readable memory and use this data to adjust the medicine dispensation.” (Estes ¶ [0086].) To the extent Estes does not expressly use the phrase processor-implemented, Yang fills the gap by disclosing “at least one processer set in any component of artificial pancreas, configured to determine the physical states of the patient, adjust related algorithms and send corresponding instructions based partly on the signals.” (Yang ¶ [0017].)
Obtaining user status sensor data indicative of a sleeping status of a user of an insulin infusion device.
Estes discloses an activity sensor that can provide user-status data, stating that “the activity sensor 246 can be used to detect and record movement characteristics such as the acceleration of the pump system 10 ... the vibrations of the pump system 10, the inclination of the pump system 10, or a combination thereof.” (Estes ¶ [0062].) Estes further states that “the activity sensor 246 or 446 may indicate to the controller device 200 that the user is lying horizontally as opposed to standing or sitting up” and that the internal clock may indicate “the time is currently within the user's selected sleep range.” (Estes ¶ [0088].) To the extent Estes does not expressly recite a sleep-detection system determining sleep from sensor data, Khan fills the gap by disclosing that “[m]otion identification logic 220 uses the motion data to identify a user falling asleep,” that “[t]he motions of wakefulness are different from the motions of sleep,” and that “[t]he motion identification logic 220 identifies that the user has fallen asleep.” (Khan ¶ [0026].)
Controlling operation of the insulin infusion device in accordance with the sleeping status of the user.
Estes discloses sleep-based pump control, stating that “the pump system 10 can modify the alerts from the user interface 220, the medicine dispensation schedule, or a combination thereof based on a determination that the user is sleeping.” (Estes ¶ [0088].) Estes further states that “the controller device 200 may be configured to decrease the medicine delivery (e.g., decrease basal rate) when the user is sleeping to help avoid nocturnal hypoglycemia.” (Estes ¶ [0088].) Yang confirms automatic closed-loop artificial-pancreas operation based on sleep state by disclosing that “operations comprise but not limited to a delivery suspend according to the low-suspend algorithm or the predictive low-suspend algorithm, a change of operation modes, an adjustment of the insulin delivery amount of a basal rate mode, and switching the CGM system 1 and the patch pump 2 into an audio-off mode for low priority alerts according to the adjusted algorithm when the patient is determined in a state of sleep or physical exercise.” (Yang ¶ [0047].)
Primary-reference gap and secondary-reference disclosure [in summary].
Estes discloses the core sleep-sensor and sleep-based infusion-control concept, but does not expressly disclose all details of a closed-loop target-glucose-setpoint framework. Keenan fills the gap by disclosing that “delivery commands for operating an insulin infusion device are determined based on a difference between a measured blood glucose value from the body of the user and a target blood glucose value by applying proportional-integral-derivative (PID) closed-loop control.” (Keenan ¶ [0022].) Keenan further discloses that “a target glucose setpoint value used by the PID control may also be adjusted ... from its normal (or unadjusted) value to account for changes in the user's insulin response.” (Keenan ¶ [0024].)
Based on the above teachings, a person of ordinary skill in the art would have been motivated to combine Estes's sleep-status pump-control disclosure with Khan's sleep-detection logic and Keenan/Yang's closed-loop artificial-pancreas control because the references address the same problem of safer insulin delivery under user physiological or activity states. Estes expressly states that sleep-based delivery changes help “avoid nocturnal hypoglycemia.” (Estes ¶ [0088].) Yang states that sensing sleep and adjusting algorithms provides “more accurate and reliable blood glucose related data that is the basis of desirable treatment plans.” (Yang ¶ [0023].) The combination would have predictably used known sleep-detection sensor data to control a known insulin infusion system in accordance with sleeping status.
In relation to claim 2, this claim depends from claim 1 and further recites that the user status sensor data comprises sensor data generated by a sleep detection system.
Base rejection incorporated.
The rejection of claim 1 is incorporated.
The user status sensor data comprises sensor data generated by a sleep detection system.
Estes discloses sensor data from the infusion pump's activity sensor, including that “the activity sensor 246 may comprise, for example, a motion sensor (e.g., an accelerometer or the like), a pulse rate sensor, a blood pressure sensor, a body temperature sensor, a perspiration sensor, or the like.” (Estes ¶ [0036].) Estes does not expressly label that arrangement a sleep detection system. Khan fills the gap by disclosing a sleep-monitoring system in which “[m]otion data may be received from an inertial sensor” and “the inertial sensor may be one or more accelerometers, gyroscopes, or a combination of accelerometers and gyroscopes.” (Khan ¶ [0025].) Khan further states that “[m]otion identification logic 220 uses the motion data to identify a user falling asleep.” (Khan ¶ [0026].)
Based on the above teachings, a person of ordinary skill would have been motivated to use Khan's sleep-detection system in Estes because Estes already uses horizontal-position and sleep-range sensor information to alter insulin delivery, and Khan supplies a known accelerometer/gyroscope sleep detector to improve the reliability of identifying sleep.
In relation to claim 3, this claim depends from claim 1 and further recites operating the insulin infusion device according to a first target glucose setpoint value, determining that the user is sleeping from user status sensor data, and in response operating according to a second different target glucose setpoint value.
Base rejection incorporated.
The rejection of claim 1 is incorporated into this rejection.
Operating the insulin infusion device to automatically control delivery of insulin to the user in accordance with a first target glucose setpoint value.
Estes discloses automatic insulin delivery adjustment by an infusion pump, including that “the controller device can having control circuitry that communicates control signals to the drive system to dispense insulin at a dispensation rate.” (Estes ¶ [0008].) Estes does not expressly disclose a first target glucose setpoint value. Keenan fills the gap by disclosing that “delivery commands for operating an insulin infusion device are determined based on a difference between a measured blood glucose value from the body of the user and a target blood glucose value.” (Keenan ¶ [0022].) Keenan further discloses that “the target glucose setpoint value 544 represents a fixed (constant) value that the user can specify.” (Keenan ¶ [0085].)
Determining, based on the user status sensor data, that the user is sleeping.
Estes discloses that “the activity sensor 246 or 446 may indicate to the controller device 200 that the user is lying horizontally as opposed to standing or sitting up,” and that the clock may indicate sleep range. (Estes ¶ [0088].) Khan further discloses that “[t]he motion identification logic 220 identifies that the user has fallen asleep.” (Khan ¶ [0026].)
In response to determining that the user is sleeping, operating the insulin infusion device to automatically control delivery of insulin to the user in accordance with a second target glucose setpoint value that is different from the first target glucose setpoint value.
Estes discloses sleep-responsive operation by stating that “the controller device 200 may be configured to decrease the medicine delivery (e.g., decrease basal rate) when the user is sleeping.” (Estes ¶ [0088].) Estes does not expressly disclose changing from a first target glucose setpoint value to a different second target glucose setpoint value. Keenan fills this gap by disclosing that “a target glucose setpoint value used by the PID control may also be adjusted ... from its normal (or unadjusted) value.” (Keenan ¶ [0024].) Desborough additionally discloses multiple target values, stating that “a plurality of target blood glucose levels may be set for a plurality of diurnal time periods and independently modified for each diurnal time period.” (Desborough ¶ [0048].)
Based on the above comments, a person of ordinary skill would have been motivated to combine Estes's sleep-based insulin control with Keenan's target-setpoint closed-loop control because Estes expressly seeks to avoid nocturnal hypoglycemia during sleep, while Keenan teaches that target setpoints and control parameters can be adjusted for user conditions affecting insulin response.
In relation to claim 4, this claim depends from claim 3 and further recites that the second target glucose setpoint value is lower than the first target glucose setpoint value.
Base rejection incorporated.
The rejection of claim 3 is incorporated into this rejection.
The second target glucose setpoint value is lower than the first target glucose setpoint value.
Estes does not expressly disclose a lower second target glucose setpoint value. Desborough fills the gap by disclosing that a system can determine temporary target glucose levels and that “the temporary target blood glucose levels may be lower than the modified one or more target blood glucose levels if the user preference is to reduce the likelihood that the PWD has a hyperglycemic event.” (Desborough ¶ [0064].) Desborough also discloses that “the one or more temporary target blood glucose levels may be set at a fixed numerical increase or decrease from the one or more modified target blood glucose levels.” (Desborough ¶ [0070].)
Based on the above teachings, a person of ordinary skill would have been motivated to use Desborough's lower target option within the sleep-responsive target framework of claim 3 because Desborough expressly teaches lower target values to reduce hyperglycemic risk, and Keenan teaches that target glucose setpoint values may be adjusted from normal values in closed-loop insulin delivery.
In relation to claim 5, this claim depends from claim 3 and further recites receiving additional user status data indicating sleeping status, determining that the user is awake, and in response returning to the first target glucose setpoint value.
Base rejection incorporated.
The rejection of claim 3 is incorporated into this rejection.
Receiving additional user status data that indicates the sleeping status of the user.
Estes discloses continuing use of activity sensor data and clock information to determine sleeping status, stating that “the activity sensor 246 or 446 may indicate to the controller device 200 that the user is lying horizontally” and that the clock may indicate the sleep range. (Estes ¶ [0088].) Khan discloses additional motion-data-based sleep status by stating that “the motion data is also sent to motion data store 225.” (Khan ¶ [0026].)
Determining from the additional user status data that the user is awake.
Estes discloses awake/upright status by stating that alerts may be delayed “until a later time after the user awake and upright.” (Estes ¶ [0088].) Khan fills any gap by disclosing that “since the system can detect when the user is awake, the alarm sounds until the user is awake.” (Khan ¶ [0045].)
In response to determining that the user is awake, operating according to the first target glucose setpoint value.
Keenan discloses that the control system may use a fixed normal target setpoint, stating that “the target glucose setpoint value 544 represents a fixed (constant) value that the user can specify.” (Keenan ¶ [0085].) Keenan further discloses that adjusted/final target glucose values can return to the target setpoint: “[a]s time progresses, the final target glucose value 546 gradually decreases back to the target glucose setpoint value 544.” (Keenan ¶ [0086].) Applying this return-to-normal-target teaching when awake is detected would have been an ordinary implementation of reverting from sleep-responsive operation to ordinary operation.
Based on the above teachings, a person of ordinary skill would have been motivated to return to the first target setpoint when awake because Estes distinguishes sleep from awake/upright states for pump operation, and Keenan teaches a normal user-specified target setpoint used by closed-loop control.
In relation to claim 6, this claim depends from claim 3 and further recites that user status sensor data includes a metric indicating sleep-related characteristics, that the characteristics include sleep quality, sleep duration, or both, and that the second target glucose setpoint is adjusted as a function of the metric.
Base rejection incorporated.
The rejection of claim 3 is incorporated into this rejection.
The user status sensor data includes a metric indicating sleep-related characteristics of the user, including sleep quality, sleep duration, or both.
Estes discloses sleep-duration-related information by stating that the controller may “signal an alert based on the amount of time a user has lying in the horizontal position.” (Estes ¶ [0088].) Khan fills the sleep-quality and sleep-duration metric gap by disclosing that “the measured details of the sleep session may include one or more of: time to fall asleep, sleep cycles, amount of light sleep and deep sleep, number and duration of awake events throughout the night, snoring, sleep talking and other noises monitored by the system.” (Khan ¶ [0039].) Khan also discloses that “the sleep statistics 255 may correlate other factors with the quality of sleep of the user.” (Khan ¶ [0048].)
Adjusting the second target glucose setpoint value as a function of the metric.
Estes does not expressly disclose adjusting a glucose setpoint as a function of a sleep-quality or sleep-duration metric. Keenan fills part of the gap by teaching condition-metric-based adjustment: “In response to detecting and identifying exercise, one or more of the PID gain coefficients are automatically decreased,” and “the amount of the decrease may be based at least in part on the duration and/or the intensity of the exercise.” (Keenan ¶ [0023].) Keenan further teaches target-setpoint adjustment, stating that “a target glucose setpoint value used by the PID control may also be adjusted ... from its normal (or unadjusted) value.” (Keenan ¶ [0024].) Desborough similarly teaches modifying target values based on calculated risk/variability: “the one or more target blood glucose levels may be modified based on a determination of a probability of the PWD having a blood glucose level below a threshold blood glucose level based on the variability of received blood glucose data over multiple days.” (Desborough ¶ [0074].)
Based on the above teachings, a person of ordinary skill would have been motivated to adjust a sleep-responsive target based on sleep metrics because Khan teaches measured sleep-session details and sleep quality, while Keenan and Desborough teach adjusting glucose control parameters and target values based on user condition metrics to improve closed-loop insulin control.
In relation to claim 7, this claim depends from claim 6 and further recites that the function of the metric is associated with a manner in which a non-diabetic person regulates glucose.
Base rejection incorporated.
The rejection of claim 6 is incorporated into this rejection.
The function of the metric is associated with a manner in which a non-diabetic person regulates glucose.
Estes and Khan do not expressly disclose this non-diabetic regulatory association. Yang fills the physiologic-regulation gap by disclosing that “[f]or a normal healthy person, the pancreas produces and releases insulin into the blood stream in response to elevated blood glucose levels” and that if beta cells are incapacitated or insufficient, “then insulin must be provided to the body of the patient from another source.” (Yang ¶ [0002].) Keenan further teaches that closed-loop control seeks physiologic glucose regulation, stating that the PID-IFB control module calculates insulin infusion “in order to achieve euglycemia.” (Keenan ¶ [0088].)
Based on the above teachings, a person of ordinary skill would have been motivated to associate the sleep-metric function with normal glucose regulation because artificial pancreas systems are designed to substitute externally delivered insulin for pancreatic insulin regulation, and Yang expressly frames the artificial pancreas problem as replacing the normal pancreas response.
In relation to claim 8, this claim depends from claim 6 and further recites monitoring sleep duration and, responsive to the sleep duration exceeding a predetermined threshold time period, transitioning from the first target glucose setpoint value to the second target glucose setpoint without user input.
Base rejection incorporated.
The rejection of claim 6 is incorporated into this rejection.
Monitoring the sleep duration of the user.
Estes discloses duration monitoring by stating that the controller can “signal an alert based on the amount of time a user has lying in the horizontal position.” (Estes ¶ [0088].) Khan further discloses sleep-duration measurements, stating that sleep-session details may include “time to fall asleep, sleep cycles, amount of light sleep and deep sleep, number and duration of awake events throughout the night.” (Khan ¶ [0039].)
Responsive to the sleep duration exceeding a predetermined threshold time period, transitioning from the first target glucose setpoint value to the second target glucose setpoint without user input.
Estes discloses threshold sleep-duration logic, stating that the controller may signal an alert when the user has been horizontal “for more than 8 hours, for more than 9 hours, or for more than 10 hours.” (Estes ¶ [0088].) Keenan fills the target-transition gap by disclosing that the final target glucose value enables a “smoother transition” and that “as time progresses, the final target glucose value 546 gradually decreases back to the target glucose setpoint value 544.” (Keenan ¶ [0086].) Yang discloses automatic operation without requiring user input by stating that the processor determines whether an operation is needed and “sends an instruction to the processer 202 of the patch pump 2 to perform the corresponding operation automatically.” (Yang ¶ [0030].)
Based on the above teachings, a person of ordinary skill would have been motivated to make sleep-duration-threshold transitions automatic because Estes already monitors prolonged horizontal sleep duration and Yang teaches automatic artificial-pancreas operations based on sensed patient state.
In relation to claim 9, this claim depends from claim 3 and further recites transitioning gradually over a predetermined period of time from the first target glucose setpoint value to the second target glucose setpoint value.
Base rejection incorporated.
The rejection of claim 3 is incorporated into this rejection.
Transitioning, gradually over a predetermined period of time, from the first target glucose setpoint value to the second target glucose setpoint value.
Estes does not expressly disclose gradual glucose-setpoint transition. Keenan fills the gap by disclosing that a final target glucose value “enables the system to make a smoother transition between open-loop and closed-loop modes (by gradually adjusting the final target glucose value 546).” (Keenan ¶ [0086].) Keenan further states that “the target glucose setpoint value 544 is set to 120 mg/dL” and that the transition “usually” occurs “in approximately two hours.” (Keenan ¶ [0086]; Keenan ¶ [0086].)
Based on the above teachings, a person of ordinary skill would have been motivated to implement a gradual transition to avoid abrupt insulin-delivery changes because Keenan expressly teaches smoother target transitions in closed-loop insulin control.
In relation to independent claim 10, this claim recites an insulin infusion device comprising one or more transceivers, one or more memories, and one or more processors configured to obtain sleep-status sensor data and control operation according to sleeping status.
An insulin infusion device for controlling delivery of insulin to a user.
Estes discloses that “a wearable infusion pump system may include a disposable and non-reusable pump device having a drive system to dispense insulin.” (Estes ¶ [0008].) Yang similarly discloses “a patch pump and a continuous glucose monitoring (CGM) system.” (Yang ¶ [0015].)
One or more transceivers.
Estes does not expressly identify transceivers. Yang fills the gap by disclosing that the CGM system, patch pump, and handset communicate, stating that the components are “equipped with a processor, which communicates with each other via a processor set in a portable handset 3 configured to receive signals, process and display data, and send instructions.” (Yang ¶ [0027].) Yang also discloses a “transmitting module 1021” that sends signals to a processor in the handset. (Yang ¶ [0048].)
One or more memories.
Estes discloses memory by stating that “the pump system 10 can store data ... in the computer readable memory and use this data to adjust the medicine dispensation.” (Estes ¶ [0086].)
One or more processors communicatively coupled with the transceivers and memories.
Yang discloses processors in artificial-pancreas components, stating that “at least one processer is set in the patch pump, the CGM system or the handset, configured to determine the physical states of the patient, adjust related algorithms and send corresponding instructions based partly on the signals.” (Yang ¶ [0020].)
Obtain user status sensor data indicative of a sleeping status of the user; and control operation of the insulin infusion device in accordance with the sleeping status.
Estes discloses that “the activity sensor 246 or 446 may indicate to the controller device 200 that the user is lying horizontally,” and that “the pump system 10 can modify the alerts ... the medicine dispensation schedule, or a combination thereof based on a determination that the user is sleeping.” (Estes ¶ [0088].) Yang discloses that “the attitudes of the patient, whether she or he is standing, sitting, lying, or changing from one of these attitudes to another, can be sensed by the three-axis accelerometer 101” and that “when the patient goes to sleep, the state can be determined.” (Yang ¶ [0038].)
Based on the above teachings, a person of ordinary skill would have been motivated to implement Estes's sleep-responsive insulin-pump method in the processor/transceiver/memory architecture of Yang because Yang describes the ordinary communication architecture for an artificial pancreas and expressly uses sensed sleep state to adjust algorithms and pump operation.
In relation to claim 11, this claim depends from claim 10 and further recites that the user status sensor data comprises sensor data generated by a sleep detection system.
Base rejection incorporated.
The rejection of claim 10 is incorporated into this rejection.
Sensor data generated by a sleep detection system.
Khan discloses sleep-system sensor data, stating that “[m]otion data may be received from an inertial sensor” and that the inertial sensor may include “one or more accelerometers, gyroscopes, or a combination of accelerometers and gyroscopes.” (Khan ¶ [0025].) Khan further discloses that “[m]otion identification logic 220 uses the motion data to identify a user falling asleep.” (Khan ¶ [0026].)
Based on the above teachings, a person of ordinary skill would have used Khan's sleep detection sensor data in the device of claim 10 to improve the sleep-status determination that Estes and Yang already use to control insulin delivery and alerts.
In relation to claim 12, this claim depends from claim 10 and recites device-processor configuration corresponding to claim 3.
Base rejection incorporated.
The rejection of claim 10 is incorporated into this rejection.
Operate according to a first target glucose setpoint value.
Keenan discloses that “delivery commands for operating an insulin infusion device are determined based on a difference between a measured blood glucose value ... and a target blood glucose value.” (Keenan ¶ [0022].) Keenan also discloses a “target glucose setpoint value 544” that “represents a fixed (constant) value that the user can specify.” (Keenan ¶ [0085].)
Determine that the user is sleeping based on user status sensor data.
Estes discloses that the activity sensor may indicate the user is lying horizontally and the clock may indicate a sleep range. (Estes ¶ [0088].) Khan discloses that “[t]he motion identification logic 220 identifies that the user has fallen asleep.” (Khan ¶ [0026].)
In response, operate according to a second different target glucose setpoint value.
Keenan discloses adjustment of a target glucose setpoint value “from its normal (or unadjusted) value.” (Keenan ¶ [0024].) Desborough discloses that “a plurality of target blood glucose levels may be set for a plurality of diurnal time periods and independently modified for each diurnal time period.” (Desborough ¶ [0048].)
Based on the above teachings, a person of ordinary skill would have combined the target-setpoint teachings of Keenan and Desborough with the sleep-state device architecture of Estes/Yang to provide sleep-responsive closed-loop insulin control.
In relation to claim 13, this claim depends from claim 12 and recites that the second target glucose setpoint value is lower than the first target glucose setpoint value.
Base rejection incorporated.
The rejection of claim 12 is incorporated into this rejection.
Lower second target glucose setpoint value.
Desborough discloses lower target values, stating that “the temporary target blood glucose levels may be lower than the modified one or more target blood glucose levels if the user preference is to reduce the likelihood that the PWD has a hyperglycemic event.” (Desborough ¶ [0064].) Desborough also states that temporary targets may be set by a “fixed numerical increase or decrease.” (Desborough ¶ [0070].)
Based on the above teachings, a person of ordinary skill would have used Desborough's lower target-value option in the sleep-responsive closed-loop device for the same reason discussed for claim 4: Desborough teaches lower targets to reduce hyperglycemic risk, and Keenan teaches target-setpoint adjustment in insulin control.
In relation to claim 14, this depends from claim 12 and recites device-processor configuration corresponding to claim 5.
Base rejection incorporated.
The rejection of claim 12 is incorporated into this rejection.
Receive additional user status data, determine awake, and operate according to the first target glucose setpoint value.
Estes discloses ongoing sleep/awake-related user status by stating that alerts may be delayed “until a later time after the user awake and upright.” (Estes ¶ [0088].) Khan expressly discloses awake detection: “since the system can detect when the user is awake, the alarm sounds until the user is awake.” (Khan ¶ [0045].) Keenan discloses the first/normal setpoint as “a fixed (constant) value that the user can specify.” (Keenan ¶ [0085].)
Based on the above teachings, a person of ordinary skill would have returned the device to normal target operation when awake is detected because Estes differentiates sleep from awake/upright states, and Keenan supplies a normal target glucose setpoint for closed-loop operation.
In relation to claim 15, Claim 15 depends from claim 12 and recites device-processor configuration corresponding to claim 6.
Base rejection incorporated.
The rejection of claim 12 is incorporated into this rejection.
Sleep metric including sleep quality, sleep duration, or both.
Khan discloses that measured sleep-session details may include “time to fall asleep, sleep cycles, amount of light sleep and deep sleep, number and duration of awake events throughout the night.” (Khan ¶ [0039].) Khan further states that “the sleep statistics 255 may correlate other factors with the quality of sleep of the user.” (Khan ¶ [0048].)
Adjust second target glucose setpoint as a function of the metric.
Keenan discloses target glucose setpoint adjustment, stating that “a target glucose setpoint value used by the PID control may also be adjusted ... from its normal (or unadjusted) value.” (Keenan ¶ [0024].) Desborough discloses target modification based on variability and probability, stating that target glucose levels may be modified “based on a determination of a probability of the PWD having a blood glucose level below a threshold blood glucose level based on the variability of received blood glucose data over multiple days.” (Desborough ¶ [0074].)
Based on the above teachings, a person of ordinary skill would have combined Khan sleep metrics with Keenan/Desborough target adjustment because measured sleep quality/duration provides patient-state information analogous to the condition metrics used by Keenan and Desborough to adjust insulin-control parameters.
In relation to claim 16, this depends from claim 15 and recites device-processor configuration corresponding to claim 7.
Base rejection incorporated.
The rejection of claim 15 is incorporated into this rejection.
Function associated with a manner in which a non-diabetic person regulates glucose.
Yang discloses normal non-diabetic glucose regulation by stating that “[f]or a normal healthy person, the pancreas produces and releases insulin into the blood stream in response to elevated blood glucose levels.” (Yang ¶ [0002].) Keenan discloses that the insulin infusion controller calculates an insulin infusion rate “in order to achieve euglycemia.” (Keenan ¶ [0088].)
Based on the above teachings, a person of ordinary skill would have associated the sleep-metric function with normal glucose regulation because artificial pancreas systems use insulin delivery to emulate normal pancreatic regulation, as expressly described by Yang.
In relation to claim 17, this depends from claim 15 and recites device-processor configuration corresponding to claim 8.
Base rejection incorporated.
The rejection of claim 15 is incorporated into this rejection.
Monitor sleep duration and transition when duration exceeds a predetermined threshold without user input.
Estes discloses threshold duration monitoring by stating that an alert may be signaled based on horizontal duration, including “when the user has been in a horizontal orientation for more than 8 hours, for more than 9 hours, or for more than 10 hours.” (Estes ¶ [0088].) Khan discloses sleep duration details including “time to fall asleep” and “sleep cycles.” (Khan ¶ [0039].) Keenan discloses gradual target transition, stating that the system makes “a smoother transition” by “gradually adjusting the final target glucose value 546.” (Keenan ¶ [0086].) Yang discloses automatic pump operation, stating that the processor sends instructions for the patch pump “to perform the corresponding operation automatically.” (Yang ¶ [0030].)
Based on the above teachings, a person of ordinary skill would have implemented automatic sleep-duration-threshold transition because Estes already monitors prolonged sleep/horizontal status and Yang teaches automatic operation of artificial-pancreas components based on sensed patient state.
In relation to claim 18, this claim depends from claim 12 and recites device-processor configuration corresponding to claim 9.
Base rejection incorporated.
The rejection of claim 12 is incorporated into this rejection.
Gradual transition over a predetermined period of time.
Keenan discloses that the final target glucose value enables “a smoother transition” by “gradually adjusting the final target glucose value 546.” (Keenan ¶ [0086].) Keenan further discloses a period, stating that “[a]s time progresses, the final target glucose value 546 gradually decreases back to the target glucose setpoint value 544 (usually in approximately two hours).” (Keenan ¶ [0086].)
Based on the above teachings, a person of ordinary skill would have used Keenan's gradual two-hour transition in the device of claim 12 to avoid abrupt changes in insulin-control targets.
In relation independent claim 19, this claim recites a method comprising operating an insulin infusion device according to a first target glucose setpoint value, obtaining sleep-detection-system sensor data indicative of sleeping status, and controlling operation in accordance with sleeping status.
Operating the insulin infusion device to automatically control delivery of insulin to the user in accordance with a first target glucose setpoint value.
Keenan discloses automatic target-based insulin control, stating that “delivery commands for operating an insulin infusion device are determined based on a difference between a measured blood glucose value from the body of the user and a target blood glucose value.” (Keenan ¶ [0022].) Keenan further discloses that “the target glucose setpoint value 544 represents a fixed (constant) value that the user can specify.” (Keenan ¶ [0085].)
Obtaining user status sensor data indicative of a sleeping status of the user, wherein the user status sensor data comprises sensor data generated by a sleep detection system.
Estes discloses activity-sensor data indicating sleep, stating that “the activity sensor 246 or 446 may indicate to the controller device 200 that the user is lying horizontally.” (Estes ¶ [0088].) Khan discloses the sleep detection system, stating that “[m]otion data may be received from an inertial sensor” and “[m]otion identification logic 220 uses the motion data to identify a user falling asleep.” (Khan ¶ [0025]; Khan ¶ [0026].)
Controlling operation of the insulin infusion device in accordance with the sleeping status of the user.
Estes discloses that the pump can modify “the medicine dispensation schedule” based on sleep and can “decrease the medicine delivery (e.g., decrease basal rate) when the user is sleeping.” (Estes ¶ [0088].) Yang discloses automatic operation changes when sleep is detected, including “a change of operation modes” and “an adjustment of the insulin delivery amount of a basal rate mode.” (Yang ¶ [0047].)
Based on the above teachings, a person of ordinary skill would have combined Keenan's first-target closed-loop insulin control with Estes/Khan sleep detection and Yang artificial-pancreas operation control to improve overnight safety and automate insulin delivery based on sleeping status.
In relation to claim 20, this depends from claim 19 and further recites determining that the user is sleeping from the sensor data and, in response, operating according to a second target glucose setpoint value different from the first.
Base rejection incorporated.
The rejection of claim 19 is incorporated into this rejection.
Determining, based on the user status sensor data, that the user is sleeping.
Khan discloses that “[m]otion identification logic 220 uses the motion data to identify a user falling asleep” and that “[t]he motion identification logic 220 identifies that the user has fallen asleep.” (Khan ¶ [0026].) Yang similarly discloses that “when the patient goes to sleep, the state can be determined” from three-axis accelerometer data. (Yang ¶ [0038].)
In response to determining that the user is sleeping, operating according to a second target glucose setpoint value different from the first target glucose setpoint value.
Estes discloses sleep-responsive insulin operation by stating that the controller can “decrease the medicine delivery (e.g., decrease basal rate) when the user is sleeping.” (Estes ¶ [0088].) Keenan fills the different-target-setpoint gap by disclosing that “a target glucose setpoint value used by the PID control may also be adjusted ... from its normal (or unadjusted) value.” (Keenan ¶ [0024].) Desborough further discloses different target values by stating that a plurality of target glucose levels may be set for “a plurality of diurnal time periods” and “independently modified for each diurnal time period.” (Desborough ¶ [0048].)
Based on the above teachings, a person of ordinary skill would have used a different target glucose setpoint in response to sleep because Estes and Yang teach sleep-state-specific artificial-pancreas operation, while Keenan and Desborough teach that glucose targets/setpoints may be adjusted for patient state and time period.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claim 19 is rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of U.S. Patent No. 11,992,656. Although the claims at issue are not identical, they are not patentably distinct from each other because claim 1 of the cited patent discloses:
[a] method of operating an insulin infusion device comprising a fluid pump mechanism and at least one controller that regulates operation of the fluid pump mechanism to deliver insulin from the insulin infusion device, the method comprising:
operating the insulin infusion device in an automatic mode to automatically control delivery of insulin to a user, in accordance with a first target glucose setpoint value;
receiving user status data that indicates sleeping status of the user, the user status data being sensor data generated by a sleep detection system;
determining, from the user status data, that the user is sleeping while the insulin infusion device is operating in the automatic mode; in response to the determining,
transitioning from the first target glucose setpoint value to a second target glucose setpoint value for use during the automatic mode, the transitioning occurring without user input, and the second target glucose setpoint value being different from the first target glucose setpoint value; and
continuing to operate the insulin infusion device in the automatic mode to automatically control delivery of insulin to the user, in accordance with the second target glucose setpoint value.
As indicated above, all the limitations of claim 19 of this application are disclosed by claim 1 of the cited patent. Therefore, although the claims at issue are not identical, they are not patentably distinct from each other.
Conclusion
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Respectfully submitted,
/MANUEL A MENDEZ/ Primary Examiner, Art Unit 3783
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