DETAILED ACTION
Response to Amendment
The amendment filed March 27, 2026 has been entered. Claim 1 has been amended and claims 1-18 are currently pending in the application.
Response to Arguments
Regarding Applicant’s arguments that the amendments to claim 1 have overcome the rejection under 35 U.S.C. 101, the Examiner agrees. The claim provides sufficient structure so as to amount to more than the judicial exception. Regarding Applicant’s arguments with respect to claim 17, the Examiner respectfully disagrees. As set forth below, Saint 2019 clearly discloses in Para. 43 that the device is clearly programmed to track priming doses and that it is necessary to be able to determine which doses are priming doses and which are therapeutic. Therefore, Saint 2019 provides explicit disclosure of tracking both dose types and providing a determination based upon their classification as either a priming dose or a therapeutic dose. The rejection is considered proper and is maintained below.
Claim Objections
Claim 1 is objected to because of the following informalities: lines 11-12 should be amended to read “…events and the distinguished pen events associated with therapeutic doses as therapeutic pen events and storing them in the memory….” Appropriate correction is required.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1,5-9,11-14,16,18 is/are rejected under 35 U.S.C. 102(a)(1)/(a)(2) as being anticipated by Saint et. al (US 20190035500 A1, hereinafter Saint 2019).
Regarding claim 1, Saint 2019 discloses a method for distinguishing between dispensing of a priming dose and a therapeutic dose of medicament from a medicament injection pen (Para. 44, “In some embodiments, the dose distinguisher module is configured to implement a dose classification method to group data associated with dispensed medicine doses and classify the dispensed doses in the group as either a prime dose or an injected (e.g., therapy) dose”), comprising: using a logging module of the medicament injection pen to identify and record to a memory an occurrence of pen events associated with dispensing of a dose of medicament from a medicament injection pen by a user (Para. 26 “In some implementations, the processor can then store the size of the dose along with a time stamp for that dose. In some implementations, the pen 10 can then transmit the dose and related information to the companion device 5. In such implementations when the dose is transmitted, the data associated with the particular transmitted dose is marked in the memory of the pen 10 as transmitted. In such implementations if the dose was not yet transmitted to the companion device 5, then the data associated with the dose will be transmitted at the next time a successful communication link between the pen 10 and the companion device 5 is established”), each of the pen events specifying a volume of medicament that is dispensed (Para. 103, “The displacement of the piston of the medicament vial 85 forces a volume of the medicament (that is proportional to the displacement of the piston) out of the vial 85, e.g., allowing it to be injected into a patient.”) and a time when the volume of medicament is dispensed; and (Para. 31, “In operation of the disclosed intelligent medicine administering system, for example, when a dosing event (e.g., an amount of fluid is dispensed from the pen device 10), a time stamp associated with the dispensing is referenced is recorded by the processing unit of the pen 10 (e.g., stored in the memory of the pen 10). For example, the time stamp may be the current time or a time where a count-up timer is used…. In some implementations, for example, the time of the dose can be determined without the pen having to know the current time.) using a processor of the medicament injection pen to distinguish between identified pen events associated with priming doses and identified pen events associated with therapeutic doses (Para. 43, “the software application of the companion device 5 can include a dose distinguisher or identification module to process dose dispensing data and determine and distinguish between a prime dose and a therapy dose that was dispensed from the pen device 10”) based at least in part on previous dosing patterns of behavior of the user (Para. 37, “The typical delivery time could be set either explicitly (e.g., set a typical time and window for that delivery time) or experimentally where the average delivery time and typical window are analyzed to determine if a dose differs from the normal pattern”); classifying the distinguished pen events associated with priming doses as priming pen evens and the distinguished pen events associated with therapeutic doses as therapeutic pen events and storing them in memory (Para. 24 discloses the use of a memory); and providing information associated with the priming pen evens and the therapeutic pen events to a user interface (Para. 43, “the software application of the companion device 5 can include a dose distinguisher or identification module to process dose dispensing data and determine and distinguish between a prime dose and a therapy dose that was dispensed from the pen device 10”; see also Para. 30 which discloses a number of display or user interface outputs for displaying the data).
Regarding claim 5, Saint further discloses the claimed invention as cited in claim 1 above. Moreover, Saint 2019 also discloses a method wherein:
the distinguishing includes establishing one or more adjustable thresholds (Para. 65, In some embodiments, the companion device 5 and/or the pen device 10 can provide an alert to warn the user of excessive insulin on board (IOB). For example, if the total IOB exceeds a threshold which is user settable to related to the max dose in some way) of a volume of a dispensed dose (Para. 44, “In some embodiments, the dose distinguisher module is configured to implement a dose classification method to group data associated with dispensed medicine doses and classify the dispensed doses in the group as either a prime dose or an injected (e.g., therapy) dose”) and/or a time between successive dispensed dosages (Para. 37, “The typical delivery time could be set either explicitly (e.g., set a typical time and window for that delivery time) or experimentally where the average delivery time and typical window are analyzed to determine if a dose differs from the normal pattern.”), the adjustable thresholds being used to between a priming pen event and a therapeutic pen event (Para. 48, “The dose distinguisher module of the disclosed systems to determine prime doses from therapeutic doses can include a separate dosing knob on the pen device 10 for prime dosing. The exemplary separate dosing knob can be structured to actuate the dose jackscrew, but not the dose encoder (as described later in this patent document). In these embodiments, for example, when the user rotates the separate dose knob, the medicine is injected but the encoder does not count the dose.”)), the adjustable thresholds being based at least in part on the previous dosing patterns of behavior of the user (Para. 37, “The typical delivery time could be set either explicitly (e.g., set a typical time and window for that delivery time) or experimentally where the average delivery time and typical window are analyzed to determine if a dose differs from the normal pattern.”)
Regarding claim 6, Saint 2019 discloses the claimed invention as cited in claim 5 above. Moreover, Saint 2019 also discloses a method wherein the previous dosing patterns of behavior of the user (Para. 37, “The typical delivery time could be set either explicitly (e.g., set a typical time and window for that delivery time) or experimentally where the average delivery time and typical window are analyzed to determine if a dose differs from the normal pattern.”) indicate that the user regularly dispenses a priming dose before dispensing a therapeutic dose (Para. 43, “Patients may need to dispense a prime or priming dose prior to injecting the therapy or therapeutic dose…. Typically, when a prime dose is delivered, it is followed by a therapy dose”) and, based thereon, increasing the adjustable dispensed volume threshold and/or the adjustable time threshold (Para. 28, In one example, the dose dispensing mechanism can be operated…to inject the dose over a time frame (e.g., 1 s, 5 s or other) to aid in the pain of dosing. In one example, the dose dispensing mechanism can be operated over a much longer period of time, e.g., to better match the dynamics of carbohydrates, which can be like an extended bolus with a pump.”).
Regarding claim 7, Saint 2019 discloses the claimed invention as cited in claim 5 above. Moreover, Saint 2019 also discloses a method wherein the previous dosing patterns of behavior (Para. 37, “The typical delivery time could be set either explicitly (e.g., set a typical time and window for that delivery time) or experimentally where the average delivery time and typical window are analyzed to determine if a dose differs from the normal pattern.”) of the user indicate that there is a consistent amount of time between a priming pen event and a therapeutic pen event (Para. 44, “In some embodiments, the dose distinguisher module is configured to implement a dose classification method to group data associated with dispensed medicine doses and classify the dispensed doses in the group as either a prime dose or an injected (e.g., therapy) dose; such that, for any group of doses happening in close temporal proximity, only the last dose is recorded as a therapeutic dose. The close temporal proximity is a predetermined temporal threshold value, e.g., which can be defined as 10 seconds, 30 seconds, 1 minute, 2 minutes, 5 minutes, or 10 minutes or other.”) and, based thereon, reducing the time threshold (Para. 37).
Regarding claim 8, Saint 2019 discloses the claimed invention as cited in claim 7 above. Moreover, it also discloses a method wherein reducing the time threshold includes reducing the time threshold below a default time threshold and further comprising requesting user confirmation (Para. 44, “In some embodiments, the dose distinguisher module is configured to implement a dose classification method to group data associated with dispensed medicine doses and classify the dispensed doses in the group as either a prime dose or an injected (e.g., therapy) dose; such that, for any group of doses happening in close temporal proximity, only the last dose is recorded as a therapeutic dose. The close temporal proximity is a predetermined temporal threshold value, e.g., which can be defined as 10 seconds, 30 seconds, 1 minute, 2 minutes, 5 minutes, or 10 minutes or other.”) that a pen event is a therapeutic pen event if the pen event is classified as a therapeutic pen event using the default time threshold but as a priming pen event using the reduced time threshold (Para. 46, “In some cases, for example, a user may prime their device and not deliver a therapeutic dose. To prevent the dose distinguisher module from improperly identifying the dose as a therapeutic dose, in such cases, the system can include an additional mechanism that may be utilized to quickly identify the dose as either “prime” or “therapeutic”. In one example of this additional dose identification mechanism, a user verification input can be included in the software application of the companion device 5 to allow the patient to identify that the recorded doses were one of the prime or therapy doses, which would then allow for such doses to be included in any therapy analytics and insulin on board calculation, as appropriate. This user verification input mechanism can include a radio button, a toggle switch, and/or graphic of the user interface allowing tapping on the dose, slider, or other mechanism”)
Regarding claim 11, Saint 2019 discloses the claimed invention of claim 5 as cited above. Moreover, Saint 2019 also discloses a method wherein previous dosing patterns of behavior of the user indicate that a volume of a priming dose is consistent for a specified time of day (Para. 37, “The typical delivery time could be set either explicitly (e.g., set a typical time and window for that delivery time) or experimentally where the average delivery time and typical window are analyzed to determine if a dose differs from the normal pattern.”), and, based thereon, adjusting the adjustable dispensed volume threshold for the specified time of day ((Para. 64 “In some embodiments, for example, the companion device 5 and/or the pen device 10 can warn the user of a missed dose. A missed dose can be identified if a dose has not been given within a certain period of time after a specific time of day or after an average time of bolus. For example, with long acting insulins (e.g., Lantus®) the injections are usually given once a day at a specific time of day. The companion device 5 and/or the pen device 10 could average the time of the injections given on a daily basis and then give a missed dose alarm if no dose is sensed within predetermined or user settable amount of time after that average time, e.g., 2 hours”))
Regarding claim 12, Saint 2019 discloses the claimed invention of claim 1 as cited above. Moreover, Saint 2019 also discloses a method wherein the previous dosing patterns of behavior of the user (Para. 37, “The typical delivery time could be set either explicitly (e.g., set a typical time and window for that delivery time) or experimentally where the average delivery time and typical window are analyzed to determine if a dose differs from the normal pattern.”) indicate that a priming pen event occurs once per day (Para. 43, “Patients may need to dispense a prime or priming dose prior to injecting the therapy or therapeutic dose…. Typically, when a prime dose is delivered, it is followed by a therapy dose”) and, based thereon, assuming that any remaining pen events occurring on a given day are therapeutic pen events (Para. 47, “the dose classification method can be implemented such that when a first dose (or intermediate dose) is larger than a predetermined dose quantity threshold, that dose is considered therapy. For example, any dose determined to be larger than 2, 5, 10 units or other size could be considered therapy regardless of their position in the dose sequence.”).
Regarding claim 13, Saint 2019 discloses the claimed invention of claim 1 as cited above. Moreover, Saint 2019 also discloses a method wherein the previous dosing patterns of behavior (Para. 37, “The typical delivery time could be set either explicitly (e.g., set a typical time and window for that delivery time) or experimentally where the average delivery time and typical window are analyzed to determine if a dose differs from the normal pattern.”) of the user indicate that a priming pen event only occurs once when a disposable medicament injection pen is first used and, based thereon, assuming that any remaining pen events associated with the disposable medicament injection pen are therapeutic pen events (Para. 47 “for example, the dose distinguisher module can be configured to include one or more additional processes or exceptions to the exemplary dose classification method to group and classify the last dose of a group of doses happening in close temporal proximity as a therapeutic dose. In an example, the dose classification method can be implemented such that following a cartridge replacement, if there is only a single dose, it would be designated a prime dose and not a therapy dose.”).
Regarding claim 14, Saint 2019 discloses the claimed invention of claim 1 as cited above. Moreover, Saint 2019 also discloses a method wherein the previous dosing patterns of behavior of the user (Para. 37, “The typical delivery time could be set either explicitly (e.g., set a typical time and window for that delivery time) or experimentally where the average delivery time and typical window are analyzed to determine if a dose differs from the normal pattern.”) indicate that a priming pen event only occurs when a medicament cartridge in the medicament injection pen is replaced with a replacement cartridge (Para. 47, “In an example, the dose classification method can be implemented such that following a cartridge replacement, if there is only a single dose, it would be designated a prime dose and not a therapy dose”); and, based thereon, assuming that any pen events other than a first pen event occurring while using the replacement cartridge are therapeutic pen events (Para. 81, “In some embodiments, for example, the pen device 10 can be configured to sense the replacement of a cartridge by detecting the retraction of the lead screw. For example, when the medicine cartridge is replaced by another medicine cartridge, the lead screw will be retracted which would cause the encoder to spin (and record movement). If the encoder were to indicate travel in an opposing direction (e.g., negative direction or away from dose) and/or of an indicative value of greater than a predetermined threshold number of units (e.g., 1, 5, 10 or other, as in the case of insulin) or other metric with other drug, then this data can be processed by the system (e.g., the data processing unit of the companion device 5 or within the pen 10 itself) to determine that the medicine cartridge has been replaced.”)
Regarding claim 16, Saint 2019 discloses the claimed invention of claim 5 as cited above. Moreover, Saint 2019 also discloses a method further comprising establishing the adjustable thresholds based at least in part on the predicted volume of dispensed doses and the predicted time between dispensed doses (Para. 37, “First, the software application resident on the companion device 5 can include a Total Daily Dose Calculation module, in which a total daily dose is determined to be the average sum of all insulin delivered (e.g., both long and short acting) in a day. This average may be calculated over different periods of time like week, month, quarter, etc. In addition, the software application resident on the companion device 5 can include drug confusion alerts that can be provided to the user via the display unit of the companion device 5. For example, with a drug confusion alert, the companion device 5 can alarm the patient if the patient injects a drug at the wrong time (e.g., because it indicates that there was confusion on which pen device the patient used). Also, for example, if the patient typically injects long-acting insulin in the morning and delivers a dose in the afternoon, a mistake likely occurred. The typical delivery time could be set either explicitly (e.g., set a typical time and window for that delivery time) or experimentally where the average delivery time and typical window are analyzed to determine if a dose differs from the normal pattern. Drug confusion alerts can also be used in the hospital setting where an injection (or planned injection) can be cross checked with the Electronic Medical Record (EMR) or physician order to determine if the dose was correctly delivered, if there is a possible drug interaction, etc.,”)
Regarding claim 18, Saint 2019 discloses the claimed invention of claim 1 as cited above. Moreover, Saint 2019 also discloses a method further comprising adjusting the user therapeutic treatment based at least in part on the monitoring (Para. 35, “In some implementations, when the medicine includes insulin for treatment of diabetes, for example, the dose calculator can be configured for patients with Type 2 diabetes. Several protocols can be used to treat such patients using the disclosed intelligent medicine administering system, including a “sliding scale” feature on the software application of the companion device 5. In an example, a sliding scale dose calculator is provided by the software app and configured to be user settable by the patient user of the companion device 5 and pen device 10 (and/or accessible and settable by a healthcare provider to the patient) to allow the patient to tailor or design the input parameters of the dose calculator to their specific needs and circumstances”).
Claim(s) 17 is/are rejected under 35 U.S.C. 102((a)(1)/(a)(2)) as anticipated by or, in the alternative, under 35 U.S.C. 103 as obvious over Saint et. al (US 20190035500 A1, hereinafter Saint 2019), in further view of Saint et al. (US 20180353698 A1, hereinafter Saint 2018).
Regarding claim 17, Saint 2019 teaches a method of claim 1 that further compromises recording and tracking pen events associated with therapeutic doses to monitor user therapeutic treatment (Para. 95, “FIG. 2B shows an example of a user interface display for an exemplary dose history record, which allows the patient to review their dose dispensing history for a particular medicine. For example, the exemplary dose history user interface can include information about the recent doses logged over a certain period of time, e.g., such as “today”, or over selected days, weeks, or other time frame”)
The Examiner is under the position that Claim 17 is anticipated by Saint 2019. Nonetheless, Saint 2018 teaches a method of claim 1 that further compromises recording and tracking pen events associated with therapeutic doses to monitor user therapeutic treatment (Saint 2018, Para. 83, “the learning dose calculator module 220 can process the analyte, activity and health context, and food data to identify a certain pattern or set of estimated patterns associated with the user at the current time and state; and process the pattern or pattern set with a stored set of dose calculator parameters to select which parameter settings should be used in a current dose calculation”)
It would have been obvious to one having ordinary skill in the art at the time of the effective filing date of the invention to combine the method of Saint 2019 with the further monitoring activities of Saint 2018 as the outcome will allow for a more thorough and personalized treatment plan for the patient (Saint 2018, Para. 58).
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.
Claim(s) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Saint et. al (US 20190035500 A1, hereinafter Saint 2019) and further in view of Saint et al. (US 20180353698 A1, hereinafter Saint 2018).
Regarding claim 2, Saint 2019 discloses the claimed invention as cited in claim 1 above. However, Saint 2019 does not teach: wherein the previous dosing patterns of behavior of the user are identified using a machine learning technique that examines historical user data that include pen events that have been manually classified as a priming pen event or a therapeutic pen event.
Saint 2018 teaches a system and technique in the same field of administering and tracking medicine to patients that discloses a method: wherein the previous dosing patterns of behavior of the user are identified using a machine learning technique that examines historical user data (Saint 2018, Para. 75, “The learning dose calculator module 220 includes a learning module in communication with the results score database and configured to perform machine learning to optimize dose calculation parameters, e.g., stored by the dose calculator parameter set database, and update accordingly.”) that include pen events (Saint 2018, Para. 30 “an intelligent medicine administration system includes a medicine injection device (also referred to as the “pen” or “pen device”)”) that have been manually classified (Saint 2018, Para. 44 “the companion device 5 can also allow the patient to manually enter boluses into the pen device 10 or another medicine delivery device”) as a priming pen event or a therapeutic pen event (Para. 30, “in communication with a patient's companion device (e.g., smartphone), in which the pen device is able to detect and record dose sizes dialed on the pen device and delivered, including the capability of distinguishing between a priming dose and a therapy dose”)
It would have been obvious to one having ordinary skill in the art at the time of the effective filing date of the invention to modify the method of Saint 2019 with the drug administration and behavior tracking method of Saint 2018 because it would benefit the patient by helping optimize their treatment plan (Saint 2018, Para. 33, “The app associated with the system 100 can aggregate and process the contextual data to generate decision support outputs to guide and aid the patient user in using the pen device 10 and/or managing their behavior to promote better health outcomes in treating his/her health condition”).
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Saint et. al (US 20190035500 A1, hereinafter Saint 2019) in view of Saint et al. ( US 20180353698 A1, hereinafter Saint 2018), and further in view of Imanbayev (WO 2020043922 A1).
Regarding claim 3, Saint 2019 in view of Saint 2018 teaches the of Claim 2 above. However, Saint 2019 in view of Saint 2018 does not teach: a machine learning technique selected from the group consisting of a decision tree, logistic regression, Bayesian analysis and a Kalman filter.
In a relevant field of insulin injection and diabetes management, Imanbayev teaches a data quality control system that uses machine learning techniques. (“In some embodiments, the model is a regression model selected from the group consisting of a linear regression model, a nonlinear regression model, a support vector machine, a random forest, a Keras artificial neural network, and a gradient tree boosting model. In some embodiments, the model is a classifier model or an ensemble model. In some embodiments, the type of model is selected from the set of nearest neighbor, naive Bayes, decision trees, linear regression, support vector machines, neural networks, k-means clustering, q-learning, temporal difference, and deep adversarial networks.” Page 34, lines 4-12). It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the method and system of the method taught by Saint 2019 in view of Saint 2018 with the machine learning techniques of Imanbayev to provide patients with greater control of their health and treatment costs (“a data quality system to process patient-gathered data and thus enable automatic titration algorithms and self-titration. This enhances patient empowerment as well as substantially reducing treatment costs by reducing the frequency of required physician consultations for dose adjustments, all without reducing therapeutic outcomes” Imanbayev, Page 16, Lines 20-23).
Claim(s) 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Saint et. al (US 20190035500 A1, hereinafter Saint 2019) in view of Saint et al. ( US 20180353698 A1, hereinafter Saint 2018) and further in view of McMahon (US 20170049383 A1).
Regarding claim 4, the combination of Saint 2019 and Saint 2018 teaches the claimed invention of Claim 2 above, Saint 2019 further teaches a way for the user to manually classify pen events (Saint 2019, Para. 100, “In some implementations, for example, the system may allow both automatic as well as manual logging of doses”).
However, Saint 2019 nor Saint 2018 do not explicitly teach: identifying anomalous pen events that do not fit the previous dosing patterns of behavior of the user and requesting manual user classification of the identified anomalous pen events. McMahon teaches a computer implemented system in the field of diabetes management that can identify anomalous pen events that do not fit the previous dosing patterns of behavior of the user (McMahon, Para. 117, “Insulin related insight events include, without limitation: bolus type; abnormal change of time intervals between boluses; suspend pump operation; significant change in total daily dose (TDD) based on long term data; abrupt change of basal pattern; substantial change of average basal rate; and change of active insulin delaying curve (derived from rate of change in insulin on board”) and request manual user classification of the identified anomalous pen events (McMahon (Para. 305, “The glucose assist system considers a number of glycemic response events that may have some relationship to the patient's glucose response and/or glucose management scheme. A glycemic response event can be conveyed in, identified by, or otherwise associated with input data obtained for the patient. Although the number and type of data inputs can vary from one embodiment to another, the exemplary embodiment considers the following, without limitation: (1) meal time and nutritional content; (2) exercise time, type, and intensity; (3) medication type, dosage, dosage time; (4) sleep time and quality; (5) stress time (based on physiological factors such as heart rate, blood pressure, skin conductance, or user input); (6) time of day and/or day of week (weekday vs weekend); (7) carbohydrate amount; (8) bolus dosage amount (in Units), time of bolus (time and/or calendar data), and bolus type (normal, square, dual); (9) active insulin amount; (10) basal rate of insulin; (11) temporary basal use; (12) consecutive boluses; (13) insulin suspension or infusion pump suspend mode; (14) insulin reservoir rewind and priming time”).
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the methods of Saint 2019 in view of Saint 2018 with the manual user classification of anomalous pen events of McMahon to provide the possibility to properly classify pen event data and provide the patient with accurate, real-time insights. As stated by McMahon, systems that allow for further classification, “can prevent or reduce unnecessary user interaction and input, and supplement predictive analytics of glucose trends based on real time data.” (Para. 7)
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Saint et. al (US 20190035500 A1, hereinafter Saint 2019) and further in view of Saint et al. (US 20180353698 A1, hereinafter Saint 2018).
Regarding claim 10, Saint 2019 discloses the method of claim 5 as cited above. Moreover, Saint 2019 also discloses a method wherein the previous dosing patterns of behavior of the user indicate that a volume of a priming dose is a consistent dose for the user for previous priming pen events (Para. 37, “The typical delivery time could be set either explicitly (e.g., set a typical time and window for that delivery time) or experimentally where the average delivery time and typical window are analyzed to determine if a dose differs from the normal pattern.”)
Saint 2019 does not disclose: and, based thereon, requesting user confirmation that a volume of a dispensed dose is below a default volume threshold but above the consistent dose. More specifically, Saint 2019 does explicitly disclose “a volume of a dispensed dose is below a default volume threshold.”
However, Saint 2018 teaches a method that can request user confirmation that a volume of a dispensed dose is below a default volume threshold but above the consistent dose (Saint 2018, Para. 72-73, “the learning dose calculator module 220 is configured to automatically adjust dose calculator recommendations based on past success for a specific food. For example, if the typical dose recommended for pizza always leaves the patient with higher glucose than desired, the learning dose calculator module 220 can add an offset to future recommendations to better achieve target when calculations consider this type of food. Such offsets can be aggregated (e.g., “crowdsourced”) across many users, helping identify foods that commonly need adjustment. This could be presented as an alert to the patient, or automatically integrated as an offset or scaling factor for the default dose recommendation for that food.”)
It would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to combine the methods of Saint 2019 with the confirmation that the volume of a dispensed dose is below a default volume threshold but above the consistent dose of Saint 2018 since it provides users with data for dose calculations to further optimize their treatments (Saint 2018, Para. 73, “the system can include a database of effective carb content of foods so that the system, via the app using the learning dose calculator module 220, can make better dose recommendations when those foods are eaten”). Additionally, it would have been obvious to one having ordinary skill in the art at the time of the effective filing date of the invention to confirm if a volume of a dispensed dose is below a default volume threshold but above the consistent dose as discovering an optimum value of a result effective variable involves only routine skill in the art. The motivation in doing so would have been to determine if the abnormal event was a result of a priming or therapy dose to increase the overall effectiveness of the data and ensure that it is as correct as possible for future calculations (Saint 2019 Para. 46).
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JUSTIN L ZAMORY whose telephone number is (571)270-1238. The examiner can normally be reached M-F 8:30am-4:30pm ET.
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/JUSTIN L ZAMORY/Examiner, Art Unit 3783
/MICHAEL J TSAI/Supervisory Patent Examiner, Art Unit 3783
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