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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12/23/2025 has been entered.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
Claim 31: Claim limitation “glycemic risk assessor configured to assess”; “insulin relationship quantifier configured to quantify”; and “an insulin recommender configured to determine”; and has been interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112 sixth paragraph, because it uses a generic placeholder “glycemic risk assessor/ insulin relationship quantifier / insulin recommender” coupled with functional language “configured to” without reciting sufficient structure to achieve the function.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
A review of the specification shows that the following appears to be the corresponding structure described in the specification for the 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph limitation:
Claim 31: “glycemic risk assessor configured to assess”, “insulin relationship quantifier”, and “an insulin recommender configured to determine” refers to the Specification as filed, (Paragraph [0056] processor 130 receives data from the insulin device 110 and the glucose monitor 120, as well as from the patient 140 in some implementations, and may be configured and/or used to perform one or more of the calculations, operations, and/or functions described further herein). Though the specification does not explicitly disclose the corresponding structure, one of ordinary skill in the art would have recognized that a device that processes signals must be implemented by circuitry or a processor with a corresponding algorithm.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 103
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, 3-6, 8, 16, 18-21, 23, 31, 33-36, and 38 are rejected under 35 U.S.C. 103 as being unpatentable over Desborough (U.S. 20170203039) (cited by Applicant) in view of Blomquist (U.S. 20080294294) (previously cited) and Agrawal (US 20130338629).
Regarding claim 1, Desborough teaches a method comprising: assessing a glycemic risk based on glucose data of a patient citation (Abstract, a method includes receiving up-to-date blood glucose data for a PWD), wherein the glucose data comprises continuous glucose monitoring (CGM) data or flash glucose monitoring (FGM) data received for the patient over a time period, (Paragraph [0091]), wherein the glycemic risk comprises at least one of a hyperglycemic risk and a hypoglycemic risk (Paragraphs [0096], [0125]);
quantifying daily insulin relationships based on insulin data (Paragraph [0093] user-specific dosage parameters can be dosage parameters that are commonly used in the treatment of diabetes, such as average total daily insulin, total daily basal (TDB) insulin), wherein the insulin data comprises basal insulin data and bolus insulin data, (Paragraph [0113] determine rates of basal insulin delivery and optionally amounts of bolus insulin delivery), wherein the basal insulin data and the bolus insulin data are received for the patient over the time period (Paragraph [0114] e.g., over multiple diurnal time segments)
wherein quantifying the daily insulin relationships based on the insulin data comprises calculating each aspect of daily insulin in a plurality of aspects of daily insulin for each day over the time period (Paragraph [0152]), and comparing the calculated aspects over the time period (Paragraph [0153] in some cases, methods and systems provided herein can make adjustments for BBR, ISF, and/or CR for multiple diurnal periods based on variations in the insulin amounts actually delivered for that diurnal period compared to the baseline basal insulin rate for that diurnal period; see also Paragraph [0181]),
wherein the aspects of daily insulin in the plurality of aspects of daily insulin comprise at least one of the total daily insulin, total daily basal, or total daily bolus; (Paragraphs [0152] For example, FIG. 2 includes the block 281 for detecting time periods when an amount of delivered basal insulin is different from a baseline basal rate (BBR), which can then be used to adjust user-specific dosage parameters at block 262. These updated user-specific dosage parameters can then be used to generate new basal delivery profiles at block 263 and used at block 264 to evaluate different basal delivery profiles. For example, for a BBR of 1.46 U/hour (associated with a TDB of 35 U/day), if a diurnal period under consideration is one hour and for the first forty-five minutes, insulin was delivered at a rate of 2.92 U/hour and only the last fifteen minutes was delivered at a rate of 1.46 U/hour, user-specific dosage parameters for a related diurnal time period (e.g., that same hour on another day in the future, or a preceding diurnal time period on a day in the future) may be adjusted); and
determining a recommendation for one or more of the aspects of daily insulin of a patient based on a target range of the glycemic risk and the daily insulin relationships quantification (Paragraph [0125] the range of possible values of the BBR for a given profile can be adjusted or modified depending on the fear of hypoglycemia index (FHI)), wherein the recommendation comprises a change in at least one of basal insulin, bolus insulin, and the total daily insulin, (Paragraph [0125] For example, in some cases, if the FHI is “prefer low” (e.g., indicating a preference for the system to aggressively keep the person with diabetes within range and not go high), the target blood glucose might be set around 100 mg/dl and the range for delivery may include 0%, 50%, 100%, 200%, and 300% BBR. As another example, if the FHI is “prefer high” (e.g., indicating that the person with diabetes prefers to avoid hypoglycemic events even with a higher risk of hyperglycemic events), the target blood glucose might be set around 140 mg/dl and the range for delivery may include 0%, 100%, and 200% of BBR.)
wherein quantifying the daily insulin relationships based on insulin data further comprises calculating at least one of a ratio and a percentage of one of the plurality of aspects of daily insulin relative to another of the plurality of aspects of the daily insulin; (Paragraph [0153] Using the example from above, for a BBR of 1.46 U/hour, if a diurnal period under consideration is one hour and for the first forty-five minutes (e.g., three iterations of profile generation and delivery actions), insulin was delivered at a rate of 2.92 U/hour and only the last fifteen minutes (e.g., one iteration of profile generation and delivery action) was delivered at a rate of 1.46 U/hour, the total amount delivered would be at 175% of the BBR for the one hour diurnal period, or an average ratio of 1.75 the BBR.)
and outputting the recommendation to a diabetes management system (10) (Paragraph [0109] a suggested dosage for a bolus to be administered using the bolus administering device 80 can be output to a user via the user interface), wherein the diabetes management system adjusts insulin delivery based on the recommendation. (Paragraphs [0152]-[0153] In some cases, methods and systems provided herein can make adjustments for BBR, ISF, and/or CR for multiple diurnal periods based on variations in the insulin amounts actually delivered for that diurnal period compared to the baseline basal insulin rate for that diurnal period; Paragraph [0154] An adjustment to the CR, ISF, and BBR can be any suitable amount. In some cases, the adjustment to the BBR is less than the difference between the delivered basal insulin and the previously programmed BBR. In some cases, a change to each user-specific dosage parameter (e.g., BBR, ISF, and CR) is at a predetermined percentage or value. For example, in some cases, each of BBR and ISF can be increased by 5%, 3%, or 1% and CR decreased by the same percent for every period where the amount of delivered basal insulin exceeds the BBR by at least 25%. In some cases, BBR and ISF can be decreased by 5%, 3%, or 1% and CR increased by the same percent for every period where the amount of delivered basal insulin exceeds the BBR by at least 25%. By setting each adjustment at a low level, methods and systems provided herein can eventually be personalized for the PWD without over adjusting the system based on an unusual day (e.g., to mitigate the risk of short-term disturbances being mistaken for changes in physiological parameters). In some cases, the adjustment to CR, ISF, and BBR may be based on a relationship between CR, ISF, and BBR, rather than a fixed amount or percentage.).
However, Desborough does not specifically teach “wherein the aspects of daily insulin in the plurality of aspects of daily insulin comprise at least two of the total daily insulin, total daily basal, or total daily bolus” and “removing outlier data from at least one of the glucose data and the insulin data prior to at least one of assessing the glycemic risk and quantifying the daily insulin relationships.”
Blomquist, in a related field of endeavor, wherein the aspects of daily insulin in the plurality of aspects of daily insulin comprise at least two of the total daily insulin, total daily basal, or total daily bolus. (Paragraph [0022] total daily dose TDD of insulin; 50% of the TDD is used for basal delivery, i.e., total basal delivery).
As a result, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Desborough to provide “wherein the aspects of daily insulin in the plurality of aspects of daily insulin comprise at least two of the total daily insulin, total daily basal, or total daily bolus” as taught by Blomquist. Doing so enables better tracking of changes of insulin rates in demand and provides assistance in determining one or more basal rates for the patient. (Paragraph [0023]).
Agrawal, in a related field of endeavor, teaches an insulin device configured for removing outlier data from at least one of the glucose data and the insulin data prior to at least one of assessing the glycemic risk and quantifying the daily insulin relationships. (Paragraphs [0198] filtering at task 904 can remove an appropriate "window" of the SG data surrounding the bolus event; Paragraphs [0199]-[0200]
The SG data may also be filtered to remove data that may be indicative of an unregistered meal, a sensor artifact, a data transmission error, or the like. For example, the SG data may be filtered to remove data that indicates a SG rate of change that exceeds a threshold value (e.g., 2.0 mg/dL/min).
The process 900 continues by analyzing at least some of the remaining SG data for the presence of any of a plurality of event occurrences (task 906). Task 906 may leverage empirical data, the results of clinical studies, and/or historical data to detect certain detectable patterns, trends, or characteristics of the SG data. In practice, therefore, the decision support software can be written such that task 906 compares the SG data against any number of predefined conditions, which in turn correspond to a suboptimal, suspicious, or potentially troublesome basal pattern.).
As a result, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Desborough to be configured for “removing outlier data from at least one of the glucose data and the insulin data prior to at least one of assessing the glycemic risk and quantifying the daily insulin relationships” as taught by Agrawal. Doing so improves accuracy of the measurements.
Regarding claim 16, Desborough teaches a system comprising: at least one processor (Paragraph [0063]); and a non-transitory computer readable medium (Paragraph [0063]) comprising instructions that, when executed by the at least one processor, cause the system to: assess a glycemic risk based on glucose data of a patient, (Paragraph [0063]), wherein the glucose data comprises continuous glucose monitoring (CGM) data or flash glucose monitoring (FGM) data received for the patient over a time period, (Paragraph [0091]), wherein the glycemic risk comprises at least one of a hyperglycemic risk and a hypoglycemic risk (Paragraphs [0096], [0125]);
quantify daily insulin relationships based on insulin data (Paragraph [0093] user-specific dosage parameters can be dosage parameters that are commonly used in the treatment of diabetes, such as average total daily insulin, total daily basal (TDB) insulin), wherein the insulin data comprises basal insulin data and bolus insulin data, (Paragraph [0113] determine rates of basal insulin delivery and optionally amounts of bolus insulin delivery), wherein the basal insulin data and the bolus insulin data are received for the patient over the time period (Paragraph [0114] e.g., over multiple diurnal time segments) wherein quantifying the daily insulin relationships based on the insulin data comprises calculating each aspect of daily insulin in a plurality of aspects of daily insulin for each day over the time period and comparing the calculated aspects over the time period wherein the aspects of daily insulin comprise at least one of total daily insulin, total daily basal, or total daily bolus; (Paragraphs [0152] For example, FIG. 2 includes the block 281 for detecting time periods when an amount of delivered basal insulin is different from a baseline basal rate (BBR), which can then be used to adjust user-specific dosage parameters at block 262. These updated user-specific dosage parameters can then be used to generate new basal delivery profiles at block 263 and used at block 264 to evaluate different basal delivery profiles. For example, for a BBR of 1.46 U/hour (associated with a TDB of 35 U/day), if a diurnal period under consideration is one hour and for the first forty-five minutes, insulin was delivered at a rate of 2.92 U/hour and only the last fifteen minutes was delivered at a rate of 1.46 U/hour, user-specific dosage parameters for a related diurnal time period (e.g., that same hour on another day in the future, or a preceding diurnal time period on a day in the future) may be adjusted; see also Paragraph [0181]); and
determine a recommendation for one or more of the aspects of daily insulin of the patient based on a target range of the glycemic risk and the daily insulin relationships quantification (Paragraph [0125] the range of possible values of the BBR for a given profile can be adjusted or modified depending on the fear of hypoglycemia index (FHI)), wherein the recommendation comprises a change in at least one of basal insulin, bolus insulin, and the total daily insulin, (Paragraph [0125] the range of possible values of the BBR for a given profile can be adjusted or modified depending on the fear of hypoglycemia index (FHI). For example, in some cases, if the FHI is “prefer low” (e.g., indicating a preference for the system to aggressively keep the person with diabetes within range and not go high), the target blood glucose might be set around 100 mg/dl and the range for delivery may include 0%, 50%, 100%, 200%, and 300% BBR. As another example, if the FHI is “prefer high” (e.g., indicating that the person with diabetes prefers to avoid hypoglycemic events even with a higher risk of hyperglycemic events), the target blood glucose might be set around 140 mg/dl and the range for delivery may include 0%, 100%, and 200% of BBR) wherein quantifying the daily insulin relationships based on the insulin data further comprises calculating at least one of a ratio and a percentage of one of the plurality of aspects of daily insulin relative to another of the plurality of aspects of daily insulin (Paragraph [0153] Using the example from above, for a BBR of 1.46 U/hour, if a diurnal period under consideration is one hour and for the first forty-five minutes (e.g., three iterations of profile generation and delivery actions), insulin was delivered at a rate of 2.92 U/hour and only the last fifteen minutes (e.g., one iteration of profile generation and delivery action) was delivered at a rate of 1.46 U/hour, the total amount delivered would be at 175% of the BBR for the one hour diurnal period, or an average ratio of 1.75 the BBR); and
output the recommendation to a diabetes management system (10) (Paragraph [0109] a suggested dosage for a bolus to be administered using the bolus administering device 80 can be output to a user via the user interface), wherein the diabetes management system adjusts insulin delivery based on the recommendation. (Paragraphs [0152]-[0153] In some cases, methods and systems provided herein can make adjustments for BBR, ISF, and/or CR for multiple diurnal periods based on variations in the insulin amounts actually delivered for that diurnal period compared to the baseline basal insulin rate for that diurnal period; Paragraph [0154] An adjustment to the CR, ISF, and BBR can be any suitable amount. In some cases, the adjustment to the BBR is less than the difference between the delivered basal insulin and the previously programmed BBR. In some cases, a change to each user-specific dosage parameter (e.g., BBR, ISF, and CR) is at a predetermined percentage or value. For example, in some cases, each of BBR and ISF can be increased by 5%, 3%, or 1% and CR decreased by the same percent for every period where the amount of delivered basal insulin exceeds the BBR by at least 25%. In some cases, BBR and ISF can be decreased by 5%, 3%, or 1% and CR increased by the same percent for every period where the amount of delivered basal insulin exceeds the BBR by at least 25%. By setting each adjustment at a low level, methods and systems provided herein can eventually be personalized for the PWD without over adjusting the system based on an unusual day (e.g., to mitigate the risk of short term disturbances being mistaken for changes in physiological parameters). In some cases, the adjustment to CR, ISF, and BBR may be based on a relationship between CR, ISF, and BBR, rather than a fixed amount or percentage.).
However, Desborough does not specifically teach “wherein the aspects of daily insulin in the plurality of aspects of daily insulin comprise at least two of the total daily insulin, total daily basal, or total daily bolus” and to “remove outlier data from at least one of the glucose data and the insulin data prior to at least one of assessing the glycemic risk and quantifying the daily insulin relationships”.
Blomquist, as previously discussed, wherein the aspects of daily insulin in the plurality of aspects of daily insulin comprise at least two of the total daily insulin, total daily basal, or total daily bolus. (Paragraph [0022] total daily dose TDD of insulin; 50% of the TDD is used for basal delivery, i.e., total basal delivery).
As a result, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Desborough to provide “wherein the aspects of daily insulin in the plurality of aspects of daily insulin comprise at least two of the total daily insulin, total daily basal, or total daily bolus” as taught by Blomquist. Doing so enables better tracking of changes of insulin rates in demand and provides assistance in determining one or more basal rates for the patient. (Paragraph [0023]).
Agrawal, as previously discussed, teaches an insulin device configured to remove outlier data from at least one of the glucose data and the insulin data prior to at least one of assessing the glycemic risk and quantifying the daily insulin relationships (Paragraphs [0198] filtering at task 904 can remove an appropriate "window" of the SG data surrounding the bolus event; Paragraphs [0199]-[0200]
The SG data may also be filtered to remove data that may be indicative of an unregistered meal, a sensor artifact, a data transmission error, or the like. For example, the SG data may be filtered to remove data that indicates a SG rate of change that exceeds a threshold value (e.g., 2.0 mg/dL/min).
The process 900 continues by analyzing at least some of the remaining SG data for the presence of any of a plurality of event occurrences (task 906). Task 906 may leverage empirical data, the results of clinical studies, and/or historical data to detect certain detectable patterns, trends, or characteristics of the SG data. In practice, therefore, the decision support software can be written such that task 906 compares the SG data against any number of predefined conditions, which in turn correspond to a suboptimal, suspicious, or potentially troublesome basal pattern.).
As a result, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Desborough to be configured to “remove outlier data from at least one of the glucose data and the insulin data prior to at least one of assessing the glycemic risk and quantifying the daily insulin relationships” as taught by Agrawal. Doing so improves accuracy of the measurements.
Regarding claim 31, Desborough teaches a system comprising:
a glycemic risk assessor (Paragraph [0063]) i.e., processor) configured to assess a glycemic risk based on glucose data of a patient, (Paragraph [0063]), wherein the glucose data comprises continuous glucose monitoring (CGM) data or flash glucose monitoring (FGM) data received for the patient over a time period, (Paragraph [0091]), wherein the glycemic risk comprises at least one of a hyperglycemic risk and a hypoglycemic risk (Paragraphs [0096], [0125]);
an insulin relationship quantifier (Paragraph [0063]) i.e., processor) configured to quantify daily insulin relationships based on insulin data (Paragraph [0093] user-specific dosage parameters can be dosage parameters that are commonly used in the treatment of diabetes, such as average total daily insulin, total daily basal (TDB) insulin), wherein the insulin data comprises basal insulin data and bolus insulin data, (Paragraph [0113] determine rates of basal insulin delivery and optionally amounts of bolus insulin delivery), wherein the basal insulin data and the bolus insulin data are received for the patient over the time period (Paragraph [0114] e.g., over multiple diurnal time segments)
wherein quantifying the daily insulin relationships based on the insulin data comprises calculating each aspect of daily insulin in a plurality of aspects of daily insulin for each day over the time period, (Paragraph [0152]), and comparing the calculated aspects over the time period, (Paragraph [0153] in some cases, methods and systems provided herein can make adjustments for BBR, ISF, and/or CR for multiple diurnal periods based on variations in the insulin amounts actually delivered for that diurnal period compared to the baseline basal insulin rate for that diurnal period; see also Paragraph [0181]),
wherein the aspects of daily insulin comprise at least one of total daily insulin, total daily basal, or total daily bolus (Paragraphs [0152] For example, FIG. 2 includes the block 281 for detecting time periods when an amount of delivered basal insulin is different from a baseline basal rate (BBR), which can then be used to adjust user-specific dosage parameters at block 262. These updated user-specific dosage parameters can then be used to generate new basal delivery profiles at block 263 and used at block 264 to evaluate different basal delivery profiles. For example, for a BBR of 1.46 U/hour (associated with a TDB of 35 U/day), if a diurnal period under consideration is one hour and for the first forty-five minutes, insulin was delivered at a rate of 2.92 U/hour and only the last fifteen minutes was delivered at a rate of 1.46 U/hour, user-specific dosage parameters for a related diurnal time period (e.g., that same hour on another day in the future, or a preceding diurnal time period on a day in the future) may be adjusted; ); and
wherein the basal insulin data and the bolus insulin data are received for the patient over the time period (Paragraphs [0152] For example, FIG. 2 includes the block 281 for detecting time periods when an amount of delivered basal insulin is different from a baseline basal rate (BBR), which can then be used to adjust user-specific dosage parameters at block 262. These updated user-specific dosage parameters can then be used to generate new basal delivery profiles at block 263 and used at block 264 to evaluate different basal delivery profiles. For example, for a BBR of 1.46 U/hour (associated with a TDB of 35 U/day), if a diurnal period under consideration is one hour and for the first forty-five minutes, insulin was delivered at a rate of 2.92 U/hour and only the last fifteen minutes was delivered at a rate of 1.46 U/hour, user-specific dosage parameters for a related diurnal time period (e.g., that same hour on another day in the future, or a preceding diurnal time period on a day in the future) may be adjusted); and
and an insulin recommender (Paragraph [0063] i.e., processor) configured to determine a recommendation for one or more of the aspects of daily insulin of the patient based on a target range of the glycemic risk and the daily insulin relationships quantification (Paragraph [0125] the range of possible values of the BBR for a given profile can be adjusted or modified depending on the fear of hypoglycemia index (FHI)), wherein the recommendation comprises a change in at least one of basal insulin, bolus insulin, and total daily insulin, (Paragraph [0125] the range of possible values of the BBR for a given profile can be adjusted or modified depending on the fear of hypoglycemia index (FHI). For example, in some cases, if the FHI is “prefer low” (e.g., indicating a preference for the system to aggressively keep the person with diabetes within range and not go high), the target blood glucose might be set around 100 mg/dl and the range for delivery may include 0%, 50%, 100%, 200%, and 300% BBR. As another example, if the FHI is “prefer high” (e.g., indicating that the person with diabetes prefers to avoid hypoglycemic events even with a higher risk of hyperglycemic events), the target blood glucose might be set around 140 mg/dl and the range for delivery may include 0%, 100%, and 200% of BBR),
wherein quantifying the daily insulin relationships based on the insulin data further comprises calculating at least one of a ratio and a percentage of one of the plurality of aspects of daily insulin relative to another of the plurality of aspects of daily insulin (Paragraph [0153] Using the example from above, for a BBR of 1.46 U/hour, if a diurnal period under consideration is one hour and for the first forty-five minutes (e.g., three iterations of profile generation and delivery actions), insulin was delivered at a rate of 2.92 U/hour and only the last fifteen minutes (e.g., one iteration of profile generation and delivery action) was delivered at a rate of 1.46 U/hour, the total amount delivered would be at 175% of the BBR for the one hour diurnal period, or an average ratio of 1.75 the BBR);
and a diabetes management system (10) receiving the recommendation and being configured to adjust insulin delivery based on the recommendation. (Paragraph [0109] a suggested dosage for a bolus to be administered using the bolus administering device 80 can be output to a user via the user interface; Paragraphs [0152]-[0153] In some cases, methods and systems provided herein can make adjustments for BBR, ISF, and/or CR for multiple diurnal periods based on variations in the insulin amounts actually delivered for that diurnal period compared to the baseline basal insulin rate for that diurnal period; Paragraph [0154] An adjustment to the CR, ISF, and BBR can be any suitable amount. In some cases, the adjustment to the BBR is less than the difference between the delivered basal insulin and the previously programmed BBR. In some cases, a change to each user-specific dosage parameter (e.g., BBR, ISF, and CR) is at a predetermined percentage or value. For example, in some cases, each of BBR and ISF can be increased by 5%, 3%, or 1% and CR decreased by the same percent for every period where the amount of delivered basal insulin exceeds the BBR by at least 25%. In some cases, BBR and ISF can be decreased by 5%, 3%, or 1% and CR increased by the same percent for every period where the amount of delivered basal insulin exceeds the BBR by at least 25%. By setting each adjustment at a low level, methods and systems provided herein can eventually be personalized for the PWD without over adjusting the system based on an unusual day (e.g., to mitigate the risk of short term disturbances being mistaken for changes in physiological parameters). In some cases, the adjustment to CR, ISF, and BBR may be based on a relationship between CR, ISF, and BBR, rather than a fixed amount or percentage.).
However, Desborough does not specifically teach “wherein the aspects of daily insulin in the plurality of aspects of daily insulin comprise at least two of the total daily insulin, total daily basal, or total daily bolus” and “wherein the glycemic risk assessor is further configured to remove outlier data from at least one of the glucose data and the insulin data prior to at least one of assessing the glycemic risk and quantifying the daily insulin relationships.”
Blomquist, as previously discussed, wherein the aspects of daily insulin in the plurality of aspects of daily insulin comprise at least two of the total daily insulin, total daily basal, or total daily bolus. (Paragraph [0022] total daily dose TDD of insulin; 50% of the TDD is used for basal delivery, i.e., total basal delivery).
As a result, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Desborough to provide “wherein the aspects of daily insulin in the plurality of aspects of daily insulin comprise at least two of the total daily insulin, total daily basal, or total daily bolus” as taught by Blomquist. Doing so enables better tracking of changes of insulin rates in demand and provides assistance in determining one or more basal rates for the patient. (Paragraph [0023]).
Agrawal, as previously discussed, teaches an insulin device configured to remove outlier data from at least one of the glucose data and the insulin data prior to at least one of assessing the glycemic risk and quantifying the daily insulin relationships. (Paragraphs [0198] filtering at task 904 can remove an appropriate "window" of the SG data surrounding the bolus event; Paragraphs [0199]-[0200]
The SG data may also be filtered to remove data that may be indicative of an unregistered meal, a sensor artifact, a data transmission error, or the like. For example, the SG data may be filtered to remove data that indicates a SG rate of change that exceeds a threshold value (e.g., 2.0 mg/dL/min).
The process 900 continues by analyzing at least some of the remaining SG data for the presence of any of a plurality of event occurrences (task 906). Task 906 may leverage empirical data, the results of clinical studies, and/or historical data to detect certain detectable patterns, trends, or characteristics of the SG data. In practice, therefore, the decision support software can be written such that task 906 compares the SG data against any number of predefined conditions, which in turn correspond to a suboptimal, suspicious, or potentially troublesome basal pattern.).
As a result, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Desborough to teach wherein the glycemic risk assessor is further configured “to remove outlier data from at least one of the glucose data and the insulin data prior to at least one of assessing the glycemic risk and quantifying the daily insulin relationships” as taught by Agrawal. Doing so improves accuracy of the measurements.
Regarding claims 2, 17, and 32, Desborough teaches a method/system further comprising receiving the glucose data and the insulin data for the patient prior to assessing the glycemic risk and quantifying the daily insulin relationships (Fig. 2, Paragraph [0110] a system can receive user inputs, such as user inputs at blocks 251 and 252, which can be used to provide initial settings, such as one or more target blood glucose values that may be used or determined at block 261 and/or one or more user-specific dosage parameters that may be used or determined at block 262. Based on the user-specific dosage parameters, the method 202 can generate multiple basal insulin delivery profiles and/or rates at block 263. In some cases, the plurality of basal insulin delivery profiles and/or rates can be based upon one or more baseline basal rates. At block 264, the method 202 can analyze each basal delivery profile or rate generated at block 263 based on variations of predicted future blood glucose values from one or more target blood glucose values (such as the target blood glucose values from block 261) using blood glucose data from a continuous glucose monitor (CGM) or blood glucose meter (BGM), such as generated in block 271. Additionally, predicted blood glucose values can include inputs regarding previous dosages of insulin and/or food consumption (e.g., estimates of carbohydrates consumed; Paragraphs [0152] For example, FIG. 2 includes the block 281 for detecting time periods when an amount of delivered basal insulin is different from a baseline basal rate (BBR), which can then be used to adjust user-specific dosage parameters at block 262. These updated user-specific dosage parameters can then be used to generate new basal delivery profiles at block 263 and used at block 264 to evaluate different basal delivery profiles. For example, for a BBR of 1.46 U/hour (associated with a TDB of 35 U/day), if a diurnal period under consideration is one hour and for the first forty-five minutes, insulin was delivered at a rate of 2.92 U/hour and only the last fifteen minutes was delivered at a rate of 1.46 U/hour, user-specific dosage parameters for a related diurnal time period (e.g., that same hour on another day in the future, or a preceding diurnal time period on a day in the future) may be adjusted);
Regarding claims 3, 18, and 33, Desborough teaches wherein the glycemic risk is a quantification of the risk of current and future hyperglycemia and/or hypoglycemia (Paragraph [0148] In some cases, methods and systems provided herein make adjustments to future blood glucose targets based on a calculated accuracy factor for data from the continuous glucose monitor 50 in order to reduce a risk of hypoglycemia. In some cases, methods and systems provided herein can estimate the current blood glucose level as being a predetermined number of standard deviations (e.g., 0.5 standard deviations, one standard deviation, two standard deviations) below data received from continuous glucose monitor 50 based on the accuracy factor in order to reduce a risk of hypoglycemia).
Regarding claims 4, 19, and 34, Desborough teaches wherein assessing the glycemic risk uses at least one of prediction and state estimation (Paragraph [0092]).
Regarding claim 5, 20, and 35, Desborough teaches wherein the glycemic risk is assessed in terms of at least one of sample means, sample variance, time-in-range, episodes of high/low BG (blood glucose), low blood glucose risk, high blood glucose risk, and overall risk. (Paragraph [0148] In some cases, methods and systems provided herein can estimate the current blood glucose level as being a predetermined number of standard deviations (e.g., 0.5 standard deviations, one standard deviation, two standard deviations) below data received from continuous glucose monitor 50 based on the accuracy factor in order to reduce a risk of hypoglycemia.)
Regarding claim 6, Desborough teaches generating a risk profile that illustrates a quantified assessment of glycemic risk (Paragraph [0062] fear of hypoglycemia index (FHI) options displayed may include at least one of a numerical blood glucose level, a probability of going below a low threshold glucose level, a probability of going above a high threshold glucose level, and a textual description of a preferred glucose level, by which the user inputs the FHI.)
Regarding claim 21, Desborough teaches wherein the computer readable medium further comprises instructions that, when executed by the at least one processor, (Paragraph [0063]), cause the system to generate a risk profile that illustrates a quantified assessment of glycemic risk. (Paragraph [0062] fear of hypoglycemia index (FHI) options displayed may include at least one of a numerical blood glucose level, a probability of going below a low threshold glucose level, a probability of going above a high threshold glucose level, and a textual description of a preferred glucose level, by which the user inputs the FHI.)
Regarding claim 36, Desborough teaches wherein the insulin relationship quantifier or the insulin recommender, (Paragraph [0063] processor), is further configured to generate a risk profile that illustrates a quantified assessment of glycemic risk. (Paragraph [0062] fear of hypoglycemia index (FHI) options displayed may include at least one of a numerical blood glucose level, a probability of going below a low threshold glucose level, a probability of going above a high threshold glucose level, and a textual description of a preferred glucose level, by which the user inputs the FHI.)
Regarding claim 8, Desborough teaches identifying relationship patterns based on the aspects of daily insulin for each day over a series of days. (Paragraphs [0152] FIG. 2 includes the block 281 for detecting time periods when an amount of delivered basal insulin is different from a baseline basal rate (BBR), which can then be used to adjust user-specific dosage parameters at block 262. These updated user-specific dosage parameters can then be used to generate new basal delivery profiles at block 263 and used at block 264 to evaluate different basal delivery profiles. For example, for a BBR of 1.46 U/hour (associated with a TDB of 35 U/day), if a diurnal period under consideration is one hour and for the first forty-five minutes, insulin was delivered at a rate of 2.92 U/hour and only the last fifteen minutes was delivered at a rate of 1.46 U/hour, user-specific dosage parameters for a related diurnal time period (e.g., a preceding diurnal time period on a day in the future) may be adjusted; Paragraph [0156] In some cases, when performing an adjustment, a related diurnal period may be adjusted based on variation from the BBR for a given diurnal period. For example, if an adjustment were to be performed because delivery from 2 PM to 3 PM exceeded 150% of the BBR, an adjustment may be made to the user-specific dosage parameters for the same time on a different day in the future (e.g., 2 PM to 3 PM on the next day) or a preceding diurnal period on a different day in the future (e.g., 1 PM to 2 PM on the next day or 12 PM to 1 PM on the next day, etc.).
Regarding claim 23, Desborough teaches wherein the computer readable medium further comprises instructions that, when executed by the at least one processor, (Paragraph [0063]), cause the system to identify relationship patterns based on the aspects of daily insulin for each day over a series of days. (Paragraphs [0152] FIG. 2 includes the block 281 for detecting time periods when an amount of delivered basal insulin is different from a baseline basal rate (BBR), which can then be used to adjust user-specific dosage parameters at block 262. These updated user-specific dosage parameters can then be used to generate new basal delivery profiles at block 263 and used at block 264 to evaluate different basal delivery profiles. For example, for a BBR of 1.46 U/hour (associated with a TDB of 35 U/day), if a diurnal period under consideration is one hour and for the first forty-five minutes, insulin was delivered at a rate of 2.92 U/hour and only the last fifteen minutes was delivered at a rate of 1.46 U/hour, user-specific dosage parameters for a related diurnal time period (e.g., a preceding diurnal time period on a day in the future) may be adjusted; Paragraph [0156] In some cases, when performing an adjustment, a related diurnal period may be adjusted based on variation from the BBR for a given diurnal period. For example, if an adjustment were to be performed because delivery from 2 PM to 3 PM exceeded 150% of the BBR, an adjustment may be made to the user-specific dosage parameters for the same time on a different day in the future (e.g., 2 PM to 3 PM on the next day) or a preceding diurnal period on a different day in the future (e.g., 1 PM to 2 PM on the next day or 12 PM to 1 PM on the next day, etc.).
Regarding claim 38, Desborough teaches wherein the insulin relationship quantifier ((Paragraph [0063] processor), is further configured to identify relationship patterns based on the aspects of daily insulin. (Paragraphs [0152] FIG. 2 includes the block 281 for detecting time periods when an amount of delivered basal insulin is different from a baseline basal rate (BBR), which can then be used to adjust user-specific dosage parameters at block 262. These updated user-specific dosage parameters can then be used to generate new basal delivery profiles at block 263 and used at block 264 to evaluate different basal delivery profiles. For example, for a BBR of 1.46 U/hour (associated with a TDB of 35 U/day), if a diurnal period under consideration is one hour and for the first forty-five minutes, insulin was delivered at a rate of 2.92 U/hour and only the last fifteen minutes was delivered at a rate of 1.46 U/hour, user-specific dosage parameters for a related diurnal time period (e.g., a preceding diurnal time period on a day in the future) may be adjusted; Paragraph [0156] In some cases, when performing an adjustment, a related diurnal period may be adjusted based on variation from the BBR for a given diurnal period. For example, if an adjustment were to be performed because delivery from 2 PM to 3 PM exceeded 150% of the BBR, an adjustment may be made to the user-specific dosage parameters for the same time on a different day in the future (e.g., 2 PM to 3 PM on the next day) or a preceding diurnal period on a different day in the future (e.g., 1 PM to 2 PM on the next day or 12 PM to 1 PM on the next day, etc.).
Claims 11-14, 26-29, and 41-44 are rejected under 35 U.S.C. 103 as being unpatentable over Desborough in view of Blomquist and Agrawal, further in view of Patek (WO 2018152358) (previously cited).
Regarding claims 11, 26, and 41, Desborough as modified teaches all of the elements of the claimed invention except “wherein determining the recommendation is performed when a daily insulin pattern is outside the target range, and wherein the recommendation is based on the glycemic risk.”
Patek teaches wherein determining the recommendation is performed when a daily insulin pattern is outside the target range, and wherein the recommendation is based on the glycemic risk (Paragraph [0034] these parameters include the thresholds for assessing periods of high and low blood glucose risks by our risk function, denoted BGhi and BGlo respectively, the minimum length of time which is allowed to constitute an actionable "risk zone" (to be defined shortly) for either hyper- or hypoglycemia, as well as a "zone attribution perimeter" (ZAP) which determines how the overall changes in basal rate should be weighted towards the above mentioned "risk zones" as opposed to overall "across- the-board" adjustments”; Paragraph [0046] when recommendation (change in basal rate) is more likely to happen within a risk zone).
As a result, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Desborough as modified to teach “wherein determining the recommendation is performed when a daily insulin pattern is outside the target range, and wherein the recommendation is based on the glycemic risk” as taught by Patek. Doing so provides as assessment to mitigate glycemic risk during the time period. (Paragraph [0034]).
Regarding claims 12, 27, and 42, Desborough as modified teaches all of the elements of the claimed invention except “wherein determining the recommendation is performed when a daily insulin pattern is outside the target range and is confirmed based on the glycemic risk, wherein the recommendation is based on the amount the daily insulin pattern is outside the range and at least one of a quantitative assessment of risk and a qualitative assessment of risk.”
Patek teaches wherein determining the recommendation is performed when a daily insulin pattern is outside the target range and is confirmed based on the glycemic risk (Paragraph [0034] these parameters include the thresholds for assessing periods of high and low blood glucose risks by our risk function, denoted BGhi and BGlo respectively, the minimum length of time which is allowed to constitute an actionable "risk zone"), wherein the recommendation is based on the amount the daily insulin pattern is outside the range (Paragraph [0034] the minimum length of time which is allowed to constitute an actionable "risk zone") and at least one of a quantitative assessment of risk (Paragraph [0034] these parameters include the thresholds for assessing periods of high and low blood glucose risks by our risk function, denoted BGhi and BGlo respectively”: quantitative values of risk used in recommendation of basal rate) and a qualitative assessment of risk.
As a result, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Desborough as modified to teach “wherein determining the recommendation is performed when a daily insulin pattern is outside the target range and is confirmed based on the glycemic risk, wherein the recommendation is based on the amount the daily insulin pattern is outside the range and at least one of a quantitative assessment of risk and a qualitative assessment of risk” as taught by Patek. Doing so provides as assessment to mitigate glycemic risk during the time period. (Paragraph [0034]).
Regarding claims 13, 28, and 43, Desborough as modified teaches all of the elements of the claimed invention except “wherein determining the recommendation is performed when a daily insulin pattern is within the target range and when a glycemic risk fails to meet at least one criteria.”
Patek teaches wherein determining the recommendation is performed when a daily insulin pattern is within the target range and when a glycemic risk fails to meet at least one criteria (Paragraphs [0044]-[0047] recommendation to change basal rate if total deviation over the full period is detected and while daily pattern is still within range. This occurs less frequently than when specific risk zones are triggered, as described above).
As a result, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Desborough as modified to teach “wherein determining the recommendation is performed when a daily insulin pattern is within the target range and when a glycemic risk fails to meet at least one criteria” as taught by Patek. Doing so provides as assessment to mitigate glycemic risk during the time period. (Paragraph [0034]).
Regarding claims 14, 29, and 44, Desborough as modified teaches all of the elements of the claimed invention except “wherein the change comprises an increase or a decrease in an amount of the at least one of basal insulin, bolus insulin, and total daily insulin.”
Patek teaches wherein the change comprises an increase or a decrease in an amount of at least one of basal insulin (Paragraph [0034] the processor 102 is configured to update the basal rate set point over a time period), bolus insulin, and total daily insulin.)
As a result, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Desborough as modified to teach “wherein the change comprises an increase or a decrease in an amount of the at least one of basal insulin, bolus insulin, and total daily insulin” as taught by Patek. Doing so improves assessment of glycemic risk.
Regarding claims 15, 30, and 45, Desborough as modified teaches all of the elements of the claimed invention except wherein the recommendation is in the form of a report, a command or signal or instructions to an insulin delivery system, or a therapy optimization algorithm.
Patek teaches wherein the recommendation is in the form of a report, a command or signal or instructions to an insulin delivery system (Paragraph [0034] the processor 102 is configured to update the basal rate set point over a time period), or a therapy optimization algorithm.
As a result, it would have been obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modified Desborough as modified to teach “wherein the recommendation is in the form of a report, a command or signal or instructions to an insulin delivery system, or a therapy optimization algorithm” as taught by Patek. Doing so provides necessary feedback to mitigate glycemic risk. (Paragraph [0034]).
Response to Arguments
Applicant’s arguments, see “Remarks”, filed 11/24/2025 with respect to the rejection of claims 1-6, 8, 11-21, 23, 26-36, 38 and 41-45 under U.S.C. 103 have been fully considered. However, upon further consideration, new grounds of rejection made in view of Agrawal were necessitated by the claim amendments to claims 1, 16, and 31.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Om A. Patel whose telephone number is (571)272-6331. The examiner can normally be reached Monday - Friday 8 a.m. - 5 p.m..
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/OM PATEL/Examiner, Art Unit 3791
/JENNIFER ROBERTSON/Supervisory Patent Examiner, Art Unit 3791