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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 9/3/2026 has been entered.
Status of the Claims
The status of the claims as of the response filed 9/3/2026 is as follows: Claims 3-7, 10-21, 23, 25, 28, 30, 32-52, 54, and 56-59 are cancelled, and all previously given rejections for these claims are considered moot. Claims 1, 8-9, 22, 24, 26-27, 29, 31, and 53 are currently amended. Claims 2 and 55 are as previously presented. Claims 60-68 are new. Claims 1-2, 8-9, 22, 24, 26-27, 29, 31, 53, 55, and 60-68 are currently pending and have been considered below.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 9/3/2026 is in compliance with the provisions of 37 CFR 1.97 and is being considered by the examiner.
Response to Arguments
Regarding 35 USC 101
On pages 12-13 of the response filed 9/3/2026 Applicant argues that claim 1 does not recite an abstract idea because it includes “limitations [that] define how physiological measurements are acquired, corrected, and processed, rather than how a patient’s behavior is managed or how a patient and medical professional interact.” Applicant further asserts that “the claimed method is far beyond the capability of a clinician’s manual assessment and does not recite interpersonal or behavioral-management steps.” Applicant’s arguments are fully considered, but are not persuasive. Examiner maintains that claim 1 includes steps that recite an abstract idea. Examiner agrees that the steps for obtaining the glucose, GA, and albumin measurements via sensors are not part of the abstract idea, and these limitations are addressed as additional elements in Steps 2A – Prong 2 and 2B; however, the mere presence of additional elements in the claims does not preclude the claims from reciting an abstract idea at all. Applicant has provided no evidence that the data processing and analysis steps recited by the claims would be “far beyond” the capabilities of a human actor; Examiner submits that calculating weekly variations in analyte measurement data, correcting CGM measurements (e.g. via simple multiplication as noted in [0101] of Applicant’s specification), finding statistical correlations between analyte measurements, making estimations or inferences about CGM measurements based on GA data, comparing analyte measurements to thresholds, generating clinical risk determinations and intervention recommendations, and determining whether another CGM measurement should be performed are all evaluations and judgments that a clinician or other medical professional would be capable of achieving either mentally or with aid of pen and paper when observing analyte data collected for a patient over various time periods. Many of these steps (e.g. calculating, determining a correlation, correcting, estimating, comparing, etc.) also recite mathematical concepts. Similarly, many of these steps (e.g. generating output information including risk and various clinical recommendations, transmitting the output information to a user, and determining whether or not a next CGM measurement should be performed) also recite certain methods of organizing human activity, because they describe steps for making and communicating clinical recommendations for lifestyle and medication behavior modifications for a patient as well as suggestions for directing the frequency of performing glucose measurements of the patient. Such activities amount to instructions for managing personal behavior, interactions, or relationships between people (e.g. interactions between a clinician and a patient in a clinical relationship). Accordingly, Examiner maintains that the claims recite an abstract idea at Step 2A – Prong 1, as explained in more detail in the updated 35 USC 101 rejections below.
On pages 13-16 Applicant argues that the newly-introduced step for correcting the CGM measurements using a function of a uric acid level prior to determining the correlation amounts to an improved method of continuous blood glucose monitoring and thus provides a technological improvement. Applicant further submits that use of the corrected measurements to determine correlations with glycated albumin measurements permits the “selective, reduced use of invasive continuous monitoring” which “integrates any alleged judicial exception into a practical application.” Applicant’s arguments are fully considered, but are not persuasive. Examiner first notes that the specification does not support correcting CGM blood glucose measurements as a function of uric acid level; uric-acid-based analyte correction appears to exclusively be contemplated for glycated albumin (GA) levels as disclosed in [0095]-[0101], with no mention of correcting blood glucose levels in a similar manner. Accordingly, this feature does not appear to offer an improvement to continuous blood glucose monitoring technology, because it is not explained as solving any specific technical problems existing in conventional CGM technology. Further, the correction of analyte measurements using a function of uric acid level can include simple mathematical steps such as multiplying the measured GA level by a coefficient as noted in [0101], such that this feature is part of the abstract idea itself because it reflects mathematical concepts as well as a step that a human actor such as a clinician could accomplish either mentally or with the aid of pen and paper when performing a clinical analysis. Additionally, the use of corrected analyte measurements in determining correlations that are then used as a basis for making determinations about whether new invasive glucose measurements should be performed (thereby resulting in the potential for reduced use of invasive continuous monitoring) is also part of the abstract idea, because it reflects mental determinations that a clinician may make, as well as represents clinical recommendations that a clinician may provide to a patient to better manage their glucose measurement behavior in the future, which falls into the ‘certain methods of organizing human activity’ grouping. Merely outputting indications to a user to let them know whether or not another CGM measurement should be performed does not improve the underlying technology of the CGM device or another technical field, but rather represents improvements to the abstract idea itself which may have the intended result of avoiding unnecessary medical procedures and optimizing usage of a CGM device if the user decides to act on the recommendations, but does not guarantee such outcomes in a technological manner. Note that improved abstract ideas do not provide a technological improvement or a practical application; see MPEP 2106.05(a): “It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements.” See also 2106.05(a)(II): “it is important to keep in mind that an improvement in the abstract idea itself… is not an improvement in technology.”
On pages 16-17 Applicant argues that “the claimed invention amounts to more than routine data collection, generic computation, or post-solution reporting” and instead “recites a specific technical solution in which CGM-derived glucose levels are corrected using a function of uric-acid level before correlation with GA, and the corrected relationship is then used to support selective use of CGM” which “provides a concrete improvement in the technical field of glucose monitoring by improving the reliability of the glucose information used in the claimed method and reducing unnecessary invasive continuous glucose measurements.” Applicant’s arguments are fully considered, but are not persuasive. Examiner respectfully disagrees that the instant claims provide a concrete improvement in the technical field of glucose monitoring, as explained in detail in the previous paragraph. Examiner maintains that the claims are directed to an abstract idea without significantly more, as explained in detail in the updated 35 USC 101 rejections below.
On page 17 Applicant argues that “the claimed method achieves a concrete, useful outcome by transforming a physical input (e.g. continuous glucose measurements, GA measurements, uric-acid information) into valuable outputs (e.g. corrected glucose information, estimated glucose levels, risk determinations, treatment-related output, whether further CGM should be performed)” and thus provides significantly more than any judicial exception. Applicant’s arguments are fully considered, but are not persuasive. The transformation of analyte measurement data into corrected glucose estimations, risk determinations, clinical recommendations, etc. does not amount to a particular transformation as described in MPEP 2106.05(c): “An ‘article’ includes a physical object or substance. The physical object or substance must be particular, meaning it can be specifically identified. ‘Transformation’ of an article means that the ‘article’ has changed to a different state or thing. Changing to a different state or thing usually means more than simply using an article or changing the location of an article. A new or different function or use can be evidence that the article has been transformed. Purely mental processes in which thoughts or human based actions are ‘changed’ are not considered an eligible transformation. For data, mere ‘manipulation of basic mathematical constructs [i.e.,] the paradigmatic ‘abstract idea,’’ has not been deemed a transformation” (emphasis added). Thus, Applicant’s arguments are not persuasive at least because analyte data is not a physical or tangible ‘article’ and because the manipulation or analysis of such data to provide other data outputs does not amount to a particular transformation.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-2, 8-9, 22, 24, 26-27, 29, 31, 53, 55, and 60-68 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 1 recites “wherein the glucose levels acquired by the continuous blood glucose measurement are corrected using a function of a uric acid level, and the correlation is determined between the uric-acid-corrected glucose levels and the GA level.” Claim 68 similarly recites “correct the glucose levels represented by the continuous glucose measurement data using a function of a uric acid level; determine a correlation between a mean value of the uric acid corrected glucose levels and glycated albumin (GA) level.” Applicant’s original specification does not provide sufficient written support for correcting glucose levels of CGM data using a function of a uric acid level, and then determining a correlation between uric-acid-corrected glucose levels and GA levels. The only mention of correcting blood glucose levels in the specification in in para. [0070], which states “the blood glucose level in the interstitial fluid is corrected on the basis of the blood glucose level measured by SMBG, and converted to the blood glucose level (also referred to as CGM-corrected blood glucose level).” Several additional references to “CGM corrected blood glucose levels” occur throughout paras. [0071]-[0106], including use of these CGM-corrected glucose levels as part of a determined correlation, but there is no disclosure of such blood glucose correction being based on a function of uric acid level. Conversely, paras. [0095]-[0101] disclose correction of glycated albumin (GA) levels as a function of uric acid level, and use of the uric-acid-corrected GA levels as part of the correlation with glucose levels. Because correcting blood glucose level as a function of uric acid level and correlating a uric-acid-corrected blood glucose level with GA level was not present in the original disclosure as filed, this limitation constitutes new matter and is rejected under 35 U.S.C. 112(a). Claims 2, 8-9, 22, 24, 26-27, 29, 31, 53, 55, and 60-67 are also rejected on this basis because they inherit the unsupported limitation due to their dependence on claim 1.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 61, 64, and 66 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 61 recites “wherein said correcting comprises multiplying the GA level by a coefficient based on the uric acid level.” However, parent claim 1 recites “wherein the glucose levels acquired by the continuous blood glucose measurement are corrected using a function of a uric acid level.” It is unclear how correction of the blood glucose levels as in claim 1 could comprise multiplying the GA level by a coefficient based on the uric acid level.
Claim 64 recites “wherein the correlation comprises a correlation between a median value of the glucose levels of the continuous blood glucose measurement and the GA level.” However, parent claim 1 recites “determining a correlation between a mean value of the variation data of the glucose levels acquired by the continuous blood glucose measurement and a glycated albumin (GA) level.” It is unclear how the correlation could be between a mean value of variation data of CGM glucose levels and the GA level as in claim 1, and further be between a median value of the CGM glucose levels and the GA level as in claim 64. This would presumably include at least two different correlations, because two different data values (mean and median) are being correlated with the GA level, rendering the claim indefinite because it refers to “the correlation” such that there only appears to be one correlation value represented.
Claim 66 recites “wherein the area between curves is an area between a 10th percentile curve and a 75th percentile curve, or an area between a 2nd percentile curve and a 75th percentile curve.” However, parent claim 27 previously recites “wherein the correlation comprises a correlation between an area between a 25th percentile curve and a 75th percentile curve of the glucose levels of the continuous blood glucose measurement and the GA level.” It is unclear how an area that is initially described as being between a 25th-75th percentile could also encompass an area between a 10th-75th percentile or a 2nd-75th percentile, because these later ranges introduced in claim 66 are broader than the initial area introduced by parent claim 27, rendering claim 66 indefinite.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-2, 8-9, 22, 24, 26-27, 29, 31, 53, 55, and 60-68 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
In the instant case, claims 1-2, 8-9, 22, 24, 26-27, 29, 31, 53, and 60-67 are directed to a method (i.e. a process), claim 55 is directed to a non-transitory storage medium (i.e. a manufacture), and claim 68 is directed to a device (i.e. a machine). Thus, each of the claims falls within one of the four statutory categories. Nevertheless, the claims fall within the judicial exception of an abstract idea.
Step 2A – Prong 1
Independent claims 1 and 68 recite steps that, under their broadest reasonable interpretations, cover mental processes, mathematical concepts, as well as certain methods of organizing human activity (e.g. managing personal behavior, relationships, or interactions between people). Specifically, claim 1 recites:
(a) continuously measuring blood glucose of a subject for several days to generate a continuous blood glucose measurement;
(b) calculating weekly variation data of glucose levels of the subject from the continuous blood glucose measurement;
(c) measuring, by a sensor, a glycated albumin concentration and an albumin concentration in a body fluid of a subject, for the several days during which the continuous blood glucose measurement was performed and for a period other than the several days;
(d) determining a correlation between a mean value of the variation data of the glucose levels acquired by the continuous blood glucose measurement and a glycated albumin (GA) level, wherein the glucose level acquired by the continuous blood glucose measurement are corrected using a function of a uric acid level, and the correlation is determined between the uric-acid-corrected glucose levels and the GA level;
(e) based on the correlation, estimating, from the GA level obtained for the period other than the several days during which the continuous blood glucose measurement was performed, a mean value of glucose levels for the period other than the several days;
(f) comparing threshold values with a corresponding each of the GA level, the mean value of glucose levels estimated from the GA level obtained for the period other than the several days during which the continuous blood glucose measurement was performed, and ambulatory glucose profile (AGP) of the variation data of the glucose levels during the several days during which the continuous blood glucose measurement was performed to identify if a risk is detected;
(g) if the risk is detected in either one of: (i) the GA level, (ii) the mean value of glucose levels estimated from the GA level obtained for the period other than the several days during which the continuous blood glucose measurement was performed, and (iii) ambulatory glucose profile (AGP) of the variation data of the glucose levels during the several days during which the continuous blood glucose measurement was performed, then generating, by a processor, based on predefined threshold and stored rule-based logic, output information including: (a) the risk, (b) first recommendations regarding lifestyle habits based on the risk and associated thresholds, and (c) second recommendations regarding taking medications determined by referencing a treatment ruleset stored in memory; and
(h) transmitting the output information to a user to notify the user of the risk, the first recommendations, and the second recommendations;
(i) wherein based on a change in GA level acquired after the continuous blood glucose measurement, the processor determines whether or not a next continuous blood glucose measurement should be performed for the subject, and generates output information including the determination,
(j) wherein when a rate of change of the GA level acquired after the continuous blood glucose measurement is greater than a predetermined value, the processor determines that the next continuous blood glucose measurement should be performed, generates output information indicating that the next continuous blood glucose measurement should be performed, thereby reducing invasive continuous blood glucose measurements by performing them selectively based on the GA level rather than continuously, and
(k) wherein when the rate of change is less than or equal to the predetermined value, the processor generates output information indicating that the next continuous blood glucose measurement is not required to be performed.
Each of these italicized steps, when considered as a whole, describe an abstract idea. For example, steps (b), (d)-(g), and (i)-(k) describe clinical data evaluation and determination steps that a human actor such as a clinician would be capable of performing either mentally or with the aid of pen and paper. Specifically, a clinician would be capable of examining weekly CGM readings to calculate weekly glucose variation levels, correcting the CGM readings using a function of measured uric acid levels (e.g. multiplying by a coefficient, adding a constant, or some other simple mathematical corrective function), and then using simple mathematical or statistical methods to correlate the corrected CGM data with measured GA concentration and albumin concentration information for different periods of time. The clinician could then use the correlation to estimate or predict mean glucose variation for a period with no CGM data based on known GA level data and make determinations about risk to a patient by evaluating/comparing the GA level, estimated mean glucose level, and/or an ambulatory glucose profile against respective threshold values for each type of data. The clinician could then generate a report or other output based on predefined thresholds and rules such that the output includes any determined risks and corresponding recommendations for lifestyle and medication treatments. The clinician could further make determinations about whether another continuous blood glucose measurement should be performed or not based on comparing a rate of change of the GA level to a predetermined value.
Limitations (b) and (d)-(f) also recite mathematical concepts, because they describe steps for performing mathematical/statistical calculations, correlations, estimations, comparisons, etc.
Limitations (g)-(k) also recite certain methods of organizing human activity, because they describe steps for making and communicating clinical recommendations for lifestyle and medication behavior modifications for a patient as well as suggestions for directing the frequency of performing glucose measurements of the patient such that invasive measurements are reduced. Such activities amount to instructions for managing personal behavior, interactions, or relationships between people (e.g. interactions between a clinician and a patient in a clinical relationship).
Similarly, claim 68 recites:
A diabetes monitoring device, comprising:
(a) a communication interface configured to receive continuous blood glucose measurement data representing glucose levels of a subject measured over several days;
(b) a sensor configured to measure a glycated albumin concentration and albumin concentration in a body fluid of the subject;
(c) a memory configured to store predefined thresholds, measurement data, information associated with the measurement data, and/or data used for generating output information; and
(d) a processor coupled to the communication interface, the sensor, and the memory, the processor configured to:
(e) calculate weekly variation data of glucose levels of the subject from the received continuous glucose measurement data;
(f) correct the glucose levels represented by the continuous glucose measurement data using a function of a uric acid level;
(g) determine a correlation between a mean value of the uric acid corrected glucose levels and glycated albumin (GA) level;
(h) based on the correlation, estimate, from the GA level obtained for the period other than the several days, a mean value of glucose levels for the period other than the several days;
(i) compare threshold values with a corresponding ones of the GA level, the estimated mean value of glucose levels, and an ambulatory glucose profile (AGP) of the variation data to determine whether a risk is detected;
(j) in response to detection of the risk, generate output information including the risk, a first recommendation regarding lifestyle habits based on the risk and associated thresholds, and a second recommendation regarding taking medication based on information stored in memory;
(k) transmit the output information to a user;
(l) determine, based on a rate of change in the GA level acquired after the continuous blood glucose measurement, whether a next continuous blood glucose measurement should be performed;
(m) when the rate of change is greater than a predetermined value, generate output information indicating that the next continuous blood glucose measurement should be performed; and
(n) when the rate of change is less than or equal to the predetermined value, generate output information indicating that the next continuous blood glucose measurement is not required, whereby invasive continuous glucose measurements are reduced by selectively performing continuous glucose monitoring based on the GA level rather than continuously.
Each of these italicized steps, when considered as a whole, describe an abstract idea. For example, limitations (c), (e)-(j), and (l)-(n) describe clinical data evaluation and determination steps that a human actor such as a clinician would be capable of performing either mentally or with the aid of pen and paper. Specifically, a clinician would be capable of storing various types of data in memory, e.g. by mentally remembering it or writing it down. A clinician could also examine weekly CGM readings to calculate weekly glucose variation levels, correct the CGM readings using a function of measured uric acid levels (e.g. multiplying by a coefficient, adding a constant, or some other simple mathematical corrective function), and then use simple mathematical or statistical methods to correlate the corrected CGM data with measured GA concentration and albumin concentration information for different periods of time. The clinician could then use the correlation to estimate or predict mean glucose variation for a period with no CGM data based on known GA level data and make determinations about risk to a patient by evaluating/comparing the GA level, estimated mean glucose level, and/or an ambulatory glucose profile against respective threshold values for each type of data. The clinician could then generate a report or other output based on their expertise or other stored information such that the output includes any determined risks and corresponding recommendations for lifestyle and medication treatments. The clinician could further make determinations about whether another continuous blood glucose measurement should be performed or not based on comparing a rate of change of the GA level to a predetermined value.
Limitations (e)-(i) also recite mathematical concepts, because they describe steps for performing mathematical/statistical calculations, correlations, estimations, comparisons, etc.
Limitations (j)-(n) also recite certain methods of organizing human activity, because they describe steps for making and communicating clinical recommendations for lifestyle and medication behavior modifications for a patient as well as suggestions for directing the frequency of performing glucose measurements of the patient such that invasive measurements are reduced. Such activities amount to instructions for managing personal behavior, interactions, or relationships between people (e.g. interactions between a clinician and a patient in a clinical relationship).
Dependent claims 2, 8-9, 22, 24, 26-27, 29, 31, 53, 55, and 60-67 inherit the limitations that recite an abstract idea from their dependence on claim 1, and thus these claims also recite an abstract idea under the Step 2A – Prong 1 analysis. In addition, claims 2, 8-9, 22, 24, 26-27, 29, 31, 60-62, and 64-67 recite further limitations that, under their broadest reasonable interpretations, merely further describe the abstract idea(s) identified in parent claim 1.
Specifically, claim 2 specifies that the AGP includes a variation range of the variation data, which a clinician would be capable of mentally evaluating to detect health risks.
Claims 8, 22, and 67 specify the schedule of the GA and/or CGM measurements, which merely further describe the frequency and/or quantity of the mentally evaluated data over a time schedule for which a clinician would be capable of performing data analysis.
Claim 9 recites various additional types of output information that may be generated or determined, each of which are types of information that a clinician would be capable of mentally determining by analyzing various patient information using their medical expertise.
Claim 24 recites that the correlation is optimized with reference to data related to the subject, which a clinician would be capable of using their medical expertise to mentally achieve.
Claims 26-27 and 64-66 further describe what the determined correlation is, each of which are types of mathematical correlations or associations that a clinician would be capable of determining either mentally or with the aid of pen and paper via mathematical concepts.
Claim 29 recites determining a correlation between a body weight and the GA level and estimating a variation in body weight from the GA level or a variation in the GA level, which describe mathematical concepts as well as mental processes that a clinician would be able to achieve via performing simple mathematical and/or statistical calculations.
Claim 31 recites storing a correlation as third data and that the output information includes the third data, which a clinician could achieve by mentally remembering this information about a patient or otherwise storing it in a patient chart, medical record, etc. and including it with the recommendations and risk information prepared for sharing with the patient.
Claim 60 specifies that the function of the uric acid level is set in accordance with various types of clinical indications, each of which are types of information that a clinician could take into consideration when mentally setting a uric-acid-based correction function for CGM data.
Claim 61 recites that correcting the CGM data comprises multiplying the GA level by a coefficient based on the uric acid level, which describes mathematical concepts as well as mental processes that a clinician would be able to achieve via performing simple mathematical calculations.
Claim 62 recites determining that the subject exhibits a uric acid abnormality when a measured value deviates from the correlation, which is a type of mental determination that a clinician could make by mentally comparing these two values and using their medical expertise to judge when a significant anomaly or deviation has occurred. Claim
However, recitation of an abstract idea is not the end of the analysis. Each of the claims must be analyzed for additional elements that indicate the abstract idea is integrated into a practical application to determine whether the claim is considered to be “directed to” an abstract idea.
Step 2A – Prong 2
The judicial exception is not integrated into a practical application. In particular, independent claims 1 and 68 do not include additional elements that integrate the abstract idea into a practical application. Claim 1 includes the additional elements of continuously measuring blood glucose of a subject for several days to generate a continuous blood glucose measurement; measuring, by a sensor, a glycated albumin concentration and an albumin concentration in a body fluid of a subject, for the several days during which the continuous blood glucose measurement was performed and for a period other than the several days; and use of a processor to generate the output information and determine whether a next continuous blood glucose measurement should or should not be performed. Claim 68 includes the additional elements of a communication interface configured to receive continuous blood glucose measurement data representing glucose levels of a subject measured over several days; a sensor configured to measure a glycated albumin concentration and albumin concentration in a body fluid of the subject; a memory configured to store various data; and a processor coupled to the communication interface, the sensor, and the memory and configured to perform the calculate, correct, determine, estimate, compare, generate, transmit, etc. functions.
The “measuring” steps of claim 1 and the analogous communication interface and sensor elements of claim 68, when considered in the context of each claim as a whole, amount to insignificant pre-solution activities in the form of necessary data gathering because these types of sensor measurements are merely performed and/or received as means of obtaining the data about CGM, GA, and albumin levels needed for the main calculation, correlation, and analysis steps, as explained above. See MPEP 2106.05(g), where similar steps for performing clinical tests on individuals to obtain input for an equation and determining the level of a biomarker in blood are provided as examples of mere data gathering insignificant extra-solution activities. The use of a processor to perform steps (g) and (j)-(l) of claim 1 and functions (e)-(n) of claim 68 amounts to instructions to “apply” the exception because it merely utilizes a high-level computing component as a tool with which to digitize and/or automate these otherwise-abstract steps (see MPEP 2106.05(f)). The use of a memory to store information also amounts to mere instructions to “apply” the exception because the otherwise-abstract function of storing information is merely being digitized such that it occurs in an electronic environment. Accordingly, claims 1 and 68 as a whole are each directed to an abstract idea without integration into a practical application.
The judicial exception recited in dependent claims 2, 8-9, 22, 24, 26-27, 29, 31, 53, 55, and 60-67 is also not integrated into a practical application under a similar analysis as above. Claims 2, 9, 26-27, 29, 31, 60-62, and 64-66 merely further describe the abstract idea(s) identified in claim 1 without introducing any new additional elements of their own, and accordingly do not provide integration into a practical application. Claims 8, 22, and 67 specify the schedule of performing the GA and/or CGM measurements, which merely nominally describe the timing of the insignificant pre-solution data gathering steps. Claim 24 specifies that optimizing the correlation is performed using machine learning or deep learning, which amounts to instructions to “apply” the exception with a computer because these methods are recited at a high level of generality (i.e. no particular types or techniques, training data, transformations, specific outputs, or other parameters of the machine learning or deep learning are described) and merely serve to digitize or automate the otherwise-abstract optimization step (see MPEP 2106.05(f)). Claims 53 and 63 specify the types of collected body fluids from which GA and albumin levels are measured, which again merely nominally describes the manner of achieving the insignificant pre-solution data gathering step. Claim 55 introduces the additional element of a non-transitory storage medium storing a software for performing the method of claim 1, which also amounts to instructions to “apply” the exception with a computer because a high-level computing component is utilized as a tool with which to automate or digitize the otherwise-abstract steps (see MPEP 2106.05(f)).
Accordingly, the additional elements of claims 1-2, 8-9, 22, 24, 26-27, 29, 31, 53, 55, and 60-68 do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Claims 1-2, 8-9, 22, 24, 26-27, 29, 31, 53, 55, and 60-68 are directed to an abstract idea.
Step 2B
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of a communication interface and sensor for receiving and/or measuring glucose, GA, and albumin levels in a body fluid as in claims 1, 8, 22, 53, 63, and 67-68 amounts to insignificant pre-solution activity in the form of necessary data gathering (see MPEP 2106.05(g)). These types of activities are also nothing more than those recognized as well-understood, routine, and conventional, as evidenced by at least MPEP 2106.05(d)(II) (noting that determining the level of a biomarker, e.g. glucose, albumin, and/or glycated albumin, in blood by any means is well-understood, routine, and conventional in the life science arts, and that receiving or transmitting data over a network is well-understood, routine, and conventional in computing) as well as Koehler et al. (US 20170215774 A1) paras. [0005]-[0006]; Smith et al. (US 20090042237 A1) abstract & para. [0013]; Nagalla et al. (US 20150276723 A1) abstract & [0004]; and Schaefer (US 20140120559 A1) abstract & para. [0008].
The use of a processor to perform steps (g) and (j)-(l) of claim 1 and functions (e)-(n) of claim 68 as well as a non-transitory storage medium storing a software for performing the method as in claim 55 amount to mere instructions to apply the exception using generic computer components. As evidence of the generic nature of the above recited additional elements, Examiner notes para. [0178] of Applicant’s specification, which provides disclosure of generic computer system elements for performing the functions of the invention. The disclosure does not indicate that the elements of the invention are particular machines, and instead provides generic examples of computer hardware, such that one of ordinary skill in the art would understand that any generic computer system including a processor executing stored software instructions could be used to implement the invention.
The use of a memory to store information also amounts to mere instructions to apply the exception, because a high-level computing component is merely being utilized as a tool with which to digitize the otherwise-abstract step of storing information. Examiner further notes that storing and retrieving information in memory is a well-understood, routine, and conventional computer function as outlined in MPEP 2106.05(d)(II).
The use of machine learning or deep learning to perform the optimization as in claim 24 also amounts to mere instructions to apply the exception using generic computer components. As evidence of the generic nature of the machine and/or deep learning, Examiner notes at least paras. [0064], [0109], [0112], [0163]-[0164], [0173], [0177] of Applicant’s specification, which provide no specifics regarding the particular types of learning, methods of training the algorithms/models, how particular inputs are transformed to particular outputs, etc. such that they amount to high-level “black box” type elements for automating otherwise-abstract analysis steps. Further, Examiner notes that it is well-understood, routine, and conventional to utilize machine learning and/or deep learning artificial intelligence techniques to analyze patient data to determine health-related outputs, as evidenced by at least Blume et al. (US 20190113520 A1) paras. [0135] & [0155]-[0157]; Cossler et al. (US 20180182475 A1) abstract; and Lewis et al. (US 20180166174 A1) para. [0116].
Thus, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception (the abstract idea). Furthermore, looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually; the overall effect of the computer implementation and sensor-based measuring steps in combination is to digitize and/or automate mentally-achievable clinical and mathematical analysis of biological analytes measured in conventional ways for the purpose of providing clinical recommendations to direct patient behavior. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Further, the combination of a computer and sensors for measuring analytes such as glucose, glycated albumin, and albumin for clinical analysis is well-understood, routine, and conventional, as evidenced by at least Schaefer abstract, [0021]-[0022], [0043], & [0048]-[0049]; Kohzuma et al. (WO 2010041439 A1) bottom half of Pg3 & first full paragraph of Pg20; Michelson et al. (US 20140046683 A1) [0152], [0160], [0171], & [0218]; and Paek et al. (US 20190321818 A1) [0013] & [0097]. Thus, when considered as a whole and in combination, claims 1-2, 8-9, 22, 24, 26-27, 29, 31, 53, 55, and 60-68 are not patent eligible.
Subject Matter Free from Prior Art
The prior art of record fails to expressly teach or suggest, either alone or in combination, each and every feature of independent claims 1 and 68 (and thus the claims depending therefrom), as explained in more detail in paras. 27-28 of the final Office action mailed 12/11/2024. Upon completion of an updated prior art search, Examiner submits that Colas (US 20140138261 A1) and Matzinger et al. (US 20140311924 A1) are relevant, showing correction of blood glucose measurements to compensate for uric acid levels, but do not teach or render obvious each and every limitation of the claims as amended.
Conclusion
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/KAREN A HRANEK/ Primary Examiner, Art Unit 3684
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