DETAILED ACTION Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Claim Status Claims 1-34 are currently pending and under exam herein. Claims 1-34 are rejected. Priority The instant application claims benefit to provisional application No. 63/212,035 filed on 17 June 2021 . Domestic benefit is acknowledged; h owever, the provisional application does not contain adequate support for all claims. Regarding claim 10, the provisional application discloses the computational model being a Gaussian process classifier (GPC), a support vector machine with a radial basis function kernel (SVM-RBF), a support vector machine with a linear kernel (SVM-linear), or a logistic regression with L2 regularization (LR-L2) . However, the provisional fails to disclose the computational model being a logistic regression with L1 regularization (LR-L1) . Regarding claim s 18-21 and 32-34 , while the provisional application notes that a treatment that is effective for one underlying pathology may be ineffective to treat a different underlying pathology, the provisional fails to correlate the treatment to be administered with the specific underlying pathology identified. Regarding claim 22, the provisional application discloses administering a treatment comprising one or more of the following: metformin, GLP-1 agonists, thiazolidinediones , sodium glucose transporter 2 inhibitors , sulfonylureas , glinides, insulin, or DPP4 inhibitors. This disclosure does not provide adequate support for a treatment of alpha-glucosidase inhibitors, dopamine agonists , or biguanides (metformin is a species but insufficient to support the claimed genus). Regarding claim 23, the provisional application fails to mention treatment comprising any of the listed dietary supplements. At this point in examination, the effective filing date of claims 1-9, 11-17, and 24-31 is 17 June 2021 and the effective filing date of claims 10, 18-23, and 32-34 is 17 June 2022 . Information Disclosure Statement The information disclosure statement (IDS) submitted on 7 November 2025 compl ies with 37 CFR 1.98. Accordingly, all references listed have been considered by the examiner. Drawings The drawings filed on 17 June 2022 are objected to under 37 CFR 1.84(a)(2) as improper color drawings in a utility patent application. Specifically, color drawings appear in figures 4 and 6-29. Color photographs and color drawings are not accepted in utility applications unless a petition filed under 37 CFR 1.84(a)(2) is granted. No petition appears in the file of the instant application. This objection may be overcome by (1) filing substitute black-and-white drawings (or grayscale where color is not essential) that clearly and legibly depict the same subject matter, in compliance with 37 CFR 1.121(d), or (2) filing a petition under 37 CFR 1.84(a)(2). Any such petition must be accompanied by the appropriate fee set forth in 37 CFR 1.17(h), one set of color drawings or color photographs, as appropriate, if submitted via the USPTO p atent e lectronic f iling s ystem or three sets of color drawings or color photographs, as appropriate, if not submitted via the via USPTO p atent e lectronic f iling s ystem , and, unless already present, an amendment to include the following language as the first paragraph of the brief description of the drawings section of the specification: The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee. Color photographs will be accepted if the conditions for accepting color drawings and black and white photographs have been satisfied. See 37 CFR 1.84(b)(2). 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. Claim s 1-20, 2 4 -32, and 34 are rejected under 35 U.S.C. 101 because the claimed invention is directed to (abstract ideas and natural phenomenon) without significantly more. Under MPEP § 2106, subject matter is patent eligible when the claimed invention is to one of the four statutory categories of invention [Step 1], and the claim is not directed to a judicial exception [Step 2A] unless the claim as a whole includes additional limitations amounting to significantly more than the exception [Step 2B]. Step 1 Claims 1- 34 describe inventions that are to one of the statutory categories. In Step 1, a claim must fall within one of the four enumerated categories of statutory subject matter (process, machine, manufacture, or composition of matter); a claim falling outside these categories is ineligible without further analysis [MPEP § 2106.03]. Claims 1- 34 are properly to one of the four statutory categories because the claimed invention s a re method s , which fall into the process category [ Step 1: Yes ]. Step 2 A Under Step 2A, a claim is directed to a judicial exception if, under the broadest reasonable interpretation, it recites an abstract idea, law of nature , or natural phenomena [Prong One] without the claim as a whole integrating the exception into a practical application [Prong Two]. Abstract ideas include mathematical concepts, mental processes , and certain methods of organizing human activity. Mathematical concepts encompass mathematical relationships, formulas, equations, and mathematical calculations [MPEP § 2106.04(a)(2)(I)]. Mental processes involve concepts that can be performed in the human mind or by a human with the aid of pen and paper, such as observations, evaluations, judgments, or opinions [MPEP § 2106.04(a)(2)(III)]. Certain methods of organizing human activity include fundamental economic principles, commercial or legal interactions, and managing personal behavior or relationships [MPEP § 2106.04(a)(2)(II)]. Laws of nature and natural phenomena, include naturally occurring principles/relations and nature-based products that are naturally occurring or that do not have markedly different characteristics compared to what occurs in nature [MPEP § 2106.04(b)-(c)]. Prong One A claim recites a judicial exception when it sets forth or describes a law of nature, natural phenomenon, or abstract idea . Claims 1 -34 recite laws of nature/natural phenomenon and abstract ideas , which fall into the groupings of mathematical concepts and mental processes. Claim s 1 and 25 recite the following limitations, which describe natural phenomenon and abstract ideas within the mathematical concepts and /or mental processes groupings : generating features from the data results of the glucose response curve; and assessing, utilizing a trained computational model, an underlying pathology of metabolic dysregulation, wherein the trained computational model is trained to predict an indicator of the underlying pathology. The limitation of generating features involves deriving quantitative metrics or observing data to derive features , which constitutes an abstract idea within the mathematical concepts or mental processes grouping. The limitation of assessing an underlying pathology involves assessing/predicting a correlation between glucose response and the pathology responsible, which constitute a natural phenomenon because it reflects inherent physiological relationships in the human body between glucose levels and metabolic functions. Additionally, assessing an underlying pathology constitutes an abstract idea within the mental processes grouping because the limitation encompasses observation, evaluation, judgment, or opinion that could be performed in the human mind, such as a clinician mentally analyzing glucose curve patterns to infer pathology, even if aided by a model. Moreover, utilizing a computational model that is trained to predict an indicator of the underlying pathology involves mathematical modeling algorithms based on the natural correlation between glucose response and the pathology responsible, constituting a natural phenomenon and an abstract idea within the mathematical concepts grouping. Dependent c laim 2 limits the underlying pathology to muscular insulin resistance, beta cell dysfunction, impaired incretin effect, or hepatic insulin resistance . Dependent claim 28 limits the underlying pathology to muscular insulin resistance, and specifies that the indicator of the underlying pathology provides an indication of insulin resistance. These claims merely narrow the scope of the judicial exceptions from the claim s upon which they depend because assessing an individual for the listed pathologies based on their glucose response i nvolves evaluating an inherent physiological relationship in the human metabolism where glucose response naturally indicates the listed dysfunctions without human intervention. Dependent c laim 5 recites the limitation wherein the features are extracted from the data results of the glucose response curve , which is an abstract idea within the mathematical concepts or mental processes grouping (see claim 1 above). Dependent c laim 6 specifies that the features include at least one of the listed metrics , which further recites explicit mathematical calculations, relationships, or formulas (e.g. AUC is an integral calculation, slopes are derivatives), constitut ing an abstract idea . Dependent c laim 7 adds a pre-processing step of generating a reduced representation of the data , which further recites an abstract idea within the mathematical concept s grouping because it involves mathematical transformations or reductions of data sets. Dependent c laim 8 specifies that the reduction involves smoothing and Z-normalizing the data , which merely narrows the scope of the mathematical concept of claim 7 because smoothing and Z-normalizing are specific mathematical operations or formulas. Dependent c laim 9 recites extracting principal components via eigen-decomposition of a covariance matrix , which further recites an abstract idea within the mathematical concepts grouping because extracting principal components via eigen-decomposition relies on linear algebra formulas. Dependent c laim 10 limits the computational model to one of the listed models , which merely narrows the scope of the abstract idea s of claim 1 because the listed models are fundamentally mathematical concepts rooted in probability/optimization theory and statistics. Dependent c laim 11 r ecites determining a contribution of the underlying pathology of metabolic dysregulation based on a deviance from a healthy underlying pathology . Similarly, dependent claim 29 recites determining a contribution of the muscular insulin resistance based on a deviance from a healthy underlying muscular insulin resistance pathology. These claim s inherit the judicial exceptions from the claims upon which they depend and further recite an abstract idea within the mathematical concepts or mental processes grouping s because determining a contribution based on a deviance involve s calculating a mathematical difference or observing and evaluating discrepancies to assess/predict the pathology responsible . Dependent c laim 12 specifies that the deviance is determined by an average underlying pathology score from a collection of individuals , and dependent claim 30 specifies that the deviance is determined by an average insulin resistance score from a collection of prediabetic individuals. These claims inherit the judicial exceptions from the claims upon which they depend and further recite an abstract idea within the mathematical concepts grouping because determining the deviance by an average score constitute s basic mathematical calculations. Dependent c laim 13 specifies that each individual of the collection of individuals has a similar overall metabolic assessmen t, which further recites an abstract idea within the mental processes grouping because grouping in dividuals with similar overall metabolic assessment s involves mental evaluation or categorization based on observations of similarities. Dependent c laim 14 recites that the determ ination of the contribution identifies a dominant underlying pathology, which constitutes an abstract idea (mathematical concepts to determine contribution) based on a natural phenomenon (the natural correlation in the human metabolism that indicates a specific dysfunction without human intervention). Dependent claim 31 recites that the contribution stratifies the prediabetic individual as insulin sensitive or insulin resistant , which constitutes an abstract idea (mathematical concepts and mental processes to evaluate the contribution) based on a natural phenomenon (the natural correlation in the human metabolism that indicates insulin status without human intervention). Dependent claims 3-4, 15-24, 26-27, and 32-34 do not narrow or further recite judicial exceptions, but these claims inherit the judicial exceptions from the claims upon which they depend. Therefore, claims 1- 34 recite natural phenomenon and abstract ideas – namely mathematical concepts and mental processes [ Step 2A, Prong One: Yes ]. Prong Two Claims 1- 20, 23-32, and 34 as a whole do not integrate the recited judicial exception s into a practical application. Claims 21-22 and 33 as a whole integrate the recited judicial exceptions into a practical application. A claim that recites a judicial exception [Prong One] is deemed to be directed to a judicial exception [Step 2A] unless the claim as a whole contains additional elements that integrat e the exception into a practical application [Prong Two]. A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception [MPEP § 2106.04(d) and MPEP § 2106.05(e) ]. A claim does not integrate a judicial exception into a practical application by reciting insignificant extra-solution activity , generally linking the exception to a particular technological environment or field of use , me rely reciting to apply the exception, merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea [ MPEP § 2106.04(d )(I)]. Insignificant extra-solution activities are nominal or tangential additions to a claim that are incidental to the primary process or product , including both pre-solution and post-solution activity (e.g. pr e-solution d ata gathering for use in a process ). If integrated into a practical application, the claim is eligible; otherwise, it is directed to the judicial exception, necessitating further analysis at Step 2B. Claims 1 and 25 recite the additional element of obtaining data results of a glucose response curve that is generated from an individual /a prediabetic individual. These limitations constitute insignificant extra-solution activities that do n ot integrate the judicial exception s into a practical application because they are data gathering steps that do not transform the nature of the claim into a patent-eligible application of the judicial exception . Additionally, the limitation of using a trained computational model to assess the underlying pathology is an additional element. The highly generalized “utilizing a trained computational model” acts as mere instructions to apply the judicial exceptions without improvement to the functioning of the computational model. Dependent claims 3 and 4 recite additional elements specifying that the glucose response curve is obtained from a continuous glucose monitor (CGM) or an oral glucose tolerance test (OGTT), respectively. These limitations simply narrow the insignificant extra-solution activit y of claim 1 because they relate to mere data gathering steps that do not integrate the judicial exceptions into a practical application. Dependent claim 15 recites an additional element of performing an additional clinical assessment based on the contribution of the underlying pathology, and dependent claim 16 specif ies that the additional clinical assessment is to confirm the assessment of the underlying pathology. Performing an additional clinical assessment to confirm the initial assessment is post-solution activity that does not transform an unpatentable principle into a patentable process , constituting insignificant extra-solution activity. MPEP § 2106.05(g ). Dependent claim 17 recites an additional element of administering a treatment to the individual based on the contribution of the underlying pathology of metabolic dysregulation. Dependent claim 31 recites an additional element of a dministering a treatment to the individual based on the contribution of the underlying pathology of metabolic muscular insulin resistance dysregulatio n. A dditional elements that apply or use the recited judicial exception to affect a particular treatment or prophylaxis for a disease or medical condition can integrate a judicial exception into a practical application. However, these claims do not provide a particular treatment to be administered, and are instead merely instructions to "apply" the judicial exception s in a generic way. Thus, the administration step of claim s 17 and 31 do not integrate the natural phenomenon and abstract ideas into a practical application. Dependent claims 18-21 recite additional elements that specify the underlying pathology contributing to the metabolic dysregulation and provide a general treatment to be administered for each pathology. The claims recite administering: an agent to improve insulin secretion ; an agent to improve insulin sensitivity ; an agent to decrease hepatic glucose production ; a GLP-1 receptor agonists or a DPP-4 inhibitor. Claims 18-20 do not provide a sufficiently particular treatment because they attempt to cover administering any agent that can improve insulin secretion/sensitivity or decrease hepatic glucose production, which equates to mere instructions to "apply" the judicial exception s in a generic way . However, claim 2 1 provides a particular treatment (GLP-1 receptor agonists or DPP-4 inhibitor ) to be administered when it is determined that impaired incretin effect contributes to an individual’s metabolic dysregulation. The additional element of claim 21 is sufficiently particular to integrate the judicial exceptions into a practical application. Thus, the administration step s of claims 18-20 do not integrate the natural phenomenon and abstract ideas into a practical application , while the administration step of claim 21 is particular and integrates the natural phenomenon and abstract ideas into a practical application . Dependent claims 22-24 recite specific treatments to be administered. Claim 22 recites a list of particular treatments that are known in the art to manage diabetes and prediabetes, which integrates the natural phenomenon and abstract ideas into a practical application . The treatment agents listed in claim 23 are particular, but not all agents have more than a nominal or insignificant relationship to the treatment or prevention of prediabetes or diabetes, such as chromium and omega-3 fatty acids . See Harvard Health Publishing , Harvard Medical School at para.1 (1 December 2019) ( Omega-3 fats don’t reduce the risk of diabetes or improve blood sugar contro l ), and Gijs Landman et al., in 5 World J Diabetes 160, (15 April 2014) . This step therefore does not apply or use the exception s in any meaningful way and does not integrate the natural phenomenon and abstract ideas into a practical application. The treatment recited in claim 24 includes a dietary alteration, an increase in exercise, or stress management , which are not sufficiently particular and do not integrate the natural phenomenon and abstract ideas into a practical application because the claim attempts to cover treatment with any alteration to diet, any increase in exercise, or any stress management technique. Dependent claim 26 recites the additional limitation specifying that the prediabetic individual has been diagnosed as prediabetic, and dependent claim 27 further specifies that the diagnosis is based upon HbA1c levels or fasting glucose levels. These limitations amount to per-solution activity of diagnosing an individual as prediabetic based on HbA1c/fasting glucose levels, which constitutes insignificant extra-solution activity that does not integrate the natural phenomenon and abstract ideas into a practical application . Dependent claim 32 recites an additional limitation specifying that the prediabetic individual is insulin resistant and providing for administration of an agent to improve insulin sensitivity along with a dietary alteration and an increase in exercise. Similarly, dependent claim 34 recites an additional limitation specifying that the prediabetic individual is insulin sensitive and providing for the administration of a dietary alteration and an increase in exercise without an agent to improve insulin sensitivity. The recited treatments ( agent to improve insulin sensitivity , dietary alteration , increase in exercise ) are not particular and do not integrate the natural phenomenon and abstract ideas into a practical application (see claims 18-20 and 24). Dependent claim 33 recites an additional limitation specifying that the agent to improve insulin sensitivity is a thiazolidinedione , which is particular and integrates the natural phenomenon and abstract ideas into a practical application . Claims 2, 5-14, and 28-30 do not recite any elements in addition to the recited judicial exceptions. Therefore, claims 21-22 and 33 contain additional elements that integrate the recited natural phenomenon and abstract ideas into a practical application [ Step 2A, Prong Two: Yes ], meaning the claims are not directed to a judicial exception and are eligible at Pathway B . However, claims 1-2 0 , 23-32, and 34 do not contain additional elements that integrate the recited natural phenomenon and abstract ideas into a practical application [ Step 2A, Prong Two: No ] , necessitating further analysis at Step 2B. Step 2B Claims 1-2 0 , 2 4 -32, and 34 do not include additional elements, whether considered individually or in combination, that are sufficient to amount to significantly more than the judicial exception s themselves . Claim 23 includes an additional element that is sufficient to amount to significantly more than the abstract ideas and natural phenomenon themselves. Under Step 2B, the claim is analyzed to determine whether there are any additional elements that, individually or in combination, constitute an “inventive concept" sufficient to ensure that the claim, as a whole, amounts to significantly more than the judicial exception itself . See MPEP § 2106.05; and Alice Corp. Pty. Ltd. v. CLS Bank Int'l , 573 U.S. 208, 217-18, 110 USPQ2d 1976, 1981 (2014). Claims 1 and 25 recite the additional elements of obtaining data results of a glucose response curve that is generated from an individual /a prediabetic individual and utilizing a trained computational model to assess the underlying pathology. Obtaining the data results is insignificant pre-solution activity that is well- understood, routine, and conventional in metabolic diagnostics. See Heather Hall , 16 PLoS Biol . e2005143, at 3 para.5 – 4 para.1 (24 July 2018); and Ismail, 61 Diabetologia 84, at 85 col.2 paras.2-3 (27 September 2017) . Utilizing the computational model is recited at such a high level of generality that it merely links the use of the recited judicial exceptions to a particular technological environment or field of use (computational models). As a whole, claims 1 and 25 amount to applying the judicial exceptions on generic computers with routine data inputs. There is no inventive concept that transforms the claims; they recite conventional diagnostic workflows that do not amount to significantly more. Claims 3 and 4 recite additional elements specifying that t he glucose response curve is obtained from a CGM/OGTT. These are clinical tests or devices for data gathering that are well-understood, routine, and conventional in metabolic assessments. Id . As a whole, claims 3 and 4 amount to pre-solution data gathering that is routine, providing no inventive concept. Claim 15 recites performing an additional clinical assessment based on the contribution of the underlying pathology of metabolic dysregulation . This constitutes generic follow-up testing that is well-understood, routine, and conventional in medicine. See Guerrero , 6(24) Ann. Transl. Med. at 2 col.2 para.2 (29 December 2018) . The claim as a whole amounts to conventional diagnostic escalation that does not constitute significantly more. C laim 16 specifies that t he additional clinical assessment is to confirm the assessment of the underlying pathology. This constitutes a verification step that is well-understood, routine, and conventional in clinical practice. Id . The claim as a whole amounts to routine confirmatory testing that does not constitute significantly more. Claims 17-20 , 24, 31-32, and 34 recite the following limitations, which are additional elements: Claim 17 recites administering a treatment to the individual based on the contribution of the underlying pathology of metabolic dysregulation. Claim 18 specifies beta cell dysregulation is determined to contribute to the metabolic dysregulation , and recites administering an agent to improve insulin secretion. Claim 19 specifies muscular insulin resistance is determined to contribute to the metabolic dysregulation, and recites administering an agent to improve insulin sensitivity. Claim 20 specifies h epatic insulin resistance is determined to contribute to the metabolic dysregulation, and recites administering an agent to decrease hepatic glucose production. Claim 24 recites that the treatment comprises a dietary alteration, an increase in exercise, or stress management. Claim 31 recites administering a treatment to the individual based on the contribution of the underlying pathology of metabolic muscular insulin resistance dysregulation . Claim 32 specifies that the prediabetic individual is insulin resistant and the individual is administered an agent to improve insulin sensitivity along with a dietary alteration and an increase in exercise. Claim 34 specifies that the prediabetic individual is insulin sensitive and the individual is administered a dietary alteration and an increase in exercise without administering an agent to improve insulin sensitivity. These claims amount to routine treatment steps that are well-understood, routine, and conventional. See Hideaki Kaneto et al., in 21 Int J Mol Sci. at 3 para.2 (11 December 2020) (discusses treating beta-cell dysfunction with glucagon-like peptide-1 receptor (GLP-1R) activators or dipeptidyl peptidase-IV (DPP-IV) inhibitors, which are known to improve insulin secretion); Marlou L. Dirks , in 600 J Physiol . 2273 col.3 para.2 , 2274 col.1 para.1 (12 April 2022) (discusses beta 2 - agonists, an agent that improves insulin sensitivity, as a promising treatment to improve muscle insulin resistance); Hana Alkhalidy et al., in 58 J Nutr Biochem . 90, Abstract (1 May 2018) (discusses kaempferol , an agent that reduces hepatic glucose production, to help treat hepatic insulin resistance); Sheri R Colberg et al., 39 Diabetes Care 2065, 2067 col.3 para.2 (11 October 2016) (d iscusses position of the ADA, which includes evidence that a dietary restriction and an increase in exercise are effective in treating/preventing diabetes and prediabetes); Fereshteh Zamani- Alavijeh et al., in 10 Diabetol Metab Syndr . Abstract Conclusion (8 May 2018) (using stress management interventions to treat diabetes) ; and Ralph A DeFronzo and Muhammad Abdul-Ghani , in 34(Suppl 2) Diabetes Care S202, S204 col.3 para.3 (discusses treating a prediabetic individual with metformin, an agent that improves insulin sensitivity) . The treatments are recited at a high level of generality and attempt to claim every mode of accomplishing that effect, which amounts to a claim that is merely adding the words "apply it" to the judicial exception . The claims as a whole do not confine the recited judicial exceptions into a particular, practical application that amount s to significantly more . Claim 23 recites an additional element of treatment comp rising alpha-lipoic acid, chromium, coenzyme Q10, garlic, hydroxychalcone (cinnamon), magnesium, omega-3 fatty acids, psyllium or vitamin D. The listed dietary supplements are not well-understood, routine, and conventional treatments for metabolic dysregulation, constituting an unc onventional step that confine the claim to a particular application [ Step 2 B : Yes ] . Claim 26 specifies that the prediabetic individual has been diagnosed as prediabetic , which is insignificant pre-solution activity that is well-understood, routine, and conventional in metabolic monitoring. See NIDDK, Recommended Tests for Identifying Prediabetes , NIH at paras.1-2 (October 2015) . Claim 27 specifies that the diagnosis is based upon HbA1c levels or fasting glucose levels , which are standard metrics that are well-understood, routine, and conventional. Id . Overall, claims 1-20, 24-32, and 34 amount to no more than insignificant extra-solution activities and implementing the abstract ideas and natural phenomenon on conventional computers in a routine way. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception itself because the claims recite additional elements that equate to insignificant extra-solution activity and mere instructions to apply the recited abstract ideas in a generic way or in a generic computing environment. Therefore, claims 1-20, 24-32, and 34 are rejected for failing to set forth patent eligible subject matter under 35 U.S.C. 101 because the claimed invention recites abstract ideas [ Step 2A, Prong One: Yes ] and the additional elements do not integrate the judicial exception into a practical application [ Step 2A, Prong Two: No ] and do not amount to claiming significantly more than the recited exception [ Step 2B: No ]. Claim Rejections - 35 USC § 102 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis ( i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. The following is a quotation of the appropriate paragraphs of pre-AIA 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a) the invention was known or used by others in this country, or patented or described in a printed publication in this or a foreign country, before the invention thereof by the applicant for a patent. Claims 1-8 and 25-28 are rejected under pre-AIA 35 U.S.C. 102 (a)(1) as being anticipated FILLIN "Insert either --clearly anticipated-- or--anticipated-- with an explanation at the end of the paragraph." \d "[ 3 ]" by Hall ( 16(7) PLoS Biol. e2005143 (24 July 2018) ). Regarding claim s 1 and 25 , Hall discloses a glucotype classification system and a classification model that can be used for identifying potential subphenotypes of glucose dysregulation. Abstract . Hall discloses obtaining the data results of a glucose response curve from individuals that are healthy, prediabetic, and diabetic. At 4 para.1; S2 Table ( obtaining data results of a glucose response curve that is generated from an individual/ a prediabetic individual ). Hall generates features from the data of the glucose response curve, including fasting blood sugar, OGTT at 2 hours, maximum glucose level, median glucose, and coefficient of variation. 18 paras.1-3 ( generating features from the data results of the glucose response curve ). Hall teaches utilizing the classification model to analyze the underlying physiology of specific patterns of glycemic responses . At 15 paras.2-3; 18 paras.3-4 ( assessing, utilizing a trained computational model, an underlying pathology of metabolic dysregulation ). Hall discloses that the model is trained to predict the entire glucose profile of an individual, at 18 para.4 , which indicates the underlying physiology of glucose dysregulation, at 14 para.1 ( wherein the trained computational model is trained to predict an indicator of the underlying pathology ). Regarding claim 2 , Hall teaches that the underlying physiology may be beta-cell dysfunction, muscle insulin resistance, liver insulin resistance, or incretin response, although Hall did not specifically quantify incretin response of hepatic insulin resistance. At 12 para.3 - 13 para.1 ( the method of claim 1, wherein the underlying pathology is muscular insulin resistance, beta cell dysfunction, impaired incretin effect, or hepatic insulin resistance ). Regarding claim 3 , Hall discloses that the glucose response curve data can be obtained from a continuous glucose monitor (CGM). At 15 para.5 ( t he method of claim 1, wherein the glucose response curve is obtained from a continuous glucose monitor (CGM) ). Regarding claim 4 , Hall discloses that the glucose response curve data can be obtained from an oral glucose tolerance test (OGTT). At 15 para.2 ( the method of claim 1, wherein the glucose response curve is obtained from an oral glucose tolerance test (OGTT) or an assessment involving administration of a glucose load ). Regarding claim 5 , Hall discloses that features for analysis are extracted from the glucose response curve data. At 15 paras.2 and 5 ( the method of claim 1, wherein the features are extracted from the data results of the glucose response curve ). Regarding claim 6 , Hall discloses that the features include glucose level at baseline (0 seconds) and at 120 minutes, at 15 para.2 , maximum glucose (peak) , median glucose (glucose level at 60 minutes for 2-hour OGTT) , and coefficient of variation , at 18 para.3 ( the method of claim 5, wherein the extracted features comprises at least one of the following: glucose level at 0 seconds (Go), glucose level at 60 minutes (G6o), glucose level at 120 minutes (G120), peak glucose level ( GPeak ), coefficient of variation (CV) ). Regarding claim 7 , Hall discloses generating a reduced representation of the glucose response curve data by smoothing and z-score normalizing the data. At 15 para.6 – 16 para.1 ( the method of claim 1 further comprising generating a reduced representation of the data results of the glucose response curve ). Regarding claim 8 , Hall discloses generating a reduced representation of the glucose response curve data by smoothing and z-score normalizing the data. At 15 para.6 – 16 para.1 ( the method of claim 7, wherein generating a reduced representation comprises smoothing and Z-normalizing the data results of the glucose response curve ). Regarding claim 26 , Hall discloses that 14 individuals were diagnosed as prediabetic. At 4 para.1; S2 Table ( t he method of claim 25, wherein the prediabetic individual has been diagnosed as prediabetic ). Regarding claim 27 , Hall discloses that the individuals were diagnose as prediabetic based on HbA1c levels or fasting blood glucose levels. Id ( t he method of claim 26, wherein the diagnosis is based upon HbA1c levels or fasting glucose levels ). Regarding claim 28 , Hall discloses that the underlying pathology can be muscle insulin resistance, which is indicated by a glucotype pattern that provides an indication of insulin resistance. At 12 para.3 – 13 para.1 ( t he method of claim 25, wherein the underlying pathology is muscular insulin resistance, and wherein the indicator of the underlying pathology provides an indication of insulin resistance ). Claim Rejections - 35 USC § 103 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis ( i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. Claim 9 is rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over Hall , as applied to claims 1-8 and 25-28 above, in view of Raschka ( Principal Component Analysis in 3 Simple Steps , (27 January 2015) ) and HXD ( Cross Validated (edited 13 April 2017) ) , as evidenced by Wicklin ( SAS Blogs (11 December 2013) ). Regarding claim 9 , Hall discloses that after the data is smoothed and z-score normalized, a Pearson’s correlation test is performed to determine the correlation between the clinical metabolic tests and the fraction of time spent in each glucotype class. At 6 para.3; Fig.3 caption . Hall constructs a heatmap (a graphical representation of a matrix, as evidenced by Wicklin , p ara.1 ) based on the correlations, Fig.4; S3 Fig. , and performs a principal component analysis to extract top principals , at 7 para. 1 . While Hall discusses projecting matrices into the eigenvector space, at 17 para.6 , Hall does not explicitly teach principal component analysis via eigen-decomposition of a covariance matrix of the smoothed and z-normalized data. However, Raschka teaches that principal component analysis occurs via eigendecomposition of a covariance or correlation matrix. § 1 - Eigendecomposition - Computing Eigenvectors and Eigenvalues . Additionally, z-score normalization of data will result in a correlation matrix as opposed to a covariance matrix, as taught by HXD , para.1 . Therefore, a person having ordinary skill in the art would understand that Hall performs a principal component analysis to extract top principals via eigendecomposition of a correlation matrix , which is a covariance matrix of z-score normalized data ( the method of claim 8 further comprising extracting one or more top principal components via eigen-decomposition of a covariance matrix of the smoothed and Z- normalized data results of the glucose response curve ). Claim 10 is rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over Hall , as applied to claims 1-8 and 25-28 above, in view of Wang ( 21:105 BMC Med Inform Decis Mak . (20 March 2021) ). Regarding claim 10 , Hall does not explicitly state if the classification model is a Gaussian process classifier (GPC), a support vector machine with a radial basis function kernel (SVM-RBF), a support vector machine with a linear kernel (SVM-linear), a logistic regression with L1 regularization (LR-L1), or a logistic regression with L2 regularization (LR-L2). H owever, Wang discloses a method of identifying individuals at high risk for diabetes using a predictive classification model , Abstract , and t eaches of common single classification algorithm s such as logistic regression and support vector machines (SVM) , at 2 col.1 para.2 . Wang discloses that logistic regression can have L1 or L2 regularization, at 5 col.2 para.2 , and SVMs can have linear, RBF, or sigmoid kernels , Table 3 . Wang discloses that after feature selection, none of the models demonstrated superior performance on all evaluation indicators. At 9 col.2 para.2 . A person having ordinary skill in the art could pursue the classification models identified by Wang to implement the method of Hall when Hall did not disclose a specific classification model. One of ordinary skill in the art would reasonably expect at least one of the disclosed classification models to be successful depending on the features selected because Wang demonstrated that the models have various levels of success based on the features selected. “Obvious to try” – choosing from a finite number of identified, predictable solutions, with a reasonable expectation of success is likely to be obvious. See KSR International Co. v. Teleflex Inc. , 550 U.S. 398, 415-421, USPQ2d 1385, 1395 – 97 (2007) ( see MPEP § 2143, E). Claim s 11-17, 19-22, and 29-31 are rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over Hall , as applied to claims 1-8 and 25-28 above, in view of Abdul-Ghani ( 29(5) Diabetes Care . 1130, 1130-9 (1 May 2006) ) , as evidenced by Kim ( 37 Korean J Fam Med . 188, 189 (11 January 2016) ) , Stanford ( Prediabetes (October 2019) ) , and Hunter ( 24(9) Nat Med . (27 August 2018) ). Regarding claim s 11 and 29 , Hall discloses performing a principal component analysis to assess the correlation between dominant glycemic signature class and current diagnostics using clinical tests and CGM metrics . At 18 para. 3 . Hall correlates each glycemic signature class with average clinical metrics , a t S4 Table caption , but Hall fails to explicitly teach determining a contribution of the underlying pathology of metabolic dysregulation based on a deviance from a healthy underlying pathology . However, Abdul-Ghani discloses a method of assessing the primary defect (beta-cell dysfunction, muscle insulin resistance, hepatic insulin resistance) contributing to impaired glucose tolerance (IGT) and impaired fasting glucose (IFG). Abstract . Abdul -Ghani teaches that OGTT measurements are used to derive indexes of insulin sensitivity and insulin secretion that reflect muscle insulin resistance, hepatic insulin resistance , incretin effect , and beta-cell function . At 1131 col.3 paras.1-2 ; at 1133 col.1 para.2 . The index values from individuals with IGT or IFG are compared with the index values from individuals with normal glucose tolerance (NGT), at 1133 col. 1 para. 4 – col.2 para.1 , to identify the predominant underlying physiological process es of IGT and IFG, at 1135 col.3 para.2 . Abdul-Ghani notes that a clearer understanding of the pathophysiologic abnormalities which characterize IGT and IFG provides insights about interventions to slow/halt the progression to type 2 diabetes . At 1136 col.1 para.2 . Additionally, Kim discloses that clinical metrics that directly assess insulin sensitivity or secretion have limitations including higher cost and more invasive procedures, prompting the use of various indirect indices of insulin sensitivity or secretion. At 189 col.1 para.2 . Hall discloses a base method of assessing the underlying pathology of metabolic dysregulation , and provides a correlation between glycemic signatures and clinical metrics . Abdul-Ghani discloses a technique of deriving index values from a glucose curve to assess the underlying pathology of IGT and IFG in order to provide effective interventions/treatments. A person having ordinary skill in the art would recognize that Abdul-Ghani ’s technique of deriving index values could be applied to Hall’s method of assessing an underlying pathology of metabolic dysregulation to yield a method of deriving index values to assess the underlying pathology of metabolic dysregulation. One of ordinary skill in the art would reasonably expect the result to be an improved method of assessing the underlying pathology of metabolic dysregulation because deriving indices reduces costs and the necessity of invasive procedures as compared to direct clinical metrics. Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to apply the technique of deriving index values to Hall’s method of assessing the underlying pathology of metabolic dysregulation. Moreover, Abdul-Ghani discloses that the underlying pathology can be muscle insulin resistance; thus, it would have been obvious to a person of ordinary skill in the art to apply the technique of deriving index values that reflect muscle insulin resistance to Hall’s method of stratifying a prediabetic individual based on an underlying pathology of metabolic dysregulation . Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results is likely to be obvious. See KSR International Co. v. Teleflex Inc. , 550 U.S. 398, 415-421, USPQ2d 1385, 1395 – 97 (2007) ( see MPEP § 2143, D ). Regarding claim s 12 and 30 , Abdul -Ghani teaches that index values from individuals with IGT or IFG are compared with the index values from individuals with normal glucose tolerance (NGT), at 1133 col.1 para.4 – col.2 para.1 , to identify the predominant underlying physiological process of IGT and IFG, at 1135 col.3 para.2 ( wherein the deviance from the healthy underlying pathology is determined by an average underlying pathology score from a collection of individuals ). Abdul-Ghani discloses that the underlying pathology can be muscle insulin resistance . At 1133 col.2 para.3 – col.3 para.1 . Individuals with IGT and IFG are prediabetic, as evidenced by Stanford . § What is prediabetes ? ( t he method of claim 29, wherein the deviance from the healthy muscular insulin resistance underlying pathology is determined by an average insulin resistance score from a collection of prediabetic individuals ). Regarding claim 13 , Abdul -Ghani compares individuals with IGT or IFG to individuals with NGT. At 1133 col.1 para.4 – col.2 para.1 . Additionally, Hall separates participants by their overall metabolic assessment, resulting in three collections of individuals (healthy, diabetic, and prediabetic). At 4 para.1 ( t he method of claim 12, wherein each individual of the collection of individuals has a similar overall metabolic assessment ). Regarding claim 14 , Abdul -Ghani teaches that the indexes derived from the OGTT identify the predominant underlying physiological process es. At 1131 col.3 paras.1-2; at 1133 col.1 para.2 ( the method of claim 11, wherein the determination of the contribution of the underlying pathology of metabolic dysregulation based on a deviance from a healthy pathology identifies a dominant underlying pathology of metabolic dysregulation ). Regarding claim 15 , Abdul -Ghani does not explicitly teach performing an additional clinical assessment based on the contribution of the underlying pathology of metabolic dysregulation. However, Abdul -Ghani correlates glucose profiles to the pathophysiologic abnormalities responsible, and indicates how the pathophysiologic abnormalities can be measured (e.g. muscle insulin sensitivity measured with insulin clamp ). At 1135 col.3 para.3 . Abdul -Ghani discloses that the underlying physiological processes can be quantitated , at 1133 col.3 para.3 , but notes that some individuals may present with index values considered to be within a normal range despite having IGT or IFG , at 1135 col.2 para.2 . A person having ordinary skill in the art would be motivated to modify the method of Abdul -Ghani to include performing an additional clinical assessment based on the index values to prevent a misdiagnosis from an uncharacteristic value. One of ordinary skill in the art would reasonably expect this modification to succeed in avoiding a misdiagnosis because the indicated pathophysiologic abnormalit y can be confirmed or rejected as the underlying physiological process after performing the specific test for that abnormality. Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art teachings to arrive at the claimed invention is likely to be obvious. See KSR International Co. v. Teleflex Inc. , 550 U.S. 398, 415-421, USPQ2d 1385, 1395 – 97 (2007) ( see MPEP § 2143, G ). Regarding claim 16 , a person having ordinary skill in the art would be motivated to modify the method of Abdul -Ghani to include performing an additional clinical assessment to confirm or reject the indicated underlying physiological process ( t he method of claim 15, wherein the additional clinical assessment is to confirm the assessment of the underlying pathology ). Regarding claim 17 , Abdul -Ghani does not explicitly administer a treatment to the individual based on the contribution of the underlying pathology of metabolic dysregulation. However, Abdul -Ghan i discloses that the indicated underlying physiological process provides insights about the most suitable interventions to slow/halt the progression of the glucose dysregulation. At 1136 col.1 para.2 . Abdul-Ghani notes that individuals who manifest predominant hepatic insulin resistance are most likely to benefit from agents that reduce hepatic insulin resistance (e.g., metformin) , subjects who predominantly have muscle insulin resistance are more likely to respond to agents that improve skeletal muscle insulin resistance (e.g., peroxisome proliferator–activated receptor-γ agonists) , and subjects with impaired incretin effect are more likely to respond to an insulin secretagogue