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 .
Applicant's response filed 1/15/2026 has been fully considered. The following rejections
and/or objections are either reiterated or newly applied.
Status of Claims
Claims 1-17 and 19-22 pending.
Claim 18 canceled.
Claims 21-22 newly added.
Claims 1-17 and 19-22 examined on the merits.
Priority
The instant application is a 371 national stage entry of PCT/EP2020/073771 filed on 8/25/2020, and claims the benefit of foreign priority to EP Application No. 19193619.4 filed on 8/26/2019. Thus, the effective filing date of the claims is 8/26/2019.
The applicant is reminded that amendments to the claims and specification must comply with 35 U.S.C. § 120 and 37 C.F.R. § 1.121 to maintain priority to an earlier-filed application. Claim amendments may impact the effective filing date if new subject matter is introduced that lacks support in the originally filed disclosure. If an amendment adds limitations that were not adequately described in the parent application, the claim may no longer be entitled to the priority date of the earlier filing.
Claim Objections
The objection to claim 1 withdrawn in view of Applicant's claim amendments filed on 1/15/2026.
Withdrawn Rejections
35 USC § 112(b)
The rejection of claims 5, 12, 16, and 19 under 35 U.S.C. 112(b) withdrawn in view of Applicant's claim amendments filed on 1/15/2026.
35 USC § 112(d)
The rejection of claim 18 under 35 U.S.C. 112(d) withdrawn in view of Applicant's claim amendments (claim 18 canceled) filed on 1/15/2026.
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 1-17 and 19-22 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of a mental process, a mathematical concept, organizing human activity, or a law of nature or natural phenomenon without significantly more. In accordance with MPEP § 2106, claims found to recite statutory subject matter (Step 1: YES) are then analyzed to determine if the claims recite any concepts that equate to an abstract idea, law of nature or natural phenomenon (Step 2A, Prong 1). In the instant application, the claims recite the following limitations that equate to an abstract idea:
Claim 1 and 21-22: “c) deriving a similarity value by a step of comparing said sample spectrum to at least one reference spectrum obtained from at least one reference sample by measuring as defined in step b), d) assigning a clinical parameter to the analysis sample based on said similarity value” provides a comparison (a comparison step involves assessing similarities or differences between items) that may be performed in the human mind and is therefore considered a mental process, which is an abstract idea.
Claim 5: “calculating the nᵗʰ derivative of the spectrum” provides a mathematical calculation (calculating the nth derivative of the spectrum involves mathematical calculation) that is considered a mathematical concept, which is an abstract idea.
Claims 7-10: “an algorithm is used for deriving the similarity value in the comparison step” (claim 7), “the algorithm is a machine learning model selected from the group consisting of neural networks, support vector machines, discriminant analysis, k-nearest neighbors algorithm, regression analysis, evolutionary- based algorithms, regression and decision tree learning, adaptive boosting, and combination thereof (claim 8), “the algorithm is based on principal component analysis-linear discriminate analysis (PCA- LDA) or principal component analysis-Mahalanobis discriminate analysis (PCA-MDA)” (claim 9), and “the algorithm is trained” (claim 10) provides a mathematical calculations (training the algorithm of claims 7-9 which provide specific mathematical formula names) that is considered a mathematical concept, which is an abstract idea.
These recitations are similar to the concepts of collecting information, analyzing it, and displaying certain results of the collection and analysis in Electric Power Group, LLC, v. Alstom (830 F.3d 1350, 119 USPQ2d 1739 (Fed. Cir. 2016)), organizing and manipulating information through mathematical correlations in Digitech Image Techs., LLC v Electronics for Imaging, Inc. (758 F.3d 1344, 111 U.S.P.Q.2d 1717 (Fed. Cir. 2014)) and comparing information regarding a sample or test to a control or target data in Univ. of Utah Research Found. v. Ambry Genetics Corp. (774 F.3d 755, 113 U.S.P.Q.2d 1241 (Fed. Cir. 2014)) and Association for Molecular Pathology v. USPTO (689 F.3d 1303, 103 U.S.P.Q.2d 1681 (Fed. Cir. 2012)) that the courts have identified as concepts that can be practically performed in the human mind or are mathematical relationships. Therefore, these limitations fall under the “Mental process” and “Mathematical concepts” groupings of abstract ideas. Additionally, while claims 16, 19, and 21 recite performing some aspects of the analysis on “a non-transitory computer-readable medium containing instructions for performing step c)" or “A system, comprising: [] a non-transitory storage medium having stored therein instructions that are executable by the one or more hardware processors to perform a method for analyzing”, there are no additional limitations that indicate that this requires anything other than carrying out the recited mental processes or mathematical concepts in a generic computer environment. Merely reciting that a mental process is being performed in a generic computer environment does not preclude the steps from being performed practically in the human mind or with pen and paper as claimed. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental processes” grouping of abstract ideas. As such, claims 1-17 and 19-22 recite an abstract idea (Step 2A, Prong 1: YES).
Claims found to recite a judicial exception under Step 2A, Prong 1 are then further analyzed to determine if the claims as a whole integrate the recited judicial exception into a practical application or not (Step 2A, Prong 2). The judicial exceptions listed above are not integrated into a practical application because the claims do not recite an additional element or elements that reflects an improvement to technology. Specifically, the claims recite the following additional elements:
Claim 1 and 21-22: “a) providing an analysis sample from the subject, wherein the analysis sample is based on the peritoneal dialysis effluent of said subject” provides insignificant extra-solution activities (collecting samples is a pre-solution activity involving sample manipulation steps) that do not serve to integrate the judicial exceptions into a practical application.
“b) measuring a sample spectrum of the analysis sample in a spectral range of from 4000 cm-1 to 400 cm-1 in a spectroscopy step applying Fourier-Transform-Infrared (FTIR) spectroscopy” provides insignificant extra-solution activities (measuring sample spectra are pre-solution activities involving data gathering steps) that do not serve to integrate the judicial exceptions into a practical application.
Claim 3: “said spectrum in step b) is obtained by either applying FTIR transmission sample technique, wherein in step a) the sample is dried, or applying FTIR attenuated total reflection (ATR), wherein in step a) the sample is provided as liquid or dried” provides insignificant extra-solution activities (obtaining spectrum data are pre-solution activities involving data gathering steps) that do not serve to integrate the judicial exceptions into a practical application.
Claim 10: “a set of reference spectra obtained by measuring a plurality of reference samples as defined in step b)” provides insignificant extra-solution activities (measuring reference sample spectra are pre-solution activities involving data gathering steps) that do not serve to integrate the judicial exceptions into a practical application.
Claims 16 and 19: “the comparison step is performed using a non-transitory computer-readable medium containing instructions for performing step c)" provides insignificant extra-solution activities (running instructions on generic computer components) that do not serve to integrate the judicial exceptions into a practical application.
Claim 17: “the analysis sample is prepared by diluting the peritoneal dialysis effluent and/or freezing and thawing the peritoneal dialysis effluent” provides insignificant extra-solution activities (sample preparation is a pre-solution activity involving sample manipulation steps) that do not serve to integrate the judicial exceptions into a practical application.
Claim 21: “A system, comprising: [] a non-transitory storage medium having stored therein instructions that are executable by the one or more hardware processors to perform a method for analyzing” provides insignificant extra-solution activities (running instructions on generic computer components) that do not serve to integrate the judicial exceptions into a practical application.
The steps for: collecting, preparing, and measuring samples and obtaining data are insignificant extra-solution activities that do not serve to integrate the recited judicial exceptions into a practical application because they are pre- and post-solution activities involving sample and data gathering and manipulation steps (see MPEP 2106.04(d)(2)). Furthermore, the limitations regarding implementing program instructions do not indicate that they require anything other than mere instructions to implement the abstract idea in a generic way or in a generic computing environment. As such, this limitation equates to mere instructions to implement the abstract idea on a generic computer that the courts have stated does not render an abstract idea eligible in Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983. See also 573 U.S. at 224, 110 USPQ2d at 1984. Therefore, claims 1-17 and 19-22 are directed to an abstract idea (Step 2A, Prong 2: NO).
Claims found to be directed to a judicial exception are then further evaluated to determine if the claims recite an inventive concept that provides significantly more than the judicial exception itself (Step 2B). The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims recite additional elements that are insignificant extra-solution activities that do not serve to integrate the recited judicial exceptions into a practical application, or equate to mere instructions to apply the recited exception in a generic way or in a generic computing environment.
As discussed above, there are no additional elements to indicate that the claimed “non-transitory computer-readable medium containing instructions for performing step c)" or “system, comprising: [] a non-transitory storage medium having stored therein instructions that are executable by the one or more hardware processors to perform a method for analyzing" requires anything other than generic computer components in order to carry out the recited abstract idea in the claims. Claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. MPEP 2106.05(f) discloses that mere instructions to apply the judicial exception cannot provide an inventive concept to the claims. Additionally, the limitations for collecting, preparing, and measuring samples and obtaining data are insignificant extra-solution activities that do not serve to integrate the recited judicial exceptions into a practical application. Furthermore, no inventive concept is claimed by these limitations as they are demonstrated to be well-understood, routine, and conventional.
The additional elements do not comprise an inventive concept when considered individually or as an ordered combination that transforms the claimed judicial exception into a patent-eligible application of the judicial exception. Therefore, the claims do not amount to significantly more than the judicial exception itself (Step 2B: No). As such, claims 1-17 and 19-22 are not patent eligible.
Response to Arguments under 35 USC § 101
Applicant’s arguments filed 1/15/2026 are fully considered but they are not persuasive.
Applicant asserts that “steps (a) and (b) - clearly represent non-abstract method steps” because step (a) provides a PDE sample and step (b) involves applying FTIR spectroscopy, and further that "the step of measuring a sample spectrum goes beyond standard preparatory measures" (Remarks 1/15/2026 Pages 4-5). Examiner notes that FTIR is indeed a standard preparatory measure for untargeted analyte probing that is well-understood, routine, and conventional as evidenced by: Jackson et al. (Jackson et al. "The use and misuse of FTIR spectroscopy in the determination of protein structure." Critical reviews in biochemistry and molecular biology 30.2 (1995): 95-120), page 1 Abstract "Fourier transform infrared (FTIR) spectroscopy is an established tool for the structural characterization of proteins"; and Movasaghi et al. (Movasaghi et al. "Fourier transform infrared (FTIR) spectroscopy of biological tissues." Applied spectroscopy reviews 43.2 (2008): 134-179), page 3 last paragraph "Recently, spectroscopy has emerged as one of the major tools for biomedical applications and has made significant progress in the field of clinical evaluation. Research has been carried out on a number of natural tissues using spectroscopic techniques, including FTIR spectroscopy".
Applicant also asserts that the step of deriving a similarity value of spectral data is too complex to be performed in the human mind, or by a human using pen and paper because the data is comprised of hundreds of data points representing molecular vibrations (Remarks 1/15/2026 page 6). Examiner notes that the judicial exception of a comparison step involving assessing similarities or differences in spectral data can indeed be practically performed in the human mind or by a human using pen a paper because by Applicant's own admission "The claimed method is preferably rooted in statistically sound comparison" (Remarks 1/15/2026 page 6), the basis of which rests upon what has been performed by a human mind. There is nothing in the cited "algorithm" (even the evaluation of non-visual features such as peak slopes and minor intensity variations) precluding a human mind from performing said comparisons instead of a machine learning model, which is not part of claim 1 to begin with and is first mentioned in claim 8. Therefore, claim 1 is directed to a judicial exception.
The Examiner further notes that MPEP 2106(I) states that if the claims are directed to a judicial exception, the second part of the Mayo test is to determine whether the claim recites additional elements that amount to significantly more than the judicial exception. Id. citing Mayo, 566 U.S. at 72-73, 101 USPQ2d at 1966). In the “search for an ‘inventive concept’” (the second part of the Alice/Mayo test), the additional elements identified do not comprise an inventive concept when considered individually or as an ordered combination that transforms the claimed judicial exception into a patent-eligible application of the judicial exception because obtaining and measuring data - even "complex" data from an FTIR spectrometer - (data gathering and manipulation steps) are all well-understood, routine, and conventional techniques that are insignificant extra-solution activities that do not serve to integrate the recited judicial exceptions into a practical application. Therefore, combining insignificant extra-solution activities with any of the identified judicial exceptions would not result in patent eligible subject matter because integrating well-understood, routine, and conventional techniques does not yield “significantly more” to a mental process, a mathematical concept, organizing human activity, or a law of nature or natural phenomenon.
Therefore, the rejection of claims 1-17 and 19-22 under 35 USC 101 is maintained or newly applied. All other claims depend from these independent claims; therefore, their rejection is likewise maintained.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-7, 9-10, 16-17, and 21 rejected under 35 U.S.C. 103 as being unpatentable over Sultan et al. (Sultan et al., "Recirculating peritoneal dialysis system using urease-fixed silk fibroin membrane filter with spherical carbonaceous adsorbent." Materials Science and Engineering: C 97 (2019): 55-66) in view of Khanmohammadi et al. (Khanmohammadi et al., "Diagnostic prediction of renal failure from blood serum analysis by FTIR spectrometry and chemometrics." Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 136 (2015): 1782-1785).
Regarding claims 1, 16, and 21, Sultan teaches (step a) providing an analysis sample from a subject, wherein the subject is subjected to peritoneal dialysis and the analysis sample is based on the peritoneal dialysis effluent of said subject (Abstract "In this study, we designed the wearable artificial kidney (WAK) system for peritoneal dialysis (PD) using urease-immobilized silk fibroin (SF) membrane and polymer-based spherical carbonaceous adsorbent (PSCA).", Page 4 section 2.10 "To evaluate the filtration capability of uremic toxins filtering kit, the effluent dialysate was passed through the micropump at a flow rate of 2 ml/min.", and page 4 section 2.11 describes the process of collecting the PD sample from subjects.).
Sultan also teaches (step b) measuring a sample spectrum of the analysis sample in a spectral range from 4000 cm-1 to 400 cm-1 in a spectroscopy step applying Fourier-Transform-Infrared (FTIR) spectroscopy (Abstract "We evaluated this kit's removal abilities of uremic toxins such as urea, creatinine, uric acid, phosphorus, and β2-microglobulin from the dialysate of end-stage renal disease (ESRD) patients in vitro." and Page 4 Section 2.8 "To qualitatively analyze the enzyme-grafted membrane surfaces, ATR-FTIR analysis was performed using an FTIR spectrometer (Frontier, PerkinElmer, UK). The membranes were ground to particle sample size and the frequency range from 400 to 4000 cm−1 with a 4 cm−1 resolution.").
Sultan does not explicitly teach determining, in a comparison step, a similarity value by comparing said sample spectrum to at least one reference spectrum obtained from at least one reference sample by measuring as defined in step b), nor assigning a clinical parameter to the analysis sample based on said similarity value.
However, Khanmohammadi teaches (step c) determining, in a comparison step, a similarity value by comparing said sample spectrum to at least one reference spectrum obtained from at least one reference sample by measuring as defined in step b) (Page 3 col 1 paragraph 2 "LDA [Linear discriminant analysis] aims to produce a linear classifier which can successfully classify two classes. [] LDA uses these functions to assign unknown objects to classes. LDA classification is based on the Mahalanobis distance that is derived from a common covariance matrix for all classes", a "distance" is a kind of similarity value, and a classification model requires the use of reference (or training) data.).
Khanmohammadi also teaches (step d) assigning a clinical parameter to the analysis sample based on said similarity value (Page 2 col 1 paragraph 1 "In this research, a new method based on a Fourier transform infrared spectroscopy and filtered spectra with advanced computer-aided pattern recognition by QDA has been applied to propose a rapid and reliable blood serum test for diagnosis of renal failure and other kidney damages which may increase the concentration of urea and creatinine in blood serum.", renal failure and other kidney damages are an outcome - a kind of clinical parameter).
Additionally, while Sultan nor Khanmohammadi explicitly teach or suggest analyzing a peritoneal dialysis analysis sample using FTIR, it would have been obvious to one of ordinary skill in the art because combining known elements of prior art is obvious when the combination is predictable (MPEP 2144). Furthermore, applying known techniques (FTIR) to known materials (PD analyte) is obvious because the technique is recognized as suitable for the purpose of analyzing an effluent sample (MPEP 2144.07), as evidenced by Derenne et al. and Lopes et al. (Derenne et al. "Lipid quantification method using FTIR spectroscopy applied on cancer cell extracts." Biochimica et Biophysica Acta (BBA)-Molecular and Cell Biology of Lipids 1841.8 (2014): 1200-1209; Lopes et al. "FTIR and Raman spectroscopy applied to dementia diagnosis through analysis of biological fluids." Journal of Alzheimer’s Disease 52.3 (2016): 801-812).
Therefore, it would have been obvious to one of ordinary skill in the art as of the effective filing date of the claimed invention to modify the methods of Sultan as taught by Khanmohammadi in order to better detect patterns in the FTIR data (Khanmohammadi, Page 3 col 1 paragraph 2 "Linear discriminant analysis (LDA) is a useful method for pattern recognition. LDA was originally proposed by Fisher [14–16] and is applied very often in chemometrics."). One skilled in the art would have a reasonable expectation of success because both methods are analyzing FTIR data from renal samples.
Regarding claim 2, Sultan in view of Khanmohammadi teach the methods of Claim 1 on which this claim depends. Sultan also teaches in step a) the analysis sample is the peritoneal dialysis effluent or wherein the analysis sample is prepared from the peritoneal dialysis effluent (Abstract "We evaluated this kit's removal abilities of uremic toxins such as urea, creatinine, uric acid, phosphorus, and β2-microglobulin from the dialysate of end-stage renal disease (ESRD) patients in vitro." and page 4 section 2.10 "To evaluate the filtration capability of uremic toxins filtering kit, the effluent dialysate was passed through the micropump at a flow rate of 2 ml/min.").
Regarding claim 3, Sultan in view of Khanmohammadi teach the methods of Claim 1 on which this claim depends. Sultan also teaches said spectrum in step b) is obtained by either applying FTIR transmission sample technique, wherein in step a) the sample is dried, or applying FTIR attenuated total reflection (ATR), wherein in step a) the sample is provided as liquid or dried (Page 3 Figure 1 shows the preparation of samples (a series of steps for drying) prior to FTIR-ATR).
Regarding claim 4, Sultan in view of Khanmohammadi teach the methods of Claim 1 on which this claim depends. Sultan also teaches in step b) the sample spectrum is measured in at least one of the spectral ranges selected from the group consisting of from 3000 cm-1 to 2800 cm-1 (fatty acid region), from 1500 cm-1 to 1200 cm-1 (mixed region protein + fatty acid), from 1800 cm-1 to 1500 cm-1 (protein region), from 1200 cm-1 to 800 cm-1 (polysaccharide region), from 1800 cm-1 to 800 cm-1 and combinations thereof (Figure 6 shows FTIR analysis ranging from 4000cm-1 to 500cm-1, which encompasses all limitation ranges of the claim).
Regarding claim 5, Sultan in view of Khanmohammadi teach the methods of Claim 1 on which this claim depends. Khanmohammadi also teaches in step c) the comparison step includes pre-processing of the sample spectrum (Page 3 col 1 last paragraph "Filters are usually used as a pre-processing step since they are simple and fast. A widely-used filtering approach is to apply a univariate criterion separately on each feature and assume no interaction between features. This method relies on simple statistic hypothesis tests which assume that the data are independently sampled from a normal distribution. As a result, t-test is applied on each feature and p-value (or the absolute values of t-statistics) is compared for each feature as a measure of its effectiveness in separating groups").
Regarding claims 6 and 7, Sultan in view of Khanmohammadi teach the methods of Claim 1 on which these claims depend. Khanmohammadi also teaches the similarity value is a numerical variable and/or categorical variable, and in the comparison step c) an algorithm is used to determine the similarity value in the comparison step (Page 3 col 1 paragraph 2 "LDA uses these functions to assign unknown objects to classes. LDA classification is based on the Mahalanobis distance that is derived from a common covariance matrix for all classes", as distance is a numerical value, the comparison algorithm is LDA classification based on Mahalanobis distance which is a kind of similarity value).
Regarding claim 9, Sultan in view of Khanmohammadi teach the methods of Claim 6 on which this claim depends. Khanmohammadi also teaches the algorithm is based on principal component analysis-linear discriminate analysis (PCA- LDA) or principal component analysis-Mahalanobis discriminate analysis (PCA-MDA) (Page 2 col 1 paragraph 1 "Advanced statistical chemometric techniques such as principal component analysis (PCA), factor analysis (FA), linear discriminant analysis (LDA), canonical discriminant analysis (DA), end-member analysis, cluster analysis (CA) and neural network (NN) have been applied in many researches and their capabilities in interpreting complex data have been discussed.").
Regarding claim 10, Sultan in view of Khanmohammadi teach the methods of Claim 7 on which this claim depends. Khanmohammadi also teaches the algorithm is trained with a set of reference spectra obtained by measuring a plurality of reference samples as defined in step b) (Page 3 col 1 paragraph 3 "In this work, QDA was performed on 30 samples of training and the results of the test set were compared to the standard approach.").
Regarding claim 17, Sultan in view of Khanmohammadi teach the methods of Claim 2 on which this claim depends. Sultan also teaches the analysis sample is prepared by diluting the peritoneal dialysis effluent and/or freezing and thawing the peritoneal dialysis effluent (Page 2 section 2.2 "The final concentration of SF [silk fibroin] in aqueous solution was 16 wt%. 10% concentrated SF solutions were prepared by diluting the 16% SF sample with distilled water. SF solutions were stored at 4 °C before use to avoid premature precipitation", the SF contained the filtered PD effluent.).
Claims 8, 11-14, 19, and 22 rejected under 35 U.S.C. 103 as being unpatentable over Sultan et al. (Sultan et al., "Recirculating peritoneal dialysis system using urease-fixed silk fibroin membrane filter with spherical carbonaceous adsorbent." Materials Science and Engineering: C 97 (2019): 55-66) in view of Khanmohammadi et al. (Khanmohammadi et al., "Diagnostic prediction of renal failure from blood serum analysis by FTIR spectrometry and chemometrics." Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 136 (2015): 1782-1785) as applied to claims 1-7, 9-10, 16-17, and 21 above, and further in view of Zhang et al. (Zhang et al., "Machine-learning algorithms define pathogen-specific local immune fingerprints in peritoneal dialysis patients with bacterial infections." Kidney international 92.1 (2017): 179-191).
Sultan et al. in view of Khanmohammadi et al. are applied to claims 1-7, 9-10, 16-17, and 21.
Regarding claim 8, Sultan in view of Khanmohammadi teach the method of Claim 7 on which this claim depends.
Sultan nor Khanmohammadi explicitly teach the machine learning model is selected from the group consisting of neural networks, support vector machines, discriminant analysis, k-nearest neighbors algorithm, regression analysis, evolutionary-based algorithms, regression and decision tree learning, adaptive boosting, and combination thereof.
However, Zhang teaches applying random forests, SVMs, ANNs (Page 12 Supplemental Material Figure S1 "Local immune fingerprints in Gram-positive infections. (A) Performance of Random Forest (RF), Support Vector Machine (SVM), and artificial neural network (ANN)–based feature elimination models for the prediction of Gram-positive infections (N = 47) against all other episodes of peritonitis (N = 36), shown as area under the curve (AUC) depending on the number of biomarkers).
Therefore, it would have been obvious to one of ordinary skill in the art as of the effective filing date of the claimed invention to modify the methods of XXX and YYY as taught by ZZZ in order to in address the complexity of the molecular data, and efficiently finding the best feature combination for classification (Zhang, Page 2 col 1 paragraph 2 "The introduction of “big data” technologies in biomedical sciences to address the complexity of the molecular and cellular mechanisms underlying disease has brought about an increasing need for advanced statistical models, machine learning, and pattern recognition techniques. In particular, wrapped feature selection methods have proved highly efficient for finding the best feature combination compared with time-consuming exhaustive searches"). One skilled in the art would have a reasonable expectation of success because both approaches are concerned with analyzing PD samples.
Regarding claims 11 and 13, Sultan in view of Khanmohammadi teach the methods of Claim 1 on which these claims depend. Zhang also teaches: the clinical parameter is selected from the group consisting of demographic parameters, physiological and pathological parameters including biomarker concentration, dialysis-related parameters, and outcome parameters; and the clinical parameter is a dialysis-related parameter selected from the group of residual urine output, ultrafiltration, residual clearance, dialysate-to-plasma creatinine ratio, residual glomerular filtration rate, peritoneal small solute transport rate, mass transfer area coefficient, effective lymphatic absorption rate, transcapillary ultrafiltration rate, free water transport, and sodium dip (Page 10 col 2 "Being based on a relatively small population in a single hospital, the biomarkers identified in this study and the corresponding algorithms now await external validation in larger patient cohorts at multiple sites in order to demonstrate the applicability of the chosen approach to other centers where the spectrum of the infecting organisms and the previous infection history as well as patient demographics and health care settings may vary. Validated biomarker combinations can then be incorporated into appropriate diagnostic tests to be used in central laboratories or at the point of care and into new patient management and treatment guidelines based on such test results. The final choice of biomarkers to be taken forward will depend on the desired performance requirements, with soluble proteins being equally suitable for automated immunodiagnostic analyzers and bedside or home tests, whilst assessments of immune cell subsets such as Vg9/Vd2 T cells would require standardized flow cytometric protocols").
Regarding claim 12 and 22, Sultan in view of Khanmohammadi and Zhang teach the methods of Claim 11 on which claim 12 depends, and Sultan and Khanmohammadi teach the methods of claim 1 that also appear in claim 22. Claim 22 also contains the limitations of claim 12. Zhang also teaches the clinical parameter is an outcome parameter indicating: the subject’s risk of having or developing a peritonitis, the subject’s risk of having or developing a peritoneal membrane deterioration, and/or the risk of technical failure (Page 2 col 1 first paragraph "PD-related peritonitis is caused by a wide spectrum of bacterial species" and Page 10 figure 7 "Shown are the top 5 biomarkers associated with the type of causative organism as indicated or with the risk of technique [technical] failure over the next 90 days.").
Regarding claim 14, Sultan in view of Khanmohammadi and Zhang teach the methods of Claim 11 on which this claim depends. Sultan also teaches the clinical parameter is a biomarker concentration, wherein the biomarker is selected from the group of proteins, metabolites, or biogenic amines (Page 4 section 2.10 "The uremic toxins (urea, uric acid, creatinine, phosphorus, and β2-microglobulin) concentration in the filtered dialysate was measured at 1, 3, 6, 10 and 24 h time point." are examples of proteins or metabolites).
Claims 15 and 20 rejected under 35 U.S.C. 103 as being unpatentable over Sultan et al. (Sultan et al., "Recirculating peritoneal dialysis system using urease-fixed silk fibroin membrane filter with spherical carbonaceous adsorbent." Materials Science and Engineering: C 97 (2019): 55-66) in view of Khanmohammadi et al. (Khanmohammadi et al., "Diagnostic prediction of renal failure from blood serum analysis by FTIR spectrometry and chemometrics." Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 136 (2015): 1782-1785) and Zhang et al. (Zhang et al., "Machine-learning algorithms define pathogen-specific local immune fingerprints in peritoneal dialysis patients with bacterial infections." Kidney international 92.1 (2017): 179-191) as applied to claims 1-14, 16-17, 19, and 21-22 above, and further in view of Margel et al. (Margel et al., "Stress proteins and cytokines are urinary biomarkers for diagnosis and staging of bladder cancer." European urology 59.1 (2011): 113-119).
Sultan et al. in view of Khanmohammadi et al. and Zhang et al. are applied to claims 1-14, 16-17, 19, and 21-22.
Regarding claims 15 and 20, Sultan in view of Khanmohammadi and Zhang teach the method of Claim 14 on which these claims depend.
Sultan, Khanmohammadi, nor Zhang explicitly teach the biomarker is a protein selected from the group of cytokines and chemokines.
However, Margel teaches the biomarker is a protein selected from the group of cytokines and chemokines; and the biomarker is a protein selected from the group consisting of interleukin-8, interleukin-6, heat shock proteins, and HSP72 (Page 1 abstract "To investigate whether Bca [bladder cancer] might be marked by urinary levels of heat shock proteins (HSPs; HSP60, HSP70, or HSP90) or cytokines (interferon [IFN]-g, tumor necrosis factor [TNF]-a, tumor growth factor [TGF]-b, interleukin [IL]-1b, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, or IL-13).").
Therefore, it would have been obvious to one of ordinary skill in the art as of the effective filing date of the claimed invention to modify the methods of Sultan, Khanmohammadi, and Zhang as taught by Margel in order to detect uremic toxins (IL-6 is a type of uremic toxin) of diagnostic value (Eberl para.0096 "Soluble mediators significantly increased in acute peritonitis included interleukin-1β (IL-1β), IL-6 []. Taken together, these measurements identify a broad range of humoral and cellular biomarkers that indicate acute inflammatory responses in PD patients, some of which might be of diagnostic value."). One skilled in the art would have a reasonable expectation of success because both approaches are in the field of nephrology and are concerned with measuring renal-related biomarkers.
Response to Arguments under 35 USC § 103
Applicant’s arguments filed 1/15/2026 are fully considered but they are not persuasive.
Applicant argues that because Sultan and Khanmohammadi do not explicitly teach analyzing a peritoneal dialysis analysis sample using FTIR, that the invention claimed by Applicant is non-obvious, and that further cited documents do not remedy these deficiencies (Remarks 1/15/2026 pages 7-8). Examiner notes above that while Sultan nor Khanmohammadi explicitly teach or suggest analyzing a peritoneal dialysis analysis sample using FTIR, it would have been obvious to one of ordinary skill in the art because combining known elements of prior art is obvious when the combination is predictable (MPEP 2144). Furthermore, applying known techniques (FTIR) to known materials (PD analyte) is obvious because the technique is recognized as suitable for the purpose of analyzing an effluent sample (MPEP 2144.07), as evidenced by Derenne et al. and Lopes et al. (Derenne et al. "Lipid quantification method using FTIR spectroscopy applied on cancer cell extracts." Biochimica et Biophysica Acta (BBA)-Molecular and Cell Biology of Lipids 1841.8 (2014): 1200-1209; Lopes et al. "FTIR and Raman spectroscopy applied to dementia diagnosis through analysis of biological fluids." Journal of Alzheimer’s Disease 52.3 (2016): 801-812).
Applicant also asserts that Zhang does not specifically teach "FTIR's holistic approach" (Remarks 1/15/2026 page 8). Examiner notes that claims 8, 11-14, and 19 depend from the obvious combination of Sultan and Khanmohammadi, therefore Zhang is not required to have the exact same approach as the instant claims.
Applicant also asserts that Margel discloses nothing about PD effluent, dialysis, or FTIR. Examiner notes that claims 15 and 20 depend from the obvious combination of Sultan and Khanmohammadi, therefore Margel is not required to have the exact same approach as the instant claims.
Finally, Applicant argues that "The Office Action provides no reasoned rationale to replace Sultan's monitoring of the dialysate (applying unspecified assays) with FTIR on the PD effluent" (Remarks 1/15/2026 page 8). Examiner notes again that analyzing a peritoneal dialysis analysis sample using FTIR would have been obvious to one of ordinary skill in the art because combining known elements of prior art is obvious when the combination is predictable, and applying known techniques (FTIR) to known materials (PD analyte) is obvious because the technique is recognized as suitable for the purpose of analyzing an effluent sample (MPEP 2144.07), as evidenced by Derenne et al. and Lopes et al.
Therefore, the rejection of claims 1-17 and 19-22 under 35 USC 103 is maintained or newly applied. All other claims depend from these independent claims; therefore, their rejection is likewise maintained.
Conclusion
No claims are allowed.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the TH REE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this finaI action.
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/R.A.P./Examiner, Art Unit 1686
/LARRY D RIGGS II/Supervisory Patent Examiner, Art Unit 1686