DETAILED ACTION
This application is made in response to the communication filed on March 14, 2025. This action is made non-final.
Claims 1-8 are pending. Claims 4 and 8 have been amended by preliminary amendment filed March 14, 2025. Claims 1 and 5 are independent claims.
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Such claim limitations are “step of acquiring” and “step of inputting” in claim 1.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 112
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 1-4 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 pre-AIA the applicant regards as the invention.
As to claims 1-4, the claims are rejected under 35 USC 112(b), for failing to clearly link or associate the disclosed structure, material, or acts to the function recited in the claim limitation, thereby invoking 35 USC 112(f). The claim limitation “step of acquiring” and “step of inputting” uses the phrase “means for” or “step for” or a generic placeholder coupled with functional language, but it is not modified by some structure, material, or acts recited in the claim. It is unclear whether the recited structure, material, or acts are sufficient for performing the claimed function because the written description fails to clearly link or associated the disclosed structure, material, or acts to the claimed function such that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function.
If applicant does not wish to have the claim limitation treated under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, 6th Paragraph applicant may:
(a) Amend the claim to add structure, material or acts that are sufficient to perform the claimed function; or
(b) Present a sufficient showing that the claim limitation recites sufficient structure, material, or acts for performing the claimed function to preclude application of 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. For more information, see MPEP § 2181.
Dependent claims 2-4 fail to resolve the 112 deficiency of their parent claim and are similarly rejected.
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 1-4 are additionally 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.
As to claim 1, the claim recites “step of acquiring” and “step of inputting”; however, the specification fails to provide sufficient description for the structure, material or acts performing the claimed function, and, therefore, lack written description under 112(a).
Dependent claims 2-4 fail to resolve the 112 deficiency of their parent claim and are similarly rejected.
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 1-8 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claims 1-4 recite a method of diagnosing a disease, which is within the statutory category of a process. Claims 5-8 recite a system for diagnosing a disease, which is within the statutory class of a machine.
Claims are eligible for patent protection under § 101 if they are in one of the four statutory categories and not directed to a judicial exception to patentability. Alice Corp. v. CLS Bank Int'l, 573 U.S. ___ (2014). Claims 1-8, each considered as a whole and as an ordered combination, are directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
MPEP 2106 Step 2A – Prong 1:
The limitations of:
Claims 1 and 5 (claim 1 being representative)
A method of risk determination which estimates risks of neurodegenerative diseases through stratification which differentiates multiple diseases, the method executed by a processor of a computer, wherein the method comprises a step of acquiring representation abundances of multiple types of bacteria from an analysis of salivary microbiota of a test subject; and a step of inputting the acquired representation abundances of multiple types of bacteria into a prediction model to estimate risks of neurodegenerative diseases occurring in the test subject through stratification which differentiates multiple diseases, wherein the prediction model has been generated by machine learning which entails obtaining an algorithm using, as explanatory variables, representation abundances of the multiple types of bacteria acquired from an analysis of salivary microbiota of healthy subjects and patients of multiple diseases belonging to the neurodegenerative diseases, and the disease states of the healthy subjects and the patients stratified across the multiple diseases belonging to neurodegenerative diseases, output as target variables, as training data, wherein said multiple types of bacteria include bacteria types having high representation abundances in the analysis of the salivary microbiota of the patients stratified, and/or bacteria types showing significant differences in the representation abundances between patients of different diseases in the analysis of the salivary microbiota of the patients stratified.
as presently drafted, under the broadest reasonable interpretation, covers a method of organizing human activity (i.e., managing personal behavior including following rules or instructions). For example, but for the noted computer elements, the claim encompasses a person following rules or instructions to retrieve and analyze data in the manner described in the abstract idea, such as a person collecting patient saliva to predict a risk of a neurodegenerative disease. The examiner further notes that “methods of organizing human activity” includes a person’s interaction with a computer (see October 2019 Update: Subject Matter Eligibility at Pg. 5). If the claim limitation, under its broadest reasonable interpretation, covers managing persona behavior or interactions between people but for the recitation of generic computer components, then it falls within the “method of organizing human activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
MPEP 2106 Step 2A – Prong 2:
This judicial exception is not integrated into a practical application because there are no meaningful limitations that transform the exception into a patent eligible application. The additional elements merely amount to instructions to apply the exception using generic computer components (“a processor”, "a computer”, “a storage unit”, “communication circuit”—all recited at a high level of generality). Although they have and execute instructions to perform the abstract idea itself, this also does not serve to integrate the abstract idea into a practical application as it merely amounts to instructions to "apply it." (See MPEP 2106.04(d)(I) indicating mere instructions to apply an abstract idea does not amount to integrating the abstract idea into a practical application). Accordingly, the additional elements do not integrate the abstract idea into a practical application because they do not impose meaningful limits on practicing the abstract idea. Therefore, the claims are directed to an abstract idea.
The claim further recites the additional elements of use of a prediction model generated by machine learning and trained with bacteria and patient stratification data. When given the broadest reasonable interpretation in light of the nonexistent description of model training in the disclosure, training of a machine learning model with the noted data amounts to a mathematical concept that creates data associations. As such, this training of the model is interpreted to be subsumed within the identified abstract idea and the use of the trained model provides nothing more than mere instructions to implement the abstract idea, supra. July 2024 Subject Matter Eligibility Examples, Example 47, Claim 2, discussion of item (c) at Pgs. 7-9. Furthermore, the use of the trained model provides nothing more than mere instructions to implement an abstract idea on a generic computer (“apply it”). See MPEP 2106.05(f). MPEP 2106.05(f); July 2024 Subject Matter Eligibility Examples, Example 47, Claim 2, discussion of items (d) and (e) at Pgs. 8-9.
The claims only manipulate abstract data elements as part of performing the abstract idea. They do not set forth improvements to another technological field or the functioning of the computer itself and instead use computer elements as tools in a conventional way to improve the functioning of the abstract idea identified above. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. None of the additional elements recited "offers a meaningful limitation beyond generally linking 'the use of the [method] to a particular technological environment,' that is, implementation via computers." Alice Corp., slip op. at 16 (citing Bilski v. Kappos, 561 U.S. 610, 611 (U.S. 2010)).
At the levels of abstraction described above, the claims do not readily lend themselves to a finding that they are directed to a nonabstract idea. Therefore, the analysis proceeds to step 2B. See BASCOM Global Internet v. AT&T Mobility LLC, 827 F.3d 1341, 1349 (Fed. Cir. 2016) ("The Enfish claims, understood in light of their specific limitations, were unambiguously directed to an improvement in computer capabilities. Here, in contrast, the claims and their specific limitations do not readily lend themselves to a step-one finding that they are directed to a nonabstract idea. We therefore defer our consideration of the specific claim limitations’ narrowing effect for step two.") (citations omitted).
MPEP 2106 Step 2B:
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception for the same reasons as presented in Step 2A Prong 2. Moreover, the additional elements recited are known and conventional generic computing elements (“a processor”, "a computer”, “a storage unit”, “communication circuit”—see Specification Fig. 2, [0032] describing the various components as general purpose, common, standard, known to one of ordinary skill, and at a high level of generality, and in a manner that indicates that the additional elements are sufficiently well-known that the specification does not need to describe the particulars of such additional elements to satisfy the statutory disclosure requirements). Therefore, these additional elements amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept that amounts to significantly more. See MPEP 2106.05(f).
The Federal Circuit has recognized that "an invocation of already-available computers that are not themselves plausibly asserted to be an advance, for use in carrying out improved mathematical calculations, amounts to a recitation of what is 'well-understood, routine, [and] conventional.'" SAP Am., Inc. v. InvestPic, LLC, 890 F.3d 1016, 1023 (Fed. Cir. 2018) (alteration in original) (citing Mayo v. Prometheus, 566 U.S. 66, 73 (2012)). Apart from the instructions to implement the abstract idea, they only serve to perform well-understood functions (e.g., receiving, translating, and displaying data—see Specification above as well as Alice Corp.; Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307 (Fed. Cir. 2016); and Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334 (Fed. Cir. 2015) covering the well-known nature of these computer functions).
Also, as discussed above with respect to integration of the abstract idea into a practical application, the additional elements of the use of a prediction model generated by machine learning and trained with bacteria and patient stratification data to make predictions were considered to be part of the abstract idea and “apply it,” respectively. This has been re-evaluated under the “significantly more” analysis and has also been found insufficient to provide significantly more. Regarding the training of the model is considered part of the abstract idea and thus cannot provide a practical application. Regarding the use of the trained model represented saying “apply it.” Using the trained model has been revaluated under the “significantly more” analysis and does not provide “significantly more” to the abstract idea. MPEP 2106.05(A) indicates also indicates that merely adding the words “apply it” or equivalent use cannot provide significantly more. Accordingly, even in combination, this additional element does not provide significantly more. As such the claim is not patent eligible.
Dependent Claims
The limitations of dependent but for those addressed below merely set forth further refinements of the abstract idea without changing the analysis already presented. Claims 2-4 (6-8) merely recites the types of diseases predicted and the types of bacteria used in the prediction, which covers a method of organizing human activity (i.e., managing personal behavior including following rules or instructions).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Scheperjans et al. (USPPN: 2017/0191998; hereinafter Scheperjans) in further view of Pawlik et al. (“The Role of Salivary Biomarkers in the Early Diagnosis of Alzheimer’s Disease and Parkinson’s Disease” <<retrieved from the internet: https://doi.org/10.3390/diagnostics11020371>>; hereinafter Pawlik).
As to claim 1, Scheperjans teaches A method of risk determination which estimates risks of neurodegenerative diseases through stratification which differentiates multiple diseases, the method executed by a processor of a computer (e.g., see Abstract, [0018], [0021] teaching a method for determining a probability risk a subject is developing of has Parkinson’s disease (PD) or another disease mimicking Parkinsons), wherein the method comprises
a step of acquiring representation abundances of multiple types of bacteria from an analysis of salivary microbiota of a test subject (e.g., see [0038], [0040], [0044] wherein a plurality of one or more microbial taxa and their relative abundances are measured, wherein the sample may be an oral sample or prevotella salivae (i.e., salivary microbiota)); and
a step of inputting the acquired representation abundances of multiple types of bacteria into a prediction model to estimate risks of neurodegenerative diseases occurring in the test subject through stratification which differentiates multiple diseases (e.g., see [0021], [0040], [0041], [0056] wherein the abundances of one or more microbial taxa in a reference sample are used in a machine learning model to determine a probability of a subject developing or having Parkinson’s disease and/or differentiating patients with PD with another disease mimicking PD)
wherein the prediction model has been generated by machine learning which entails obtaining an algorithm using, as explanatory variables, representation abundances of the multiple types of bacteria acquired from an analysis of salivary microbiota of healthy subjects and patients of multiple diseases belonging to the neurodegenerative diseases, and the disease states of the healthy subjects and the patients stratified across the multiple diseases belonging to neurodegenerative diseases, output as target variables, as training data (e.g., see [0040]-[0041], [0045], [0054], [0056], [0081] wherein the machine learning model is trained from abundances of microbial taxa retrieved from a healthy control group and those with PD to output the probability of whether or not the subject developing or having PD is low),
wherein said multiple types of bacteria include bacteria types having high representation abundances in the analysis of the salivary microbiota of the patients stratified, and/or bacteria types showing significant differences in the representation abundances between patients of different diseases in the analysis of the salivary microbiota of the patients stratified (e.g., see [0021], [0038], [0044], [0045], [0048], [0056] wherein the relative abundances of the microbial taxa, including those retrieved orally (i.e., salivary microbiota), are indicative of determining the probability of the subject developing or having PD and/or determining a clinical subtype of PD and/or differentiating another disease mimicking PD).
While Scheperjans teaches stratifying between healthy patients and patients who have PD, wherein the absence or presence of a neurodegenerative disease is interpreted as reading upon the claimed “disease states”; for the purposes of compact prosecution and in the same field of endeavor of diagnosis of neurodegenerative diseases, Pawlik teaches the disease states of the healthy subjects and the patients stratified across the multiple diseases belonging to neurodegenerative diseases (e.g., see 7:8-22, 9:7-9, table 3 wherein patients were stratified across different groups including those with different neurodegenerative diseases, those with mild impairment, and health patients with no impairment).
Accordingly, it would have been obvious to modify Scheperjans in view of Pawlik before the effective date of the application with a reasonable expectation of success. One would have been motivated to make the modification to provide for early screening and diagnosis of neurodegenerative diseases before the onset of symptoms (e.g., see Abstract of Pawlik).
As to claim 2, the rejection of claim 1 is incorporated. While Scheperjans teaches stratifying between healthy patients and patients who have PD, Scheperjans fails to explicitly teach wherein the stratification which differentiates multiple diseases comprises stratification to differentiate healthy aged subjects, mild cognitive impairment (MCI), and dementia (DE), stratification to differentiate healthy aged subjects, mild cognitive impairment (MCI), dementia (DE), and dementia with Lewy bodies (DLB), or stratification to differentiate Parkinson's disease (PD) and dementia with Lewy bodies (DLB).
However, in the same field of endeavor of diagnosis of neurodegenerative diseases, Pawlik teaches wherein the stratification which differentiates multiple diseases comprises stratification to differentiate healthy aged subjects, mild cognitive impairment (MCI), and dementia (DE), stratification to differentiate healthy aged subjects, mild cognitive impairment (MCI), dementia (DE), and dementia with Lewy bodies (DLB), or stratification to differentiate Parkinson's disease (PD) and dementia with Lewy bodies (DLB) (e.g., see 7:8-22, 9:7-9, table 3, 13 wherein patients were stratified across different groups including those with different neurodegenerative diseases, those with mild impairment, and health patients with no impairment, Lewy body variants, dementia with Lewy bodies).
Accordingly, it would have been obvious to modify Scheperjans in view of Pawlik before the effective date of the application with a reasonable expectation of success. One would have been motivated to make the modification to provide for early screening and diagnosis of neurodegenerative diseases before the onset of symptoms (e.g., see Abstract of Pawlik).
As to claim 3, the rejection of claim 1 is incorporated. Scheperjans teaches wherein the multiple diseases include Parkinson's disease (PD) (e.g., see Abstract teaching detection of Parkinson’s disease).
While Scheperjans teaches the disease being PD, Schperjans fails to teach wherein the multiple diseases include dementia with Lewy bodies (DLB) (e.g., see Page 13, section 3 teaching identifying other neurodegenerative diseases including PD with or without dementia, Lewy body variants of Alzheimer’s disease, multiple system atrophy, and dementia with Lewy bodies).
Accordingly, it would have been obvious to modify Scheperjans in view of Pawlik before the effective date of the application with a reasonable expectation of success. One would have been motivated to make the modification to provide for early screening and diagnosis of neurodegenerative diseases before the onset of symptoms (e.g., see Abstract of Pawlik).
As to claim 4, the rejection of claim 1 is incorporated. Scheperjans further teaches wherein the multiple types of bacteria include one or more types of bacteria selected from the group consisting of: [Eubacterium] brachy, Porphyromonas endodontalis, Alloprevotella tannerae, Capnocytophaga leadbetteri, Streptococcus gordonii, Campylobacter concisus, Tannerella forsythia, Filifactor alocis, [Eubacterium] nodatum, Streptococcus cristatus, Neisseria elongata, Treponema denticola, Actinomyces oris, [Eubacterium] saphenum, Streptococcus constellatus, Parvimonas micra, Prevotella denticola, Leptotrichia hofstadii, Fusobacterium nucleatum, Catonella morbi, Lactobacillus antri, Alloprevotella rava, Streptococcus anginosus, Prevotella jejuni, Streptococcus mitis, Gemella haemolysans, Neisseria macacae, Prevotella multiformis, Abiotrophia defectiva, Streptococcus salivarius, Streptococcus lactarius, Corynebacterium matruchotii, Oribacterium asaccharolyticum, Prevotella loescheii, Aggregatibacter segnis, Peptostreptococcus stomatis, Veillonella infantium, Capnocytophaga granulosa, Leptotrichia buccalis, Veillonella atypica, Streptococcus pseudopneumoniae, Corynebacterium durum, Granulicatella adiacens, [Eubacterium] sulci, Selenomonas infelix, Capnocytophaga sputigena, Lactobacillus crispatus, Streptococcus parasanguinis, Rothiamucilaginosa, Streptococcus sobrinus, Atopobium parvulum, Solobacterium moorei, Neisseria perflava, Bifidobacterium dentium, Actinomyces graevenitzii, Streptococcus mutans, Prevotella pallens, Porphyromonas gingivalis, Rothia dentocariosa, Fusobacterium periodonticum, Lactobacillus fermentum, Prevotella melaninogenica, Leptotrichia wadei, Lautropia mirabilis, Streptococcus infantis, Neisseria oralis, Prevotella pleuritidis, Prevotella oris, Lactobacillus paracasei, Lachnoanaerobaculum orale, Haemophilus parahaemolyticus, Prevotella nanceiensis, Lactobacillus salivarius, Streptococcus sanguinis, Haemophilus parainfluenzae, Lactobacillus vaginalis, Bacteroides heparinolyticus, Prevotella salivae, Gemella morbillorum, Gemella sanguinis, Prevotella shahii, Haemophilus haemolyticus, Schaalia odontolytica, Lactobacillus gasseri, Streptococcus australis, Streptococcus oralis, Prevotella histicola, Schaalia meyeri, Porphyromonas pasteri, Prevotella intermedia, Granulicatella elegans, Streptococcus downei, Parascardovia denticolens, Staphylococcus aureus, Haemophilus sputorum, and Prevotella oulorum (e.g., see [0029], [0044], [0048] teaching multiple types of bacteria including Prevotella melaninogenica, Prevotella oris, Prevotella salivae, Prevotella tannerae).
Claim(s) 5-8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Scheperjans and Pawlik, as applied above, and in further view of Neumann (USPPN: 2022/0172836; hereinafter Neumann).
As to claims 5-8, the claims are directed to the apparatus implementing the method of claims 1-4 and are similarly rejected.
While Scheperjans teaches using machine learning models for the predictions, Scheperjans fails to explicitly teach a processor, a storage unit which stores a computer program executed by the processor, and a communication circuit which receives.
However, in the same field of endeavor of biomarkers for predictive interventions, Neumann teaches a processor, a storage unit which stores a computer program executed by the processor, and a communication circuit which receives (e.g., see Abstract, Fig. 1, [0016] teaching a system for receiving biomarker patient data, a processor, and a storage unit for storing instructions for performing the predictions).
Accordingly, it would have been obvious to modify Scheperjans-Pawlik in view of Neumann before the effective filing date with a reasonable expectation of success. One would have been motivated to make the modification in order to provide for a system for using biomarker data for predictive interventions (e.g., see [0003] of Neumann).
It is noted that any citation to specific pages, columns, lines, or figures in the prior art references and any interpretation of the references should not be considered to be limiting in any way. “The use of patents as references is not limited to what the patentees describe as their own inventions or to the problems with which they are concerned. They are part of the literature of the art, relevant for all they contain.” In re Heck, 699 F.2d 1331, 1332-33, 216 USPQ 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006, 1009, 158 USPQ 275, 277 (CCPA 1968)). Further, a reference may be relied upon for all that it would have reasonably suggested to one having ordinary skill the art, including nonpreferred embodiments. Merck & Co. v. Biocraft Laboratories, 874 F.2d 804, 10 USPQ2d 1843 (Fed. Cir.), cert. denied, 493 U.S. 975 (1989). See also Upsher-Smith Labs. v. Pamlab, LLC, 412 F.3d 1319, 1323, 75 USPQ2d 1213, 1215 (Fed. Cir. 2005); Celeritas Technologies Ltd. v. Rockwell International Corp., 150 F.3d 1354, 1361, 47 USPQ2d 1516, 1522-23 (Fed. Cir. 1998).
Conclusion
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/STELLA HIGGS/Primary Examiner, Art Unit 3681