Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 5/28/2025 has been entered.
Applicant’s amendment
Applicant’s amendment filed 5/28/2025 has been received and entered. Claims 1 and 8 have been amended, claims 15-16 have been added, and claims 2, 3, 5, 6, 9, 10, 12, 13 have been cancelled.
Claims 1, 4, 7-8, 11, 14-16 are pending.
Election/Restriction
In prosecution, Applicant's elected with traverse of the species of metabolites and classifiers in the reply filed on 4/26/2022, and in review of the evidence of the specification and given the correlation with various forms of statistical analysis, the evaluation of other classifiers does not appear to be a burden and the restriction requirement was withdrawn.
The amendments adding new claims 15-16 are consistent with the elected invention.
Claims 1, 4, 7-8, 11, 14-16 are currently under examination.
Priority
This application filed 6/7/2018 claims benefit to US Provisional 62/516288 filed 6/7/2017.
Applicant does not provide any comment on the summary of priority.
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, 4, 7-8, 11, 14 and newly added claims 15-16 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.
Claim analysis
Claims 1 and 8 have been amended and still are generally directed to obtaining concentrations of specific metabolites in the blood and associating them with ‘a high likelihood of having autism. Claim 1 is directed to a system in which the analysis steps of the method of claim 8 are performed. The claims have been amended consistently and set forth that the method provides an identification of higher likelihood of autism based on a ‘calculated test score’ which is above or below a classifier established threshold value.
The claim still provides steps of receiving a plurality of training data arrays which are ‘from a plurality of training subjects’ and are used ‘for the purpose of training the classifier’ and that the training results in determination between an autism class. The distinction is still used to ‘define a nonlinear border threshold between the autism class and the neurotypical class’ which is used to group the test scores. The values used in the analysis require having and using the values of seven different measurable metabolites set forth in the final wherein clause. For the analysis steps, the metabolite values are received and converted into scores in a data array, and using the arrays of information the sample/individual information is correlated and classified according to the values into autism and neurotypical classes, and using the classification and analysis as a reference to evaluate a test sample with the same metabolites having been measured. In summary, the claims require obtaining values for metabolites to establish an array of data representing autism and a neurotypical class and using the array to classify a test sample as provided in the specification at [5]:
“The data processing system can classify the score for each of the plurality of data arrays into an autism class and a neurotypical class. The data processing system can receive a test data array that can include a plurality of test values. Each of the plurality of test values can represent the concentration of the different metabolites. The data processing system can calculate a test score for the test data array based on a relationship between the plurality of test values. The data processing system can group the test score into one of the autism class and the neurotypical class based on the test score for the test data array.”
Newly added claims 15 and 16 indicate to use biomarkers from metabolic pathways generally (and is consistent with the specific metabolites listed in the independent claims) and the pathway represents the FOTM or TS pathways. Dependent claims have not been amended and still provide for greater detail for calculating scores and classification based on the data obtained.
For step 1 of the 101 analysis, the claims are found to be directed to a statutory category of a product and a process.
For step 2A of the 101 analysis, the judicial exception of the claims are the steps of accessing metabolite values and correlating them to autism and neurotypical classifications, and subsequently using what is observed to assess other test samples. The claims provide instructional steps for the analysis and correlation of metabolite concentrations for classification and correlation to autism or neurotypical groupings. The claims provide for generically classifying based on concentration alone, however based on the guidance of the specification and art of record, this would be classified based on knowledge of the source, i.e. prior classification of the individual for each of the metabolite data sources. Independent claims broadly and generically require classifying and calculating, and dependent claims provide for the use of know analysis tools like FDA, SVM, PCA, and regression, and requires evaluating and computing similarities and differences among the data set values. The judicial exception is a set of instructions for analysis of metabolite data and appear to fall into the category of Mathematical Concepts, that is for the use of mathematical formulas or equations to group and correlate values to a condition/classification, and to Mental Processes, that is concepts performed in the human mind (including an observation, evaluation, judgment, opinion) given the breadth of a relatively small number of number of metabolite values, and the generic nature of the instructions for classification and calculating for providing the final group or correlation with the metabolite concentrations and autism and/or neurotypical groupings associated with the metabolite concentrations. For both, there is no specific requirement for what the values are and can be the values represented in the measured sample, and no complex analysis of the seven metabolites for their classification or correlative requirement for them representing each of autism or neurotypical condition in establishing control values which are used to assess a test sample.
Recent guidance from the office requires that the judicial exception be evaluated under a second prong to determine whether the judicial exception is practically applied. In the instant case, the system claims do not have an additional element to which the analysis is applied, while the method has an additional step for obtaining a sample and metabolite values but appears to rely on the art to support and enable obtaining values, and appears to be simply obtaining the concentrations which are analyzed as a form of data. This judicial exception requires steps recited at high level of generality and are only stored on a non-transitory, and is not found to be a practical application of the judicial exception as broadly set forth. The evidence of record suggests that well known analysis algorithms are intended to be used, and do not provide for significantly more to the claim as a whole.
For step 2B of the 101 analysis, each of the independent claims for the system do not recite any additional elements. As such, the claims do not provide for any additional element to consider under step 2B. For the method, the claims have been amended to require obtaining a blood sample and metabolite values, and in view of the specification do not provide any specific or unique means for obtaining the values, and appear to require conventional known means. The method has been amended, and no longer requires that it is directed to a computer implemented method and broadly are instructions to group control sample values into an array of data and use the array data in evaluating test samples. While broadly the data array is information in a table, to the extent the method can still employ the use of a computer in the evaluation of the metabolite values and the fact that the system comprises the use of memory and processors, in view of the analysis of the claim breadth and the specification as set forth above, it is noted that in explaining the Alice framework, the Court wrote that "[i]n cases involving software innovations, [the step one] inquiry often turns on whether the claims focus on the specific asserted improvement in computer capabilities or, instead, on a process that qualifies as an abstract idea for which computers are invoked merely as a tool." The Court further noted that "[s]ince Alice, we have found software inventions to be patent-eligible where they have made non-abstract improvements to existing technological processes and computer technology." Moreover, these improvements must be specific -- "[a]n improved result, without more stated in the claim, is not enough to confer eligibility to an otherwise abstract idea . . . [t]o be patent-eligible, the claims must recite a specific means or method that solves a problem in an existing technological process." Here, the claims are directed to the instructions of using metabolite concentrations and correlating them to autism or neurotypical groupings, the subsequently using them to analyze other test samples. A review of the art provides that the claimed concept and methodology for similar range of metabolites was previous performed, for example Howsmon et al (2017) who provide classification and adaptive behavior prediction of children with autism spectrum disorder based upon multivariate data analysis of markers of oxidative stress and DNA methylation, and Melnyk (2012) or Rose et al. (2012) who provide evidence that indicate that the deficit in antioxidant and methylation capacity is specific for autism and use linear regression and other forms of regression analysis in the analysis of the data values obtained. It is also noted that the specification indicates that the list of metabolites and data was obtained from the data source IMAGE which appears to originally be derived from the work of Melnyk et al.
As indicated in the summary of the judicial exception above and in view of the teachings of the specification, the steps are drawn to analysis of metabolite data. While the instruction are stored on a medium and could be implemented on a computer, together the steps do not appear to result in significantly more than a means to compare sequences. The judicial exception of the method as claimed can be performed by hand and in light of the previous claims to a computer medium and in light of the teaching of the specification on a computer. In review of the instant specification the methods do not appear to require a special type of processor and can be performed on a general purpose computer. No additional steps are recited in the instantly claimed invention that would amount to significantly more than the judicial exception. Without additional limitations, a process that employs mathematical algorithms (SVM, FDA,..) to manipulate existing information (metabolite concentrations) to generate additional information about test samples is not patent eligible. Furthermore, if a claim is directed essentially to a method of calculating, using a mathematical formula, even if the solution is for a specific purpose, the claimed method is non-statutory. In other words, patenting abstract idea (evaluating and correlating metabolite concentrations with a neurological state) cannot be circumvented by attempting to limit the use to a particular technological environment or purpose and desired result.
Response to Applicants arguments.
Applicants provide an overview of MPEP 2106, note the requirements and amendments to the claims and provide a summary of the basis of the rejection. Applicants argue that the amendments meaningfully limit the claims and now require ‘training’ which can be done any myriad of processors and can be applied to test values from any patient. Applicants argue that the claims are directed to an improvement and provides a practical application for evaluating blood tests.
In response, the claim amendments are acknowledged and interpreted not to affect the scope of the claim previous examined. Previously, the claims required classification based on the score, the additional step of providing a ‘class template based on the plurality of the data arrays’ appears simply to be a description of what occurred as a consequence of classification. The amendment is generic with no specific steps on how a template is generated or any detail on how the non-linear threshold is determined except that it is based on a plurality of values. The limitations require simply to ‘define a nonlinear border threshold’ between autism and neurotypical classes based on the presence or absence of metabolite values.
Applicants argue that ‘diagnosis’ satisfies patent eligibility and provides the basis of a practical application.
In response, Applicants assertion that a diagnosis is sufficient for patent eligibility under step 2A is not consistent with the claims nor the guidance for 101 analysis. The present claims have been amended to indicate that any learned correlation from training sets, then subsequently applied to analysis is indicative of ‘a higher likelihood of having autism’ and is not even diagnostic per se as argued. Moreover, the present claimed invention requires both identification of a correlation, then application of any observed correlation to providing a diagnosis or indication that a correlation based on testing data exists. Examiner acknowledges the art does provide that changes in detectable metabolites in the blood have been associated with various neurotypical conditions including autism, however the claims provide only abstract steps for analysis of data to provide for a conclusion based on a possible correlation or classification of what was observed in a training set of data. The claim limitations are inconsistent with Applicants arguments and appear consistent with the guidance and case law provided in the MPEP.
As noted previously and as summarized above the claims comprise instructions for obtaining values of metabolites from control samples represented by values obtained from siblings or neurotypic individuals and using them to evaluate and classify the observed values of metabolites, then using the controls values to assess a test sample. The claims are directed to establishing a correlation of metabolite concentrations representing normal and autism, and using the observation in assessing other samples, and do not appear to provide an improvement but rather the scope of scientific approach for creating and using a correlation that exists in nature. As provided in the cited art, the general status of oxidative stress was observed and associated with autism for several of the specific metabolites recited in the claims, as well as the means of using statistical approaches such as regression in assessing the data to establish an existence of any natural occurring correlation that may exist. In review of the specification, the means for obtaining the metabolite values does not appear to be new or unconventional, nor does there appear to be evidence that the combination of metabolite values provides any improvement in practicing the method as a whole. With respect to paragraphs [0051]-[0053] note in the arguments, it appears that the description of figure 5 supports and cross validation studies suggests that generally the more variables used increases the C-statistic, however that it is not improved beyond five variables, and improved marginally 0.98 to 0.99 when comparing three variables to five variables.
More generally, the evidence and data provided in the specification appear to be a statistical analysis for cross validation among the metabolites listed. Additionally, evidence was provided in view of Howsmon et al that analysis important to various metabolic pathways was conventional, and provides evidence that the association of metabolites related to oxidative stress and abnormal DNA methylation have been implicated in the pathophysiology of autism, and for the analysis of the dynamics of an integrated metabolic pathway essential for cellular antioxidant and methylation capacity in children with autism. It is noted that the prosecution and analysis of Step 2B did not rely upon solely Howsmon et al. so even removing the teachings from consideration the evidence appears to support the analysis of blood samples for metabolites associated with oxidative stress.
Therefore, for the reasons above and of record, the rejection is maintained.
As noted previously, one way to overcome a rejection for non-patent-eligible subject matter is to persuasively argue that the claimed subject matter is not directed to a judicial exception. Another way for the applicants to overcome the rejection is to persuasively argue that the claims contain elements in addition to the judicial exception that either individually or as an ordered combination are not well understood, routine, or conventional. Another way for the applicants to overcome the rejection is to persuasively argue that the claims as a whole result in an improvement to a technology. Persuasive evidence for an improvement to a technology could be a comparison of results of the claimed subject matter with results of the prior art, or arguments based on scientific reasoning that the claimed subject matter inherently results an improvement over the prior art. The applicants should show why the claims require the improvement in all embodiments.
Conclusion
No claim is allowed.
An updated search of the art demonstrates that prior to the effective date of the application, the analysis of metabolites in the blood to establish a correlation to autism spectrum disorder were known. For example, Taitha et al. provide a comprehensive review of MRS metabolite spectrum in Autism Spectrum Disorder (2016). Further, as evidenced by the record, the art of record provides that oxidative stress and abnormal DNA methylation have been implicated in the pathophysiology of autism, and for the analysis of the dynamics of an integrated metabolic pathway essential for cellular antioxidant and methylation capacity in children with autism and control children. In the studies, oxidative protein/DNA damage and DNA hypomethylation (epigenetic alteration) were found in autistic children but not paired normal siblings or controls. Generally, the data indicated that the deficit in antioxidant and methylation capacity is specific for autism and may promote cellular damage and altered epigenetic gene expression. For example, Nardone et al. (2014) provide evidence of DNA methylation analysis of the autistic brain reveals multiple dysregulated biological pathways. Melnyk et al. (2012) and (2011) more generally provide for metabolic imbalance associated with methylation dysregulation and oxidative damage in children with autism. More focused studies by Rose et al. (2012) provide detailed evidence of oxidative damage and inflammation associated with low glutathione redox status in the autism brain, by James et al. (2008) that abnormal transmethylation/trans-sulfuration metabolism and DNA hypomethylation occurs with children with autism, and by Howsmon et al. (2016) and (2017) for classification and adaptive behavior prediction of children with autism spectrum disorder based upon multivariate data analysis of markers of oxidative stress and DNA methylation.
The art provides a clear correlation with changes in metabolites and the ability to correlate differences between individuals with autism and controls, and provides a variety of means to demonstrate the significance of the measured observations and calculations with the general suggestion that the evidence can be used in further studies. However, while such factors or correlative in specific circumstances, the art fails to provide the comparison of other neurotypical classes in the classification or the use of a non-linear border to generate a test score as required of the claims
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Joseph T Woitach whose telephone number is (571)272-0739. The examiner can normally be reached Mon-Fri; 8:00-4:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Karlheinz R Skowronek can be reached on 571 272-9047. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Joseph Woitach/Primary Examiner, Art Unit 1687