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 .
Status of the Claims
Claims 1-24 were pending. Claims 1, 6, 14, 18, 20, and 22-24 are amended.
Claims 1-24 are examined herein.
Withdrawn Rejections
The objections to claims 1, 6, 14, 18, 20, and 23 are withdrawn in view of claims 1 and 14 amendments.
The rejection of claims 1-21 under 35 U.S.C. 112(a) as related to identifying risk of cerebral edema is withdrawn in view of claim 1 amendments. However, the claims are still rejected under 35 U.S.C. 112(a) as failing to comply with the written description requirement as related to the amendment reciting predicting edema volume.
The rejection of claims 22-24 under 35 U.S.C. 103 is withdrawn in view of claim 22 amendments. However, the amendments necessitated new grounds of rejection under 35 U.S.C. 112(a), 112(b), and 101.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL. —The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-24 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claims 1 and 22 recite methods of predicting edema volume in a subject using expression levels of protein biomarkers REG3A, CCL18, IL20RA, and IL10RA. Dependent claim 14 recites using levels of additional biomarkers: TNFRS9, IL5, KIT, TNF, CCL16, and GNLY for predicting infarct volume.
The invention is directed to detecting expression levels of protein biomarkers in subject’s blood and predicting edema and infarct volumes in the subject.
FIG. lA discloses cardiometabolic panel volcano plot illustrating proteomic log2 fold changes in Normalized Protein eXpression (NPX) in intracranial blood compared with systemic blood. Labeled proteins include prolyl endopeptidase (FAP), phospholipid transfer protein (PLTP), fetuin- B (FETUB), uromodulin (UMOD), ficolin-2 (FCN2), and superoxide dismutase 1 (SODl) ([0020]).
FIG. 1B discloses inflammatory panel volcano plot illustrating proteomic log2 fold changes in Normalized Protein eXpression (NPX) in intracranial blood compared with systemic blood. Labeled proteins include C- C motif chemokine 19 (CCL19), C- C motif chemokine 20 (CCL20), fibroblast growth factor 21 (FGF21), transforming growth factor alpha (TGF-a), C- C motif chemokine 23 (CCL23), and axin-1 (AXINl) ([0021]).
FIGS. 2A and 2B disclose predicted and measured edema values by Lasso on training data (FIG. 2A) and testing data (FIG. 2B) with a ratio of 4: I random split ([0022]).
The specification discloses examples of sample acquisition ([0056]), sample preparation ([0058]), protein analysis ([0061]), patient characteristics ([0062]-[0064]), proteomics ([0065]-[0069]), linear regression analysis ([0070]-[0072]), infarct volume and edema volume calculation ([0073]-[0074]), infarct volume and edema volume prediction ([0075]-[0086]), and proteomic changes at the site of infarct ([0087]-[0098]).
Prior art is silent on using recited biomarkers REG3A, CCL18, IL20RA, IL10RA, TNFRS9, IL5, KIT, TNF, CCL16, and GNLY for predicting edema or infarct volumes. The art of using proteomic biomarkers for predicting medical conditions in human subjects is highly unpredictable. Applicant is required to disclose the invention in details.
The level of one of ordinary skill is high with an ordinary practitioner possessing a PhD and related post-doctoral research experience.
The specification is silent on correlations between detected expression levels of: (a) REG3A, CCL18, IL20RA, and IL10RA, and edema volume; and (b) TNFRS9, IL5, KIT, TNF, CCL16, and GNLY, and infarct volume.
Fig. 1A and 1B demonstrate cardiometabolic panel volcano plot illustrating proteomic log2 fold changes in Normalized Protein eXpression (NPX) in intracranial blood compared with systemic blood, however the claimed biomarkers are not present in the figures. Fig. 1A and 1B show results for biomarkers not relevant to instant disclosure.
Fig. 2A and 2B demonstrate predicted and measured edema values in different subjects, however there are no biomarkers or biomarker levels indicated in the figures. Moreover, the predicted and measured data points require proper statistical evaluation to determine if the differences are statistically significant. For example, the predicted and measured data points for subjects 0, 1, and 2 (Fig. 2B) differ significantly and cannot be used as proper evidence without statistical evaluation.
The specification discloses the use of machine learning for infarct volume and edema volume prediction ([0075]), but fails to provide actual data. For example, Table 3 merely lists REG3A, IL20RA, and IL10RA biomarkers without providing data for any volumes.
The key parameters: the edema volume and infarct volume are not disclosed either alone or as correlations with the biomarker’s expression levels.
Claims 8-13 reciting some treatments options for subjects of claim 1 do not disclose the choice of the treatments depending on the edema volume identified in claim 1. For example, claim 13 recites the surgery is a decompressive craniectomy, but the specification fails to link this radical treatment to a specific predicted edema volume. The same argument is applied to other treatments recited in claims 11 and 12. Moreover, the machine-learning model recited in claims 1, 6, 14, and 22 is not configured to output appropriate treatments corresponding to the predicted edema and infarct volumes.
Therefore, based on the above findings, one of ordinary skill in the art would conclude that Applicant did not have possession of the claimed invention.
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 1-24 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites detecting expression levels of REG3A, CCL18, IL20RA, and IL10RA in the sample, and predicting edema volume. It is unclear how the edema volume is predicted based on the expression levels because the specification fails to disclose directions of changes, specific ranges, or specific fold differences for REG3A, CCL18, IL20RA, and IL10RA expression and the recited machine-learning model is just a “black box” as far as the prediction method is concerned. The metes and bounds of the claim are not clear.
Claim 6 fails to recite specific ranges or specific fold differences for REG3A, CCL18, IL20RA, and IL10RA levels for predicting edema volume. The metes and bounds of the claim are not clear.
Claim 14 recites further detecting TNFRS9, ILS, KIT, TNF, CCL16, and GNLY in the samples, and predicting infarct volume. It is unclear how the infarct volume is calculated based on the detected expression levels of TNFRS9, ILS, KIT, TNF, CCL16, and GNLY. The metes and bounds of the claim are not clear.
Claim 18 fails to recite directions of changes, specific ranges, or specific fold differences for detected REG3A, CCL18, IL20RA, IL10RA, TNFRS9, ILS, KIT, TNF, CCL16, and GNLY for predicting infarct volume. The metes and bounds of the claim are not clear.
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 1-24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a law of nature and/or an abstract idea without significantly more.
Claims 1 and 22 recite detecting expression levels of REG3A, CCL18, IL20RA, and IL10RA proteins in a sample and predicting edema volume.
Claims 1 and 22 are directed to a process, which is one of the four statutory categories.
The claims describe the relationship between expression levels of REG3A, CCL18, IL20RA, and IL10RA proteins in the sample and edema volume which is categorized as a naturally occurring correlation.
This judicial exception is not integrated into a practical application because the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Besides the naturally occurring correlation, claims 1 and 22 recite obtaining a blood sample from a subject and detecting expression levels of the proteins in the sample. This limitation does not integrate the judicial exception of the naturally occurring correlation into a practical application, because the steps of obtaining a blood sample and detecting expression levels are necessary steps for decision making and their purpose is merely to obtain data. These steps do not go beyond that which was considered insignificant pre-solution activity, i.e., mere data gathering steps necessarily performed for the judicial exception (see MPEP 2106.05(g)).
Claims 1 and 22 recite a step of processing the detected expression levels for predicting edema volume using a machine-learning model. The limitation of “processing” falls into the “Mathematical concepts” groupings of abstract ideas and therefore belongs to judicial exceptions.
Therefore, the claims as a whole fail to integrate the recited judicial exception into a practical application of the exception.
The dependent claims 2-5, 7, 15-17, and 19 recite additional limitations on blood samples and the subjects. Claims 14, 18, 20, and 23 recite additional biomarker proteins TNFRS9, ILS, KIT, TNF, CCL16, and GNLY. Claims 23 and 24 recite limitations on a device comprising biomarker-specific probes.
These additional limitations fail to add significantly more to the judicial exception of the naturally occurring correlation, and therefore, fail to integrate the recited judicial exception of claims 1 and 22 into a practical application of the exception.
Claims 8-13 recite administering various treatments to the subject. However, the additional recited treatment elements are recited at a high level of generality: “administering a treatment” (claim 8), “the treatment is capable of mitigating cerebral edema” (claim 9), “the treatment comprises a therapeutic agent” (claim 10), “the therapeutic agent is selected from the group consisting of: an osmolar agent, a diuretic, an anesthetic, a sedative, and combinations thereof” (claim 11), “the treatment comprises surgery” (claim 12), and “the surgery is a decompressive craniectomy” (claim 13).
Additionally, the limitations: “administering a treatment”, “the treatment is capable of mitigating cerebral edema”, and “the treatment comprises a therapeutic agent” is an attempt to generally link the judicial exception to a field of use. The limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application. MPEP 2106.05(h). The limitations fail to meaningfully limit claim 1 because they do not require any particular application of the abstract idea and therefore amounts only to a generic instruction to “apply” the exception or to a mere indication of the field of use or technological environment in which the abstract idea is performed.
The limitations: “the therapeutic agent is selected from the group consisting of: an osmolar agent, a diuretic, an anesthetic, a sedative, and combinations thereof” (claim 11), “the treatment comprises surgery” (claim 12), and “the surgery is a decompressive craniectomy” (claim 13) are very high-level treatment options not specifically linked to predicted edema volumes. Therefore, the limitations of claims 11-13 are generic instructions to “apply” the exception for treatments having no disclosed relations to predicted edema volumes.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Step 2B analysis indicates that the additional elements of claims 1 and 22 of obtaining a sample and detecting expression levels of REG3A, CCL18, IL20RA, and IL10RA proteins fail to qualify as "significantly more" because they simply append well-understood, routine, conventional activities previously known to the art, specified at a high level of generality, to the judicial exception that have been recognized by the courts as being routine laboratory techniques. See Genetic Techs. v. Merial LLC, 818 F.3d 1369, 1377 (Fed. Cir. 2016) (analyzing DNA to provide sequence information or to detect allelic variants is conventional in the art); MPEP 2106.05(d), subsection II.
The specification only describes carrying out sample collection and detecting expression levels as “Various techniques for detecting polypeptides or proteins in a sample are known to those of ordinary skill in the art, and can be used in connection with the presently disclosed subject matter. For example, mass spectrometry and/or immunoassay devices and methods can be used, although other methods are well-known to those skilled in the art” ([0027]).
The detecting steps of claims 1 and 22 fail to go beyond what was considered routine and conventional in the assay art at the time. For example, it was routine and conventional to detect REG3A plasma level using ELISA assay in plasma - Sun et al. (Blood, Volume 122, Issue 21, 2013, Page 4602, Method section). Regarding the detecting step of claim 14, Dossus et al. (J Immunol Methods. 2009 Oct 31;350(1-2):125-32) teach ELISA assay of TNF-α protein (pg. 126, col. 2, par. 4). TNF-α of Dossus is another name for TNF of instant disclosure.
Regarding claims 20-21, Sun and Dossus also teach that it was routine and conventional to detect proteins using the device comprising probe specific for target biomarkers and affixed to a substrate because these are inherent features of ELISA assay format.
Regarding claim 24, Eteshola et al. (Sensors and Actuators B: Chemical, Volume 72, Issue 2, 2001, Pages 129-133) teach a microfluidic enzyme-linked immunosorbent assay (ELISA) device.
Claims 1 and 22 as a whole do not amount to significantly more than the recited exception, i.e., the additional element, or combination of additional elements, do not add an inventive concept to the claim (MPEP 2106.05).
Following all of this, claims 1-24 are ineligible under 35 U.S.C. 101.
Subject Matter Free of the Prior Art
Claims 1-24 are free of the prior art.
Predicting edema volume in the subject by detecting expression levels of REG3A, CCL18, IL20RA, and IL10RA; and predicting infarct volume by detecting expression levels of TNFRS9, IL5, KIT, TNF, CCL16, and GNLY are not known in the art.
The prior art teaches detecting or measuring expression levels of the individual biomarkers: REG3A - Sun teaches measuring REG3A using ELISA assay (Method section); CCL18 - Malhotra teaches measuring CCL18 using ELISA assay (Abstract); IL20RA - Christensen teaches antibody derivatives with heterodimeric coiled coil domain (Abstract) capable of binding IL20RA (pg. 95, par. 3); IL10RA - Sokolowska teaches measuring changes in protein release of IL10RA by ELISA (pg. 2103, col. 1, par. 1; Results, pg. 2103, col. 1, par. 2); TNFRS9 -Abdelhakim teaches immunophenotypic characterization of T cells was performed on a flow cytometer using surface markers CD137(pg. 1, Methods). CD137 is another name for TNFRSF9 of instant invention; KIT - Sobotka teaches serum proteins were tested by ELISA method including CD117(Material and Methods). CD117 is another name for KIT of instant invention; TNF - Dossus teaches ELISA assay of TNF-α protein (pg. 126, col. 2, par. 4). TNF-α is another name for TNF of instant invention; CCL16 - Hayatbakhsh teaches serum levels of CCL16 was measured via enzyme-linked immunosorbent assay (Abstract. Methods); and GNLY - Xu teaches protein expression of GNLY in the peripheral blood plasma was measured using ELISA (Abstract), but none of the reference teach predicting edema or infarct volume based on the expression levels of the recited biomarkers.
Response to Arguments
Applicant’s arguments filed March 30, 2026 have been fully considered.
Claims 1-21 were rejected under 35 U.S.C § 112(a) as failing to comply with the written description requirement.
Applicant argues that “As amended, independent claim 1 no longer merely "identif[ies] risk" based on the presence of biomarkers” (pg. 8, par. 1). The argument is persuasive and the rejection of claims 1-21 under 35 U.S.C. 112(a) as related to identifying risk of cerebral edema is withdrawn in view of claim 1 amendments. However, the claims are still rejected under 35 U.S.C. 112(a) as failing to comply with the written description requirement as related to the amendment reciting predicting edema volume.
Applicant further argues the written description rejection that “Example 8 also expressly identifies the four proteins of amended claim 1: "The algorithm found that proteins CCL 18, IL10Ra, IL20Ra and REG3A are predictors for both edema and infarct volume."” (pg. 8, par. 2). The argument is not persuasive because Example 8 fails to provide any edema volumes and their correlations with the four biomarkers of claim 1. For example, Table 3 merely lists the biomarkers without any numerical values for edema volumes. On an additional note, it is hard to understand what Table 3 illustrates.
Applicant further argues the written description rejection stating that “the application-as-filed provides written description support for detecting expression levels (as opposed to mere presence/absence) of the recited proteins in systemic blood/plasma samples” and “describes that infarct and edema outcomes may be prognosticated "on the plasma expression dataset" with proteins as "features." Example 8 describes taking "the edema volume ... as an outcome" and using "proteins ... as different features," and further explains that "all the measured plasma proteins" may be used as features” (pg. 8, par. 3). The argument is not persuasive because “taking "the edema volume ... as an outcome"” and “that "all the measured plasma proteins" may be used as features” is not a sufficient disclosure of the invention. The statement that “These disclosures provide possession of measuring and using protein expression levels as inputs to predictive models” (id.) fails to point out the actual measured protein expression levels and their correlations with edema volume.
Applicant further argues the written description rejection stating that “the application-as-filed provides written description support for outputting a prediction of edema volume based on the detected expression levels. In particular, Example 8 describes predictive modeling of edema volume as an "outcome," including predicted and measured edema values” (pg. 9, par. 1). The argument is not persuasive because Example 8 fails to provide expression levels, edema volumes, and any evidence linking expression levels to edema volumes. Fig. 2A-B show only data points and lack required statistical analysis of data. For example, the predicted and measured data points for subjects 0, 1, and 2 (Fig. 2B) differ significantly and cannot be used as evidence without statistical evaluation.
Applicant further argues the written description rejection stating that “the application-as-filed provides written description support for using the prediction to guide clinical management. The Summary and Description explain that early identification of edema risk/outcomes is critical because "as time progresses without treatment ... clinical outcome declines," and the disclosure expressly contemplates administering treatment once edema risk is identified, including medical and surgical interventions” (pg. 9, par. 2). The argument is not persuasive because Applicant fails to point out where in the specification the actual data on edema and infarct volumes are linked to the treatment options recited in claims 8-13.
Applicant further argues the written description rejection stating that “The Office Action asserts that "the specification is silent on the key data for (a) a correlation between detecting the claimed biomarkers ... and (b) a risk of cerebral edema," and further asserts that the specification "fails to provide actual data." Office Action, p. 4. Applicant respectfully disagrees. The application-as-filed includes an example expressly directed to predictive modeling of edema volume and infarct volume using measured plasma protein expression features (Example 8), identifies the specific biomarker set of amended claim 1 as predictive for edema and infarct volume (Example 8), and provides exemplary predictive modeling outputs (FIGS. 2A-2B) as well as supporting discussion of feature selection and model construction (ERT and Lasso)” (pg. 9, last par.). The argument is moot because the limitation of risk of cerebral edema is removed from amended claim 1.
Applicant further argues the written description rejection summarizing that “the application-as-filed reasonably conveys to those of ordinary skill in the art that the inventors were in possession, as of the filing date, of (i) measuring expression levels of the recited biomarkers in systemic blood/plasma samples, (ii) using those measured expression levels as inputs to a machine-learning model, and (iii) outputting a prediction of edema volume for use in clinical management” (pg. 10, par. 1). The argument is not persuasive because Applicant fails to disclose measured expression levels, their correlations with edema and infarct volumes, and outputs of the prediction model.
Claims 1-21 and 23, and 6 and 18 were rejected under 35 U.S.C. §112(b) as being indefinite for lacking biomarker thresholds (pg. 10, par. 3 and pg. 11, par. 4-6).
Applicant traverses the rejection and argues that “By expressly reciting use of a machine-learning model to process quantitative expression data and output a defined clinical parameter (edema volume), amended claim 1 eliminates any ambiguity as to how the claimed determination is made. A person of ordinary skill in the art would readily understand that the "prediction of edema volume" is produced algorithmically based on the model's training and feature weighting, not by comparison to manually selected thresholds or arbitrary fold-change cutoffs” (pg. 11, par. 1). The argument is not persuasive because Applicant attempts to substitute the missing biomarker ranges with general reference to the machine-learning model. However, the machine-learning model is not disclosed in the specification as an algorithm or a formula that can be readily implemented/used by a person of ordinary skill in the art. Therefore, in the absence of any biomarker concentrations or their changes (e.g., an increase or a decrease in concentration) the reference to the model fails to satisfy the written description requirement.
Applicant later states that “Accordingly, the Examiner's objections regarding unspecified ranges, fold differences, or protein combinations are no longer applicable to amended claim 1” (pg. 11, par. 3). The argument is not persuasive because Applicant still needs to demonstrate some data supporting the written description requirement. The current state of the disclosure is as follows: some, undisclosed measured concentrations of the biomarkers were fed into a model with undisclosed parameters or an algorithm, and some, undisclosed output values were generated.
Applicant also states that “The Federal Circuit has repeatedly recognized that claims need not recite specific numerical cutoffs where the specification teaches an objective method for generating an output” (pg. 11, par. 2). The process of patent examination relies on the MPEP. The Federal Circuit decisions must be cited in the current revision of MPEP to be considered.
Applicant argues rejection of claim 14 for being “indefinite because it is "unclear how the infarct volume is calculated based on the detected amounts" of the recited proteins” (pg. 12, par. 2). Specifically, Applicant argues that “claim 14 recites prediction of infarct volume, not manual calculation based on individual protein levels” (pg. 12, par. 3). The argument is not persuasive because replacing the term “calculation” with the term “prediction” does not change the nature of the rejection. When using a computer for prediction purposes Applicant still relies on calculations made by the software. The model generated by the machine learning algorithm can be expressed as a formula or a set of formulas. The specification fails to disclose any formula.
Applicant argues that “the specification separately discloses how infarct volume itself is defined and measured (e.g., imaging-based segmentation), thereby providing clear meaning to the output parameter. When read in light of the specification, claim 14 informs those of ordinary skill in the art that infarct volume is predicted algorithmically from expression data using disclosed modeling approaches. The claim therefore has clear metes and bounds” (pg. 12, pg. 4). The argument is not persuasive because it fails to address the metes and bounds and instead replaces it with “informs those of ordinary skill in the art”.
Claims 1-21 stand rejected under 35 U.S.C. §101 as being drawn to a natural correlation and mental processes, with detection steps considered routine and conventional (pg. 12, last par.). Applicant traverses the rejection and analyses subject matter eligibility (pg. 12-16).
Specifically, Applicant argues that “claim 1 no longer merely "identifies risk"” (pg. 13, last par.) and “Under MPEP §2106.04(d), claims integrate a judicial exception into a practical application when they apply the exception in a manner that "imposes a meaningful limit" and results in a real-world effect. That is precisely what amended claim 1 does” (pg. 14, par. 3). The argument is not persuasive because Applicant fails to point out where this “meaningful limit” in disclosed in the specification. Additionally, Applicant fails to demonstrate the “a real-world effect” because the specification fails to provide evidence of patients treated according to the predictions of the machine-learning model. Finally, neither the machine-learning model nor the specification link the treatment options of claims 8-13 to edema and infarct volumes that are outputted by the machine-learning model. Therefore, the “a real-world effect” is not supported by provided evidence.
Applicant argues that “The Examiner's "Mental Process" Characterization Is No Longer Applicable” (pg. 14, par. 4-6). The argument is persuasive and the “mental process” is removed from 101 rejection.
Applicant argues that “Machine-Learning Processing Supplies the "Something More"” (pg. 15, par. 4- pg. 16, par. 1). Specifically, Applicant argues that “In Ex parte Desjardins, designated precedential by USPTO Director John A Squires on November 4, 2025, the Appeals Review Panel held that claims directed to machine-learning techniques were patent-eligible where they improved how the machine-learning model itself operates and were not evaluated at an impermissibly high level of abstraction” (pg. 15, par. 7).
The argument is not persuasive because the cited document is not related to just any use of machine learning. The document states that “In Step 2A Prong Two, the ARP then determined that the specification identified improvements as to how the machine learning model itself operates, including training a machine learning model to learn new tasks while protecting knowledge about previous tasks to overcome the problem of “catastrophic forgetting” encountered in continual learning systems” (Advance notice of change to the MPEP in light of Ex Parte Desjardins, pg. 2, par. 2). In Ex Parte Desjardins, improvements were made as to how the machine learning model itself operates. In the instant case, Applicant merely used a known extremely randomized trees approach without making any contribution to the field of machine learning. Therefore, the cited USPTO document does not apply.
Additionally, the document states that “if the specification explicitly sets forth an improvement only in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine that the claim improves technology or a technical field” (id., par. 2). Instant specification does not provide “the detail necessary to be apparent to a person of ordinary skill in the art”.
Applicant argues that “Treatment Claims Are Not Mere Field-of-Use Limitations” (pg. 16, par. 3-4). Specifically, that “Under MPEP §2106.05(e), claims that control or guide treatment based on a computed output constitute a practical application and weigh strongly in favor of eligibility” (id., par. 4). The argument is not persuasive because MPEP §2106.05(e) does not address any computer-guided treatments.
To summarize Applicant’s arguments related to rejection of claims 1-21 under §101 – Applicant fails to provide persuasive evidence that the claims: “Are not directed to a judicial exception alone; Integrate any judicial exception into a practical, real-world medical application; and Recite an inventive concept that is significantly more than any alleged natural correlation or abstract idea” (pg. 16, par. 6).
Claims 22-23 were rejected under 35 U.S.C. 103 (pg. 16, last par.). Applicant argues that “in view of the amendment to claim 22, which recasts the claim as a method of predicting edema volume using a specific biomarker panel and a specific analytical workflow, as also reflected in claims 1-21, which the Examiner has already determined are free of the prior art” (pg. 17, par. 3). The argument is persuasive and the rejection of claims 22-24 under 35 U.S.C. 103 is withdrawn.
Conclusion
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 THREE-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 date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Alexander Volkov whose telephone number is (571) 272-1899. The examiner can normally be reached M-F 9:00AM-5:00PM (EST).
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Bao-Thuy Nguyen can be reached on (571) 272-0824. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ALEXANDER ALEXANDROVIC VOLKOV/Examiner, Art Unit 1677
/REBECCA M GIERE/Primary Examiner, Art Unit 1677
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