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 .
Herein, “the previous Office action” refers to the Final Rejection filed on 2/27/2025.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 7/25/2025 has been entered.
Priority
As detailed on the Filing Receipt filed 6/1/2020, the instant application claims priority to as early as 11/15/2018. Applicant’s claim for the benefit of a prior-filed application under 35 USC § 120 is acknowledged. Applicant has not complied with one or more conditions for receiving the benefit of an earlier filing date under 35 USC § 120 as follows:
The later-filed application must be an application for a patent for an invention which is also disclosed in the prior application (the parent or original nonprovisional application or provisional application). The disclosure of the invention in the parent application and in the later-filed application must be sufficient to comply with the requirements of 35 USC § 112(a) except for the best mode requirement. See Transco Products, Inc. v. Performance Contracting, Inc., 38 F.3d 551, 32 USPQ2d 1077 (Fed. Cir. 1994).
The disclosure of the prior-filed application, Provisional Application No. 62/768,054 (filed 11/15/2018, hereafter “‘054”), fails to provide adequate support or enablement in the manner provided by 35 USC § 112(a) for one or more claims of this application.
With respect to claim 29 and dependents therefrom, the prior-filed application does not disclose generating a data set comprising gene expression data from a plurality of gene signatures comprising transcripts of at least 25 genes selected from a group of genes consisting of: B4GALT3, CALR, CALU, CANX, CDS2, CHST12, CHST2, DERL1, DERL2, DNAJC3, EDEM2, EDEM3, EMC9, ERAP1, ERGIC2, ERO1L, EXT1, GALNT2, GOLT1B, HERPUD1, HYOU1, IER3IP1, IMPAD1, KDELC1, KDELR2, LMAN2, LPGAT1, MAN1A1, MANEA, MANF, NUCB2, PDIA4, PDIA6, PIGK, PPIB, SEC24D, SEC61G, SPCS3, SSR1, SSR3, TRAM1, TRAM2, UGGT1, and XBP1.
With respect to claim 34, the prior-filed application does not disclose generating a data set comprising gene expression data from a plurality of gene signatures comprising transcripts of at least 30 genes selected from a group of genes consisting of: B4GALT3, CALR, CALU, CANX, CDS2, CHST12, CHST2, DERL1, DERL2, DNAJC3, EDEM2, EDEM3, EMC9, ERAP1, ERGIC2, ERO1L, EXT1, GALNT2, GOLT1B, HERPUD1, HYOU1, IER3IP1, IMPAD1, KDELC1, KDELR2, LMAN2, LPGAT1, MAN1A1, MANEA, MANF, NUCB2, PDIA4, PDIA6, PIGK, PPIB, SEC24D, SEC61G, SPCS3, SSR1, SSR3, TRAM1, TRAM2, UGGT1, and XBP1.
With respect to claim 53, the prior-filed application does not disclose generating a data set comprising gene expression data from a plurality of gene signatures comprising transcripts of at least 35 or more genes selected from a group of genes consisting of: B4GALT3, CALR, CALU, CANX, CDS2, CHST12, CHST2, DERL1, DERL2, DNAJC3, EDEM2, EDEM3, EMC9, ERAP1, ERGIC2, ERO1L, EXT1, GALNT2, GOLT1B, HERPUD1, HYOU1, IER3IP1, IMPAD1, KDELC1, KDELR2, LMAN2, LPGAT1, MAN1A1, MANEA, MANF, NUCB2, PDIA4, PDIA6, PIGK, PPIB, SEC24D, SEC61G, SPCS3, SSR1, SSR3, TRAM1, TRAM2, UGGT1, and XBP1.
With respect to claim 54, the prior-filed application does not disclose generating a data set comprising gene expression data from a plurality of gene signatures comprising transcripts of a group of genes consisting of: B4GALT3, CALR, CALU, CANX, CDS2, CHST12, CHST2, DERL1, DERL2, DNAJC3, EDEM2, EDEM3, EMC9, ERAP1, ERGIC2, ERO1L, EXT1, GALNT2, GOLT1B, HERPUD1, HYOU1, IER3IP1, IMPAD1, KDELC1, KDELR2, LMAN2, LPGAT1, MAN1A1, MANEA, MANF, NUCB2, PDIA4, PDIA6, PIGK, PPIB, SEC24D, SEC61G, SPCS3, SSR1, SSR3, TRAM1, TRAM2, UGGT1, and XBP1.
Accordingly, claims 29 and dependents therefrom are not entitled to the benefit of the ‘054 application.
The disclosure of the prior-filed application, Provisional Application No. 62/828,895 (filed 4/3/2019, hereafter “‘895”), fails to provide adequate support or enablement in the manner provided by 35 USC § 112(a) for one or more claims of this application.
With respect to claim 29 and dependents therefrom, the prior-filed application does not disclose generating a data set comprising gene expression data from a plurality of gene signatures comprising transcripts of at least 25 genes selected from a group of genes consisting of: B4GALT3, CALR, CALU, CANX, CDS2, CHST12, CHST2, DERL1, DERL2, DNAJC3, EDEM2, EDEM3, EMC9, ERAP1, ERGIC2, ERO1L, EXT1, GALNT2, GOLT1B, HERPUD1, HYOU1, IER3IP1, IMPAD1, KDELC1, KDELR2, LMAN2, LPGAT1, MAN1A1, MANEA, MANF, NUCB2, PDIA4, PDIA6, PIGK, PPIB, SEC24D, SEC61G, SPCS3, SSR1, SSR3, TRAM1, TRAM2, UGGT1, and XBP1.
With respect to claim 34, the prior-filed application does not disclose generating a data set comprising gene expression data from a plurality of gene signatures comprising transcripts of at least 30 genes selected from a group of genes consisting of: B4GALT3, CALR, CALU, CANX, CDS2, CHST12, CHST2, DERL1, DERL2, DNAJC3, EDEM2, EDEM3, EMC9, ERAP1, ERGIC2, ERO1L, EXT1, GALNT2, GOLT1B, HERPUD1, HYOU1, IER3IP1, IMPAD1, KDELC1, KDELR2, LMAN2, LPGAT1, MAN1A1, MANEA, MANF, NUCB2, PDIA4, PDIA6, PIGK, PPIB, SEC24D, SEC61G, SPCS3, SSR1, SSR3, TRAM1, TRAM2, UGGT1, and XBP1.
With respect to claim 53, the prior-filed application does not disclose generating a data set comprising gene expression data from a plurality of gene signatures comprising transcripts of at least 35 or more genes selected from a group of genes consisting of: B4GALT3, CALR, CALU, CANX, CDS2, CHST12, CHST2, DERL1, DERL2, DNAJC3, EDEM2, EDEM3, EMC9, ERAP1, ERGIC2, ERO1L, EXT1, GALNT2, GOLT1B, HERPUD1, HYOU1, IER3IP1, IMPAD1, KDELC1, KDELR2, LMAN2, LPGAT1, MAN1A1, MANEA, MANF, NUCB2, PDIA4, PDIA6, PIGK, PPIB, SEC24D, SEC61G, SPCS3, SSR1, SSR3, TRAM1, TRAM2, UGGT1, and XBP1.
With respect to claim 54, the prior-filed application does not disclose generating a data set comprising gene expression data from a plurality of gene signatures comprising transcripts of a group of genes consisting of: B4GALT3, CALR, CALU, CANX, CDS2, CHST12, CHST2, DERL1, DERL2, DNAJC3, EDEM2, EDEM3, EMC9, ERAP1, ERGIC2, ERO1L, EXT1, GALNT2, GOLT1B, HERPUD1, HYOU1, IER3IP1, IMPAD1, KDELC1, KDELR2, LMAN2, LPGAT1, MAN1A1, MANEA, MANF, NUCB2, PDIA4, PDIA6, PIGK, PPIB, SEC24D, SEC61G, SPCS3, SSR1, SSR3, TRAM1, TRAM2, UGGT1, and XBP1.
With respect to claim 56, the prior-filed application does not disclose a k-nearest neighbors classifier.
Accordingly, claims 29 and dependents therefrom are not entitled to the benefit of the ‘895 application.
The earliest claimed priority application which provides adequate support for all instant limitations is Provisional Application No. 62/833,493, which was filed on 4/12/2019. Claims 29, 33-34, 42-50, 53-54, 56-57 and 59 are thus accorded an effective filing date of 4/12/2019.
Information Disclosure Statement
The Information Disclosure Statements filed on 7/25/2025 and 10/17/2025 are in compliance with the provisions of 37 CFR 1.97 and have been considered in full. Signed copies of the IDS are included with this Office Action.
Claim Status
Claims 1-28, 30-32, 35-41, 51-52, 55 and 58 are canceled.
Claims 29, 33-34, 42-50, 53-54, 56-57 and 59 are pending.
Claims 42-50 stand withdrawn pursuant to 37 CFR 1.142(b) as being directed to a nonelected invention, there being no currently allowable generic or linking claim. Election was made without traverse in the reply filed on 8/24/2022.
Claims 29, 33-34, 53-54, 56-57 and 59 are examined herein.
Withdrawn Objections/Rejections
The rejection of claims 55 and 58 under 35 USC § 101, as being directed to nonstatutory subject matter, is hereby withdrawn in view of Applicant’s cancellation of the claims.
The rejection of claim 58 under 35 USC § 103, as being unpatentable over Pascual, in view of Lugar, is hereby withdrawn in view of Applicant’s cancellation of the claim.
The rejection of claim 55 under 35 USC § 103, as being unpatentable over Pascual, in view of Lugar, Patel and Sun, is hereby withdrawn in view of Applicant’s cancellation of the claim.
Claim Interpretation
Claim 29 requires performance of the following method steps ‘by a device’:
“assaying, by a device, a biological sample obtained or derived from the subject” (line 3), the assaying comprising:
“performing, by the device, an analysis with a microarray… comprising measuring a concentration of a nucleic acid sequence from the biological sample or an amplicon thereof” (lines 6-8);
“performing, by the device, an RNA-Seq analysis comprising analyzing the transcriptome of the biological sample by sequencing a complementary DNA (cDNA) synthesized from an RNA nucleic acid sequence from the biological sample or an amplicon of the cDNA” (lines 9-12);
“generating, by the device, a data set based on the assaying of the biological sample… comprising gene expression data from a plurality of gene signatures” (lines 13-14), the generation comprising at least:
“extracting, by the device, based on the performed analysis or performed RNA-Seq analysis, information related to the plurality of gene signatures” (lines 15-16);
The specification reads, “In some embodiments, the platforms, systems, media, and methods described herein include a digital processing device, or use of the same… In further embodiments, the digital processing device includes one or more hardware central processing units (CPUs) or general purpose graphics processing units (GPGPUs)… suitable digital processing devices include, by way of non-limiting examples… computers” (para. 0386-7).
In light of the specification, the term “device” as used in the instant claims is understood to encompass, while not being limited to, a general-purpose computer hardware device. Thus, limitation of claimed method steps to performance “by a device” is understood to encompass performance on a computer.
Claim Rejections - 35 USC § 101
35 USC § 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 29, 31, 33-34, 53-54, 56-57 and 59 are rejected under 35 USC § 101 because the claimed invention is directed to non-statutory subject matter. The new grounds of rejection presented herein were necessitated by Applicant’s amendment of the claims (filed 11/15/2024) to incorporate newly-presented limitations.
"Claims directed to nothing more than abstract ideas, natural phenomena, and laws of nature are not eligible for patent protection" (MPEP 2106.04 § I).
Abstract ideas include mathematical concepts (including formulas, equations and calculations), and procedures for evaluating, analyzing or organizing information, which are a type of mental process (MPEP 2106.04(a)(2)).
Laws of nature and natural phenomena include principles, relations, and products that are naturally occurring or do not have markedly different characteristics compared to what occurs in nature (MPEP 2106.04(b)).
The claims as a whole, considering all claim elements both individually and in combination, do not amount to significantly more than an abstract idea (e.g., the process of identifying an immunological state of a subject) or a law of nature (e.g., the natural correlation between lupus activity and expression of gene signatures).
Step 1: The Four Categories of Statutory Subject Matter (MPEP 2106.03)
The claims are directed to a method, which falls under the ‘process’ category of statutory subject matter.
Step 2A, Prong One: Whether the Claims Set Forth or Describe a Judicial Exception (MPEP 2106.04 § II.A.1)
‘Mathematical concepts’ are relationships between variables and numbers, numerical formulas or equations, or acts of calculation, which need not be expressed in mathematical symbols (MPEP 2106.04(a)(2) § I). The claims recite the following element that encompasses mathematical concepts, at least under the broadest reasonable interpretation:
“a machine learning algorithm trained on a set of gene expression data” (claim 29), i.e., an optimized series of equations, wherein:
“the machine learning algorithm trained on a set of gene expression data is a k-nearest neighbor classifier, or a random forest classifier” (claim 56), i.e., particular types of algorithms.
The recited trained machine learning classifier is a series of equations, or algorithm, and the process of its use is an act of calculation. Thus, the claims recite elements that encompass mathematical concepts.
‘Mental processes’ are processes that can be performed in the human mind at least with use of a physical aid, e.g., a slide rule or pen and paper (MPEP 2106.04(a)(2) § III). The above recited act of calculation is practicably performable in the human mind, rendering it a mental process as well. See, for example, the cited article by Cover et al (IEEE Transactions on Information Theory 13(1): 21–27; published January 1967), which discusses performance by a statistician (i.e., a human) of the technique of k-nearest neighbor classification and does not include any mention of computer implementation.
The claims further recite the following additional elements that encompass mental processes, at least under their broadest reasonable interpretation:
“identifying… the immunological state of the subject” (claim 29), i.e., making an inference based on associated information;
“annotating… records associated with the subject based on the identified immunological state” (claim 29), i.e., adding additional information to existing records.
The human mind is capable of making an inference based on considered information, and adding information to existing (e.g., written) records. Thus, the claims recite elements that encompass mental processes.
Mathematical concepts and mental processes constitute enumerated categories of abstract ideas (MPEP 2106.04(a)(2) §§ I and III). Hence the claims recite elements that, individually and in combination, constitute an abstract idea.
Correlations between subject biomarker levels or genotype and subject clinical condition are a natural consequence of underlying biology, and the courts have consequently identified such correlations as laws of nature. For example, in Cleveland Clinic Foundation v. True Health Diagnostics, LLC, 859 F.3d 1352 (Fed. Cir. 2017; hereafter “CCF”), the court ruled that a correlation between levels of methylperoxidase in a subject sample and subject risk of cardiovascular disease was a law of nature (see 859 F.3d at 1361). In Vanda Pharmaceuticals Inc. v. West-Ward Pharmaceuticals, 887 F.3d 1117 (Fed. Cir. 2018, hereafter “Vanda”), the court similarly ruled that a relationship between subject genotype and treatment outcome was a law of nature (see 887 F.3d at 1135-36).
The claims require performance of data processing upon “[a] dataset comprising a quantitative measure of each of a plurality of gene signatures” (claim 29), derived from a subject sample, to achieve the function of “identifying… the immunological state of the subject” (claim 29). These limitations require that data processing be performed on genomic measurement data derived from subject samples, and utilized to identify a subject clinical condition. The claimed function of identifying relies upon naturally occurring correlations between quantitative measures of gene signatures in subject samples and subject immunological state. The referenced limitations, like those considered in CCF and Vanda, thus constitute a law of nature.
This law of nature is further delimited by the following limitations:
“the plurality of gene signatures comprises transcripts of at least 25 genes selected from a group of genes consisting of: B4GALT3, CALR… and XBP1” (claim 29);
“the immunological state is a lupus condition or systemic lupus erythematosus (SLE)” (claim 33);
“the plurality of gene signatures comprises transcripts of at least 30 genes selected from a group of genes consisting of: B4GALT3, CALR… and XBP1” (claim 34);
“the plurality of gene signatures comprises transcripts of at least 35 genes selected from a group of genes consisting of: B4GALT3, CALR… and XBP1” (claim 53);
“the plurality of gene signatures comprises transcripts of a group of genes consisting of: B4GALT3, CALR… and XBP1” (claim 54); and
“the biological sample comprises a whole blood sample or a peripheral blood mononuclear cell sample” (claim 57).
The above limitations further specify the clinical conditions and genes between which a natural association is observed by the claimed invention.
Thus, the claims recite elements that constitute an abstract idea and a law of nature. The claims must therefore be examined further to determine whether they integrate these judicial exceptions into a practical application (MPEP 2106.04(d)).
Step 2A, Prong Two: Whether the Claims Contain Additional Elements that Integrate the Judicial Exception(s) into a Practical Application (MPEP 2106.04 § II.A.2)
The claims recite the following additional elements, which gather data necessary for performance of claimed functions:
“assaying… a biological sample obtained or derived from a subject… comprising: performing, by the device, an analysis with a microarray, the analysis comprising measuring a concentration of a nucleic acid sequence from the biological sample or an amplicon thereof; or performing, by the device, an RNA-Seq analysis comprising analyzing the transcriptome of the biological sample by sequencing a complementary DNA (cDNA) synthesized from an RNA nucleic acid sequence from the biological sample or an amplicon of the cDNA” (claim 29); and
“generating… a data set based on the assaying of the biological sample, the data set comprising gene expression data from a plurality of gene signatures, the generation comprising at least extracting, by the device, based on the performed analysis of performed RNA-seq analysis, information related to the plurality of gene signatures” (claim 29), i.e., receiving measured gene expression values.
Necessary data gathering is considered insignificant pre-solution activity, and as such insufficient to integrate judicial exceptions into a practical application (MPEP 2106.05(g)). Furthermore, the obtained and derived data are representative of natural phenomena.
The claims further recite the additional element of “by a device” (claim 29), which requires performance of claimed functions using, e.g., computer hardware (see ‘Claim Interpretation’ section). The claims also recite a step of “executing… an application” (claim 29), i.e., a computer program, which necessarily requires performance using computer hardware.
The claims do not describe any specific computational steps by which computer hardware performs or carries out functions drawn to the abstract idea, nor do they provide any details of how specific structures of computer hardware are used to implement this abstract idea.
The claims state nothing more than that a device, e.g., a generic computer hardware device performs functions drawn to the abstract idea, and therefore amount to mere instructions to apply the abstract idea using computer hardware. As such, the claims do not integrate the abstract idea into a practical application (see MPEP 2106.04(d) § I and 2106.05(f)). See also MPEP 2106.04(a)(2) § III(C-D), regarding computer implementation of mental processes.
No further additional elements are recited.
When the claims are considered as a whole: they do not improve the functioning of a computer, other technology, or technical field (MPEP 2106.04(d)(1) and 2106.05(a)); they do not apply the judicial exceptions to effect a particular treatment or prophylaxis for a disease or medical condition (MPEP 2106.04(d)(2)); they do not implement the judicial exceptions with, or in conjunction with, a particular machine (MPEP 2106.05(b)); they do not effect a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)); and they do not apply or use the judicial exceptions in some other meaningful way beyond linking the use of the judicial exceptions to a particular field of use (i.e., clinical diagnosis; MPEP 2106.05(h)).
Therefore, the claims do not integrate the judicial exceptions into a practical application. See MPEP 2106.04(d) § I.
Because the claims recite an abstract idea and a natural phenomenon, and do not integrate those judicial exceptions into a practical application, the claims are directed to those judicial exceptions. Claims that are directed to judicial exceptions must be examined further to determine whether the additional elements besides the judicial exceptions render the claims significantly more than the judicial exceptions. Additional elements besides the judicial exceptions may constitute inventive concepts that are sufficient to render the claims significantly more (MPEP 2106.05).
Step 2B: Whether the Claims Contain Additional Elements that Amount to an Inventive Concept (MPEP 2106.05)
As noted above, several recited additional elements amount to insignificant extra-solution activities. Mere addition of insignificant extra-solution activities does not amount to an inventive concept that would render the claims significantly more than recited judicial exceptions, particularly when the activities are well-understood or conventional (MPEP 2106.05(g)).The conventionality of recited additional elements that amount to insignificant extra-solution activity must be further considered.
Recited additional elements amounting to insignificant extra-solution activities encompass processes which are indicated as well-known, routine and conventional activity and/or activity that may be performed with commercially-available products by the instant specification (see MPEP 2106.07(a) § III).
The instant specification reads, in relevant part: “Methods of assaying may include any assay known in the art or described in the literature, for example, a microarray assay, a sequencing assay (e.g., DNA sequencing, RNA sequencing, or RNA-Seq), or a quantitative polymerase chain reaction (qPCR) assay” (pg. 112, para. 0458). The specification additionally indicates that exemplary gene expression data was collected using ‘HG-UI33’ and ‘Human HT-12v4.0’ microarray chips sold by Affymetrix and Illumina (pg. 290, paras. 1025-26 and Table 5).
In this way, the instant specification indicates that the extra-solution activity encompassed by the following elements is well-understood, routine and conventional: assaying a biological sample to generate gene expression data; performing analysis with a microarray; and performing an RNA-Seq analysis.
Additionally, processes of determining biomarker levels in biological samples have been recognized by the courts as well-understood, routine, and conventional activities. See the court decisions in Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 79 (2012); Cleveland Clinic Foundation v. True Health Diagnostics, LLC, 859 F.3d 1352, 1362 (Fed. Cir. 2017).
Hence, the encompassed activity is considered well-understood, routine and conventional. Well-understood, routine and conventional activities are insufficient to constitute an inventive concept that would render the claims significantly more than an abstract idea (MPEP 2106.05(d)).
The claims limit a number of method steps to performance “by a device”, including steps which encompass the following activities that the courts have recognized as well-understood, routine and conventional functions of general-purpose computer hardware:
necessary data gathering, including receiving information (see CyberSource v. Retail Decisions, 654 F.3d 1366, 1370 (Fed. Cir. 2011); EON Corp. IP Holdings LLC v. AT&T Mobility LLC, 785 F.3d 616, 622 (Fed. Cir. 2015); OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015));
“determining… an immunological state of the subject based on the generated data set”, i.e., processing data and/or analyzing data and producing a result (see EON Corp. IP Holdings LLC v. AT&T Mobility LLC, 785 F.3d 616, 622 (Fed. Cir. 2015); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 614-15 (Fed. Cir. 2016));
“executing… an application… with the data set as input to the application”, i.e., inputting information into a computer program (see Content Extraction & Transmission LLC v. Wells Fargo Bank, N.A., 776 F.3d 1343, 1345 (Fed. Cir. 2014)); and
“annotating… records”, i.e., electronic recordkeeping (see Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225 (2014); Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 716 (Fed. Cir. 2014)).
Thus, limitation of the encompassing steps to performance “by [a] device” does not amount to significantly more than mere instructions to apply judicial exceptions using computer hardware. Mere instructions to apply judicial exceptions using computer hardware are insufficient to constitute an inventive concept that would render the claims significantly more than said judicial exceptions (MPEP 2106.05(f)).
When the claims are considered as a whole: they do not improve the functioning of a computer, other technology, or technical field (MPEP 2106.04(d)(1) and 2106.05(a)); they do not implement the judicial exceptions with, or in conjunction with, a particular machine (MPEP 2106.05(b)); they do not effect a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)); they do not add specific limitations or steps, other than what is well-understood, routine and conventional activity in the field, that confine the claims to a particular useful application (MPEP 2106.05(d)); and they do not provide meaningful limitations beyond linking the use of the judicial exceptions to a particular field of use (i.e., clinical diagnosis; MPEP 2106.05(h)).
Therefore, the claims do not provide an inventive concept and/or significantly more than the judicial exceptions themselves. See MPEP 2106.05.
Conclusion: Claims are Directed to Non-statutory Subject Matter
For these reasons, the claims, when the limitations are considered individually and as a whole, are directed to judicial exceptions and lack an inventive concept. Hence, the claimed invention does not constitute significantly more than the judicial exceptions, so the claims are rejected under 35 USC § 101 as being directed to non-statutory subject matter.
Response to Arguments - Claim Rejections Under 35 USC § 101
In the reply filed 7/25/2025, Applicant traverses the rejection under 35 USC § 101 and presents arguments in support of patent eligibility.
Applicant alleges that the claims are not directed to laws of nature (e.g., naturally occurring correlations or fundamental scientific principles), but rather a concrete technological application (pg. 10, para. 1 – pg. 11, para. 2). Applicant points to the court decisions in Diamond v. Chakrabarty, 447 U.S. 303 (1980, hereafter “Chakrabarty”) and Rapid Litig. Mgmt. v. CellzDirect, Inc., 827 F.3d 1042 (Fed. Cir. 2016, hereafter “CellzDirect”) as precedent for distinction in subject matter eligibility between naturally occurring phenomena and specific human applications or technological processes that utilize such phenomena, e.g., the claimed subject matter (pg. 11, para. 3).
The Chakrabarty case regards the eligibility of an invention drawn to a genetically engineered bacterium. The Court distinguished the claimed bacterium from an unmodified product of nature, noting that “the patentee has produced a new bacterium with markedly different characteristics from any found in nature… His discovery is not nature’s handiwork, but his own” (447 U.S. at 310). The instant application does not regard a human-modified organism, but rather a method involving measurement and analysis of naturally-occurring biological parameters (gene expression levels). The instant fact pattern is not viewed as particularly analogous to that considered in Chakrabarty. In CellzDirect, the court considers claims directed to a method preserving liver cells comprising multiple freeze-thaw cycles. The CellzDirect court reasoned that the claims at issue apply a discovered natural phenomenon (the ability of liver cells to survive the multiple freeze-thaw process) to create a “new and improved technique for producing a tangible and useful result” (Id. at 1049-50). The Court also distinguished this application from mere observation or detection of a natural phenomenon, comparing the considered fact pattern with those of a number of earlier cases, and noted that prior art teaches away from performance of multiple freezings (Id. at 1048, 1051).
The cited earlier cases include Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66 (2012, hereafter “Mayo”), Ariosa Diagnostics, Inc. v. Sequenom, Inc., 788 F.3d 1371 (Fed. Cir. 2015, hereafter “Sequenom”), and Genetic Techs., Ltd. v. Merial LLC, 818 F.3d 1369 (Fed. Cir. 2016, hereafter “Genetic Techs”). In each of these cases, the courts considered claims involving measuring and analyzing biological parameters (metabolite levels in Mayo, cell-free fetal DNA in Sequenom, coding DNA regions in Genetic Techs) and concluded that recited additional elements did not amount to significantly more than observation or identification of natural phenomena.
Unlike Chakrabarty or CellzDirect, the instant claims do not involve either a human-modified organism or a process that applies a natural law to produce a tangible result in an improved manner. Like Mayo, Ariosa and Genetic Techs, the instant claims involve determination of additional information through analysis of naturally-occurring parameters. In the absence of significant additional elements, a process that employs mathematical algorithms to manipulate existing information to generate additional information is not patent eligible (Digitech Image Techs., LLC vs. Elecs. For Imaging, Inc., 758 F.3d 1344, 1351 (Fed. Cir. 2014)).
Thus, the argument against consideration of the claims as directed to laws of nature is found unpersuasive. See also Cleveland Clinic Foundation v. True Health Diagnostics, LLC, 859 F.3d 1352 (Fed. Cir. 2017, hereafter “CCF”), wherein the court held as ineligible claims involving measuring of myeloperoxidase levels and analytical correlation with subject risk of cardiovascular disease.
Applicant states that mathematical concepts include fundamental mathematical truths, formulas, and calculations that can be performed mentally or with pen and paper, while the recited trained machine learning algorithm represents a specific, concrete technological application rather than an abstract mathematical principle (pg. 12, paras. 1-2).
Mathematical concepts are not limited to those which can be practicably performed mentally (e.g., with pen and paper). A machine learning algorithm is a series of mathematical functions used to sequentially transform input values, whether evaluated with pen and paper or on a computer, and thus is a mathematical concept. A trained machine learning algorithm is simply a series of mathematical functions with optimized parameters, and is likewise a mathematical concept. The fact that the claimed machine learning algorithm is trained on particular data merely signifies its application to a particular field of use, which is not sufficient to demonstrate the integration of the mathematical concept into a practical application as defined by the courts (MPEP 2106.05(f) and (h)).
Thus, the argument against consideration of the algorithm as a mathematical concept is found unpersuasive. See Recentive Analytics, Inc. v. Fox Corp., 134 F.4th 1205 (Fed. Cir. 2025), wherein the court considered the statutory nature of claims applying a trained machine learning algorithm in a particular field of use.
Applicant notes precedent from Diamond v. Diehr, 450 U.S. (1981)) that mathematical algorithms become patent-eligible when applied to transform or reduce an article to a different state or thing, and asserts that the claimed machine learning algorithm transforms raw gene expression data into immunological state determinations (pg. 5, para. 2; pg. 11, para. 2; pg. 12, para. 3).
The courts have distinguished between particular transformation of an article and ineligible transformation of data, holding that “mere manipulation or reorganization of data… does not satisfy the transformation prong” (CyberSource Corp. vs. Retail Decisions, Inc., 654 F.3d 1366, 1375 (Fed. Cir. 2011)). Thus, the argument of transformation is found unpersuasive.
Applicant notes precedent from Genetic Techs that claims involving specific genetic markers can be patent-eligible when they involve concrete applications, and asserts that the claims specify particular gene signatures rather than reciting generic data analysis (pg. 12, para. 4).
The Genetic Techs court found the detection of a specific genetic allele by the invention, considered in combination with conventional laboratory techniques, to not supply sufficient inventive concept to render claims as patent eligible (818 F.3d at 1377-80). Microarray and RNA-Seq analyses are considered as conventional laboratory techniques. Review of the instant specification, alongside prior art, indicates that measurement of the specified genes via these techniques is well-understood, routine and conventional activity. See rejection for full details. Thus, the argument of specific genetic markers is found unpersuasive.
Applicant alleges that the present claims cannot possibly be performed mentally due to their technological complexity, highlighting the technological requirements of the claimed nucleic acid measurement steps and machine learning algorithm execution (pg. 13, paras. 1-3).
The previous Office action did not assert that the nucleic acid measurement steps encompass mental processes, while the referenced limitation of “executing, by the device, an application defined by a machine learning algorithm”(claim 29) was incorporated by Applicant’s amendment (filed 7/25/2025) and has not been previously examined. Neither the nucleic acid measurement steps nor the application execution step are themselves viewed as mental processes. Rather, these steps are considered as additional elements that are not sufficient to integrate the recited judicial exceptions (e.g., mental processes) into a practical application or provide a significant inventive concept. Thus, the claims as a whole are considered as directed to judicial exceptions without significantly more. The argument that said steps require non-mental technological implementation is found unpersuasive regarding eligibility of the claims as a whole.
Applicant alleges that the claimed data generation step requires computational processing of complex genomic data relating to a specifically enumerated gene list, and cannot be performed mentally (pg. 13, para. 4).
Mental processes include both processes which can be performed mentally as claimed, and processes “which are the equivalent of human mental work” (CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1371 (Fed. Cir. 2011)) as claimed. The courts have consistently held that the mere computer implementation of processes which can be performed mentally does not alter their nature as equivalent to human mental work. See, e.g., SAP America,
Inc. v. InvestPic, LLC, 898 F.3d 1161, 1163 (Fed. Cir. 2018).
But for limitation to performance “by a device”, the referenced step as written (“extracting…signatures”) could be performed mentally under its broadest reasonable interpretation. A human is capable of reading a printout of results from a performed analysis, comprising gene expression values, and (with pen and paper) hand-copying particular values to a matrix on a separate sheet. That is, extracting information related to a plurality of gene signatures and generating a data set based on a performed analysis. The referenced step is therefore considered as the equivalent of human mental work as written, and the argument against its consideration as a mental process is found unpersuasive.
Applicant notes that the instant claims, similarly to those held eligible in SiRF Technology, Inc. v. International Trade Commission, 601 F.3d 1319 (Fed. Cir. 2010, hereafter “SiRF Tech”), require specific technological implementation (pg. 13, para. 5 – pg. 14, para. 1). The method claims held eligible in SiRF Tech required the use of a GPS receiver, which the court held to be a particular machine, and could not be performed otherwise (601 F.3d at 1331-3). The instant claims do not require the use of a particular machine, but merely a “device” encompassing a general-purpose computer (see ‘Claim Interpretation’ section). The instant claims are not considered as eligible under similar reasoning to that provided by the SiRF Tech court, and the argument of specific technological implementation is found unpersuasive.
Applicant alleges that the claimed methods, similarly to those held eligible in BASCOM Global Internet v. AT&T Mobility LLC, 827 F.3d 1341 (Fed Cir. 2016, hereafter “BASCOM”) include a non-conventional combination of specific technological elements that constitute significantly more than abstract concepts. Applicant highlights the following claim features: device-based assaying of specific gene signatures using sophisticated analytical techniques, specific biological sample processing and analysis, generation of quantitative gene expression datasets, execution of trained machine learning algorithms, and automated record annotation based on determined immunological states (pg. 14, paras. 3-4).
The claims considered in BASCOM are directed to a content filtering system and server for filtering content retrieved from an Internet computer network. The court found these claims to recite a particular combination of technical features providing an improvement in the functioning of the claimed computer system over prior content filtering systems, despite conventionality of the claimed elements as considered individually (827 F.3d at 1348-51). The BASCOM court specifically noted that the claims considered therein did not merely recite abstract ideas and require their performance with generic computer components, which would not have conferred eligibility, but were found eligible due to provision of said improvement as supported by the specification (827 F.3d at 1351).
Instant limitations drawn to the referenced features of data processing, the algorithm, and record annotation recite a number of judicial exceptions (see rejection for full details). The unconventional nature in combination of the recited judicial exceptions themselves is not germane to patentability under § 101 (RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1327-28 (Fed. Cir. 2017)). Recited additional elements include the referenced genetic assaying steps and the referenced limitation of recited steps to performance by a device, which the instant specification indicates as encompassing a generic computer device (see ‘Claim Interpretation’ section).
Steps of measuring specific genetic information via conventional laboratory techniques (e.g., RNA-Seq) have been particularly recognized by the courts as well-understood, routine and conventional and as such insufficient to provide significant inventive concept. See Sequenom at 1377-80; Genetic Techs at 1376-77. Therefore, the addition of this necessary data gathering activity to the recited judicial exceptions does not confer eligibility to the claims.
Steps of receiving, processing, analyzing data, inputting data to programs, and electronic recordkeeping have been recognized by the courts as well-understood, routine and conventional functions of a general-purpose computer (see rejection for case law citations). Limitation of numerous steps to performance by the claimed device is therefore insufficient to provide significant inventive concept to the judicial exceptions encompassed therein, and does not confer eligibility to the claims.
Unlike the claims considered in BASCOM, the instant claims merely gather data required for performance of abstract steps, and implement these steps with a generic device. Indeed, court precedent has held that each of recited steps encompassing abstract ideas are conventional computer functions. Unlike that considered in BASCOM, the instant specification does not supply evidence that technical features of the claimed invention improve the functioning of the claimed device itself compared to technology conventionally employed within the field of the invention.
The instant claims are not considered as eligible under similar reasoning to that provided by the BASCOM court, and the argument of provision of a significant inventive concept by unconventional combination is unpersuasive.
Applicant alleges that the claimed methods, similarly to those held eligible in Enfish, LLC v. Microsoft Corp., 822 F.3d 1327 (Fed. Cir. 2016; hereafter, “Enfish”) represent concrete, technological improvements over conventional methods employed in the field of the invention (pg. 14, para. 5 – pg. 15, para. 1).
The conclusion of eligibility in Enfish was supported by discussion in the considered specification of how the claimed implementation of a specific, recited logical structure provided improved data storage and retrieval functionality to conventional computer hardware (822 F.3d at 1339). Applicant has not pointed to analogous support in the instant specification for a conclusion of technological improvement. Applicant’s assertion of technological improvement is considered conclusory, and found unpersuasive. See Simio, LLC v. FlexSim Software Prods., Inc., 983 F.3d at 1353 (Fed. Cir. 2020).
For these reasons, the arguments are found unpersuasive and the rejection is maintained.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 USC § 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 USC § 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.
The factual inquiries for establishing a background for determining obviousness under 35 USC § 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 USC § 102(b)(2)(C) for any potential 35 USC § 102(a)(2) prior art against the later invention.
Claims 29, 33-34, 56-57 and 59 are rejected under 35 USC § 103 as being unpatentable over Pascual et al (US 2007/0059717; published 3/15/2007; previously cited), in view of Lugar et al (PLoS ONE 7(9): article e44362, pp. 1-15; published September 2012; on IDS 1/8/2021; previously cited). This rejection is maintained from the previous Office action, and has been revised to address the amended claims (filed 7/25/2025).
Claim 29 recites a method for identifying an immunological state of a subject, comprising:
a) assaying, by a device, a biological sample obtained or derived from the subject to generate a data set comprising gene expression data from a plurality of gene signatures, comprising:
1. performing, by the device, an analysis with a microarray, the analysis comprising measuring a concentration of a nucleic acid sequence from the biological sample or an amplicon thereof, or
2. performing, by the device, an RNA-Seq analysis comprising analyzing the transcriptome of the biological sample by sequencing a complementary DNA (cDNA) synthesized from an RNA nucleic acid sequence from the biological sample or an amplicon of the cDNA;
b) generating, by the device, a data set based on the assaying of the biological sample, the data set comprising gene expression data from a plurality of gene signatures, the generation comprising at least extracting, by the device, based on the performed analysis or performed RNA-Seq analysis, information related to the plurality of gene signatures, wherein:
1. the data set comprising gene expression data comprises a quantitative measure of each of a plurality of gene signatures, and
2. the plurality of gene signatures comprises transcripts of at least 25 genes selected from a group of genes consisting of: B4GALT3, CALR, CALU, CANX, CDS2, CHST12, CHST2, DERL1, DERL2, DNAJC3, EDEM2, EDEM3, EMC9, ERAP1, ERGIC2, ERO1L, EXT1, GALNT2, GOLT1B, HERPUD1, HYOU1, IER3IP1, IMPAD1, KDELC1, KDELR2, LMAN2, LPGAT1, MAN1A1, MANEA, MANF, NUCB2, PDIA4, PDIA6, PIGK, PPIB, SEC24D, SEC61G, SPCS3, SSR1, SSR3, TRAM1, TRAM2, UGGT1, and XBP1;
c) determining, by the device, an immunological state of the subject based on the
generated data set, the determination comprising:
1. executing, by the device, an application defined by a machine learning algorithm trained on a set of gene expression data, with the data set as input to the application, and
2. identifying, based on the execution, the immunological state of the subject; and
d) annotating, by the device, records associated with the subject based on the identified immunological state of the subject.
With respect to claim 29, Pascual discloses “methods for aiding in… disease monitoring… in a subject” (Abstract) including “monitoring disease state in an adult subject having systemic lupus erythematosus” (pg. 2, para. 0020), comprising:
a) “contacting [a] suitable sample with a diagnostic composition… under conditions that are favorable to the recognition of one or more nucleic acids… and detecting the location and identity of the nucleic acids recognized” (pg. 3, para. 022) whereby “gene expression profiles can be determined” (pg. 62, para. 0115), i.e., assaying a biological sample obtained or derived from the subject to generate a data set comprising gene expression data from a plurality of gene signatures, wherein:
1. “In one embodiment, the level of mRNA expression is detected… by hybridization to a probe…[that] is immobilized” (pg. 59, para. 0098) such as “a probe immobilized on a substrate that is formed as a microarray” (pg. 60, para. 0103),
2. “Alternatively, gene expression profiles can be determined by sequencing mRNA in a sample… the gene transcripts can be converted to cDNA… subjected to sequence-specific analysis and quantified” (pg. 62, para. 0115), wherein “Detection can… includ[e], e.g., detecting the quantity of… a cDNA produced from the reverse transcription of the mRNA… [or] a DNA amplified from the cDNA” (pg. 59, para. 0097), i.e., sequencing a cDNA synthesized from an RNA nucleic acid sequence from the biological sample or an amplicon of the cDNA, and
b) “Results from the chip assay are typically analyzed using a computer software program… The hybridization data can be read into the program, which calculates the expression levels of the targeted gene(s)” (pp. 61-62, para. 0114), wherein:
1. “The expression profile may contain… a plurality of values representing the levels of expression of multiple genes” (pg. 10, para. 0067), and
2. “By expression profile is meant the level of expression of one or more of the human genes listed… herein” (pg. 10, para. 0067), wherein disclosed genes include CALR (pp. 31, 39), CALU (pp. 28, 39), GALNT2 (pp. 31, 43), KDELR2 (pp. 31, 44), PPIB (pg. 9), SEC61G (pg. 9) and SSR3 (pp. 8, 31, 51), i.e., 7 genes from the claimed set;
c) “The likelihood that an SLE patient will develop renal disease can be predicted by correlation with the over expression and/or under expression of the transcripts identified” (pg. 62, para. 0115), wherein:
1. “data were… import[ed] into GeneSpring software… for gene expression analysis… Statistical comparisons were performed in GeneSpring… The Class Predictor algorithm in GeneSpring and Prediction Analysis of Microarrays (PAM) were used… The class predictor algorithm is a supervised learning algorithm” (pg. 64, paras. 0131-32), i.e., executing, by a device, an application defined by a machine learning algorithm trained on a set of gene expression data, with the data set as input to the application, and
2. “Using the PAM package (Predicted Analysis of Microarrays)… a minimum of 99 probe sets predicted… [patients] who later developed renal disease with 100% accuracy. 37 probe sets predicted later renal disease onset with 86% accuracy (6/7 patients predicted correctly)” (pp. 9-10, para. 0063) and “A supervised learning algorithm”, i.e., the Class Predictor algorithm, “was applied to identify the minimum number of transcripts that discriminate SLE from flu and healthy” (pg. 64, para. 0139), i.e., identifying, based on the execution of software, the immunological state of the subject; and
d) “the expression level of a subject may be determined and stored” (pg. 7, para. 0057).
Additionally, Pascual discloses comparing a subject expression profile to stored reference expression profiles (pg. 5, para. 0047) and storing determined control and/or subject expression levels for subsequent comparison (pg. 7, para. 0057). Pascual also describes comparing subject gene transcript abundances to reference database sequence abundances including data sets for SLE and healthy patients, i.e., patients of known immunological state (pg. 59, para. 0097).
Annotating stored subject expression profiles with determined subject diagnoses, for subsequent use as reference profiles, is considered an obvious variant of the outlined teachings. In this way, Pascual is considered to make obvious annotating records associated with the subject based on the identified immunological state of the subject.
Pascual further discloses “nucleic acid arrays for use in the methods described herein… [that] may include… at least 30.. nucleic acid molecules that specifically hybridize to genes [disclosed therein]” (pg. 59, para. 0096), i.e., assaying expression levels of a plurality of gene signatures comprising at least 25 genes. However, Pascual does not specifically disclose any of the genes B4GALT3, CANX, CDS2, CHST12, CHST2, DERL1, DERL2, DNAJC3, EDEM2, EDEM3, EMC99, ERAP1, ERGIC2, ERO1L, EXT1, GOLT1B, HERPUD1, HYOU1, IER3IP1, IMPAD1, KDELC1, LMAN2, LPGAT1, MAN1A1, MANEA, MANF, NUCB2, PDIA4, PDIA6, PIGK, SEC24D, SPCS3, SSR1, TRAM1, TRAM2, UGGT1 or XBP1, and thus does not disclose analysis of a plurality of gene signatures comprising at least 25 genes from the claimed set.
Lugar discusses “Systematic lupus erythematosus.. a generalized autoimmune disorder characterized by abnormal B cell activation and the occurrence of increased frequencies of circulating plasma cells (PC)… [and] Microarray analysis of gene expression… to characterize circulating PC in subjects with active SLE” (pg. 1, Abstract), and teaches that “The frequency of circulating PC correlates with disease activity… In the normal, non-diseased state, the frequency of circulating PC is quite low and increases in a tightly regulated manner following vaccination or infection. However, in active SLE, the presence of PC is dysregulated with the persistent appearance of increased numbers in the circulation” (pg. 1, l. column). Lugar further teaches that “mature PC have a known gene expression, including the up-regulation of genes limiting apoptosis linked to the unfolded protein response and ER stress” (pg. 2, l. column).
Lugar presents “genes… differentially expressed in SLE PC” (pg. 6, Figure 2 caption), which are listed in supplementary Table S2. These genes include B4GALT3 (line 420), CALR (560), CALU (317 and 457), CHST12 (listed as ‘C4S-2’, 402), CHST2 (470), DERL1 (355), DERL2 (‘F-LAN-1’, 319), DNAJC3 (32), EDEM2 (‘C20orf31’, 553), EDEM3 (‘C1orf22’, 363), ERAP1 (‘ARTS-1’, 527), EXT1 (306), GALNT2 (341), GOLT1B (‘CGI-141’, 338), HYOU1 (292), KDELC1 (234), KDELR2 (238 and 536), LMAN2 (‘C5orf8’, 514), LPGAT1 (624), MAN1A1 (42 and 122), MANEA (45), MANF (‘ARMET’, 76), NUCB2 (14), PDIA4 (‘ERP70’, 185 and 415), PDIA6 (492), PPIB (160 and 263), SEC24D (49 and 126), SEC61G (438), SPCS3 (381 and 567), SSR1 (245 and 296), SSR3 (243), TRAM1 (‘TRAM’, 450), TRAM2 (328) and XBP1 (51).
The combined teachings of Pascual and Lugar exemplify 34 genes from the claimed set, i.e., at least 25 genes from the claimed set.
With respect to claim 33, as detailed above, Pascual discloses “monitoring disease state in an adult subject having systemic lupus erythematosus” (pp. 2-3, para. 0020) wherein “A supervised learning algorithm… was applied to… discriminate SLE”, systemic lupus erythematosus, “from flu and healthy” (pg. 64, para. 0139).
With respect to claim 34, Pascual discloses “nucleic acid arrays for use in the methods described herein… [that] may include… at least 30.. nucleic acid molecules that specifically hybridize to genes [disclosed therein]” (pg. 59, para. 0096), i.e., assaying expression levels of a plurality of gene signatures comprising transcripts of at least 30 genes. As detailed above, the combined teachings of Pascual and Lugar exemplify 34 genes from the claimed set, i.e., at least 30 genes from the claimed set.
With respect to claim 56, Pascual discloses that “Statistical comparisons were performed in GeneSpring… The Class Predictor algorithm in GeneSpring… is a supervised learning algorithm based on Fisher’s exact test combined with k-nearest neighbors clustering” (pg. 64, paras. 0131-32), i.e., a trained machine learning algorithm that is a k-nearest neighbors classifier.
With respect to claim 57, Pascual discloses that “samples used for this invention encompass body fluid… or cells derived therefrom… Cells may be obtained from blood, e.g., peripheral blood mononuclear cells” (pg. 59, para. 0099).
With respect to claim 59, Pascual discloses comparing a subject expression profile to a plurality of reference expression profiles (i.e., molecular endotypes), each associated with the presence/absence and severity of SLE, and selecting the most similar reference profile to thereby diagnose the subject (pg. 58, para. 0089). In other words, identifying the immunological state of the subject as a subset of a lupus condition associated with a particular molecular endotype.
An invention would have been obvious to one of ordinary skill in the art if some teaching in the prior art would have led that person to combine prior art reference teachings to arrive at the claimed invention. Before the effective filing date of the clamed invention, said practitioner would have implemented a gene expression panel further comprising B4GALT3, CHST12, CHST2, DERL1, DERL2, DNAJC3, EDEM2, EDEM3, ERAP1, EXT1, GOLT1B, HYOU1, KDELC1, LMAN2, LPGAT1,MAN1A1, MANEA, MANF, NUCB2, PDIA4, PDIA6, SEC24D, SPCS3, SSR1, TRAM1, TRAM2 and/or XBP1, to enhance the lupus state assessment method of Pascual, because Lugar teaches that expression levels of these genes are differentially associated with systemic lupus erythematosus. Said practitioner would have had a reasonable expectation of success because Pascual and Lugar both discuss measuring expression of genes associated with systemic lupus erythematosus (e.g., CALR, CALU, GALNT2, KDELR2, PPIB, SEC61G and SSR3).
In this way the disclosure of Pascual, in view of Lugar, makes obvious the limitations of claims 29, 33-34, 56-57 and 59. Thus, the invention is prima facie obvious.
Claim 53 is rejected under 35 USC § 103 as being unpatentable over Pascual, in view of Lugar, as applied to claim 29 above, and further in view of Patel (Gene Expression Profiling to Understand the Alterations in the Monocyte Compartment of Pediatric Systemic Lupus Erythematosus [Dissertation], Baylor University; published 2008; previously cited). This rejection is maintained from the previous Office action, and has been revised to address the amended claims (filed 7/25/2025).
With respect to claim 53, Pascual discloses “nucleic acid arrays for use in the methods described herein… [that] may include… at least 40.. nucleic acid molecules that specifically hybridize to genes [disclosed therein]” (pg. 59, para. 0096), i.e., assaying expression levels of a plurality of gene signatures comprising at least 35 or more genes. Pascual exemplifies the genes CALR (pp. 31, 39), CALU (pp. 28, 39), GALNT2 (pp. 31, 43), KDELR2 (pp. 31, 44), PPIB (pg. 9), SEC61G (pg. 9) and SSR3 (pp. 8, 31, 51), i.e., 7 genes from the claimed set.
Pascual does not specifically disclose any of the genes B4GALT3, CANX, CDS2, CHST12, CHST2, DERL1, DERL2, DNAJC3, EDEM2, EDEM3, EMC99, ERAP1, ERGIC2, ERO1L, EXT1, GOLT1B, HERPUD1, HYOU1, IER3IP1, IMPAD1, KDELC1, LMAN2, LPGAT1, MAN1A1, MANEA, MANF, NUCB2, PDIA4, PDIA6, PIGK, SEC24D, SPCS3, SSR1, TRAM1, TRAM2, UGGT1 or XBP1, and thus does not disclose analysis of a plurality of gene signatures comprising at least 35 or more genes from the claimed set.
Lugar presents “genes… differentially expressed in SLE PC” (pg. 6, Figure 2 caption), which are listed in supplementary Table S2. These genes include B4GALT3 (line 420), CALR (560), CALU (317 and 457), CHST12 (listed as ‘C4S-2’, 402), CHST2 (470), DERL1 (355), DERL2 (‘F-LAN-1’, 319), DNAJC3 (32), EDEM2 (‘C20orf31’, 553), EDEM3 (‘C1orf22’, 363), ERAP1 (‘ARTS-1’, 527), EXT1 (306), GALNT2 (341), GOLT1B (‘CGI-141’, 338), HYOU1 (292), KDELC1 (234), KDELR2 (238 and 536), LMAN2 (‘C5orf8’, 514), LPGAT1 (624), MAN1A1 (42 and 122), MANEA (45), MANF (‘ARMET’, 76), NUCB2 (14), PDIA4 (‘ERP70’, 185 and 415), PDIA6 (492), PPIB (160 and 263), SEC24D (49 and 126), SEC61G (438), SPCS3 (381 and 567), SSR1 (245 and 296), SSR3 (243), TRAM1 (‘TRAM’, 450), TRAM2 (328) and XBP1 (51).
Lugar does not specifically disclose any of the genes CANX, CDS2, EMC9, ERGIC2, ERO1L, HERPUD1, IER3IP1, IMPAD1, PIGK and/or UGGT1. The combined teachings of Pascual and Lugar exemplify 34 genes from the claimed set, and thus do not disclose at least 35 or more genes from the claimed set. Patel discusses “gene expression profiling of monocytes from children with active, newly diagnosed and untreated… SLE” (pg. i, Abstract), systemic lupus erythematosus, and presents results regarding differential expression of various genes in these subjects. Patel exemplifies differentially-expressed genes including CALR (pg. 325), CALU (pp. 173 and 336), CANX (pg. 118), CDS2 (pp. 84, 120 and 201), EMC9 (‘CGI-112’, pg. 326), ERAP1 (PG. 118), ERGIC2 (pg. 105), ERO1L (pp. 104, 163 and 210), GALNT2 (pp. 87, 132, 371 and 287), HERPUD1 (pg. 303), IMPAD1 (pp. 110 and 185), KDELR2 (pp. 164 and 338), PIGK (pg. 233), PPIB (pg. 231), SSR3 (pp. 166 and 318) and UGGT1 (‘UGCGL1’, pg. 132).
The combined teachings of Pascual, Lugar and Patel exemplify 43 genes from the claimed set, i.e., at least 35 or more genes from the claimed set.
An invention would have been obvious to one of ordinary skill in the art if some teaching in the prior art would have led that person to combine prior art reference teachings to arrive at the claimed invention. Before the effective filing date of the clamed invention, said practitioner would have implemented a gene expression panel further comprising CANX, CDS2, EMC9, ERGIC2, ERO1L, HERPUD1, IMPAD1, PIGK, and/or UGGT1, to enhance the lupus state assessment method of Pascual, in view of Lugar, because Pascual discloses combined analysis of at least 40 genes differentially associated with systemic lupus erythematosus and Patel teaches that expression levels of these genes are differentially associated with systemic lupus erythematosus (see citations above). The claimed set thus constitutes a combination of favorably-indicated biomarkers, i.e., an obvious-to-try variant of the method of Pascual in light of the additional prior art. Said practitioner would have had a reasonable expectation of success because Pascual and Patel both discuss measuring expression of genes differentially associated with systemic lupus erythematosus (specifically including CALR, CALU, GALNT2, KDELR2, PPIB and SSR3).
In this way the disclosure of Pascual, in view of Lugar and Patel, makes obvious the limitations of claim 53. Thus, the invention is prima facie obvious.
Claim 54 is rejected under 35 USC § 103 as being unpatentable over Pascual, in view of Lugar, as applied to claim 29 above, and further in view of Patel and Sun et al (Oncotarget 8(34): 56768-56779; published 5/25/2017; previously cited). This rejection is maintained from the previous Office action.
With respect to claim 54, Pascual discloses “nucleic acid arrays for use in the methods described herein… [that] may include… at least 50.. nucleic acid molecules that specifically hybridize to genes [disclosed therein]” (pg. 59, para. 0096), i.e., assaying expression levels of a plurality of gene signatures comprising 40 genes. Pascual exemplifies the genes CALR (pp. 31, 39), CALU (pp. 28, 39), GALNT2 (pp. 31, 43), KDELR2 (pp. 31, 44), PPIB (pg. 9), SEC61G (pg. 9) and SSR3 (pp. 8, 31, 51), i.e., 7 genes from the claimed set. Pascual further discloses deriving nucleic acids from plasmablasts and B cells (pg. 63, para. 0128).
Pascual does not specifically disclose any of the genes B4GALT3, CANX, CDS2, CHST12, CHST2, DERL1, DERL2, DNAJC3, EDEM2, EDEM3, EMC99, ERAP1, ERGIC2, ERO1L, EXT1, GOLT1B, HERPUD1, HYOU1, IER3IP1, IMPAD1, KDELC1, LMAN2, LPGAT1, MAN1A1, MANEA, MANF, NUCB2, PDIA4, PDIA6, PIGK, SEC24D, SPCS3, SSR1, TRAM1, TRAM2, UGGT1 or XBP1, and thus does not disclose analysis of a plurality of gene signatures constituting the claimed set.
Lugar teaches that “The frequency of circulating PC correlates with disease activity… In the normal, non-diseased state, the frequency of circulating PC is quite low and increases in a tightly regulated manner following vaccination or infection. However, in active SLE, the presence of PC is dysregulated with the persistent appearance of increased numbers in the circulation” (pg. 1, l. column). Lugar further teaches that “mature PC have a known gene expression, including the up-regulation of genes limiting apoptosis linked to the unfolded protein response and ER stress” (pg. 2, l. column).
Lugar presents “genes… differentially expressed in SLE PC” (pg. 6, Figure 2 caption), which are listed in supplementary Table S2. These genes include B4GALT3 (line 420), CALR (560), CALU (317 and 457), CHST12 (listed as ‘C4S-2’, 402), CHST2 (470), DERL1 (355), DERL2 (‘F-LAN-1’, 319), DNAJC3 (32), EDEM2 (‘C20orf31’, 553), EDEM3 (‘C1orf22’, 363), ERAP1 (‘ARTS-1’, 527), EXT1 (306), GALNT2 (341), GOLT1B (‘CGI-141’, 338), HYOU1 (292), KDELC1 (234), KDELR2 (238 and 536), LMAN2 (‘C5orf8’, 514), LPGAT1 (624), MAN1A1 (42 and 122), MANEA (45), MANF (‘ARMET’, 76), NUCB2 (14), PDIA4 (‘ERP70’, 185 and 415), PDIA6 (492), PPIB (160 and 263), SEC24D (49 and 126), SEC61G (438), SPCS3 (381 and 567), SSR1 (245 and 296), SSR3 (243), TRAM1 (‘TRAM’, 450), TRAM2 (328) and XBP1 (51).
Lugar does not disclose any of the genes CANX, CDS2, EMC9, ERGIC2, ERO1L, HERPUD1, IER3IP1, IMPAD1, PIGK and/or UGGT1. The combined teachings of Pascual and Lugar exemplify 34 genes from the claimed set, and thus do not disclose the claimed set.
Patel discusses “gene expression profiling of monocytes from children with active, newly diagnosed and untreated… SLE” (pg. i, Abstract), systemic lupus erythematosus, and presents results regarding differential expression of various genes in these subjects. Patel exemplifies differentially-expressed genes including CALR (pg. 325), CALU (pp. 173 and 336), CANX (pg. 118), CDS2 (pp. 84, 120 and 201), EMC9 (‘CGI-112’, pg. 326), ERAP1 (PG. 118), ERGIC2 (pg. 105), ERO1L (pp. 104, 163 and 210), GALNT2 (pp. 87, 132, 371 and 287), HERPUD1 (pg. 303), IMPAD1 (pp. 110 and 185), KDELR2 (pp. 164 and 338), PIGK (pg. 233), PPIB (pg. 231), SSR3 (pp. 166 and 318) and UGGT1 (‘UGCGL1’, pg. 132).
Patel does not exemplify IER3IP1. Thus, the combined teachings of Pascual, Lugar and Patel do not disclose the claimed set.
Sun discusses “Immediate early response 3 interacting protein 1 (IER3IP1)… a highly conserved protein… expressed in… peripheral blood leukocytes” (pg. 56768, l. column), e.g., plasma cells, and presents study findings regarding “the role of IER3IP1 in β-cell survival and proliferation, and… the mechanism of β-cell apoptosis induced by IER3IP1 suppression” (pg. 56769, l. column).
Sun teaches that “Multiple factors can disturb ER homeostasis… which will eventually trigger the UPR”, unfolded protein response, “[t]he initial effect of [which] is to reestablish homeostasis… When the UPR fails to compensate, ER stress is not mitigated and homeostasis is not restored, cell death is induced, typically by apoptosis… IER3IP1 suppression shuts down activation of the UPR” (pg. 56775, l. column). Sun concludes that “IER3IP1 suppression leads to apoptotic cell death… IER3IP1 is required for UPR activation and cell proliferation” (pg. 56776, r. column), i.e., plasma cell maturation. In this way, Sun teaches that IER3IP1, expressed in plasma cells, is a gene which limits apoptosis linked to the unfolded protein response and ER stress.
Additionally, Sun teaches significant correlation between “mRNA levels of IER3IP1… and IER3IP1 protein levels” (pg. 56769, l. column), and exemplifies “Quantification of mRNA levels… [via] gene expression assays” (pg. 56777, l. column). The combined teachings of Pascual, Lugar, Patel and Sun thus exemplify all genes constituting the claimed set.
An invention would have been obvious to one of ordinary skill in the art if some teaching in the prior art would have led that person to combine prior art reference teachings to arrive at the claimed invention. Before the effective filing date of the clamed invention, said practitioner would have implemented a gene expression panel further comprising CANX, CDS2, EMC9, ERGIC2, ERO1L, HERPUD1, IMPAD1, PIGK, and/or UGGT1, to enhance the lupus state assessment method of Pascual, in view of Lugar, because Pascual discloses combined analysis of at least 40 genes differentially associated with systemic lupus erythematosus and Patel teaches that expression levels of these genes are differentially associated with systemic lupus erythematosus (see citations above). The claimed set thus constitutes a combination of favorably-indicated biomarkers, i.e., an obvious-to-try variant of the method of Pascual in light of the additional prior art. Said practitioner would have had a reasonable expectation of success because Pascual and Patel both discuss measuring expression of genes differentially associated with systemic lupus erythematosus (specifically including CALR, CALU, GALNT2, KDELR2, PPIB and SSR3).
An invention would have been obvious to one of ordinary skill in the art if some teaching in the prior art would have led that person to combine prior art reference teachings to arrive at the claimed invention. Before the effective filing date of the clamed invention, said practitioner would have implemented a gene expression panel further comprising IER3IP1, to enhance the lupus state assessment method of Pascual, in view of Lugar and Patel, because Lugar teaches that active SLE is associated with increased frequency of circulating plasma cells that exhibit characteristic upregulation of genes which limit apoptosis linked to the unfolded protein response and ER stress, while Sun teaches that IER3IP1 is a gene expressed in plasma cells (pg. 56768, l. column) which has such function (pg. 56775, l. column; pg. 56776, r. column) and is readily detectable via gene expression assay (pg. 56769, l. column; pg. 56777, l. column).
Therefore, one of ordinary skill in the art would be aware that increased expression of IER3IP1 is both detectable via the disclosed methods of Pascual and associated with active SLE. Thus, analysis of a set of genes including IER3IP1 constitutes an obvious-to-try variant of the method of Pascual in light of the additional prior art. Said practitioner would have had a reasonable expectation of success because Pascual and Sun both discuss measuring gene expression in subject samples.
In this way the disclosure of Pascual, in view of Lugar, Patel and Sun, makes obvious the limitations of claim 54. Thus, the invention is prima facie obvious.
Response to Arguments - Claim Rejections Under 35 USC § 103
In the reply filed 7/25/2025, Applicant traverses the rejections under § 103 and presents supportive arguments.
Applicant alleges that the method of Pascual relies on a basic comparison of gene expression levels, and does not provide at least the claimed feature of using a machine learning algorithm trained on a set of gene expression data (pg. 15, para. 4).
Pascual discloses determination of immune states (discrimination of ‘SLE’ from ‘flu’ and ‘healthy’) with a supervised learning algorithm, via supervised learning and hierarchical clustering of gene expression data (pg. 64, para. 0139). One of ordinary skill in the art would understand that a supervised learning algorithm is a type of machine learning algorithm, and supervised learning is training of the algorithm on labeled data.
Pascual further discloses that all genes were assayed using HG-U133 chip arrays, sold by Affymetrix (pp. 37-38, para. 0074; pg. 62, para. 0114; pg. 63, para. 0130), which the instant specification indicates were also used to generate gene expression data from which Applicant identified the claimed set of genes (see originally-filed specification at paras. 0383 and 1025). Pascual is thus considered to disclose use of a machine learning algorithm trained on gene expression data as claimed. Thus, the argument of deficiency in the teachings of Pascual is not persuasive.
Applicant asserts that neither Lugar nor Patel remedy the alleged deficiency of Pascual (pg. 15, para. 4 – pg. 16, para. 4). As the alleged deficiency is contested herein, this argument is considered moot.
For the above reasons, the arguments are found unpersuasive and the rejections are maintained.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Instant claims 29, 33, 56 and 59 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-3, 15 and 17-18 of copending Application No. 18/806,149 (hereafter, “‘149”), in view of Lugar (previously cited). ‘149 shares joint inventors (LIPSKY, Peter E.; GRAMMER, Amrie C.; BACHALI, Prathyusha) and a common assignee (AMPEL BioSolutions, LLC) with the instant application. With respect to instant claim 29, ‘149 claims steps of: analyzing a patient data set comprising or derived from gene expression measurements data of at least 2 genes from a biological sample obtained or derived from the patient (claim 1); wherein the patient data set comprises or is derived from gene expression measurements data of at least 25 genes selected from genes listed in disclosed Tables 17-1 to 17-30 (claim 2) and a different or same number of genes selected from different Tables (claim 3); wherein analyzing the patient data set comprises providing the data set as an input to a machine-learning model trained to generate an inference of whether the patient data set is indicative of the patient having type 1 lupus, type 2 lupus, or type 1-2 lupus (claim 15), i.e., determining an immunological state of the subject based on the generated data set, comprising executing an application defined by a machine learning algorithm trained on a set of gene expression data, with the data set as input; and outputting a report indicating the lupus disease state of the patient based on the inference (claim 17), i.e., identifying, based on the execution, the immunological state of the subject and annotating records associated with the subject based on the identified immunological state.
The disclosed Tables list genes including the following: B4GALT3 (Table 3B, pg. 285 of as-filed specification), CALR (Table 1C, pg. 156), CALU (Table 1C, pg. 156), CANX (Table 1C, pg. 156), EDEM2 (Table 3B, pp. 221 and 234), EXT1 (Table 24-15, pg. 404), LMAN2 (Table 3B, pp. 287 and 294), MANEA (Table 1C, pg. 153), MANF (Table 3B, pg. 304), NUCB2 (Table 3B, pg. 308), PDIA4 (Table 1C, pg. 154; Table 3B, pg. 255), PDIA6 (Table 1C, pg. 154; Table 3B, pg. 309), PPIB (Table 1C, pg. 154), SEC61G (‘SEC61G-DT’ in Table 17-29, pg. 395), SSR3 (Table 1C, pg. 154) and TRAM2 (Table 1C, pg. 154). In other words, 16 of the genes recited in the instant claim.
‘149 does not claim assaying the biological sample; and does not appear to list at least 9 additional (to thus list at least 25) of the recited genes.
Lugar discusses microarray analysis of gene expression in circulating plasma cells of patients with active systemic lupus erythematosus (pg. 1, Abstract), and presents findings regarding “genes… differentially expressed in SLE PC” (pg. 6, Figure 2 caption) which are listed at length in supplementary Table S2. Lugar lists several genes that are also listed in Tables of ‘149, including: B4GALT3 (line 420 of Table S2), CALR (560), CALU (317 and 457), EDEM2 (‘C20orf31’, 553), EXT1 (306), LMAN2 (‘C5orf8’, 514), MANEA (45), MANF (‘ARMET’, 76), NUCB2 (14), PDIA4 (‘ERP70’, 185 and 415), PDIA6 (492), PPIB (160 and 263), SEC61G (438), SSR3 (243) and TRAM2 (328).
Lugar also uniquely lists the following genes: CHST12 (listed as ‘C4S-2’, line 402), CHST2 (470), DERL1 (355), DERL2 (‘F-LAN-1’, 319), DNAJC3 (32), EDEM3 (‘C1orf22’, 363), ERAP1 (‘ARTS-1’, 527), GALNT2 (341), GOLT1B (‘CGI-141’, 338), HYOU1 (292), KDELC1 (234), KDELR2 (238 and 536), LPGAT1 (624), MAN1A1 (42 and 122), SEC24D (49 and 126), SPCS3 (381 and 567), SSR1 (245 and 296), TRAM1 (‘TRAM’, 450) and XBP1 (51). In other words, an additional 19 of the genes recited in the instant claim.
Taken together, ‘149 and Lugar list 34 (i.e., at least 25) genes from the claimed set.
With respect to instant claim 33, ‘149 claims analysis of whether the patient data set is indicative of the patient having type 1 lupus, type 2 lupus, or type 1-2 lupus (claim 15), i.e., a lupus condition.
With respect to instant claim 56, ‘149 claims wherein the machine-learning model is trained using k-nearest neighbors or Random Forest (claim 18).
With respect to instant claim 59, ‘149 claims analysis of whether the patient data set is indicative of the patient having type 1 lupus, type 2 lupus, or type 1-2 lupus (claim 15), i.e., a subset of a lupus condition associated with a molecular endotype.
An invention would have been obvious to one of ordinary skill in the art if some teaching in the prior art would have led that person to combine prior art reference teachings to arrive at the claimed invention. Before the effective filing date of the clamed invention, said practitioner would have implemented microarray analysis of genes further comprising CHST12, CHST2, DERL1, DERL2, DNAJC3, EDEM3, ERAP1, GALNT2, GOLT1B, HYOU1, KDELC1, KDELR2, LPGAT1, MAN1A1, SEC24D, SPCS3, SSR1, TRAM1 and/or XBP1, to enhance the lupus state assessment method of ‘149, because ‘149 discloses combined analysis of at least 25 genes differentially associated with systemic lupus erythematosus and Lugar teaches that expression levels of these additional genes are differentially associated with systemic lupus erythematosus and can be measured by microarray analysis (see citations above).
The 34 genes collectively listed in ‘149 and Lugar thus constitute a combination of favorably-indicated biomarkers, i.e., an obvious-to-try variant of the method of ‘149 in light of the additional prior art. Said practitioner would have had a reasonable expectation of success because ‘149 and Lugar both discuss measuring expression of genes differentially associated with systemic lupus erythematosus (specifically including B4GALT3, CALR, CALU, EDEM2, EXT1, LMAN2, MANEA, MANF, NUCB2, PDIA4, PDIA6, PPIB, SEC61G, SSR3 and TRAM2).
In this way the claims of ‘149, in view of Lugar, make obvious the limitations of instant claims 29, 33, 56 and 59. Thus, the invention is prima facie obvious. This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
Instant claims 29, 33-34, 53-54, 56-57 and 59 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1, 3, 18-20, 26 of copending Application No. 18/934,801 (hereafter, “‘801”). ‘801 shares joint inventors (LIPSKY, Peter E.; GRAMMER, Amrie C.; BACHALI, Prathyusha) and a common assignee (AMPEL BioSolutions, LLC) with the instant application.
With respect to instant claim 29, ‘801 claims steps of: analyzing a data set comprising or derived from gene expression measurements of at least 2 genes obtained from a biological sample obtained or derived from the patient (claim 1), wherein the data set comprises or is derived from gene expression measurements of at least 25 genes selected from genes listed in each one or more Tables selected from Tables 1 to 32 (claim 3); wherein analyzing the patient data set comprises providing the data set as an input to a trained machine-learning model trained to generate an inference of whether the patient data set is indicative of the patient having groups A-H lupus disease states and classify the lupus disease state of the patient based on the inference (claim 18), i.e., determining an immunological state of the subject based on the generated data set, comprising executing an application defined by a machine learning algorithm trained on a set of gene expression data, with the data set as input; receiving the inference, and outputting a report classifying the lupus disease state of the patient (claim 19), i.e., identifying, based on the execution, the immunological state of the subject and annotating records associated with the subject based on the identified immunological state.
The disclosed Table 32 list genes including the following: B4GALT3, CALR, CALU, CANX, CDS2, CHST12, CHST2, DERL1, DERL2, DNAJC3, EDEM2, EDEM3, EMC9, ERAP1, ERGIC2, ERO1L, EXT1, GALNT2, GOLT1B, HERPUD1, HYOU1, IER3IP1, IMPAD1, KDELC1, KDELR2, LMAN2, LPGAT1, MAN1A1, MANEA, MANF, NUCB2, PDIA4, PDIA6, PIGK, PPIB, SEC24D, SEC61G, SPCS3, SSR1, SSR3, TRAM1, TRAM2, UGGT1 and XBP1 (pg. 215 of as-filed specification).
With respect to instant claim 33, ‘801 claims analysis of whether the patient data set is indicative of the patient having groups A-H lupus disease states (claim 18), i.e., a lupus condition.
With respect to instant claim 34, ‘801 claims wherein the data set comprises or is derived from gene expression measurements of at least 30 genes selected from genes listed in each one or more Tables selected from Tables 1 to 32 (claim 3).
With respect to instant claim 53, ‘801 claims wherein the data set comprises or is derived from gene expression measurements of at least 35 genes selected from genes listed in each one or more Tables selected from Tables 1 to 32 (claim 3).
With respect to instant claim 54, ‘801 claims wherein the data set comprises or is derived from gene expression measurements of all genes listed in each one or more Tables selected from Tables 1 to 32 (claim 3).
With respect to instant claim 56, ‘801 claims wherein the machine-learning model is trained using k-nearest neighbors or Random Forest (claim 20).
With respect to instant claim 57, ‘801 claims wherein the biological sample comprises a blood sample, or isolated peripheral blood mononuclear cells (claim 26).
With respect to instant claim 59, ‘801 claims analysis of whether the patient data set is indicative of the patient having groups A-H lupus disease states (claim 18), i.e., a subset of a lupus condition associated with a molecular endotype.
In this way, instant claims 29, 33-34, 53-54, 56-57 and 59 are not patentably distinct from claims of ‘801. This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
Instant claims 29, 33-34, 56-57 and 59 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-2, 14-16, 20, 24 and 26 of copending Application No. 19/199,677 (hereafter, “‘677”), in view of Lugar (previously cited). ‘677 shares joint inventors (LIPSKY, Peter E.; GRAMMER, Amrie C.; LABONTE, Adam; OWEN, Katherine A.; BACHALI, Prathyusha) and a common assignee (AMPEL BioSolutions, LLC) with the instant application.
With respect to instant claim 29, ‘677 claims steps of: analyzing a data set comprising or derived from gene expression measurements of at least 2 genes obtained from a biological sample from the patient (claim 1), wherein the data set comprises or is derived from gene expression measurements of at least 25 genes (claim 2); wherein analyzing the patient data set comprises providing the data set as an input to a machine-learning model that generates an inference indicative of the patient based on the data set (claim 14), i.e., determining an immunological state of the subject based on the generated data set, comprising executing an application defined by a machine learning algorithm trained on a set of gene expression data, with the data set as input; receiving the inference, and outputting a report classifying the lupus disease state of the patient (claim 15), i.e., identifying, based on the execution, the immunological state of the subject and annotating records associated with the subject based on the identified immunological state.
‘677 does not list at least 25 genes of those recited by the instant claims.
Lugar discusses microarray analysis of gene expression in circulating plasma cells of patients with active systemic lupus erythematosus (pg. 1, Abstract), and presents findings regarding “genes… differentially expressed in SLE PC” (pg. 6, Figure 2 caption) which are listed at length in supplementary Table S2. Lugar lists genes including: B4GALT3 (line 420 of Table S2), CALR (560), CALU (317 and 457), CHST12 (listed as ‘C4S-2’, line 402), CHST2 (470), DERL1 (355), DERL2 (‘F-LAN-1’, 319), DNAJC3 (32), EDEM2 (‘C20orf31’, 553), EDEM3 (‘C1orf22’, 363), ERAP1 (‘ARTS-1’, 527), EXT1 (306), GALNT2 (341), GOLT1B (‘CGI-141’, 338), HYOU1 (292), KDELC1 (234), KDELR2 (238 and 536), LPGAT1 (624), LMAN2 (‘C5orf8’, 514), MAN1A1 (42 and 122), MANEA (45), MANF (‘ARMET’, 76), NUCB2 (14), PDIA4 (‘ERP70’, 185 and 415), PDIA6 (492), PPIB (160 and 263), SEC24D (49 and 126), SEC61G (438), SPCS3 (381 and 567), SSR1 (245 and 296), SSR3 (243), TRAM1 (‘TRAM’, 450), TRAM2 (328) and XBP1 (51). In other words, 33 genes of those recited in the instant claim.
Lugar thus lists at least 25 of the genes recited in the instant claim.
With respect to instant claim 33, ‘677 claims analysis of whether the patient data set is indicative of the lupus disease state of the patient (claim 14), i.e., a lupus condition.
With respect to instant claim 34, ‘677 claims wherein the data set comprises or is derived from gene expression measurements of at least 30 genes (claim 2).
With respect to instant claim 56, ‘677 claims wherein the machine-learning model is trained using k-nearest neighbors or Random Forest (claim 16).
With respect to instant claim 57, ‘677 claims wherein the biological sample comprises a blood sample, or isolated peripheral blood mononuclear cells (claim 20).
With respect to instant claim 59, ‘677 claims analysis of whether the patient data set is indicative of the lupus disease state of the patient (claim 14) wherein the method classifies whether the patient has active or inactive lupus (claim 26) i.e., a subset of a lupus condition associated with a molecular endotype.
An invention would have been obvious to one of ordinary skill in the art if some teaching in the prior art would have led that person to combine prior art reference teachings to arrive at the claimed invention. Before the effective filing date of the clamed invention, said practitioner would have implemented microarray analysis of at least 25 genes selected from B4GALT3, CALR, CALU, CHST12, CHST2, DERL1, DERL2, DNAJC3, EDEM2, EDEM3, ERAP1, EXT1, GALNT2, GOLT1B, HYOU1, KDELC1, KDELR2, LPGAT1, LMAN2, MAN1A1, MANEA, MANF, NUCB2, PDIA4, PDIA6, PPIB, SEC24D, SEC61G, SPCS3, SSR1, SSR3, TRAM1, TRAM2 and/or XBP1, to generate gene expression data for the lupus state assessment method of ‘677, because ‘677 discloses combined analysis of at least 25 genes to classify lupus state and Lugar teaches that expression levels of these 33 genes are differentially associated with lupus and can be measured by microarray analysis (see citations above).
These 33 genes listed in Lugar thus constitute a combination of favorably-indicated biomarkers, i.e., an obvious-to-try variant of the method of ‘677 in light of the additional prior art. Said practitioner would have had a reasonable expectation of success because ‘677 and Lugar both discuss measuring expression of genes differentially associated with lupus.
In this way the claims of ‘677, in view of Lugar, make obvious the limitations of instant claims 29, 33-34, 56-57 and 59. Thus, the invention is prima facie obvious. This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
Instant claims 29, 33, 54, 56-57 and 59 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 11, 16 and 19 of copending Application No. 19/259,293 (hereafter, “‘293”). ‘293 shares joint inventors (LIPSKY, Peter E.; GRAMMER, Amrie C.; BACHALI, Prathyusha) and a common assignee (AMPEL BioSolutions, LLC) with the instant application.
With respect to instant claim 29, ‘293 claims steps of: analyzing a data set comprising or derived from gene expression measurements of at least 2 genes selected from genes listed in each one or more Tables selected from Tables 4A-1 to 4A-20 and 4B-1 to 4B-28, wherein the gene expression measurements are obtained from a biological sample from the patient (claim 11); wherein analyzing the patient data set comprises providing the data set as an input to a trained machine-learning model trained to generate an inference of whether the data set is indicative of the patient having groups A-H lupus skin disease states and classify the lupus skin disease state of the patient based on the inference (claim 16), i.e., determining an immunological state of the subject based on the generated data set, comprising executing an application defined by a machine learning algorithm trained on a set of gene expression data, with the data set as input; receiving the inference, and outputting a report classifying the lupus skin disease state of the patient (claim 16), i.e., identifying, based on the execution, the immunological state of the subject and annotating records associated with the subject based on the identified immunological state.
The disclosed Table 4B-26 list genes including the following: B4GALT3, CALR, CALU, CANX, CDS2, CHST12, CHST2, DERL1, DERL2, DNAJC3, EDEM2, EDEM3, EMC9, ERAP1, ERGIC2, ERO1L, EXT1, GALNT2, GOLT1B, HERPUD1, HYOU1, IER3IP1, IMPAD1, KDELC1, KDELR2, LMAN2, LPGAT1, MAN1A1, MANEA, MANF, NUCB2, PDIA4, PDIA6, PIGK, PPIB, SEC24D, SEC61G, SPCS3, SSR1, SSR3, TRAM1, TRAM2, UGGT1 and XBP1 (pg. 247 of as-filed specification).
With respect to instant claim 33, ‘293 claims analysis of whether the patient data set is indicative of the patient having groups A-H lupus skin disease states (claim 16), i.e., a lupus condition.
With respect to instant claim 54, ‘293 claims wherein the data set comprises or is derived from gene expression measurements of all genes listed in each of one or more Tables selected from Tables 4A-1 to 4A-20 and 4B-1 to 4B-28 (claim 11).
With respect to instant claim 56, ‘293 claims wherein the trained machine learning model is trained using k-nearest neighbors or Random Forest (claim 16).
With respect to instant claim 57, ‘293 claims wherein the biological samples are selected from a blood sample, or isolated peripheral blood mononuclear cells (claim 19).
With respect to instant claim 59, ‘293 claims analysis of whether the patient data set is indicative of the patient having groups A-H lupus skin disease states (claim 11), i.e., a subset of a lupus condition associated with a molecular endotype.
In this way, instant claims 29, 33, 54, 56-57 and 59 are not patentably distinct from claims of ‘293. This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
Instant claims 29, 33-34, 53 and 56-57 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-2, 19, 21, 25 and 31-32 of copending Application No. 19/267,957 (hereafter, “‘957”). ‘957 shares joint inventors (LIPSKY, Peter E.; GRAMMER, Amrie C.; OWEN, Katherine A.) and a common assignee (AMPEL BioSolutions, LLC) with the instant application.
With respect to instant claim 29, ‘957 claims steps of: assaying a biological sample obtained or derived from a subject to produce a data set comprising gene expression measurements of the biological sample at each of a plurality of disease-associated genomic loci (claim 1), wherein the plurality comprises at least a portion of 25 genes selected from the group of genes listed in Tables 1-37 (claim 2); computer processing the data set to determine the disease state of the subject (claim 1), comprising using a trained machine learning classifier to analyze the data set to determine the disease state of the subject (claim 19) i.e., determining an immunological state of the subject based on the generated data set, comprising executing an application defined by a machine learning algorithm trained on a set of gene expression data, with the data set as input; and outputting a report indicative of the disease state of the subject (claim 1) , i.e., identifying, based on the execution, the immunological state of the subject and annotating records associated with the subject based on the identified immunological state.
The disclosed Tables list genes including at least the following: B4GALT3 (Table 8, pg. 165 of as-filed specification), CALR (Table 8, pp. 154 and 165), CALU (Table 8, pp. 148, 154, 163 and 165), CANX (Table 8, pp. 156 and 164), CDS2 (Table 8, pp. 148, 154 and 163), CHST12 (Table 8, pp. 148, 156, 163 and 165), CHST2 (Table 8, pp. 154 and 165), DERL2 (Table 8, pp. 149, 156 and 166), DNAJC3 (Table 8, pg. 154), EDEM2 (Table 8, pp. 154 and 166), EDEM3 (Table 8, pp. 151 and 166); EMC9 (Table 8, pg. 154), ERAP1 (Table 8, pp. 156 and 166), ERGIC2 (Table 8, pp. 154 and 163), ERO1L (Table 8, pp. 149, 154 and 163), GALNT2 (Table 8, pp. 155, 163 and 166), GOLT1B (Table 8, pp. 156 and 166), HERPUD1 (Table 8, pp. 149 and 156), IER3IP1 (Table 8, pg. 149), IMPAD1 (Table 8, pg. 154), KDELR2 (Table 8, pg. 156), LMAN2 (Table 8, pp. 156), MAN1A1 (Table 8, pp. 156 and 166), MANEA (Table 8, pp. 156 and 166), MANF (Table 8, pp. 156 and 166), NUCB2 (Table 8, pg. 166), PDIA4 (Table 8, pp. 156 and 166), PDIA6 (Table 8, pp. 149, 156 and 166), PIGK (Table 8, pg. 156), PPIB (Table 8, pg. 166), SEC24D (Table 8, pg. 157), SEC61G (Table 18, pg. 157), SPCS3 (Table 8, pp. 148, 157 and 166), SSR1 (Table 8, pg. 157), SSR3 (Table 8, pp. 155, 156 and 166), TRAM1 (Table 8, pp. 157 and 166), TRAM2 (Table 8, pp. 157 and 166) and XBP1 (Table 8, pp. 157 and 166). In other words, 38 of the genes recited in the instant claim.
With respect to instant claim 33, ‘957 claims wherein the disease comprises a lupus condition (claim 31) that is systemic lupus erythematosus (claim 32).
With respect to instant claim 34, ‘957 claims wherein the plurality of genomic loci comprises at least a portion of 30 genes selected from the group of genes listed in Tables 1-37 (claim 2).
With respect to instant claim 53, ‘957 claims wherein the plurality of genomic loci comprises at least a portion of 35 genes selected from the group of genes listed in Tables 1-37 (claim 2).
With respect to instant claim 56, ‘957 claims wherein the trained machine learning model is trained using k-nearest neighbors or Random Forest (claim 21).
With respect to instant claim 57, ‘957 claims wherein the biological samples are selected from the group consisting of: a blood sample, or isolated peripheral blood mononuclear cells (claim 25).
In this way, instant claims 29, 33-34, 53 and 56-57 are not patentably distinct from claims of ‘957. This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
Conclusion
At this point in prosecution, no claim is allowed.
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/T.C.S./Examiner, Art Unit 1685
/JESSE P FRUMKIN/Primary Examiner, Art Unit 1685 December 13, 2025
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