DETAILED ACTION
Applicant's response, filed 7/8/2026, has been fully considered. The following rejections and/or
objections are either reiterated or newly applied. They constitute the complete set presently being
applied to the instant application.
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 .
Priority
The instant application claims benefit of priority to U.S. Provisional Application No. 62/010,252 filed on 6/10/2014. The claim to the benefit of priority is acknowledged. As such, the effective filing date of claims 9-10, 12-16, 19-21, 23-25, and 28-31 is 6/10/2014.
Claim Status
Claims 9-10, 12-16, 19-21, 23-25, and 41-50 are pending.
Claims 1-8, 11, 17-18, 22, 26-40 are cancelled.
Claims 9-10, 12-16, 19-21, 23-25, and 41-50 are rejected.
Withdrawn Rejections/Objections
The rejection of claims 9-16, 19-25, and 28-31 under 35 U.S.C. §101 in the Office action mailed 2/20/2026 is withdrawn in view of the amendments filed 7/8/2026.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 19-21, 23-25, and 46-50 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claims contain subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventors, at the time the application was filed, had possession of the claimed invention. Specifically claim 19 recites a computer implemented method, but additionally recites an active step of administering a specific therapy for axSpA. However, there is provided no information or structure as to how a computer is made able to actively administer treatment for a disease to a patient. Thus, the specification does not reasonable convey to a person of ordinary skill in the art that the inventor was in possession of this specific claimed computer-implemented method at the time of filing. As such claim 19, and all dependent claims as they fail to cure said deficiencies, are rejected under 35 U.S.C. 112(a) for failing to properly describe the invention.
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 42-44 and 47-49 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
A broad range or limitation together with a narrow range or limitation that falls within the broad range or limitation (in the same claim) may be considered indefinite if the resulting claim does not clearly set forth the metes and bounds of the patent protection desired. See MPEP § 2173.05(c). In the present instance, claims 42-44 and 47-49 recite the broad recitation of the biomarkers comprising those specified, of which there are articulated to be 5, 5, and 12 joined by the conjunction “and”, and the claim also recites the limitation of “at least three biomarkers” which is the narrower statement of the range/limitation. The claims are considered indefinite because there is a question or doubt as to whether the feature introduced by such narrower language is (a) merely exemplary of the remainder of the claim, and therefore not required, or (b) a required feature of the claims. As such the claims are rejected with the “and” being interpreted as an “or”.
Claim Rejections - 35 USC § 101
Response to Amendment
In view of applicant’s amendments to the claims, previous rejections under 35 U.S.C. 101 have been withdrawn.
Response to Arguments
Applicant’s arguments, see page 8 of the Remarks, filed 7/8/2026, with respect to the rejection of claims 9-16, 19-25, and 28-31 under 35 U.S.C. 101 for being drawn to abstract ideas without significantly more, have been fully considered and are persuasive. The rejection of claims 9-16, 19-25, and 28-31 has been withdrawn.
Claim Rejections - 35 USC § 103
Response to Amendment
In view of applicant’s amendments to the claims, previous rejections under 35 U.S.C. 103 have been reviewed, updated, and provided below.
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 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.
Claims 9-10, 12, 14, 19-21, 23, and 41-50 are rejected under 35 U.S.C. 103 as being unpatentable over Centola et al. (PloS One (2013) 1-13; previously cited), in view of Mackay et al. (Journal of autoimmunity (2009) 170-177; newly cited), Sieper et al. (Current rheumatology reports (2013) 1-6), and Inman et al. (Clinical & Experimental Rheumatology (2009) 26-32; newly cited).
Claim 9 is directed to a method for monitoring the presence/absence, activity, diagnosing, or predicting risk of progression of axial spondyloarthritis using a dataset of biomarkers from a population to determine a standard score, along with a dataset of biomarkers from an individual to compare said individual’s score with said standard to determine disease activity.
Claim 19 is directed to a computer implemented method for monitoring the presence/absence, activity, diagnosing, or predicting risk of progression of axial spondyloarthritis using a dataset of biomarkers from a population to determine a standard score, along with a dataset of biomarkers from an individual to compare said individual’s score with said standard to determine disease activity.
Centola et al. teaches in the abstract “Biomarkers with qualifying assays were prioritized in a series of studies based on their correlations to RA clinical disease activity and their contributions to multivariate models. Prioritized biomarkers were used to train an algorithm to measure disease activity” and “Biomarker-based scores were significantly correlated with DAS28-CRP and could discriminate patients with low vs. moderate/high clinical disease activity. Such scores were also able to track changes in DAS28-CRP and were significantly associated with both joint inflammation measured by ultrasound and damage progression measured by radiography”, reading on a method for monitoring the presence or absence of axial spondyloarthritis (axSpA) disease activity in a subject, for diagnosing axSpA in a subject, or for predicting risk of progressive damage. Centola et al. teaches on page 2, column 1, paragraph 4 “Protein biomarkers can provide complementary, objective, and reliable measurements reflecting underlying pathophysiological processes”, on page 2, column 2, paragraph 4 ” Biomarkers were assayed from stored serum samples obtained from patients from multiple clinical studies/cohorts”, on page 6, column 2, paragraph 1 “four lower-ranking biomarkers were selected due to their representation of key biological functions or pathways in RA, especially those implicated by other prioritized biomarkers: VCAM1 was included as complementary to ICAM1 (adhesion molecules), IL1b was included for its relation to IL1Ra (IL-1 pathway), MMP1 was included for its similarity to MMP3 (both MMPs) and CCL22 (MDC) was included to represent monocyte/macrophage biology”, and page 8, column 1, paragraph 6 “The final algorithm was a 12-biomarker model for the multi biomarker disease activity (MBDA) score. In this algorithm, 11 biomarkers (tumor necrosis factor receptor I (TNF-RI), interleukin 6 (IL-6), vascular cell adhesion molecule 1 (VCAM-1), epidermal growth factor (EGF), VEGF-A, cartilage glycoprotein 39 (YKL40), matrix metalloproteinase 1 (MMP1), MMP3, serum amyloid A (SAA), leptin, and resistin) are used for prediction of the TJC28, SJC28 and PGA, with different biomarkers and weightings used to predict each component”, reading on wherein the at least three biomarkers selected from a group comprising calprotectin (dimer of S100A8 and S100A9 protein subunits; RP-8/14); chitinase 3-like 1 (cartilage glycoprotein-39) (CHI3L1, or YKL-40); C-reactive protein, pentraxin-related (CRP); epidermal growth factor (beta-urogastrone) (EGF); intercellular adhesion molecule 1 (ICAM1); interleukin 6 (IL6); interleukin 8 (IL8); interleukin 1, beta (IL1B); interleukin 6 receptor (IL6R); leptin (LEP); Macrophage-derived chemokine (MDC); matrix metallopeptidase 1 (interstitial collagenase) (MMP1); matrix metallopeptidase 3 (stromelysin 1, progelatinase) (MMP3); resistin (RETN); serum amyloid Al (SAA1); tumor necrosis factor receptor superfamily, member lA (TNFRSFIA or TNF-R1); vascular cell adhesion molecule 1 (VCAM1); and vascular endothelial growth factor A (VEGFA). Additionally, this reads on determining a second dataset associated with a sample from said subject wherein said second dataset comprises the selected biomarkers; determining a MBDA score for said subject. It would be inherent to the process that any quantitative measure of disease for predicting progression or tracking changes in disease activity, as Centola et al. teaches on page 8, column 1, paragraph 1 “we were able to evaluate whether the biomarker based disease activity scores could also track changes in clinical disease activity. Indeed, changes in the biomarker-based scores were significantly correlated to changes”, would therefore necessitate the calculation of a population ground truth, or score to compare a diseased state to. Therefore, this would also read on determining a first dataset associated with samples from a population of individuals wherein said population is negative for axSpA, determining a plurality of MBDA scores for the individuals in said population based on the first dataset and deriving an aggregate MBDA value for said population. Centola et al. teaches on page 6, column 1, paragraph 1 “A total of 130 candidate biomarkers were selected based on comprehensive literature review, previous experiments, the availability of immunoassay components, and evaluation of measurability in serum” and on page 4, column 2 paragraph 1 “For the Oklahoma cohort samples, anti-CCP was measured using a commercially available ELISA kit (Quanta Lite CCP 3.1 IgG/IgA Kit, INOVA Diagnostics Inc., San Diego, CA) and RF was measured with the EL-RF/3 kit… All assays were run in 96-well plates with 8 point standard curves (7 standards and a blank). Both standards and patient samples were run in duplicate in adjacent wells on the same plate in all studies. A single lot of each assay reagent was used in each study wherever possible to minimize plate to plate variation. Pools of commercially available human sera (Bioreclamation Inc., Nassau, NY) from rheumatoid arthritis patients, osteoarthritis patients, systemic lupus erythematosus patients and unaffected controls were run as process controls on each plate”, reading on wherein said datasets are obtained by a method comprising: obtaining said samples from said population and said sample from said subject, wherein said samples comprise a plurality of analytes; contacting said samples with reagents; generating a plurality of complexes between said reagents with said plurality of analytes; and detecting said plurality of complexes to obtain said datasets wherein said datasets comprise quantitative data for said biomarkers.
Mackay et al. teaches in the abstract “The concept that autoimmune diseases are characterized by shared (common) threads is well illustrated by their propensity to co-associate in a patient or direct relatives, as coexistences or overlaps. Recognized are two major autoimmune clusters, ‘‘thyrogastric’’ (mostly organ-specific) and ‘‘lupus-associated’’ (mostly multisystem). Additionally, some autoimmune diseases distribute within either cluster and a few appear not to associate. Also, within each cluster there are overlaps constituting virtually a distinct syndrome. These patterns of coexistence/overlaps depend predominantly on genetic determinants as judged by data accruing from numerous highly powered genome-wide association studies. Gene polymorphisms thus revealed include those that may determine tissue targeting particularly HLA alleles (and others), the (numerous) genes that influence orderly progression (or tolerogenesis) among immune responses from innate immunity to effector processes, genes that influence pathways of apoptosis, and genes that influence vulnerability of target organs to immune-mediated damage”.
Sieper et al. teaches on page 1, column 1, paragraph 1 “Axial spondyloarthritis (axSpA) is a new term covering both patients with typical radiographic sacroillitis, termed ankylosing spondylitis, and patients in the earlier stage before the occurrence of structural bony damage…Tremendous progress have been made over the last 10 years in the treatment of axSpA: NSAIDs have generally been accepted as an effective first-line therapy…TNF-blockers have been proven to be highly effective if conventional treatment fails”, reading on administering a therapy for axSpA to the subject based on said comparison, wherein said therapy comprises one or more of a therapeutic compound selected from disease-modifying antirheumatic drugs (DMARDs), biologic DMARDs, non-steroidal anti-inflammatory drugs (NSAIDs), and corticosteroids; a physical therapy, dietary modification and/or supplementation; or a bariatric surgical intervention.
Inman et al. teaches in the abstract “Ankylosing spondylitis (AS) and rheumatoid arthritis (RA) are immune-mediated inflammatory joint diseases with the potential for significant target organ damage. Genetic factors play an important role in defining disease susceptibility. Both diseases are mediated in part by TNF, since anti-TNF therapies have proved effective in both AS and RA”, and on page 30, column 2, paragraph 2 “Because of the clinical interrelationships between ReA and AS, it has been proposed that AS may represent a chronic form of ReA, in which it may be difficult identifying the triggering pathogen if that event occurred in the remote past”.
It would have been obvious at the time of first filing to have modified the teachings of Centola et al. for the method of claim 9, to use axial spondylarthritis, particularly in view of the teachings of Inman et al., Mackay et al., and Sieper et al., as the latter establishes “Axial spondyloarthritis (axSpA) is a new term covering both patients with typical radiographic sacroillitis, termed ankylosing spondylitis”, Inman et al. teaches “Ankylosing spondylitis (AS) and rheumatoid arthritis (RA) are immune-mediated inflammatory joint diseases…Genetic factors play an important role in defining disease susceptibility. Both diseases are mediated in part by TNF, since anti-TNF therapies have proved effective in both AS and RA…Growing knowledge of new aspects of the host immune response (such as innate immune responses and Th17 cells) is adding to new insights into shared mechanisms of pathogenesis between these two diseases”, and Mackay et al. teaching “The concept that autoimmune diseases are characterized by shared (common) threads is well illustrated…”. Thus previous research has shown links between the diseases within the autoimmune category suggesting similar treatments and/or etiologies (See Mackay et al. 2009 and Inman et al. 2009), though some differences may still be present. One would have had a reasonable expectation of success given that both are autoimmune diseases, forms of arthritis, and genetically similar in their etiologies suggesting similarities in MBDA profiles and possible treatments (See Spieper et al. TNF-Blockers & NSAIDs). Therefore, it would have been obvious to a person skilled in the art to have modified the teachings of Centola et al. and to have been successful.
Claim 10 is directed to the method of claim 9 but further requires that the biomarkers be comprised from the group specified.
Claim 20 is directed to the method of claim 19 but further requires that the biomarkers be comprised from the group specified.
Centola et al. teaches on page 8, column 1, paragraph 6 “The final algorithm was a 12-biomarker model for the multi biomarker disease activity (MBDA) score. In this algorithm, 11 biomarkers (tumor necrosis factor receptor I (TNF-RI), interleukin 6 (IL-6), vascular cell adhesion molecule 1 (VCAM-1), epidermal growth factor (EGF), VEGF-A, cartilage glycoprotein 39 (YKL40), matrix metalloproteinase 1 (MMP1), MMP3, serum amyloid A (SAA), leptin, and resistin) are used for prediction of the TJC28, SJC28 and PGA, with different biomarkers and weightings used to predict each component”, reading on wherein the biomarkers comprise VCAM-1, EGF, VEGF-A, IL-6, TNF-R1, MMP-1, MMP-3, YKL-40, Leptin, Resistin, SAA, and CRP.
Claim 12 is directed to the method of claim 9 but further specifies that the score be predictive of a clinical assessment.
Claim 23 is directed to the method of claim 19 but further specifies that the score be predictive of a clinical assessment.
Centola et al. teaches in the abstract “Biomarkers with qualifying assays were prioritized in a series of studies based on their correlations to RA clinical disease activity” and “We followed a stepwise approach to develop a quantitative serum-based measure of RA disease activity, based on 12-biomarkers, which was consistently associated with clinical disease activity levels”, reading on wherein said MBDA score for the subject is predictive of a clinical assessment.
Claim 14 is directed to the method of claim 9 but further specifies that a third dataset be taken from a second sample of the subject at a different time so as to compute a change of scores over time and thus disease activity over time.
Claim 21 is directed to the method of claim 19 but further specifies that a third dataset be taken from a second sample of the subject at a different time so as to compute a change of scores over time and thus disease activity over time.
Centola et al. teaches on page 8, column 1, paragraph 3 “we optimized the individual biomarker assays to function in a multiplex environment with precision across time, instruments, operators, and reagent lots”, and on page 7, column 2, paragraph 1 “For example, biomarker-based scores calculated at baseline and year 1 had a Spearman correlation with 12 month change in total Sharp score (baseline to year 1, year 1 to year 2, respectively) of 0.52 (P,0.001, Figure 2b) compared to a correlation of 0.43 (P= 0.006) between the DAS28-CRP and changes in total Sharp Score. Biomarker-based disease activity scores and subsequent 12-month change in Sharp score were also correlated when calculated separately for the two years of the study (baseline scores vs. first year change correlation = 0.44, P =0.05; year 1 scores vs. second year change correlation = 0.61, P= 0.005)”, reading on receiving a third dataset associated with a second sample obtained from said subject, wherein said sample obtained from said subject and said second sample are obtained from said subject at different times; determining a second MBDA score for said subject from said third dataset; and comparing said MBDA score and said second MBDA score for said subject to determine a change in said MBDA scores, wherein said change indicates a change in axSpA activity in said subject, or the presence of axSpA in the subject.
Claim 41 is directed to the method of claim 9 but further specifies that the biomarkers comprise those specified.
Claim 46 is directed to the method of claim 19 but further specifies that the biomarkers comprise those specified.
Centola et al. teaches on page 8, column 1, paragraph 6 “The final algorithm was a 12-biomarker model for the multi biomarker disease activity (MBDA) score. In this algorithm, 11 biomarkers (tumor necrosis factor receptor I (TNF-RI), interleukin 6 (IL-6), vascular cell adhesion molecule 1 (VCAM-1), epidermal growth factor (EGF), VEGF-A, cartilage glycoprotein 39 (YKL40), matrix metalloproteinase 1 (MMP1), MMP3, serum amyloid A (SAA), leptin, and resistin) are used for prediction of the TJC28, SJC28 and PGA, with different biomarkers and weightings used to predict each component” Figure 4 describes a ”Newtork map of MBDA biomarker roles in cellular communication in RA”, including VEGF, on page 2, column 1, paragraph 4 “Erythrocyte sedimentation rate (ESR) and CRP measurements are currently incorporated into clinical disease activity measures”, and on page 6, column 2, paragraph 1 “four lower-ranking biomarkers were selected due to their representation of key biological functions or pathways in RA, especially those implicated by other prioritized biomarkers: VCAM1 was included as complementary to ICAM1 (adhesion molecules), IL1b was included for its relation to IL1Ra (IL-1 pathway), MMP1 was included for its similarity to MMP3 (both MMPs) and CCL22 (MDC) was included to represent monocyte/macrophage biology”, reading on wherein the at least three biomarkers comprise CHI3L1, TNFRSF1A, and RETN.
Claim 42 is directed to the method of claim 9 but further specifies that the biomarkers comprise those specified.
Claim 47 is directed to the method of claim 19 but further specifies that the biomarkers comprise those specified.
Centola et al. teaches on page 8, column 1, paragraph 6 “The final algorithm was a 12-biomarker model for the multi biomarker disease activity (MBDA) score. In this algorithm, 11 biomarkers (tumor necrosis factor receptor I (TNF-RI), interleukin 6 (IL-6), vascular cell adhesion molecule 1 (VCAM-1), epidermal growth factor (EGF), VEGF-A, cartilage glycoprotein 39 (YKL40), matrix metalloproteinase 1 (MMP1), MMP3, serum amyloid A (SAA), leptin, and resistin) are used for prediction of the TJC28, SJC28 and PGA, with different biomarkers and weightings used to predict each component” Figure 4 describes a ”Newtork map of MBDA biomarker roles in cellular communication in RA”, including VEGF, on page 2, column 1, paragraph 4 “Erythrocyte sedimentation rate (ESR) and CRP measurements are currently incorporated into clinical disease activity measures”, and on page 6, column 2, paragraph 1 “four lower-ranking biomarkers were selected due to their representation of key biological functions or pathways in RA, especially those implicated by other prioritized biomarkers: VCAM1 was included as complementary to ICAM1 (adhesion molecules), IL1b was included for its relation to IL1Ra (IL-1 pathway), MMP1 was included for its similarity to MMP3 (both MMPs) and CCL22 (MDC) was included to represent monocyte/macrophage biology”, reading on wherein the at least three biomarkers comprise CRP, SAA1, VCAM1, MMP1, and MMP3.
Claim 43 is directed to the method of claim 9 but further specifies that the biomarkers comprise those specified.
Claim 48 is directed to the method of claim 19 but further specifies that the biomarkers comprise those specified.
Centola et al. teaches on page 8, column 1, paragraph 6 “The final algorithm was a 12-biomarker model for the multi biomarker disease activity (MBDA) score. In this algorithm, 11 biomarkers (tumor necrosis factor receptor I (TNF-RI), interleukin 6 (IL-6), vascular cell adhesion molecule 1 (VCAM-1), epidermal growth factor (EGF), VEGF-A, cartilage glycoprotein 39 (YKL40), matrix metalloproteinase 1 (MMP1), MMP3, serum amyloid A (SAA), leptin, and resistin) are used for prediction of the TJC28, SJC28 and PGA, with different biomarkers and weightings used to predict each component” Figure 4 describes a ”Newtork map of MBDA biomarker roles in cellular communication in RA”, including VEGF, on page 2, column 1, paragraph 4 “Erythrocyte sedimentation rate (ESR) and CRP measurements are currently incorporated into clinical disease activity measures”, and on page 6, column 2, paragraph 1 “four lower-ranking biomarkers were selected due to their representation of key biological functions or pathways in RA, especially those implicated by other prioritized biomarkers: VCAM1 was included as complementary to ICAM1 (adhesion molecules), IL1b was included for its relation to IL1Ra (IL-1 pathway), MMP1 was included for its similarity to MMP3 (both MMPs) and CCL22 (MDC) was included to represent monocyte/macrophage biology”, reading on wherein the at least three biomarkers comprise ICAM-1, VCAM-1, VEGF, CRP and SSA.
Claim 44 is directed to the method of claim 9 but further specifies that the biomarkers comprise those specified.
Claim 49 is directed to the method of claim 19 but further specifies that the biomarkers comprise those specified.
Centola et al. teaches on page 8, column 1, paragraph 6 “The final algorithm was a 12-biomarker model for the multi biomarker disease activity (MBDA) score. In this algorithm, 11 biomarkers (tumor necrosis factor receptor I (TNF-RI), interleukin 6 (IL-6), vascular cell adhesion molecule 1 (VCAM-1), epidermal growth factor (EGF), VEGF-A, cartilage glycoprotein 39 (YKL40), matrix metalloproteinase 1 (MMP1), MMP3, serum amyloid A (SAA), leptin, and resistin) are used for prediction of the TJC28, SJC28 and PGA, with different biomarkers and weightings used to predict each component” Figure 4 describes a ”Newtork map of MBDA biomarker roles in cellular communication in RA”, including VEGF, on page 2, column 1, paragraph 4 “Erythrocyte sedimentation rate (ESR) and CRP measurements are currently incorporated into clinical disease activity measures”, and on page 6, column 2, paragraph 1 “four lower-ranking biomarkers were selected due to their representation of key biological functions or pathways in RA, especially those implicated by other prioritized biomarkers: VCAM1 was included as complementary to ICAM1 (adhesion molecules), IL1b was included for its relation to IL1Ra (IL-1 pathway), MMP1 was included for its similarity to MMP3 (both MMPs) and CCL22 (MDC) was included to represent monocyte/macrophage biology”, reading on wherein the at least three biomarkers comprise at least four, five, six, seven, eight, nine, ten, or eleven biomarkers selected from CHI3L1, CRP, EGF, IL6, LEP, MMP1, MMP3, RETN, SAA1, TNFRSFIA, VCAM1, and VEGFA.
Claim 45 is directed to the method of claim 9 but further specifies determining the sample concentrations of one or more the additional biomarkers specified.
Claim 50 is directed to the method of claim 19 but further specifies determining the sample concentrations of one or more the additional biomarkers specified.
Centola et al. teaches in Supplemental Table S3 “Details of assays used in Development studies”, reading on further comprising determining in the sample concentrations of one or more additional biomarkers comprising calprotectin (dimer of S100A8 and S100A9 protein subunits; MRP-8/14); intercellular adhesion molecule 1 (ICAM1); interleukin 8 (IL8); interleukin 1, beta (IL1B); interleukin 6 receptor (IL6R); or Macrophage- derived chemokine (MDC).
Claims 13, 15, 16, 24, 25 are rejected under 35 U.S.C. 103 as being unpatentable over Centola et al. (PloS One (2013) 1-13; previously cited), Mackay et al. (Journal of autoimmunity (2009) 170-177; newly cited), Sieper et al. (Current rheumatology reports (2013) 1-6), and Inman et al. (Clinical & Experimental Rheumatology (2009) 26-32; newly cited) in view of Poddubnyy et al. (Annals of the Rheumatic Diseases (2014) 2137-2143; previously cited).
Claim 13 is directed to the method of claim 9 but further specifies that the clinical assessment be selected from the group specified.
Claim 24 is directed to the method of claim 19 but further specifies that the clinical assessment be selected from the group specified.
Centola et al. teaches the method of claims 9-12, 14, and 19-23 as described above.
Centola et al. does not teach the clinical assessment being selected from the group of assessments provided.
Poddubnyy et al. teaches the use of the modified Stoke Ankylosing Spodylitis Spinal Score in the abstract “Spinal radiographs obtained at baseline and after 2 years of follow-up were scored independently by two trained readers in a concealed and randomly selected order according to the modified Stoke Ankylosing Spondylitis Spine Score (mSASSS) scoring system and for the presence of syndesmophytes”, reading on wherein said clinical assessment is selected from the group consisting of Ankylosing Spondylitis Disease Activity Score (ASDAS), the Stoke Ankylosing Spondylitis Spinal Score (SASSS); the modified Stoke Ankylosing Spondylitis Spinal Score (mSASSS); Ankylosing Spondylitis Quality of Life Scale (ASQOL); Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Bath Ankylosing Spondylitis Functional Index (BASFI), Bath Ankylosing Spondylitis Global Score (BAS-G), Bath Ankylosing Spondylitis Metrology Index (BASMI), Dougados Functional Index (DFI), Health Assessment Questionnaire for the Spondyloarthropathies (HAQ-S), Revised Leeds Disability Questionnaire (RLDQ), and MRI.
It would have been obvious at the time of invention to modify the teachings of Centola et al. for the method of claims 9 and 19 with the use of mSASSS as described in Poddubnyy et al. as the later points out on page 1, column 1, paragraph 1 “Radiographic spinal progression is considered as a relevant outcome in patients with ankylosing spondylitis (AS) and axial spondyloarthritis (axSpA) in general. Available data indicate a clear (although non-linear) association between radiographic damage in the spine (as measured by the modified Stoke AS Spine Score (mSASSS)) and impairedspinal mobility, as well as with the reduction of physical function”. One would have had a reasonable expectation of success given that Centola et al. is teaching a method for general arthritis, whereas Poddubnyy et al. is specifically looking at axSpA and points out the utility of such measures as outlined previously. Therefore, it would have been obvious to one with ordinary skill in the art to incorporate the teachings of each and to be successful.
Claim 15 is directed to the method of claim 9 but further specifies that a report be prepared to be disseminated to the subject or caregiver to make decisions based upon the findings.
Claim 25 is directed to the method of claim 19 but further specifies that a report be prepared to be disseminated to the subject or caregiver to make decisions based upon the findings.
Centola et al. teaches the method of claims 9-12, 14, and 19-23 as described above.
Centola et al. does not teach the preparation of a report to be disseminated to the subject or caregiver.
It would have been obvious to one skilled in the art at the time of invention to incorporate the generating of a report as Centola et al. is using clinically derived biomarkers to predict disease progression and severity. As previously discussed, Centola et al. teaches in the abstract “Biomarkers with qualifying assays were prioritized in a series of studies based on their correlations to RA clinical disease activity” and “We followed a stepwise approach to develop a quantitative serum-based measure of RA disease activity, based on 12-biomarkers, which was consistently associated with clinical disease activity levels”, which reads on wherein said MBDA score for the subject is predictive of a clinical assessment, and the reporting of a clinical assessment or a score which is predictive of such an assessment, is prima facie obvious.
Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over Centola et al. (PloS One (2013) 1-13; previously cited), Mackay et al. (Journal of autoimmunity (2009) 170-177: newly cited), Sieper et al. (Current rheumatology reports (2013) 1-6), and Inman et al. (Clinical & Experimental Rheumatology (2009) 26-32; newly cited) as applied to claim 9 above, and further in view of Li et al. (Current medical research and opinion (2013) 85-92; newly cited).
Claim 16 is directed to the method of claim 9 but further specifies that the sample come from a subject who has been treated for axSpA and a score be determined to use to determine treatment efficacy via comparison with those who have not been treated.
Centola et al. teaches the method of claims 9-12, 14, and 19-23 as described above.
Centola et al. does not teach comparing the scores of an individual that received treatment to determine a treatment efficacy.
Li et al. teaches in the abstract “To assess how use of a multi-biomarker disease activity (MBDA) blood test for rheumatoid arthritis (RA) affects treatment decisions made by health care providers (HCPs) in clinical practice. At routine office visits, 101 patients with RA were assessed by their HCPs (N¼6), and they provided blood samples for MBDA testing. HCPs completed surveys before and after viewing the MBDA test result, recording dosage and frequency for all planned RA medications and physician global assessment of disease activity. Frequency and types of change in treatment plan that resulted from viewing the MBDA test result were determined. Prior to HCP review of the MBDA test, disease modifying anti-rheumatic drug (DMARD) use by the 101 patients included methotrexate in 62% of patients; hydroxychloroquine 29%; TNF inhibitor 42%; non-TNF inhibitor biologic agent 19%; and other drugs at lower frequencies. Review of MBDA test results changed HCP treatment decisions in 38 cases (38%), of which 18 involved starting, discontinuing or switching a biologic or non-biologic DMARD. Other changes involved drug dosage, frequency or route of administration. The total frequency of use of the major classes of drug therapy changed by55%. Treatment plans changed 63% of the time when the MBDA test result was perceived as being not consistent or somewhat consistent with the HCP assessment of disease activity. The addition of the MBDA test to clinical assessment led to meaningful changes in the treatment plans of 38% of RA patients being cared for by HCPs in office practice. Even though treatment was potentially improved, the overall quantity of drug use was minimally affected”, reading on determining a second MBDA score for a second subject wherein said second subject is of the same species as said first subject and wherein said second subject has received treatment for axSpA; comparing said MBDA score of said subject to said second MBDA score; and determining a treatment efficacy for said first subject based on said score comparison.
It would have been obvious at the time of first filing to modify the teachings of Centola et al. for the method of claim 9 with the teachings of Li et al. for the use of a multi-biomarker disease activity score (MBDA) to identify, select, and monitor the results of a treatment for a disease which the biomarkers characterize, specifically as the latter reference did just that and found meaningful changes in 38% of patients examined. One would have had a reasonable expectation of success given that both papers focus on the use of biomarker scores (MBDA’s) for autoimmune diseases, which share substantial genetic etiologies, and the development of a score has already been shown to be of use in treatment identification, selection, and examination. Therefore, it would have been obvious to a person skilled in the art to have modified the teachings of each and to have been successful.
Response to Arguments
Applicant’s arguments, see page 9 of the Remarks, filed 7/8/2026, with respect to the rejections of claims 9-10, 12-16, 19-21, 23-25 under 35 U.S.C. 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new grounds of rejection is made in view of Sieper et al. (Current rheumatology reports (2013) 1-6).
Applicant asserts on page 9 of the Remarks filed 7/8/2026 that the cited references do not teach the administering of one of the claimed therapies for axSpA. However, examiner has provided Sieper et al. in order to cure said deficiencies.
Applicant asserts that there is no reasonable justification in the combination of references. However, examiner directs applicant to referenced citations MacKay et al. and Inman et al. which establish links between autoimmune diseases and specifically axial spondylarthritis and rheumatoid arthritis, respectively, specifically Sieper et al. teaches “Axial spondyloarthritis (axSpA) is a new term covering both patients with typical radiographic sacroillitis, termed ankylosing spondylitis”, Inman et al. teaches “Ankylosing spondylitis (AS) and rheumatoid arthritis (RA) are immune-mediated inflammatory joint diseases…Genetic factors play an important role in defining disease susceptibility. Both diseases are mediated in part by TNF, since anti-TNF therapies have proved effective in both AS and RA…Growing knowledge of new aspects of the host immune response (such as innate immune responses and Th17 cells) is adding to new insights into shared mechanisms of pathogenesis between these two diseases”, and Mackay et al. teaching “The concept that autoimmune diseases are characterized by shared (common) threads is well illustrated…”. Additionally, both autoimmune diseases are forms of arthritis with etiologies known at the time to exist within the HLA domain of the X-chromosome. To a person skilled in the art while the direct use of specific treatments for one might, and I stress here might, not be obvious, the use of similar methods in diagnosis and treatment selection would be as suggested by MacKay et al., Sieper et al., and Inman et al. within their abstracts.
Applicant asserts on page 11 of the Remarks filed 7/8/2026 that there is no reasonable expectation of success and prima facie case for obviousness for the selection of the specific biomarkers as Centola et al. is directed to RA and not axSpA, with Mackay et al. and Inman et al. not curing said deficiencies. However, examiner reminds applicant that there are no deficiencies, particularly in view of Sieper et al. which teaches that axSpA is merely a term used to encompass ankylosing spondylitis, which is shown in the abstract of Inamn et al. and Mackay et al. to share genetic etiologies with rheumatoid arthritis. Furthermore, Sieper et al. shows a similarity in treatments used for the diseases with NSAIDs and TNF-blockers being used to treat both diseases. While there exists some dissimilarities as well, the shared genetic etiologies and treatments suggest that similar methods to diagnose and treat these two diseases would be obvious. Poddubnyy et al. furthers this by stating “NSAIDs, unless contraindicated, are the treatment of choice for the majority of patients with axSpA. Beyond NSAIDs, only tumour necrosis factor (TNF) α blockers are effective and approved for the treatment of active axSpA. Several novel drugs (i.e. monoclonal antibodies targeting interleukin-17, interleukin-12/23, inhibitors of phosphodiesterase-4 and kinases), which might be effective in axSpA, are currently under investigation”.
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.
Claims 9-10, 12-16, 19-21, 23-25 and 28-31 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of U.S. Patent No. 11493512 in view of Li et al. (Current medical research and opinion (2013) 85-92; newly cited).
It would have been obvious at the time of first filing to modify the teachings of U.S. Patent No. 11493512 for the method of claim 9 with the teachings of Li et al. for the use of a multi-biomarker disease activity score (MBDA) to identify, select, and monitor the results of a treatment for a disease which the biomarkers characterize, specifically as the latter reference did just that and found meaningful changes in 38% of patients examined. One would have had a reasonable expectation of success given that both papers focus on the use of biomarker scores (MBDA’s) for autoimmune diseases, which share substantial genetic etiologies, and the development of a score has already been shown to be of use in treatment identification, selection, and examination. Therefore, it would have been obvious to a person skilled in the art to have modified the teachings of each and to have been successful.
Instant Application: 17/464,061
U.S. Patent No. 11493512
Claims 9 and 19: A method for monitoring the presence or absence of axial spondyloarthritis (axSpA) disease activity in a subject, for diagnosing axSpA in a subject,or for predicting risk of progressive damage, the method comprising:determining a first dataset associated with samples from a population of individuals wherein said population is negative for axSpA, wherein said first dataset comprises quantitative data for at least three biomarkers, wherein the at least three biomarkers are selected from a group comprising calprotectin (dimer of S100A8 and S100A9 protein subunits; MRP- 8/14); chitinase 3-like 1 (cartilage glycoprotein-39) (CHI3L1, or YKL-40); C-reactive protein, pentraxin-related (CRP); epidermal growth factor (beta-urogastrone) (EGF);intercellular adhesion molecule 1 (ICAM1); interleukin 6 (IL6); interleukin 8 (IL8);interleukin 1, beta (IL1B); interleukin 6 receptor (IL6R); leptin (LEP); Macrophage- derived chemokine (MDC); matrix metallopeptidase 1 (interstitial collagenase) (MMP1);matrix metallopeptidase 3 (stromelysin 1, progelatinase) (MMP3); resistin (RETN);serum amyloid Al (SAA1); tumor necrosis factor receptor superfamily, member 1A (TNFRSF1A or TNF-R1); vascular cell adhesion molecule 1 (VCAM1); and vascular endothelial growth factor A (VEGFA);determining a plurality of MBDA scores for the individuals in said population based on the first dataset; deriving an aggregate MBDA value for said population; determining a second dataset associated with a sample from said subject wherein said second dataset comprises the selected biomarkers; determining a MBDA score for said subject;comparing the aggregate MBDA value to the MBDA score for the subject; and determining disease activity of axSpA in the subject, or diagnosing axSpA in the subject, based at least in part on said comparison; wherein said datasets are obtained by a method comprising (i) obtaining said samples from said population and said sample from said subject, wherein said samples comprise a plurality of analytes; (ii) contacting said samples with reagents: (iii) generating a plurality of complexes between said reagents with said plurality of analytes; and (iv) detecting said plurality of complexes to obtain said datasets wherein said datasets comprise quantitative data for said biomarkers.
Claim 1: A method for treating axial spondyloarthritis (axSpA) disease activity in a subject, the method comprising: providing a test sample comprising bodily fluid taken from the subject; determining in the sample concentrations of biomarkers comprising chitinase 3-like 1 (cartilage glycoprotein-39) (CHI3L1, or YKL-40); C-reactive protein, pentraxin-related (CRP); epidermal growth factor (beta-urogastrone) (EGF); interleukin 6 (IL6); leptin (LEP); matrix metallopeptidase 1 (interstitial collagenase) (MMP1); matrix metallopeptidase 3 (stromelysin 1, progelatinase) (MMP3); resistin (RETN); serum amyloid A1 (SAA1); tumor necrosis factor receptor superfamily, member 1A (TNFRSF1A or TNF-R1); vascular cell adhesion molecule 1 (VCAM1); and vascular endothelial growth factor A (VEGFA); determining from the sample biomarker concentrations of chitinase 3-like 1 (cartilage glycoprotein-39) (CHI3L1, or YKL-40); C-reactive protein, pentraxin-related (CRP); epidermal growth factor (beta-urogastrone) (EGF); interleukin 6 (IL6); leptin (LEP); matrix metallopeptidase 1 (interstitial collagenase) (MMP1); matrix metallopeptidase 3 (stromelysin 1, progelatinase) (MMP3); resistin (RETN); serum amyloid A1 (SAA1); tumor necrosis factor receptor superfamily, member 1A (TNFRSF1A or TNF-R1); vascular cell adhesion molecule 1 (VCAM1); and vascular endothelial growth factor A (VEGFA) a biomarker axSpA disease activity score with one or more statistical tools to provide an interpretation function; classifying disease activity of axSpA in the subject based on the axSpA disease activity score, wherein the classification indicates a need for a therapy for axSpA; and administering a therapy for axSpA to the subject in need thereof comprising one or more of DMARD therapy, bariatric surgery, and administration of a therapeutic compound.
Li et al. teaches in the abstract “To assess how use of a multi-biomarker disease activity (MBDA) blood test for rheumatoid arthritis (RA) affects treatment decisions made by health care providers (HCPs) in clinical practice. At routine office visits, 101 patients with RA were assessed by their HCPs (N¼6), and they provided blood samples for MBDA testing. HCPs completed surveys before and after viewing the MBDA test result, recording dosage and frequency for all planned RA medications and physician global assessment of disease activity. Frequency and types of change in treatment plan that resulted from viewing the MBDA test result were determined. Prior to HCP review of the MBDA test, disease modifying anti-rheumatic drug (DMARD) use by the 101 patients included methotrexate in 62% of patients; hydroxychloroquine 29%; TNF inhibitor 42%; non-TNF inhibitor biologic agent 19%; and other drugs at lower frequencies. Review of MBDA test results changed HCP treatment decisions in 38 cases (38%), of which 18 involved starting, discontinuing or switching a biologic or non-biologic DMARD. Other changes involved drug dosage, frequency or route of administration. The total frequency of use of the major classes of drug therapy changed by55%. Treatment plans changed 63% of the time when the MBDA test result was perceived as being not consistent or somewhat consistent with the HCP assessment of disease activity. The addition of the MBDA test to clinical assessment led to meaningful changes in the treatment plans of 38% of RA patients being cared for by HCPs in office practice. Even though treatment was potentially improved, the overall quantity of drug use was minimally affected”
Claims 10 and 20: The method of claim 9 wherein the biomarkers comprise VCAM-1, EGF,VEGF-A, IL-6, TNF-R1, MMP-1, MMP-3, YKL-40, Leptin, Resistin, SAA, and CRP.
11493512: Specification Paragraph [0006], “In an embodiment, a method for monitoring the presence or absence of axial spondyloarthritis (axSpA) disease activity in a subject, for diagnosing axSpA in a subject, or for predicting risk of progressive damage, is provided. The method comprises providing a test sample comprising a sample of bodily fluid taken from the subject, and determining sample concentrations for three or more biomarkers selected from a group comprising calprotectin (dimer of S100A8 and S100A9 protein subunits; MRP-8/14); chitinase 3-like 1 (cartilage glycoprotein-39) (CHI3L1, or YKL-40); C-reactive protein, pentraxin-related (CRP); epidermal growth factor (beta-urogastrone) (EGF); intercellular adhesion molecule 1 (ICAM1); interleukin 6 (IL6); interleukin 8 (IL8); interleukin 1, beta (IL1B); interleukin 6 receptor (IL6R); leptin (LEP); Macrophage-derived chemokine (MDC); matrix metallopeptidase 1 (interstitial collagenase) (MMP1); matrix metallopeptidase 3 (stromelysin 1, progelatinase) (MMP3); resistin (RETN); serum amyloid A1 (SAA1); tumor necrosis factor receptor superfamily, member 1A (TNFRSF1A or TNF-R1); vascular cell adhesion molecule 1 (VCAM1); and vascular endothelial growth factor A (VEGFA). The method further comprises determining whether the sample concentration for each biomarker is statistically significantly greater than minimum diagnostic concentration of corresponding control biomarkers that are indicative of axSpA, and classifying disease activity of axSpA in the subject, or diagnosing axSpA in the subject, based at least in part on the determination of whether the sample concentrations for the biomarkers from the subject are statistically significantly greater than minimum diagnostic concentrations indicative of axSpA. In an embodiment, the biomarkers comprise VCAM-1, EGF, VEGF-A, IL-6, TNF-R1, MMP-1, MMP-3, YKL-40, Leptin, Resistin, SAA, and CRP. In an embodiment, the sample concentrations for the subject are predictive a clinical assessment. In an embodiment, the clinical assessment is selected from the group consisting of Ankylosing Spondylitis Disease Activity Score (ASDAS), the Stoke Ankylosing Spondylitis Spinal Score (SASSS); the modified Stoke Ankylosing Spondylitis Spinal Score (mSASSS); Ankylosing Spondylitis Quality of Life Scale (ASQOL); Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Bath Ankylosing Spondylitis Functional Index (BASFI), Bath Ankylosing Spondylitis Global Score (BAS-G), Bath Ankylosing Spondylitis Metrology Index (BASMI), Dougados Functional Index (DFI), Health Assessment Questionnaire for the Spondyloarthropathies (HAQ-S), Revised Leeds Disability Questionnaire (RLDQ), and MRI. In an embodiment, the subject has received a treatment for axSpA, and determining efficacy of the treatment based on a statistically significant difference between the sample concentrations from the subject and the sample concentrations of the control. In an embodiment, a report is prepared in a format that is capable of being disseminated to the subject or a caregiver of the subject that provides information allowing the subject or caregiver to make decisions based on the diagnosis. In an embodiment, the axSpA is nr-axSpA (non-radiographic axial spondyloarthritis) or ankylosing spondylitis (AS). In an embodiment, the progressive damage is damage to a spine or sacroiliac joint.”
Claims 12 and 23: The method of claim 9 wherein said MBDA score for the subject is predictive of a clinical assessment.
11493512: Specification Paragraph [0007], “In another embodiment, a method for monitoring the presence or absence of axSpA disease activity in a subject, for diagnosing axSpA in a subject, or for predicting risk of progressive damage is provided. The method comprises determining a first dataset associated with samples from a population of individuals wherein said population is negative for axSpA, wherein said first dataset comprises quantitative data for three or more biomarkers selected from a group comprising calprotectin (dimer of S100A8 and S100A9 protein subunits; MRP-8/14); chitinase 3-like 1 (cartilage glycoprotein-39) (CHI3L1, or YKL-40); C-reactive protein, pentraxin-related (CRP); epidermal growth factor (beta-urogastrone) (EGF); intercellular adhesion molecule 1 (ICAM1); interleukin 6 (IL6); interleukin 8 (IL8); interleukin 1, beta (IL1B); interleukin 6 receptor (IL6R); leptin (LEP); Macrophage-derived chemokine (MDC); matrix metallopeptidase 1 (interstitial collagenase) (MMP1); matrix metallopeptidase 3 (stromelysin 1, progelatinase) (MMP3); resistin (RETN); serum amyloid A1 (SAA1); tumor necrosis factor receptor superfamily, member 1A (TNFRSF1A or TNF-R1); vascular cell adhesion molecule 1 (VCAM1); and vascular endothelial growth factor A (VEGFA); determining a plurality of MBDA scores for the individuals in said population based on the first dataset. The method further comprises deriving an aggregate MBDA value for said population, determining a second dataset associate with a sample from said subject wherein said second dataset comprises the selected biomarkers, determining a MBDA score for said subject, comparing the aggregate MBDA value to the MBDA score for the subject, and determining disease activity of axSpA in the subject, or diagnosing axSpA in the subject, based at least in part on said comparison. In an embodiment, the biomarkers comprise VCAM-1, EGF, VEGF-A, IL-6, TNF-R1, MMP-1, MMP-3, YKL-40, Leptin, Resistin, SAA, and CRP. In an embodiment, the datasets are obtained by a method comprising obtaining said samples from said population and said sample from said subject wherein said samples comprise a plurality of analytes, contacting said samples with reagents, generating a plurality of complexes between said reagents with said plurality of analytes, and detecting said plurality of complexes to obtain said datasets wherein said datasets comprise quantitative data for said biomarkers. In an embodiment, the MBDA score for the subject is predictive of a clinical assessment.”
Claims 13 and 24: The method of claim 12 wherein said clinical assessment is selected from the group consisting of Ankylosing Spondylitis Disease Activity Score (ASDAS), the Stoke Ankylosing Spondylitis Spinal Score (SASSS); the modified Stoke Ankylosing Spondylitis Spinal Score (mSASSS); Ankylosing Spondylitis Quality of Life Scale (ASQOL); Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Bath Ankylosing Spondylitis Functional Index (BASFI), Bath Ankylosing Spondylitis Global Score (BAS-G), Bath Ankylosing Spondylitis Metrology Index (BASMI), Dougados Functional Index (DFI), Health Assessment Questionnaire for the Spondyloarthropathies (HAQ-S), Revised Leeds Disability Questionnaire (RLDQ), and MRI.
11493512: Specification Paragraph [0007], “In an embodiment, the clinical assessment is selected from the group consisting of Ankylosing Spondylitis Disease Activity Score (ASDAS), the Stoke Ankylosing Spondylitis Spinal Score (SASSS); the modified Stoke Ankylosing Spondylitis Spinal Score (mSASSS); Ankylosing Spondylitis Quality of Life Scale (ASQOL); Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Bath Ankylosing Spondylitis Functional Index (BASFI), Bath Ankylosing Spondylitis Global Score (BAS-G), Bath Ankylosing Spondylitis Metrology Index (BASMI), Dougados Functional Index (DFI), Health Assessment Questionnaire for the Spondyloarthropathies (HAQ-S), Revised Leeds Disability Questionnaire (RLDQ), and MRI. In an embodiment, the method further comprises receiving a third dataset associated with a second sample obtained from said subject, wherein said sample obtained from said subject and said second sample are obtained from said subject at different times, determining a second MBDA score for said subject from said third dataset, and comparing said MBDA score and said second MBDA score for said subject to determine a change in said MBDA scores, wherein said change indicates a change in axSpA activity in said subject, or the presence of axSpA in the subject. In an embodiment a report is prepared in a format that is capable of being disseminated to the subject or a caregiver of the subject that provides information allowing the subject or caregiver to make decisions based on the diagnosis. In an embodiment, the subject has received a treatment for axSpA, and the method further comprises determining a second MBDA score for a second subject wherein said second subject is of the same species as said first subject and wherein said second subject has received treatment for axSpA, comparing said MBDA score of said subject to said second MBDA score, and determining a treatment efficacy for said first subject based on said score comparison. In an embodiment, the axSpA is nr-axSpA or AS. In an embodiment, the progressive damage is damage to a spine or sacroiliac joint.”
Claims 14 and 21: The method of claim 9, further comprising: receiving a third dataset associated with a second sample obtained from said subject, wherein said sample obtained from said subject and said second sample are obtained from said subject at different times; determining a second MBDA score for said subject from said third dataset; and comparing said MBDA score and said second MBDA score for said subject to determine a change in said MBDA scores, wherein said change indicates a change in axSpA activity in said subject, or the presence of axSpA in the subject.
11493512: Specification Paragraph [0008], “In another embodiment, a computer-implemented method for scoring a sample is provided. The method comprises receiving a first dataset associated with a first sample obtained from a first subject, wherein said first dataset comprises quantitative data for three or more biomarkers selected from a group comprising calprotectin (dimer of S100A8 and S100A9 protein subunits; MRP-8/14); chitinase 3-like 1 (cartilage glycoprotein-39) (CHI3L1, or YKL-40); C-reactive protein, pentraxin-related (CRP); epidermal growth factor (beta-urogastrone) (EGF); intercellular adhesion molecule 1 (ICAM1); interleukin 6 (IL6); interleukin 8 (IL8); interleukin 1, beta (IL1B); interleukin 6 receptor (IL6R); leptin (LEP); Macrophage-derived chemokine (MDC); matrix metallopeptidase 1 (interstitial collagenase) (MMP1); matrix metallopeptidase 3 (stromelysin 1, progelatinase) (MMP3); resistin (RETN); serum amyloid A1 (SAA1); tumor necrosis factor receptor superfamily, member 1A (TNFRSF1A or TNF-R1); vascular cell adhesion molecule 1 (VCAM1); and vascular endothelial growth factor A (VEGFA), and determining, by a computer processor, a first MBDA score from said first dataset using an interpretation function, wherein said first MBDA score provides a classification of disease activity of axSpA in the subject, a diagnosis of axSpA in the subject, or a prediction of risk of progressive damage. In an embodiment, the biomarkers comprise VCAM-1, EGF, VEGF-A, IL-6, TNF-R1, MMP-1, MMP-3, YKL-40, Leptin, Resistin, SAA, and CRP. In an embodiment, the method further comprises receiving a second dataset associated with a second sample obtained from said first subject, wherein said first sample and said second sample are obtained from said first subject at different times, determining a second MBDA score from said second dataset using said interpretation function, and comparing said first MBDA score and said second MBDA score to determine a change in said MBDA scores, wherein said change indicates a change in said inflammatory disease activity in said first subject, or a diagnosis of axSpA in the subject.”
Claims 15 and 25: The method of claim 9 wherein a report is prepared in a format that is capable of being disseminated to the subject or a caregiver of the subject that provides information allowing the subject or caregiver to make decisions based on the diagnosis.
11493512: Specification Paragraph [0008], “In an embodiment, a report is prepared in a format that is capable of being disseminated to the subject or a caregiver of the subject that provides information allowing the subject or caregiver to make decisions based on the diagnosis. In an embodiment, the axSpA is nr-axSpA or AS. In an embodiment, the progressive damage is damage to a spine or sacroiliac joint.”
Claim 16: The method of claim 9 wherein said subject has received a treatment for axSpA, and further comprising the steps of:determining a second MBDA score for a second subject wherein said second subject is of the same species as said first subject and wherein said second subject has received treatment for axSpA; comparing said MBDA score of said subject to said second MBDA score; and determining a treatment efficacy for said first subject based on said score comparison.
11493512: Specification Paragraph [0075], “These properties of the disclosed biomarkers can be used for several purposes. On a subject-specific basis, they provide a context for understanding the relative level of disease activity. The rating of disease activity can be used, e.g., to guide the clinician in determining treatment, in setting a treatment course, and/or to inform the clinician that the subject is in remission. Moreover, it provides a means to more accurately assess and document the qualitative level of disease activity in a subject. It is also useful from the perspective of assessing clinical differences among populations of subjects within a practice. For example, this tool can be used to assess the relative efficacy of different treatment modalities.”
Claim 28: The method of claim 9,further comprising selecting an axSpA therapeutic regimen based on said MBDA score.
11493512: Specification Paragraph [0077], “The MBDA score can be used for several purposes. On a subject-specific basis, it provides a context for understanding the relative level of disease activity. The MBDA rating of disease activity can be used, e.g., to guide the clinician in determining treatment, in setting a treatment course, and/or to inform the clinician that the subject is in remission. Moreover, it provides a means to more accurately assess and document the qualitative level of disease activity in a subject. It is also useful from the perspective of assessing clinical differences among populations of subjects within a practice. For example, this tool can be used to assess the relative efficacy of different treatment modalities. Moreover, it is also useful from the perspective of assessing clinical differences among different practices. This would allow physicians to determine what global level of disease control is achieved by their colleagues, and/or for healthcare management groups to compare their results among different practices for both cost and comparative effectiveness. Because the MBDA score demonstrates strong association with established disease activity assessments, the MBDA score can provide a quantitative measure for monitoring the extent of subject disease activity, and response to treatment.”
Claim 29: The method of claim 28 further comprising providing said axSpA therapeutic regimen.
Claim 30: The method of claim 28, further comprising determining a response to the treatment based on said MBDA score.
Claim 31: The method of claim 28, further comprising determining an axSpA treatment course based on said MBDA score.
Response to Arguments
Applicants argue that upon notification of allowable subject matter, applicants will timely file a terminal disclaimer. Applicants’ amendments do not overcome the rejection. Thus, applicant is advised that until claims of the instant application are amended so that the claimed subject matter of the the instant applications is patentably distinct, or until a terminal disclaimer is filed and approved, the rejection under the judicially created doctrine of double patenting will be maintained and no allowable subject matter will be indicated. A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the conflicting application or patent is shown to be commonly owned with this application. See 37 CFR 1.130(b).
Conclusion
No claims are allowed.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/K.N.A./Examiner, Art Unit 1687
/LARRY D RIGGS II/Supervisory Patent Examiner, Art Unit 1686
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