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 .
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.
Withdrawn Rejection
In light of the amendments, the 35 U.S.C. 103 rejection over Farokhzad is hereby withdrawn.
Claim Objections
Claim 1 is objected to because of the following informalities: To be consistent through the claims, last line of claim 1 recites “a comorbidity” should be – a comorbidity thereof –. Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-6, 8-9, and 11-17 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: The instantly claimed invention is directed a method comprising obtaining a biofluid sample from a subject at risk of having NSCLC or a comorbidity thereof , generating a data set from the fraction of the proteins or fragment thereof, and applying a classifier to the data set to identify a degree of risk for the biofluid sample of the NSCLC. Therefore, the instantly claimed invention falls into one of the four statutory categories. (Step 1: YES)
ELIGIBILITY STEP 2A; WHETHER A CALIM IS DIRECTED TO A JUDICIAL EXCEPTION. First it is determined in Prong One whether a claim recites a judicial exception, and if so, then it is determined in in Prong Two if the recited judicial exception is integrated into a practical application of that exception.
Step 2A Prong 1
Claim 1 recites the following steps which fall under the mental processes and mathematical concepts of abstract ideas and nature/natural phenomena:
Claim 1 is drawn to obtaining a biofluid sample from a subject at risk of having NSCLC or a comorbidity thereof, generating a data set from the fraction of the proteins or fragments thereof, and applying a classifier to a data set (i.e., subset) to identify a degree of risk for the biofluid sample of the NSCLC, wherein the classifier is trained to distinguish NSCLC from comorbidity.
The limitations of a subject at risk of having NSCLC or a comorbidity and the amount of fraction from the proteins or fragments thereof are directed to a judicial exception because the claim language clearly conveys the naturally occurring relationship between the proteins/ fragments thereof and the risk of NSCLC or comorbidity. This constitutes law of nature/natural phenomena, as in the identification of a correlation between the presence of protein or fragment thereof in a bodily sample and the risk of NSCLC or comorbidity thereof.
Additionally, the step of generating a data set from the fraction of the proteins or fragments thereof maybe categorized as abstract ideas, namely mental processes/ concepts performed in the human mind (such as a person simply thinking about the fraction concentration of said proteins or fragments thereof). Such step would read on purely mental activity such as a practitioner looking at a subject’s chart and thinking about the fraction concentration of the protein or fragment thereof.
Furthermore, the limitations that recite mathematical concepts are applying a classifier to the data set to identify a degree of risk for the biofluid sample wherein the classifier is trained to distinguish the NSCLC from the comorbidity thereof. The broadest reasonable interpretation encompasses, for example, a mathematical calculation of performing a statistical analysis, algorithm, or calculating the data set from a classifier (see MPEP 2106.04(a)(2) l C, examples i-vi). The data set requires performing the addition of weighted variables with a classifier, and thus amounts to a textual equivalent to performing mathematical calculations.
Furthermore, in claim 2, the claim recites the classifier as a mathematical concept of a receiver operating characteristic curve having an area under the curve of at least 0.8. Thus, the claim is directed to the abstract ideas.
Dependent claims 3-6, 11 and 14 further recite limitations related to the natural phenomena or natural products for the natural correlation between the biomarkers and NSCLC or a comorbidity thereof.
Dependent claims 13 and 15-17 further recite limitations for or related to the abstract ideas. Claim 13 recites the classifier comprises classification features comprising one or more particle-protein pairs, which is part of the mathematical concept as recited in claims 1-2. Claim 15 recites wherein the data set further comprises distinct peptide sequences or pos-translational modification information for the one or more proteins or fragments thereof, which is part of the mathematical concept recited in claims 1-2. Claim 16 recites the classifier is trained with a training data set that comprises a concentration or an amount of proteins that do not include depleted plasma proteins, which is part of the mathematical concept recited in claims 1-2. Claim 17 recites the classifier has an increased protein detection consistency relative to a second classifier trained with proteomic data from depleted plasma samples, which is part of the mathematical concept recited in claims 1-2 (Step 2A, Prong 1: YES).
Step 2A: Prong 2:
The Step 2A, Prong 2 analysis requires identifying whether there are any additional elements recited in the claim beyond the judicial exception(s), and evaluating those additional elements to determine whether they integrate the exception into a practical application of the exception. Besides the abstract ideas, claim 1 recites obtaining a biofluid sample from a subject, extracting the proteins or fragments thereof from the biofluid sample and producing a fraction of the one or more proteins or fragments thereof (steps b-c and (1) and (2)). When so evaluated, these additional elements represent mere data gathering that is necessary for use of the recited judicial exception (i.e., extracting concentration of protein/ fragment thereof to produce a data set and applying the data set to distinguish between NSCLC and comorbidity thereof) and is recited at a high level of generality. In particular, to obtain the data set through detecting for concentration with physicochemically distinct particles and selectively removing one or more components other than the protein or fragment thereof are insignificant extra-solution activity to obtain data information for the classifier to distinguish between NSCLC and comorbidity thereof. As stated above, these limitations are recited at a high level of generality because the physiochemically distinct particles are generic structures and generically couple to all proteins of fragments thereof in the biofluid sample. This judicial exception is not integrated into a practical application for the following reasons.
Claims 8-9 and 12 recite limitations that are directed to limitations necessary to perform the recited judicial exception. When so evaluated, these additional elements represent mere data gathering that is necessary for use of the recited judicial exception and is recited at a high level of generality. As stated, these limitations are recited at a high level of generality because the physiochemically distinct particles are generic structures that generically couple to all proteins of fragments thereof in the biofluid sample and detecting all proteins and fragments through mass spectrometry. This judicial exception is not integrated into a practical application for the following reasons. (Step 2A, Prong 2: NO).
Step 2B: In step 2B, it is determined whether the claimed subject matter includes additional elements that amount to significantly more than the judicial exception. See MPEP 2106.05. The claims do not include any additional steps appended to the judicial exception that are sufficient to amount to significantly more than the judicial exception. The additional limitations in claims 1, 8-9 and 12 are well-understood, routine, and conventional.
Farokhzad et al. (US2018/0172694A1, published 06/21/2018, IDS submitted on 12/18/2024, cite no. 056) disclose a method for using protein corona sensor arrays for early detection of disease comprising the following steps (abstract) and physiochemically distinct particles (see Fig. 19A). Farokhzad teaches combining more nanoparticles for plasma fractionating and proteomic analysis provides significantly more information for cancer detection and discrimination with superior sensitivity, specificity and prediction accuracy (see pg. 39, right col., middle para. of para. [0367]). Farokhzad teaches the supernatant will be removed and the collected particles would be re-dispersed in 500 microliter of PBS (see middle of para. [0387]). Farokhzad discloses obtaining protein information from a plasma sample (FIG. 1; [0326]; claim 1). Farokhzad teaches small and large non-small cell lung carcinoma [0266] wherein the protein information comprises measurements of distinct peptides of a protein group (FIG.1; [0326], e.g. peptides of proteins analyzed via mass spectrometry, [0326]). Farokhzad discloses comparing a biomolecule fingerprint obtained from a protein corona of a subject to a panel of biomolecule fingerprints associated with a plurality of diseases or disorders, and diagnosing the disease or disorder ([0288]). Farokhzad teaches one would expect the protein corona sensor array to cross-reactively adsorb a wide range of proteins involved in cancer induction and development that could be used for cancer identification and discrimination [0311]. Farokhzad teaches that the discrimination between different groups occurs as a result of several predictors and not individual biomarkers that change simultaneously in a systematic manner, forming patterns unique to each specific type of cancer [0319]. Farokhzad teaches the multi-nanoparticle protein corona enables discrimination of cancers at early stages (see Example 1B, [0341]). Farokhzad teaches in Table 5 the protein information comprises a concentration or an amount of a secreted protein.
Falahati et al. (A health concern regarding the protein corona, aggregation and disaggregation, 2019, BBA-General Subjects, 1863, pg. 971-991, of record) review the medical and clinical implementations of nanoparticle-protein complexes, or protein coronas, including cancer diagnosis (Abstract), and teaches that these protein coronas on nanoparticles are used for cancer diagnosis (i.e. the protein coronas are used on subjects suspected of having cancer/disease) by changing the physico-chemical properties of the nanoparticles (i.e. physiochemically distinct particles) and incubating the nanoparticles with human plasma (i.e. a biofluid sample) (pg. 980, col. 1, para. 2; pg. 986, col. 1, para. 1). Falahati further teaches methods that are employed to study the proteins adsorbed on the nanoparticle surface (i.e. the protein corona) includes quantifying the protein coronas using mass-spectrometry (pg. 972, col. 2 , para. 1). Falahati teaches methods of identifying the protein coronas with SDS-PAGE and MS (see pg. 972, right col, under Methods 3).
Silvio et al. (“Technical tip: high-resolution isolation of nanoparticle–protein corona complexes from physiological fluids”, Nanoscale, 2015, vol. 7, pgs. 11980-11990”) discloses nanoparticles in contact with biological fluids are generally coated with environmental proteins, forming a stronger layer of proteins around the NP surface called the hard corona and protein corona complexes provide the biological identity of the NPs and their isolation and characterization are essential to understand their in vitro and in vivo behavior (see abstract). The abstract further teaches NPs to be separated from complex fluids containing biological particles (also see Scheme 1). Silvio teaches sequential cycles of centrifugation washing are carefully optimized according to the NP and media properties (see pg. 11981, left col., para. 1).
Therefore, these additional elements when viewed alone and in combination are not sufficient to amount to significantly more than the recited judicial exception.
Therefore, taken alone, the additional elements do not amount to significantly more than the above-identified judicial exception(s). Even when viewed as a combination, the additional elements fail to transform the exception into a patent-eligible application of that exception. Thus, the claims as a whole do not amount to significantly more than the exception itself. (Step 2B: NO).
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.
Claims 1-6, 8-9, and 12-17 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
MPEP § 2163 states that, for a claimed genus, the written description requirement may be satisfied through sufficient description of a representative number of species by actual reduction to practice, reduction to drawings, or by disclosure of relevant, identifying characteristics, i.e., structure or other physical and/or chemical properties, by functional characteristics coupled with a known or disclosed correlation between function and structure, or by a combination of such identifying characteristics, sufficient to show the applicant was in possession of the claimed genus.
The claims are directed to a method of obtaining a data set comprising protein information from biomolecule coronas that correspond to physiochemically distinct particles incubated with a biofluid sample from a subject suspected of having non-small cell lung cancer (NSCLC) or a comorbidity thereof, and applying a classifier to the data set to identify the biofluid sample as indicative of the NSCLC or the comorbidity thereof, wherein the classifier distinguishes the NSCLC from the comorbidity thereof or wherein the classifier distinguishes the comorbidity from the NSCLC.
The claims as a whole cover a genus of protein information from biomolecule coronas. Explicit in the claims is that such protein information process certain functional characteristics; namely, the ability to be incorporated into a classifier to identify and distinguish between NSCLC and comorbidity thereof.
Level of skill and knowledge in the art:
Forder et al. teach that largely, it has been shown that squamous cell carcinoma (SCC), a subtype of NSCLC, has a greater association with COPD (e.g., risk, decreased overall survival, severity), as well as an increased risk of SCLC with the presence of COPD independent of smoking status (see bottom of pg. 1 to top of pg. 2). Forder further teaches in Fig. 1B an overlap of 40-70% of lung cancer patients have COPD (also see caption under (B)). (“Mechanisms Contributing to the Comorbidity of COPD and Lung Cancer”, International Journal of Molecular Sciences, 2023, vol. 24, 2859, pgs. 1-20, of record).
The disclosure:
Applicant’s specification only discloses protein information used to distinguish between NSCLC and comorbidity thereof through a classifier is from protein serine protease HTRAI (HTRAI), peroxidasin homolog (PXDN), Anthrax toxin receptor 2 (ANTR2), versican core protein (CSPG2), Anthrax toxin receptor I (ANTRI), palmitoleoyl-protein carboxylesterase NOTUM (NOTUM), cartilage intermediate layer protein I (CILPI), Calpain-2 catalytic subunit (CAN2) and Platelet glycoprotein Ib beta chain (GP1BB) (see FIG. 1-2 and 14; Example 1 in [0214]-[0230]; Example 2 in [0231]-[0232]. For example, Applicant’s specification does not provide any examples of using other known conventional proteins to distinguish NSCLC from comorbidity thereof.
Given the claimed broadly class of protein information and in the absence of sufficient disclosure of relevant identifying characteristics for the broadly claimed protein information, the patentee must establish “a reasonable structure-function correlation” either within the specification or by reference to the knowledge of one skilled in the art with functional claims AbbVie Deutschland GmbH & Co. v. Janssen Biotech, Inc. (Fed. Cir. 2014) and the specification at best describes plan for making fusion proteins encompassed by the “limitations above” and then identifying those that satisfy claim limitations, but mere “wish or plan” for obtaining claimed invention is not sufficient. Centocor Ortho Biotech Inc. v. Abbott Laboratories, 97 USPQ2d 1870 (Fed. Cir. 2011).
In particular, Forder teaches in Fig. 1 that COPD (i.e., comorbidity of NSCLC) overlaps with NSCLC in detection in patients. Thus, the biofluid samples would have overlapping similarities in measurements. However, the specification has not provided common structures of said biomarkers to identify common features for the classifier to distinguish NSCLC from its comorbidity in biofluid samples. Therefore, the specification does not adequately describe a representative number of species for the genus of protein information to distinguish NSCLC from its comorbid state with a classifier.
The claimed invention as a whole may not be adequately described if the claims require an essential or critical feature which is not adequately described in the specification and which is not conventional or known in the art. See MPEP 2163 I. Specifically, the written description requirement for a claimed genus may be satisfied through sufficient description of a representative number of species by actual reduction to practice (see i)(A) above), reduction to drawings (see i)(B) above), or by disclosure of relevant, identifying characteristics, i.e., structure or other physical and/or chemical properties, by functional characteristics coupled with a known or disclosed correlation between function and structure, or by a combination of such identifying characteristics, sufficient to show the inventor was in possession of the claimed genus (see i)(C) above). A "representative number of species" means that the species which are adequately described are representative of the entire genus. Thus, when there is substantial variation within the genus, one must describe a sufficient variety of species to reflect the variation within the genus. See MPEP 2163 3)(a)(ii).
In conclusion, there is nothing in the application as filed that discloses a representative of species to the claimed protein information or suggest any chemical relationship beyond the instant disclosure (i.e., claim 11). As written, the claims encompass generic structures for desired functional properties, namely the classifier distinguishes between NSCLC and its comorbidity. The fact is that NSCLC and its comorbidity overlaps in similarities, a skilled artisan cannot, as one can do with a fully described genus, visualize or recognize the identity of the members of the claimed genus to distinguish general protein information of NSCLC from its comorbidity in a biofluid sample for a subject that is suspected of having NSCLC or comorbidity thereof. The specification does not evidence the possession of these genuses that are undefined and uncharacterized falling within the potentially large genus to establish possession. Consequently, Applicant was not in possession of the instant claimed invention. The full breadth of the claims do not meet the written description provision of 35 U.S.C. 112, first paragraph.
Claim Rejections - 35 USC § 103
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 1-6, 8-9, and 12-17 are rejected under 35 U.S.C. 103 as being unpatentable over Farokhzad et al. (US 2018/0172694 A1, published 06/21/2018, IDS submitted on 12/18/2024, cite no. 056) in view of Kocher et al. (“Cardiovascular Comorbidities and Events in NSCLC: Often Underestimated but Worth Considering”. Clinical Lung Cancer, Vol. 16 (4), pgs. 305- 312, published July 2015).
Regarding claim 1, Farokhzad discloses a method for using protein corona sensor arrays for early detection of disease comprising the following steps (abstract). Farokhzad discloses obtaining protein information from a plasma sample (FIG. 1; [0326]; claim 1). Farokhzad teaches small and large non-small cell lung carcinoma [0266] wherein the protein information comprises measurements of distinct peptides of a protein group (FIG.1; [0326], e.g. peptides of proteins analyzed via mass spectrometry). Farokhzad discloses comparing a biomolecule fingerprint obtained from a protein corona of a subject to a panel of biomolecule fingerprints associated with a plurality of diseases or disorders, and diagnosing the disease or disorder ([0288]). Farokhzad teaches the physiochemically distinct particles coupled to said protein or fragment thereof (see Fig. 19A). Farokhzad further discloses that a machine learning algorithm (i.e. a classifier) can be used to associate the biomolecule fingerprints with different disease states and make the diagnosis by distinguishing between disease states ([0284]; [0312]). Farokhzad further teaches the classifier is used to identify cancer in the subject and distinguish between diseases [0348]. Farokhzad discloses the machine learning model can determine if a subject has or does not have cancer [0284]. Farokhzad further discloses the diseases can include inflammatory diseases, including asthma, emphysema pulmonary embolism, (i.e. comorbidity thereof) [0267] and [0273], and early stage 1 non-small cell lung cancer ([0265]; [0266]; [0273]; [0277]). Farokhzad teaches advantages of being able to treat a disease at a very early stage even before development of the disease (see bottom of para. [0275]). Farokhzad further discloses the classifier diagnoses the subject with cancer ([0255]; [0264]-[0265]). Farokhzad teaches one would expect the protein corona sensor array to cross-reactively adsorb a wide range of proteins involved in cancer induction and development that could be used for cancer identification and discrimination [0311]. Farokhzad teaches that the discrimination between different groups occurs as a result of several predictors and not individual biomarkers that change simultaneously in a systematic manner, forming patterns unique to each specific type of cancer [0319]. Farokhzad teaches the multi-nanoparticle protein corona enables discrimination of cancers at early stages (see Example 1B, [0341]). Farokhzad teaches combining more nanoparticles for plasma fractionating and proteomic analysis provides significantly more information for cancer detection and discrimination with superior sensitivity, specificity and prediction accuracy (see pg. 39, right col., middle para. of para. [0367]). Farokhzad teaches the supernatant will be removed and the collected particles would be re-dispersed in 500 microliter of PBS (see middle of para. [0387]). Farokhzad teaches that the array has the ability to determine cancer from cardiovascular disease (see para. [0285]). Farokhzad teaches obtaining the data set comprises contacting the biofluid sample with the physiochemically distinct particles to form the biomolecule coronas (Figs. 1-2B and 15A-B; and [0031]). Farokhzad teaches in Table 5 the protein information comprises a concentration or an amount of a secreted protein.
Even though Farokhzad teaches using biomolecule fingerprints obtained from a protein corona of a subject with a trained classifier through physiochemically distinct particles (see para. [0349]), the reference does not explicitly teach applying the classifier to the data set to identify a degree of risk for the biofluid sample of the NSCLC wherein the classifier is trained to distinguish the NSCLC from a comorbidity thereof.
Kocher teaches patients with non-small-cell lung cancer (NSCLC) and cardiovascular (CV) disease often share a comparable demographic profile and the analysis of CV comorbidities, risk factors, CV events, and outcome in large consecutive NSCLC cohort found that preexisting CV comorbidities and development of CV events are frequently observed in NSCLC patients and to provide definitive recommendations on impact, prevention and screening of CV disease in NSCLC are desirable (see abstract). Kocher teaches CV comorbidity was hypertension and general comorbidities were COPD and patients with hypertension was present at the time of NSCLC diagnosis (see pg. 308, left col., para. 2). Kocher concluded that patients with NSCLC have a high burden of CV comorbidities and develop a considerable number of CV events (see pg. 311, right col., Conclusion).
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have used the method of training a classifier from the detection of biomolecules through sensor arrays for determining early disease states of NSCLC as taught by Farokhzad with the consideration that NSCLC and its comorbidity (e.g., cardiovascular disease) overlap in profiling as taught by Kocher because Farokhzad teaches that protein corona sensor array can be used to accurately identify and the classifier was trained to discriminate early stage of diseases through forming patterns unique to specific disease. It would have been obvious to have applied a classifier to identify the probability of early stage of NSCLC by discriminating its comorbidity, for example, cardiovascular disease, from the subject because NSCLC and cardiovascular diseases share and overlap in profiling and Farokhzad teaches that the advantage of identifying a disease early, even before development of the disease, is being able to treat the disease at a very early stage. Thus, the discrimination of NSCLC from its comorbidity will prevent misdiagnosing early stage of NSCLC.
The person would have a reasonable expectation of success in using protein corona sensor array to discriminate NSCLC from a comorbidity thereof because Farokhzad teaches that the array has the ability to determine cancer states and cardiovascular disease.
With respect to claim 2, Farokhzad teaches the biomolecule fingerprint can distinguish between different possible biological states (e.g., disease states) of a subject and in some embodiments, the biomolecule fingerprint is associated with the development of a disease or disorder and/or is able associated with a disease state of the subject (see para. [0244]). Farokhzad teaches in Figs. 8A-C the receiver operating characteristic (ROC) plot derived from PLS-DA based on the top 69 ranked variables. Figs. 8A-C shows the ROC having an area under the curve of at least 0.8. However, the reference does not explicitly teach an area under the curve of at least 0.8 when distinguishing between the NSCLC and comorbidity.
It has long been settled to be no more than routine experimentation for one of ordinary skill in the art to discover an optimum value for a result effective variable of measuring a high area under the curve (AOC) for ROC to distinguish/discriminate diseases. “[W]here the general conditions of a claim are disclosed in the prior art, it is not inventive to discover the optimum of workable ranges by routine experimentation” Application of Aller, 220 F.2d 454, 456, 105 USPQ 233, 235-236 (C.C.P.A. 1955). “No invention is involved in discovering optimum ranges of a process by routine experimentation.” Id. at 458, 105 USPQ at 236-237. The “discovery of an optimum value of a result effective variable in a known process is ordinarily within the skill of the art.” Since applicant has not disclosed that the concentrations recited in the claims are for any particular purpose or solve any stated problem. It would have been obvious for the person of ordinary skill to discover the optimum effective scores for ROC to distinguish between NSCLC and comorbidity.
With respect to claims 3 and 6, Farokhzad further discloses the diseases can include inflammatory diseases, including asthma, emphysema pulmonary embolism, (i.e. comorbidity thereof) [0267] and [0273])
With respect to claims 4-5, Farokhzad teaches early stage 1 non-small cell lung cancer/carcinoma ([0265]; [0266]; [0273]; [0277]).
With respect to claim 8, Farokhzad teaches physicochemical properties of different liposomes before and after interactions with human plasma from patients with different diseases ([0031]).
With respect to claim 9, Farokhzad teaches advances in proteomic analyses using mass spectrometry ([0173]).
With respect to claim 12, Farokhzad teaches the physiochemically distinct particles comprise nanoparticle (Figs. 1-2B and 15A-B; and [0031]).
With respect to claim 13, Farokhzad teaches each liposome-protein pair ([0352]).
With respect to claim 14, Farokhzad teaches the biofluid sample comprises plasma (Fig. 14).
With respect to claim 15, Farokhzad teaches distinct peptide sequences and post-translational modification information (Table 5 under uniport).
With respect to claim 16, Farokhzad teaches the protein corona composition contains a wide range of less-abundant and very rare plasma proteins, without need for depletion ([0361]).
With respect to claim 17, Farokhzad teaches the classifier has an increased protein detection consistency relative to a second classifier generated using proteomic data from depleted plasma samples ( Fig. 10B and [0073], the horizontal lines straddling the dots indicate 25th and 75th percentiles of the importance across classifiers trained).
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 USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The 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/process/file/efs/guidance/eTD-info-I.jsp.
Claims 1-6, 8-9, and 11-17 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-21 of U.S. Patent No. 12087405B2 (‘405) in view of Farokhzad et al. (US 2018/0172694 A1, published 06/21/2018, IDS submitted on 12/18/2024, cite no. 056).
Instant claims 1 and 11, although the claims at issue are not identical, they are not patentably distinct from each other because claim 1 of Patent ‘405 recites a method of contacting a biofluid sample from a subject suspected of having a non-small cell lung cancer (NSCLC) or a comorbidity of NSCLC with particles to form biomolecule coronas comprising proteins of the biofluid adsorbed to the particles, wherein the proteins comprise one or more of serine protease HTRA1 (HTRA1), peroxidasin homolog (PXDN), anthrax toxin receptor 2 (ANTR2), versican core protein (CSPG2), anthrax toxin receptor 1 (ANTR1), palmitoleoyl-protein carboxylesterase NOTUM (NOTUM), cartilage intermediate layer protein 1 (CILP1), neural cell adhesion molecule 1 (NCAM1), 60S acidic ribosomal protein P2 (RLA2), protein S100-A8 (S10A8), protein S100-A9 (S10A9), tubulin alpha-1 A chain (TBA1 A), and calpain-2 catalytic subunit (CAN2); obtaining a data set by identifying and measuring the proteins of the biomolecule coronas; inputting the data set into a classifier that distinguishes between the NSCLC and the comorbidity of NSCLC; identifying the data set as indicative of the NSCLC or the comorbidity of NSCLC through the classifier. Patent claim 2 recites contacting the biofluid sample with particles comprises contacting the biofluid sample with physiochemically distinct sets of particles. Patent claim 3 recites separating the adsorbed proteins from non-adsorbed proteins; and ionizing the adsorbed proteins or contacting the adsorbed proteins with a detection probe. Patent claim 5 recites identifying and measuring the proteins comprises detecting the proteins by mass spectrometry.
However, Patent ‘405 does not recite producing a fraction of the protein or fragment thereof. Farokhzad has been discussed in the above rejection. It would have been obvious to the person at the time of filing to have used the method of distinguishing between NSCLC and the comorbidity of NSCLC through particles forming biomolecule coronas as recited in the Patent with producing a fraction of the protein or fragment thereof of Farokhzad because Farokhzad teaches combining more nanoparticles for plasma fractionating and proteomic analysis provides significantly more information for cancer detection and discrimination with superior sensitivity, specificity and prediction accuracy. The person would have a reasonable expectation of success because it has been well understood to use physiochemically distinct particles for assaying.
Instant claim 2, Patent claim 17 recites the classifier is characterized by a ROC curve having an AUC of at least 0.9 in discriminating between the NSCLC and the comorbidity of NSCLC.
Instant claim 3, Patent claim 12 recites wherein the comorbidity of NSCLC comprises a pulmonary comorbidity.
Instant claim 4, Patent claim 13 recites wherein the NSCLC comprises stage 1, 2, or 3 NSCLC.
Instant claim 5, Patent claim 5 recites the subject has not undergone a cancer treatment.
Instant claim 6, Patent claim 15 recites the pulmonary comorbidity is selected from the group consisting of: chronic obstructive pulmonary disease (COPD), emphysema, pulmonary fibrosis, asthma, a chronic lung disease, and any combination thereof.
Instant claim 8, Patent claim 4 recites wherein the particles comprise lipid particles, metal particles, silica particles, or polymer particles.
Instant claim 9, Patent claim 5 recites identifying and measuring the proteins comprises detecting the proteins by mass spectrometry.
Instant claims 12-13, Patent claim 11 recites nanoparticle-protein pairs.
Instant claim 14, Patent claim 7 recites the biofluid comprises plasma.
Instant claim 15, Patent claim 5 recites identifying and measuring the proteins comprises detecting the proteins by mass spectrometry, which would comprise distinct peptide sequences.
Instant claim 16, Patent claim 9 recites the data set excludes proteins otherwise measurable by mass spectrometry in depleted plasma samples without the use of the particles.
Instant claim 17, Patent claim 10 recites the AUC is improved relative to a second classifier generated using proteomic data from depleted plasma samples.
Claims 1-6, 8-9, and 11-17 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-15 of U.S. Patent No. 11664092B2 (‘092) in view of Farokhzad et al. (US 2018/0172694 A1, published 06/21/2018, IDS submitted on 12/18/2024, cite no. 056).
Instant claims 1, 3 and 11, although the claims at issue are not identical, they are not patentably distinct from each other because claim 1 of Patent ‘092 recites obtaining a data set comprising protein information from biomolecule coronas that correspond to physicochemically distinct particles incubated with a biofluid sample from a subject suspected of having a cancer state or a comorbidity of the cancer state, wherein the protein information comprises a concentration or amount of serine protease HTRA1 (HTRA1), Peroxidasin homolog (PXDN), Anthrax toxin receptor 2 (ANTR2), Versican core protein (CSPG2), Anthrax toxin receptor 1 (ANTR1), Palmitoleoyl-protein carboxylesterase NOTUM (NOTUM), Cartilage intermediate layer protein 1 (CILP1), or Calpain-2 catalytic subunit (CAN2), and wherein the cancer state comprises non-small cell lung cancer (NSCLC) and the comorbidity of the cancer state comprises a pulmonary comorbidity; applying a classifier to the data set to identify the biofluid sample as indicative of a healthy state, the cancer state, or the comorbidity of the cancer state, wherein the classifier distinguishes the cancer state from the comorbidity of the cancer state, and wherein the classifier identifies the biofluid sample as indicative of the cancer state. Patent claim 6 recites obtaining the data set comprises contacting the biofluid sample with the physicochemically distinct particles to form the biomolecule coronas. Patent claim 8 recites detecting the proteins of the biomolecule coronas by mass spectrometry.
However, Patent ‘092 does not recite producing a fraction of the protein or fragment thereof. Farokhzad has been discussed in the above rejection. It would have been obvious to the person at the time of filing to have used the method of distinguishing between NSCLC and the comorbidity of NSCLC through particles forming biomolecule coronas as recited in the Patent with producing a fraction of the protein or fragment thereof of Farokhzad because Farokhzad teaches combining more nanoparticles for plasma fractionating and proteomic analysis provides significantly more information for cancer detection and discrimination with superior sensitivity, specificity and prediction accuracy. The person would have a reasonable expectation of success because it has been well understood to use physiochemically distinct particles for assaying.
Instant claim 2, Patent claim 2 recites the classifier is characterized by a receiver operating characteristic curve having an area under the curve of at least 0.8.
Instant claim 4, Patent claim 3 recites the NSCLC comprises stage 1, 2, or 3 NSCLC.
Instant claim 5, Patent claim 4 recites the subject has not yet undergone a cancer treatment.
Instant claim 6, Patent claim 5 recites the pulmonary comorbidity is selected from the group consisting of: chronic obstructive pulmonary disease (COPD), emphysema, pulmonary fibrosis, asthma, a chronic lung disease, and any combination thereof.
Instant claim 8, Patent claim 7 recites the physicochemically distinct particles comprise lipid particles, metal particles, silica particles, or polymer particles.
Instant claim 9, Patent claim 8 recites obtaining the data set comprises detecting the proteins of the biomolecule coronas by mass spectrometry.
Instant claims 12-13, Patent claim 10 recites nanoparticle-protein pairs.
Instant claim 14, Patent claim 12 recites the biofluid comprises plasma.
Instant claim 15, Patent claim 15 recites the distinct peptides comprise distinct peptide sequences or post-translational modifications.
Instant claims 16-17, Patent claim 14 recites the protein information further comprises a second protein group measurement comprising pooled measurements of distinct peptides of the second group, and wherein the classifier is further applied to the second protein group measurement.
Response to Arguments
Applicant's arguments filed 09/02/2025 have been fully considered but they are not persuasive. In view of the amendments, the rejections have been modified.
With respect to 35 U.S.C. 101 rejection, Applicant argues on page 7 that the amended claim 1(steps b-c) is patent eligible under the Step 2B because even if an additional element does not amount to significant more on its own, it can still amount to significantly more when considered in combination with the other elements of the claim. Applicant further argues that like the Arisoa Diagnostics case, the instant claims should be patent eligible under Step 2B. In particular, Applicant argues that the instant step (c2) recite limitations that are significantly more than the judicial exception.
The arguments are not found persuasive for the following reasons. As stated above, the 101 rejection has been modified in view of the amendments. Based from the references above, it has been well understood and routine in the art to extract the target protein or fragment thereof, isolate and measure the concentration (fraction) of the intended proteins or fragments thereof. Even though the Arisoa Diagnostics case are patent eligible under step 2B, the fact patterns for the instant claims differ because it is routine and well understood in the art to extract proteins or fragments thereof from a sample, produce measurable concentrations, and isolate or remove the intended proteins or fragment thereof with physiochemically distinct particles for analysis (see cited references above).
With respect to 35 U.S.C. 112(a) rejection, Applicant argues on page 9 that the amended claim 1 satisfies the written description requirement.
The argument is not found persuasive because, as stated above, Applicant’s specification only discloses protein information used to distinguish between NSCLC and comorbidity thereof through a classifier from the claimed proteins of claim 11.
However, the specification has not provided common structures of said biomarkers to identify common features for the classifier to distinguish NSCLC from its comorbidity in biofluid samples. Therefore, the specification does not adequately describe a representative number of species for the genus of protein information to distinguish NSCLC from its comorbidity state with a classifier.
With respect to 35 U.S.C. 103 rejection over Farokhzad, Applicant argues on page 10 that Farokhzad does not provide the skilled person with any reasonable expectation of success in arriving at the claimed subject matter, namely “(e) applying a classifier to the data set of (d) to identify a degree of risk for the biofluid sample of the NSCLC, wherein the classifier is trained to distinguish NSCLC from a comorbidity”. The person would have no reasonable expectation of success in modifying the machine learning approach in Farokhzad to distinguish NSCLC from a comorbidity as claimed. For example, Farokhzad fails to teach or even suggest a training dataset that includes comorbidities.
As stated above, the 103 rejection has been modified in view of the amendments. The arguments are not found persuasive because, as stated above, it would have been obvious to have used the method of training a classifier from detecting biomolecules through sensor arrays of determining early disease states of NSCLC as taught by Farokhzad with the consideration that NSCLC and its comorbidity (e.g., cardiovascular disease) overlap in profiling as taught by Kocher. In particular, Farokhzad teaches that the advantage of identifying a disease early, even before development of the disease, is being able to treat the disease at a very early stage. Thus, the discrimination of NSCLC from its comorbidity will prevent misdiagnosing early stage of NSCLC. The person would have a reasonable expectation of success in using protein corona sensor array to discriminate NSCLC from a comorbidity thereof because Farokhzad teaches that the array has the ability to determine cancer states and cardiovascular disease (see para. [0285]).
With respect to the nonstatutory double patenting rejections over Patent Nos. 12087405 and 11664092, Applicant argues that the amended claim 1 and the dependent claims are patentably distinct from the cited Patent claims.
The arguments are not found persuasive. In view of the amendments, the rejections have been modified. For the reasons stated above in the nonstatutory double patenting rejections, the rejections are maintained (see above).
Conclusion
No claim is 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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/N.P.N/Examiner, Art Unit 1678
/SHAFIQUL HAQ/Primary Examiner, Art Unit 1678