DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Election/Restrictions
Restriction to one of the following inventions was required under 35 U.S.C. 121:
I. Claims 1-58 and 69-78, drawn to computer-aided diagnosis, classified in G16H 50/20.
II. Claims 59-68, drawn to chromatography systems, classified in G01N 30/72.
In the response received on 12/09/2025 Applicant elected the claims of Group I without traverse.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 04/10/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Claim Rejections - 35 USC § 112(b)
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 70-71 and 77 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 70 recites the limitation “said cartridge” in line 1 of the claim. There is insufficient antecedent basis for this limitation in the claim.
Claim 71 recites the limitation “the cartridge” in line 1 of the claim. There is insufficient antecedent basis for this limitation in the claim.
Claim 77 recites the limitation “said cartridge” in line 2 of the claim. There is insufficient antecedent basis for this limitation in the claim.
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 1-58 and 69-78 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1-58 are drawn to systems and claims 69-78 are drawn to a system, each of which is within the four statutory categories. Claims 1-58 and 69-78 are further directed to an abstract idea on the grounds set out in detail below. As discussed below, the claims do not include additional elements that are sufficient to amount to significantly more than the abstract idea because the additional computer elements, which are recited at a high level of generality, provide conventional computer functions that do not add meaningful limits to practicing the abstract idea (Step 1: YES).
Step 2A:
Prong One:
Claim 1 recites a method for determining a metabolic profile of a subject, comprising:
1) (a) obtaining chromatography data obtained from a biological sample of said subject;
2) (b) processing, using a) a machine-learning (ML) algorithm, a set of input features of said chromatography data to generate output data, wherein said set of input features do not comprise a presence or a quantity of a metabolite of said biological sample; and
3) (c) determining said metabolic profile based at least in part on said output data.
Claim 1 recites, in part, performing the steps of 1) (a) obtaining chromatography data obtained from a biological sample of said subject, 2) (b) processing, using an algorithm, a set of input features of said chromatography data to generate output data, wherein said set of input features do not comprise a presence or a quantity of a metabolite of said biological sample, and 3) (c) determining said metabolic profile based at least in part on said output data. These steps correspond to Certain Methods of Organizing Human Activity, more particularly, managing personal behavior or relationships or interactions between people (including following rules or instructions). For example, the claims describes how one could determine data about a person using data from a person. Independent claim 30 recites similar limitations and is also directed to an abstract idea under the same analysis.
Claim 69 recites a system, comprising:
b) a chromatography system configured to 4) generate chromatography data comprising a set of input features from at least a portion of a biological sample of a subject,
c) one or more computer processors operatively coupled to said chromatography system, wherein said one or more computer processors are individually or collectively programmed to 5) process, using a) a machine-learning (ML) algorithm, said chromatography data to generate output data related to a metabolic profile of said subject.
Claim 69 recites, in part, performing the steps of 4) a chromatography system configured to generate chromatography data comprising a set of input features from at least a portion of a biological sample of a subject, 5) process, using an algorithm, said chromatography data to generate output data related to a metabolic profile of said subject. These steps correspond to Certain Methods of Organizing Human Activity, more particularly, managing personal behavior or relationships or interactions between people (including following rules or instructions). For example, the claims describes how one could determine data about a person using data from a person. Independent claim 30 recites similar limitations and is also directed to an abstract idea under the same analysis.
Depending claims 2-29, 31-58, and 70-78 include all of the limitations of claims 1, 30, and 69, and therefore likewise incorporate the above described abstract idea. Depending claims 2 and 31 add the additional step of “(d) processing said metabolic profile to determine a presence or an absence of a disease state”; claims 11 and 40 add the additional step of “processing said metabolic profile to determine a presence or an absence of use of a compound by said subject”; claims 17 and 46 add the additional step of “repeating (a) - (c) for a plurality of biological samples of a plurality of subjects to generate a plurality of metabolic profiles”; claims 18 and 47 add the additional step of “analyzing said plurality of metabolic profiles to determine a differential feature of said plurality of metabolic profiles”; claims 19 and 48 add the additional step of “prior to (a), performing chromatography on said biological sample to generate said chromatography data”; claims 23 and 52 add the additional step of “subsequent to (a), processing said sample with a mass spectrometer”; claims 24 and 53 add the additional step of “determining said presence or said quantity of said metabolite”; claims 25 and 54 add the additional step of “determining said metabolic profile based further on said presence or said quantity of said metabolite”; claim 75 adds the additional step of “transmit data associated with said at least a portion of said biological sample from said chromatography system to the one or more computer processors”; and claim 77 adds the additional step of “provide a plurality of cartridges comprising said cartridge to said chromatography system”. Additionally, the limitations of depending claims 3-10, 12-16, 20-22, 26-29, 32-39, 41-45, 49-51, 55-58, 70-74, 76, and 78 further specify elements from the claims from which they depend on without adding any additional steps. These additional limitations only further serve to limit the abstract idea. Thus, depending claims 2-29, 31-58, and 70-78 are nonetheless directed towards fundamentally the same abstract idea as independent claims 1, 30, and 69 (Step 2A (Prong One): YES).
Prong Two:
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of – using a) a machine-learning (ML) algorithm, b) a chromatography system, c) one or more computer processors operatively coupled to said chromatography system, wherein said one or more computer processors are individually or collectively programmed, and d) an autosampler configured to provide a plurality of cartridges comprising said cartridge to said chromatography system (from claim 77) to perform the claimed steps.
The a) machine-learning (ML) algorithm and c) one or more computer processors in these steps are recited at a high-level of generality (i.e., as generic components performing generic computer functions) such that it amount to no more than mere instructions to apply the exception using generic computer components (see: Applicant’s specification, for lack of description for something other than what may be considered as generic components for these elements, see MPEP 2106.05(f)).
The b) chromatography system in these steps adds insignificant extra-solution activity to the abstract idea (such as recitation of b) a chromatography system and d) an autosampler amounts to mere data gathering, see MPEP 2106.05(g)).
Dependent claims recite additional subject matter which amount to limitations consistent with the additional elements in the independent claims. Looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation and do not impose a meaningful limit to integrate the abstract idea into a practical application.
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea (Step 2A (Prong Two): NO).
Step 2B:
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of using a) a machine-learning (ML) algorithm, b) a chromatography system, c) one or more computer processors operatively coupled to said chromatography system, wherein said one or more computer processors are individually or collectively programmed, and d) an autosampler configured to provide a plurality of cartridges comprising said cartridge to said chromatography system to perform the claimed steps amounts to no more than insignificant extra-solution activity in the form of WURC activity (well-understood, routine, and conventional activity) and mere instructions to apply the exception using generic computer components that does not offer “significantly more” than the abstract idea itself because the claims do not recite an improvement to another technology or technical field, an improvement to the functioning of any computer itself, or provide meaningful limitations beyond generally linking an abstract idea to a particular technological environment. It should be noted that the claims do not include additional elements that amount to significantly more than the judicial exception because the Specification recites mere generic computer components, as discussed above that are being used to apply certain method steps of organizing human activity. Specifically, MPEP 2106.05(d) and MPEP 2106.05(f) recite that the following limitations are not significantly more:
Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 573 U.S. at 225, 110 USPQ2d at 1984 (see MPEP § 2106.05(d)); and
Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp., 134 S. Ct. at 2360, 110 USPQ2d at 1984 (see MPEP § 2106.05(f)).
The current invention determine a profile utilizing a) a machine-learning (ML) algorithm and c) one or more computer processors, thus these computing components are adding the words “apply it” with mere instructions to implement the abstract idea on a computer.
Additionally, the b) a chromatography system and d) an autosampler in these steps add insignificant extra-solution activity/pre-solution activity in the form of WURC activity to the abstract idea. The following is an example of a court decision demonstrating computer functions as well-understood, routine and conventional activities, e.g. see MPEP 2106.05(d)(II): Receiving or transmitting data over a network, e.g. see Intellectual Ventures v. Symantec – similarly, the current invention receives chromatography data, and transmits the data to system with an algorithm over a network, for example the Internet.
Mere instructions to apply an exception using generic computer components or insignificant extra-solution activity in the form of WURC activity cannot provide an inventive concept. The claims are not patent eligible (Step 2B: NO).
Claims 1-58 and 69-78 are therefore rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-5, 12-17, 19-20, 30-34, 41-46, 48-49, 69, 72-73, and 78 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by U.S. 2019/0214145 to Kurek et al.
As per claim 1, Kurek et al. teaches a method for determining a metabolic profile of a subject, comprising:
--(a) obtaining chromatography data obtained from a biological sample of said subject; (see: paragraph [0042] where there is a metabolite set of information which is being quantified from a biological sample. Data is being obtained from a sample of the subject)
--(b) processing, using a machine-learning (ML) algorithm, a set of input features of said chromatography data to generate output data, (see: paragraphs [0010] and [0061] where there is generation of a scoring metric (output data) using a plurality of records (set of input features) and a machine learning method/algorithm) wherein said set of input features do not comprise a presence or a quantity of a metabolite of said biological sample; (see: paragraphs [0101] – [0106] where the system uses a plurality of records is a metabolite set of information which is being quantified from a biological sample absent the use of cannabis so the presence of the metabolites related to cannabis are not present in the data such that the data may serve as a control) and
--(c) determining said metabolic profile based at least in part on said output data (see: paragraph [0132] where the control data is used to compare against sample data to determine metabolites associated with a depressive state. The scoring metrics (output data) are used here in order to determine a profile).
As per claim 2, Kurek et al. teaches the method of claim 1, see discussion of claim 1. Kurek et al. further teaches (d) processing said metabolic profile to determine a presence or an absence of a disease state (see: paragraph [0148] where there is a method involving calculation of a correlation of a patient metabolite profile data to a disease state metabolite profile and recommend a treatment regime therefrom).
As per claim 3, Kurek et al. teaches the method of claim 2, see discussion of claim 2. Kurek et al. further teaches wherein said processing in (d) further comprises processing a characteristic of said subject (see: paragraph [0062] where the processing overview of the recommendation engine uses demographic characteristics of the patient to identify high efficacy treatments).
As per claim 4, Kurek et al. teaches the method of claim 3, see discussion of claim 3. Kurek et al. further teaches wherein said characteristic is selected from the group consisting of previous tumor, demographics, clinical characteristic, demographic characteristic, and phenotypic characteristic (see: paragraph [0062] where the processing overview of the recommendation engine uses demographic characteristics of the patient to identify high efficacy treatments).
As per claim 5, Kurek et al. teaches the method of claim 2, see discussion of claim 2. Kurek et al. further teaches wherein said disease state is selected from the group consisting of an oncological disease, an infectious disease, a chronic disease, a nutritional deficiency, an environmental disease, an autoimmune disorder, and a genetic disease (see: paragraph [0118] where there is a chronic disease).
As per claim 12, Kurek et al. teaches the method of claim 1, see discussion of claim 1. Kurek et al. further teaches wherein said biological sample is a urine sample (see: paragraph [0052] where there is a urine sample).
As per claim 13, Kurek et al. teaches the method of claim 1, see discussion of claim 1. Kurek et al. further teaches wherein said chromatography data is derived from a gas chromatography system (see: paragraph [0042] where there is gas chromatography).
As per claim 14, Kurek et al. teaches the method of claim 1, see discussion of claim 1. Kurek et al. further teaches wherein said chromatography data is derived from a liquid chromatography system (see: paragraph [0042] where there is liquid chromatography).
As per claim 15, Kurek et al. teaches the method of claim 1, see discussion of claim 1. Kurek et al. further teaches wherein said set of input features do not comprise a presence or a quantity of an analyte of said biological sample (see: Table 1 and paragraph [0101] where the control has no presence of THC or CBD in the sample. There is a subject that is not a cannabis user here).
As per claim 16, Kurek et al. teaches the method of claim 1, see discussion of claim 1. Kurek et al. further teaches wherein said ML algorithm comprises a fuzzy decision network (see: paragraph [0010] where there is a system built using a fuzzy logic algorithm).
As per claim 17, Kurek et al. teaches the method of claim 1, see discussion of claim 1. Kurek et al. further teaches repeating (a) - (c) for a plurality of biological samples of a plurality of subjects to generate a plurality of metabolic profiles (see: Table 1 where these steps are repeated for a plurality of subjects to generate a plurality of profiles).
As per claim 19, Kurek et al. teaches the method of claim 1, see discussion of claim 1. Kurek et al. further teaches prior to (a), performing chromatography on said biological sample to generate said chromatography data (see: paragraph [0042] where in a previous step chromatography is being performed).
As per claim 20, Kurek et al. teaches the method of claim 19, see discussion of claim 19. Kurek et al. further teaches wherein said chromatography does not comprise derivatization of said biological sample (see: Kurek et al. where there is no discussion of derivatization of a sample).
As per claim 30, Kurek et al. teaches a method of determining a multi-omic profile of a subject, comprising:
--(a) obtaining chromatography data obtained from a biological sample of said subject; (see: paragraph [0042] where there is a metabolite set of information which is being quantified from a biological sample. Data is being obtained from a sample of the subject)
--(b) processing, using a machine-learning (ML) algorithm, a set of input features of said chromatography data to generate output data, (see: paragraphs [0010] and [0061] where there is generation of a scoring metric (output data) using a plurality of records (set of input features) and a machine learning method/algorithm) wherein said set of input features do not comprise a presence or a quantity of a metabolite of said biological sample; (see: paragraphs [0101] – [0106] where the system uses a plurality of records is a metabolite set of information which is being quantified from a biological sample absent the use of cannabis so the presence of the metabolites related to cannabis are not present in the data such that the data may serve as a control) and
--(c) determining said multi-omic profile based at least in part on said output data (see: paragraph [0132] where the control data is used to compare against sample data to determine metabolites associated with a depressive state. The scoring metrics (output data) are used here in order to determine a profile).
As per claim 31, Kurek et al. teaches the method of claim 30, see discussion of claim 30. Kurek et al. further teaches (d) processing said metabolic profile to determine a presence or an absence of a disease state (see: paragraph [0148] where there is a method involving calculation of a correlation of a patient metabolite profile data to a disease state metabolite profile and recommend a treatment regime therefrom).
As per claim 32, Kurek et al. teaches the method of claim 31, see discussion of claim 31. Kurek et al. further teaches wherein said processing in (d) further comprises processing a characteristic of said subject (see: paragraph [0062] where the processing overview of the recommendation engine uses demographic characteristics of the patient to identify high efficacy treatments).
As per claim 33, Kurek et al. teaches the method of claim 32, see discussion of claim 32. Kurek et al. further teaches wherein said characteristic is selected from the group consisting of previous tumor, demographics, clinical characteristic, demographic characteristic, and phenotypic characteristic (see: paragraph [0062] where the processing overview of the recommendation engine uses demographic characteristics of the patient to identify high efficacy treatments).
As per claim 34, Kurek et al. teaches the method of claim 31, see discussion of claim 31. Kurek et al. further teaches wherein said disease state is selected from the group consisting of an oncological disease, an infectious disease, a chronic disease, a nutritional deficiency, an environmental disease, an autoimmune disorder, and a genetic disease (see: paragraph [0118] where there is a chronic disease).
As per claim 41, Kurek et al. teaches the method of claim 30, see discussion of claim 30. Kurek et al. further teaches wherein said biological sample is a urine sample (see: paragraph [0052] where there is a urine sample).
As per claim 42, Kurek et al. teaches the method of claim 30, see discussion of claim 30. Kurek et al. further teaches wherein said chromatography data is derived from a gas chromatography system (see: paragraph [0042] where there is gas chromatography).
As per claim 43, Kurek et al. teaches the method of claim 30, see discussion of claim 30. Kurek et al. further teaches wherein said chromatography data is derived from a liquid chromatography system (see: paragraph [0042] where there is liquid chromatography).
As per claim 44, Kurek et al. teaches the method of claim 30, see discussion of claim 30. Kurek et al. further teaches wherein said set of input features do not comprise a presence or a quantity of an analyte of said biological sample (see: Table 1 and paragraph [0101] where the control has no presence of THC or CBD in the sample. There is a subject that is not a cannabis user here).
As per claim 45, Kurek et al. teaches the method of claim 30, see discussion of claim 30. Kurek et al. further teaches wherein said ML algorithm comprises a fuzzy decision network (see: paragraph [0010] where there is a system built using a fuzzy logic algorithm).
As per claim 46, Kurek et al. teaches the method of claim 30, see discussion of claim 30. Kurek et al. further teaches repeating (a) - (c) for a plurality of biological samples of a plurality of subjects to generate a plurality of metabolic profiles (see: Table 1 where these steps are repeated for a plurality of subjects to generate a plurality of profiles).
As per claim 48, Kurek et al. teaches the method of claim 30, see discussion of claim 30. Kurek et al. further teaches prior to (a), performing chromatography on said biological sample to generate said chromatography data (see: paragraph [0042] where in a previous step chromatography is being performed).
As per claim 49, Kurek et al. teaches the method of claim 48, see discussion of claim 48. Kurek et al. further teaches wherein said chromatography does not comprise derivatization of said biological sample (see: Kurek et al. where there is no discussion of derivatization of a sample).
As per claim 69, Kurek et al. teaches a system, comprising:
--a chromatography system configured to generate chromatography data comprising a set of input features from at least a portion of a biological sample of a subject; (see: paragraph [0042] where there is a metabolite set of information which is being quantified from a biological sample)
--one or more computer processors operatively coupled to said chromatography system, (see: paragraphs [0091] and [0096] where there is such a processor) wherein said one or more computer processors are individually or collectively programmed to process, using a machine-learning (ML) algorithm, said chromatography data to generate output data related to a metabolic profile of said subject (see: paragraph [0148] where output is being generated related to a metabolic profile of the subject where a recommended treatment regime from the disease state database is being generated. Also see: paragraph [0154] where machine learning is used for this determination).
As per claim 72, Kurek et al. teaches the system of claim 69, see discussion of claim 69. Kurek et al. further teaches wherein said chromatography system comprises a gas chromatography system (see: paragraph [0042] where there is gas chromatography).
As per claim 73, Kurek et al. teaches the system of claim 69, see discussion of claim 69. Kurek et al. further teaches wherein said chromatography system comprises a liquid chromatography system (see: paragraph [0042] where there is liquid chromatography).
As per claim 78, Kurek et al. teaches the system of claim 69, see discussion of claim 69. Kurek et al. further teaches wherein said chromatography system comprises one or more of a flame ionization detector (FID), thermal conductivity detector (TCD), electron capture detector (ECD), photoionization detector (PID), mass spectrometer (MS), ion mobility spectrometer (IMS), nitrogen-phosphorus detector (NPD), Raman detector, ultraviolet-visible (UV-Vis) detector, photodiode array detector (PDA), fluorescence detector, evaporative light scattering detector (ELSD), refractive index detector (RID), and conductivity detector (see: paragraph [0042] where mass spectrometry is used).
Claim Rejections - 35 USC § 103
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 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
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.
Claims 6-11, 18, 21-29, 35-40, 47, and 50-58 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. 2019/0214145 to Kurek et al. in view of U.S. 2015/0276764 to Slupsky.
As per claim 6, Kurek et al. teaches the method of claim 2, see discussion of claim 2. Kurek et al. may not further, specifically teach wherein said disease state comprises a plurality of disease states, and wherein the method further comprises processing the metabolic profile to determine a presence or absence of each of the plurality of disease states.
Slupsky teaches:
--wherein said disease state comprises a plurality of disease states, and wherein the method further comprises processing the metabolic profile to determine a presence or absence of each of the plurality of disease states (see: paragraph [0062] where the staging involves determining the presence or absence of each of the plurality of disease states).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to have wherein said disease state comprises a plurality of disease states, and wherein the method further comprises processing the metabolic profile to determine a presence or absence of each of the plurality of disease states as taught by Slupsky in the method as taught by Kurek et al. with the motivation(s) of determining the state of disease in a subject (see: paragraph [0023] of Slupsky).
As per claim 7, Kurek et al. and Slupsky in combination teaches the method of claim 6, see discussion of claim 6. Slupsky further teaches wherein said plurality of disease states comprises at least about 5 disease states (see: paragraph [0062] where there are at least 5 disease states).
The motivations to combine the above-mentioned references are discussed in the rejection of claim 6, and incorporated herein.
As per claim 8, Kurek et al. and Slupsky in combination teaches the method of claim 7, see discussion of claim 7. Slupsky further teaches wherein said plurality of disease states comprises at least about 50 disease states (see: paragraph [0062] where there are many disease states. The threshold of 50 states is merely non-functional, descriptive material, and therefore provides little patentable weight).
The motivations to combine the above-mentioned references are discussed in the rejection of claim 6, and incorporated herein.
As per claim 9, Kurek et al. teaches the method of claim 2, see discussion of claim 2. Kurek et al. may not further, specifically teach wherein said presence or said absence of said disease state is determined at an accuracy of at least about 85%.
Slupsky teaches:
--wherein said presence or said absence of said disease state is determined at an accuracy of at least about 85% (see: paragraph [0069] where when used for urinary diagnosis of mycobacterium tuberculosis the method resulted in a 95% specificity).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to have wherein said presence or said absence of said disease state is determined at an accuracy of at least about 85% as taught by Slupsky in the method as taught by Kurek et al. with the motivation(s) of determining the state of disease in a subject (see: paragraph [0023] of Slupsky).
As per claim 10, Kurek et al. teaches the method of claim 2, see discussion of claim 2. Kurek et al. may not further, specifically teach wherein said presence or said absence of said disease state is determined using a single sample from said subject.
Slupsky teaches:
--wherein said presence or said absence of said disease state is determined using a single sample from said subject (see: paragraph [0019] where the biological test sample may be one of blood, blood plasma, blood serum, cerebrospinal fluid, bile acid, saliva, synovial fluid, pleural fluid, pericardial fluid, peritoneal fluid, feces, nasal fluid, ocular fluid, intracellular fluid, intercellular fluid, lymph fluid, and urine).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to have wherein said presence or said absence of said disease state is determined using a single sample from said subject as taught by Slupsky in the method as taught by Kurek et al. with the motivation(s) of determining the state of disease in a subject (see: paragraph [0023] of Slupsky).
As per claim 11, Kurek et al. teaches the method of claim 1, see discussion of claim 1. Kurek et al. may not further, specifically teach processing said metabolic profile to determine a presence or an absence of use of a compound by said subject.
Slupsky teaches:
--processing said metabolic profile to determine a presence or an absence of use of a compound by said subject (see: paragraph [0113] where there is a database of hundreds of metabolite compounds is used to determine the presence or absence of compounds in the subject’s sample).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to process said metabolic profile to determine a presence or an absence of use of a compound by said subject as taught by Slupsky in the method as taught by Kurek et al. with the motivation(s) of determining the state of disease in a subject (see: paragraph [0023] of Slupsky).
As per claim 18, Kurek et al. teaches the method of claim 17, see discussion of claim 17. Kurek et al. may not further, specifically teach analyzing said plurality of metabolic profiles to determine a differential feature of said plurality of metabolic profiles.
Slupsky teaches:
--analyzing said plurality of metabolic profiles to determine a differential feature of said plurality of metabolic profiles (see: paragraph [0037] where differential metabolic profiles pertaining to specific states of a disease based on biomarker identifications are created and the ample metabolic profile is compared to each to determine what state the disease is in).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to analyze said plurality of metabolic profiles to determine a differential feature of said plurality of metabolic profiles as taught by Slupsky in the method as taught by Kurek et al. with the motivation(s) of determining the state of disease in a subject (see: paragraph [0023] of Slupsky).
As per claim 21, Kurek et al. teaches the method of claim 1, see discussion of claim 1. Kurek et al. may not further, specifically teach wherein said biological sample is an unpreserved biological sample.
Slupsky teaches:
--wherein said biological sample is an unpreserved biological sample (see: paragraph [0080] where the biological sample is processed using a point-of-care device thereby indicating the sample has just been received from the subject and is not preserved and is raw).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to have wherein said biological sample is an unpreserved biological sample as taught by Slupsky in the method as taught by Kurek et al. with the motivation(s) of determining the state of disease in a subject (see: paragraph [0023] of Slupsky).
As per claim 22, Kurek et al. and Slupsky in combination teaches the method of claim 21, see discussion of claim 21. Slupsky further teaches wherein said unpreserved biological sample is a raw biological sample (see: paragraph [0080] where the biological sample is processed using a point-of-care device thereby indicating the sample has just been received from the subject and is not preserved and is raw).
The motivations to combine the above-mentioned references are discussed in the rejection of claim 21, and incorporated herein.
As per claim 23, Kurek et al. teaches the method of claim 1, see discussion of claim 1. Kurek et al. may not further, specifically teach subsequent to (a), processing said sample with a mass spectrometer.
Slupsky teaches:
--subsequent to (a), processing said sample with a mass spectrometer (see: paragraph [0022] where the respective concentration of each of the identified metabolites is determined using a spectrometric technique wherein the spectrometric technique is mass spectrometry).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to subsequent to (a), process said sample with a mass spectrometer as taught by Slupsky in the method as taught by Kurek et al. with the motivation(s) of determining the state of disease in a subject (see: paragraph [0023] of Slupsky).
As per claim 24, Kurek et al. teaches the method of claim 1, see discussion of claim 1. Kurek et al. may not further, specifically teach determining said presence or said quantity of said metabolite.
Slupsky teaches:
--determining said presence or said quantity of said metabolite (see: paragraphs [0024] – [0025] where the metabolite profile indicative of the disease state is made up of the respective concentrations of individual metabolite biomarkers in the sample).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to determine said presence or said quantity of said metabolite as taught by Slupsky in the method as taught by Kurek et al. with the motivation(s) of determining the state of disease in a subject (see: paragraph [0023] of Slupsky).
As per claim 25, Kurek et al. and Slupsky in combination teaches the method of claim 24, see discussion of claim 24. Kurek et al. may not further, specifically teach determining said metabolic profile based further on said presence or said quantity of said metabolite.
Slupsky teaches:
--determining said metabolic profile based further on said presence or said quantity of said metabolite (see: paragraphs [0024] – [0025] where the metabolite profile indicative of the disease state is made up of the respective concentrations of individual metabolite biomarkers in the sample).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to determine said metabolic profile based further on said presence or said quantity of said metabolite as taught by Slupsky in the method as taught by Kurek et al. with the motivation(s) of determining the state of disease in a subject (see: paragraph [0023] of Slupsky).
As per claim 26, Kurek et al. teaches the method of claim 1, see discussion of claim 1. Kurek et al. may not further, specifically teach wherein said output data comprises said presence or said quantity of said metabolite.
Slupsky teaches:
--wherein said output data comprises said presence or said quantity of said metabolite (see: paragraph [0022] where the respective concentration of each of the identified metabolites is determined using a spectrometric technique wherein the spectrometric technique is chromatography).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to have wherein said output data comprises said presence or said quantity of said metabolite as taught by Slupsky in the method as taught by Kurek et al. with the motivation(s) of determining the state of disease in a subject (see: paragraph [0023] of Slupsky).
As per claim 27, Kurek et al. teaches the method of claim 1, see discussion of claim 1. Kurek et al. may not further, specifically teach wherein said chromatography data comprises a first gas chromatography data and a second liquid chromatography data.
Slupsky teaches:
--wherein said chromatography data comprises a first gas chromatography data and a second liquid chromatography data (see: paragraph [0009] where the method uses input features from samples of serum, plasma, and urine. Also see: paragraph [0022] which may be analyzed using a number of methods including liquid chromatography or gas chromatography).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to have wherein said chromatography data comprises a first gas chromatography data and a second liquid chromatography data as taught by Slupsky in the method as taught by Kurek et al. with the motivation(s) of determining the state of disease in a subject (see: paragraph [0023] of Slupsky).
As per claim 28, Kurek et al. teaches the method of claim 1, see discussion of claim 1. Kurek et al. may not further, specifically teach wherein said set of input features further comprises additional data.
Slupsky teaches:
--wherein said set of input features further comprises additional data (see: paragraph [0009] where the method uses input features from samples of serum, plasma, and urine. Also see: paragraph [0022] which may be analyzed using a number of methods including liquid chromatography or gas chromatography).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to have wherein said set of input features further comprises additional data as taught by Slupsky in the method as taught by Kurek et al. with the motivation(s) of determining the state of disease in a subject (see: paragraph [0023] of Slupsky).
As per claim 29, Kurek et al. and Slupsky in combination teaches the method of claim 28, see discussion of claim 28. Slupsky further teaches wherein said additional data comprises additional data selected from the group consisting of additional chromatography data and additional optical data (see: paragraph [0009] where the method uses input features from samples of serum, plasma, and urine. Also see: paragraph [0022] which may be analyzed using a number of methods including liquid chromatography or gas chromatography).
The motivations to combine the above-mentioned references are discussed in the rejection of claim 28, and incorporated herein.
As per claim 35, Kurek et al. teaches the method of claim 31, see discussion of claim 31. Kurek et al. may not further, specifically teach herein said disease state comprises a plurality of disease states, and wherein the method further comprises processing the metabolic profile to determine a presence or absence of each of the plurality of disease states.
Slupsky teaches:
--wherein said disease state comprises a plurality of disease states, and wherein the method further comprises processing the metabolic profile to determine a presence or absence of each of the plurality of disease states (see: paragraph [0062] where the staging involves determining the presence or absence of each of the plurality of disease states).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to have wherein said disease state comprises a plurality of disease states, and wherein the method further comprises processing the metabolic profile to determine a presence or absence of each of the plurality of disease states as taught by Slupsky in the method as taught by Kurek et al. with the motivation(s) of determining the state of disease in a subject (see: paragraph [0023] of Slupsky).
As per claim 36, Kurek et al. and Slupsky in combination teaches the method of claim 35, see discussion of claim 35. Slupsky further teaches wherein said plurality of disease states comprises at least about 5 disease states (see: paragraph [0062] where there are at least 5 disease states).
The motivations to combine the above-mentioned references are discussed in the rejection of claim 35, and incorporated herein.
As per claim 37, Kurek et al. and Slupsky in combination teaches the method of claim 36, see discussion of claim 36. Slupsky further teaches wherein said plurality of disease states comprises at least about 50 disease states (see: paragraph [0062] where there are many disease states. The threshold of 50 states is merely non-functional, descriptive material, and therefore provides little patentable weight).
The motivations to combine the above-mentioned references are discussed in the rejection of claim 35, and incorporated herein.
As per claim 38, Kurek et al. teaches the method of claim 31, see discussion of claim 31. Kurek et al. may not further, specifically teach wherein said presence or said absence of said disease state is determined at an accuracy of at least about 85%.
Slupsky teaches:
--wherein said presence or said absence of said disease state is determined at an accuracy of at least about 85% (see: paragraph [0069] where when used for urinary diagnosis of mycobacterium tuberculosis the method resulted in a 95% specificity).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to have wherein said presence or said absence of said disease state is determined at an accuracy of at least about 85% as taught by Slupsky in the method as taught by Kurek et al. with the motivation(s) of determining the state of disease in a subject (see: paragraph [0023] of Slupsky).
As per claim 39, Kurek et al. teaches the method of claim 31, see discussion of claim 31. Kurek et al. may not further, specifically teach wherein said presence or said absence of said disease state is determined using a single sample from said subject.
Slupsky teaches:
--wherein said presence or said absence of said disease state is determined using a single sample from said subject (see: paragraph [0019] where the biological test sample may be one of blood, blood plasma, blood serum, cerebrospinal fluid, bile acid, saliva, synovial fluid, pleural fluid, pericardial fluid, peritoneal fluid, feces, nasal fluid, ocular fluid, intracellular fluid, intercellular fluid, lymph fluid, and urine).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to have wherein said presence or said absence of said disease state is determined using a single sample from said subject as taught by Slupsky in the method as taught by Kurek et al. with the motivation(s) of determining the state of disease in a subject (see: paragraph [0023] of Slupsky).
As per claim 40, Kurek et al. teaches the method of claim 30, see discussion of claim 30. Kurek et al. may not further, specifically teach processing said metabolic profile to determine a presence or an absence of use of a compound by said subject.
Slupsky teaches:
--processing said metabolic profile to determine a presence or an absence of use of a compound by said subject (see: paragraph [0113] where there is a database of hundreds of metabolite compounds is used to determine the presence or absence of compounds in the subject’s sample).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to process said metabolic profile to determine a presence or an absence of use of a compound by said subject as taught by Slupsky in the method as taught by Kurek et al. with the motivation(s) of determining the state of disease in a subject (see: paragraph [0023] of Slupsky).
As per claim 47, Kurek et al. teaches the method of claim 46, see discussion of claim 46. Kurek et al. may not further, specifically teach analyzing said plurality of metabolic profiles to determine a differential feature of said plurality of metabolic profiles.
Slupsky teaches:
--analyzing said plurality of metabolic profiles to determine a differential feature of said plurality of metabolic profiles (see: paragraph [0037] where differential metabolic profiles pertaining to specific states of a disease based on biomarker identifications are created and the ample metabolic profile is compared to each to determine what state the disease is in).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to analyze said plurality of metabolic profiles to determine a differential feature of said plurality of metabolic profiles as taught by Slupsky in the method as taught by Kurek et al. with the motivation(s) of determining the state of disease in a subject (see: paragraph [0023] of Slupsky).
As per claim 50, Kurek et al. teaches the method of claim 30, see discussion of claim 30. Kurek et al. may not further, specifically teach wherein said biological sample is an unpreserved biological sample.
Slupsky teaches:
--wherein said biological sample is an unpreserved biological sample (see: paragraph [0080] where the biological sample is processed using a point-of-care device thereby indicating the sample has just been received from the subject and is not preserved and is raw).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to have wherein said biological sample is an unpreserved biological sample as taught by Slupsky in the method as taught by Kurek et al. with the motivation(s) of determining the state of disease in a subject (see: paragraph [0023] of Slupsky).
As per claim 51, Kurek et al. and Slupsky in combination teaches the method of claim 50, see discussion of claim 50. Slupsky further teaches wherein said unpreserved biological sample is a raw biological sample (see: paragraph [0080] where the biological sample is processed using a point-of-care device thereby indicating the sample has just been received from the subject and is not preserved and is raw).
The motivations to combine the above-mentioned references are discussed in the rejection of claim 50, and incorporated herein.
As per claim 52, Kurek et al. teaches the method of claim 30, see discussion of claim 30. Kurek et al. may not further, specifically teach teaches subsequent to (a), processing said sample with a mass spectrometer.
Slupsky teaches:
--subsequent to (a), processing said sample with a mass spectrometer (see: paragraph [0022] where the respective concentration of each of the identified metabolites is determined using a spectrometric technique wherein the spectrometric technique is mass spectrometry).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to subsequent to (a), process said sample with a mass spectrometer as taught by Slupsky in the method as taught by Kurek et al. with the motivation(s) of determining the state of disease in a subject (see: paragraph [0023] of Slupsky).
As per claim 53, Kurek et al. teaches the method of claim 30, see discussion of claim 30. Kurek et al. may not further, specifically teach determining said presence or said quantity of said metabolite.
Slupsky teaches:
--determining said presence or said quantity of said metabolite (see: paragraphs [0024] – [0025] where the metabolite profile indicative of the disease state is made up of the respective concentrations of individual metabolite biomarkers in the sample).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to determine said presence or said quantity of said metabolite as taught by Slupsky in the method as taught by Kurek et al. with the motivation(s) of determining the state of disease in a subject (see: paragraph [0023] of Slupsky).
As per claim 54, Kurek et al. teaches the method of claim 53, see discussion of claim 53. Kurek et al. may not further, specifically teach determining said metabolic profile based further on said presence or said quantity of said metabolite.
Slupsky teaches:
--determining said metabolic profile based further on said presence or said quantity of said metabolite (see: paragraphs [0024] – [0025] where the metabolite profile indicative of the disease state is made up of the respective concentrations of individual metabolite biomarkers in the sample).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to determine said metabolic profile based further on said presence or said quantity of said metabolite as taught by Slupsky in the method as taught by Kurek et al. with the motivation(s) of determining the state of disease in a subject (see: paragraph [0023] of Slupsky).
As per claim 55, Kurek et al. teaches the method of claim 1, see discussion of claim 1. Kurek et al. may not further, specifically teach wherein said output data comprises said presence or said quantity of said metabolite.
Slupsky teaches:
--wherein said output data comprises said presence or said quantity of said metabolite (see: paragraph [0022] where the respective concentration of each of the identified metabolites is determined using a spectrometric technique wherein the spectrometric technique is chromatography).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to have wherein said output data comprises said presence or said quantity of said metabolite as taught by Slupsky in the method as taught by Kurek et al. with the motivation(s) of determining the state of disease in a subject (see: paragraph [0023] of Slupsky).
As per claim 56, Kurek et al. teaches the method of claim 30, see discussion of claim 30. Kurek et al. may not further, specifically teach wherein said chromatography data comprises a first gas chromatography data and a second liquid chromatography data.
Slupsky teaches:
--wherein said chromatography data comprises a first gas chromatography data and a second liquid chromatography data (see: paragraph [0009] where the method uses input features from samples of serum, plasma, and urine. Also see: paragraph [0022] which may be analyzed using a number of methods including liquid chromatography or gas chromatography).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to have wherein said chromatography data comprises a first gas chromatography data and a second liquid chromatography data as taught by Slupsky in the method as taught by Kurek et al. with the motivation(s) of determining the state of disease in a subject (see: paragraph [0023] of Slupsky).
As per claim 57, Kurek et al. teaches the method of claim 30, see discussion of claim 30. Kurek et al. may not further, specifically teach wherein said set of input features further comprises additional data.
Slupsky teaches:
--wherein said set of input features further comprises additional data (see: paragraph [0009] where the method uses input features from samples of serum, plasma, and urine. Also see: paragraph [0022] which may be analyzed using a number of methods including liquid chromatography or gas chromatography).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to have wherein said set of input features further comprises additional data as taught by Slupsky in the method as taught by Kurek et al. with the motivation(s) of determining the state of disease in a subject (see: paragraph [0023] of Slupsky).
As per claim 58, Kurek et al. and Slupsky in combination teaches the method of claim 57, see discussion of claim 57. Slupsky further teaches wherein said additional data comprises additional data selected from the group consisting of additional chromatography data and additional optical data (see: paragraph [0009] where the method uses input features from samples of serum, plasma, and urine. Also see: paragraph [0022] which may be analyzed using a number of methods including liquid chromatography or gas chromatography).
The motivations to combine the above-mentioned references are discussed in the rejection of claim 57, and incorporated herein.
Claims 70-71 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. 2019/0214145 to Kurek et al. in view of U.S. 2018/0217068 to Tabb et al.
As per claim 70, Kurek et al. teaches the system of claim 69, see discussion of claim 69. Kurek et al. may not further, specifically teach wherein said cartridge comprises a test strip.
Tabb et al. teaches:
--wherein said cartridge comprises a test strip (see: paragraph [0107] where there is a test strip).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to have wherein said cartridge comprises a test strip as taught by Tabb et al. in the system as taught by Kurek et al. with the motivation(s) of being a type of collection device (see: paragraph [0107] of Tabb et al.).
Furthermore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to substitute wherein said cartridge comprises a test strip as taught by Tabb et al. for the collection device as disclosed by Kurek et al. since each individual element and its function are shown in the prior art, with the difference being the substitution of the elements. In the present case, Kurek et al. already teaches of a collection device thus swapping this device for another collection device would produce predictable results of using a collection device in order to make a determination. Thus, one of ordinary skill in the art could have substituted the one known element for the other to produce a predictable result (MPEP 2143).
As per claim 71, Kurek et al. teaches the system of claim 69, see discussion of claim 69. Kurek et al. may not further, specifically teach wherein the cartridge comprises a collection cup.
Tabb et al. teaches:
--wherein the cartridge comprises a collection cup (see: paragraph [0107] where there is a test strip).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to have wherein the cartridge comprises a collection cup as taught by Tabb et al. in the system as taught by Kurek et al. with the motivation(s) of being a type of collection device (see: paragraph [0107] of Tabb et al.).
Furthermore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to substitute wherein the cartridge comprises a collection cup as taught by Tabb et al. for the collection device as disclosed by Kurek et al. since each individual element and its function are shown in the prior art, with the difference being the substitution of the elements. In the present case, Kurek et al. already teaches of a collection device thus swapping this device for another collection device would produce predictable results of using a collection device in order to make a determination. Thus, one of ordinary skill in the art could have substituted the one known element for the other to produce a predictable result (MPEP 2143).
Claims 74-76 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. 2019/0214145 to Kurek et al. in view of U.S. 2015/0137992 to Potyrailo et al.
As per claim 74, Kurek et al. teaches the system of claim 69, see discussion of claim 69. Kurek et al. may not further, specifically teach wherein said chromatography system is a single use chromatography system.
Potyrailo et al. teaches:
--wherein said chromatography system is a single use chromatography system (see: paragraph [0032] where there are such single-use systems).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to substitute wherein said chromatography system is a single use chromatography system as taught by Potyrailo et al. for the system as disclosed by Kurek et al. since each individual element and its function are shown in the prior art, with the difference being the substitution of the elements. In the present case, Kurek et al. already teaches of using a system to measure data thus one could switch with a single-use system and obtain predictable results of using a system to perform measurements. Thus, one of ordinary skill in the art could have substituted the one known element for the other to produce a predictable result (MPEP 2143).
As per claim 75, Kurek et al. teaches the system of claim 69, see discussion of claim 69. Kurek et al. may not further, specifically teach a data connection configured to transmit data associated with said at least a portion of said biological sample from said chromatography system to the one or more computer processors.
Potyrailo et al. teaches:
--a data connection configured to transmit data associated with said at least a portion of said biological sample from said chromatography system to the one or more computer processors (see: paragraphs [0025] and [0051] where there is transmission of data between devices, from a system to a computer).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to use a data connection configured to transmit data associated with said at least a portion of said biological sample from said chromatography system to the one or more computer processors as taught by Potyrailo et al. in the system as taught by Kurek et al. with the motivation(s) of helping facilitate real-time control over a system (see: paragraph [0033] of Potyrailo et al.).
As per claim 76, Kurek et al. and Potyrailo et al. in combination teaches the system of claim 75, see discussion of claim 75. Kurek et al. may not further, specifically teach wherein said data connection comprises a wireless data connection.
Potyrailo et al. teaches wherein said data connection comprises a wireless data connection (see: paragraph [0027] where there is data transmission via a wireless communication path).
The motivations to combine the above-mentioned references are discussed in the rejection of claim 75, and incorporated herein.
Claim 77 is rejected under 35 U.S.C. 103 as being unpatentable over U.S. 2019/0214145 to Kurek et al. in view of U.S. 2019/0049353 to Henion et al.
As per claim 77, Kurek et al. teaches the system of claim 69, see discussion of claim 69. Kurek et al. may not further, specifically teach an autosampler configured to provide a plurality of cartridges comprising said cartridge to said chromatography system.
Henion et al. teaches:
--an autosampler configured to provide a plurality of cartridges comprising said cartridge to said chromatography system (see: paragraph [0166] where there is such an autosampler).
One of ordinary skill before the effective filing date of the claimed invention would have found it obvious to use an autosampler configured to provide a plurality of cartridges comprising said cartridge to said chromatography system as taught by Henion et al. in the system as taught by Kurek et al. with the motivation(s) of improving robustness of the device (see: paragraph [0130] of Henion et al.).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Steven G.S. Sanghera whose telephone number is (571)272-6873. The examiner can normally be reached M-F 7:30-5:00 (alternating Fri).
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/STEVEN G.S. SANGHERA/Primary Examiner, Art Unit 3684