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
Applicant’s election without traverse of Species Group 1, claim 3, drawn to computing distance values based on probability binning, and of Sub-species Group 1A, claim 4, drawn to probability binning based on a chi-squared statistic, are acknowledged in the reply filed on 8/13/2026.
Claims 5-6, 13, and 16-22 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to nonelected species, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on 8/13/2026.
Claim Status
Claims 8-12, 14-15, 23, 26, 29-31, and 33-92 are cancelled.
Claims 1-7, 13, 16-22, 24-25, 27-28, and 32 are pending.
Claims 1-4, 7, 24-25, 27-28, and 32 are examined on the merits.
Claims 5-6, 13, and 16-22 are withdrawn.
Priority
The instant application is a 371 of PCT/US2021/048403 filed on 8/31/2021, which claims priority to U.S. Provisional Application 63/074,953 filed on 9/4/2020. At this point in examination, the effective filing date of claims 1-4, 7, 24-25, 27-28, and 32 is 9/4/2020.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 2/27/2023 and 2/28/2023 are in compliance with the provisions of 37 CFR 1.97. A signed copy of the corresponding 1449 form has been included with this Office Action.
Drawings
The drawings filed on 2/27/2023 are accepted.
Specification
There is a hyperlink in pg. 57, line 24 of the instant specification. The disclosure is objected to because it contains an embedded hyperlink and/or other form of browser-executable code. Applicant is required to delete the embedded hyperlink and/or other form of browser-executable code; references to websites should be limited to the top-level domain name without any prefix such as http:// or other browser-executable code. See MPEP § 608.01.
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 1-4, 7, 24-25, 27-28, and 32 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite: (a) mathematical concepts, (e.g., mathematical relationships, formulas or equations, mathematical calculations); and (b) mental processes, i.e., concepts performed in the human mind, (e.g., observation, evaluation, judgement, opinion).
Subject matter eligibility evaluation in accordance with MPEP 2106:
Eligibility Step 1: Claims 1-4, 7, 24-25, 27-28, and 32 are directed to a method (process). Therefore, these claims are encompassed by the categories of statutory subject matter and thus satisfy the subject matter eligibility requirements under Step 1.
[Step 1: YES]
Eligibility Step 2A: First, it is determined in Prong One whether a claim recites a judicial exception, and if so, then it is determined in Prong Two whether the recited judicial exception is integrated into a practical application of that exception.
Eligibility Step 2A, Prong One: In determining whether a claim is directed to a judicial exception, examination is performed that analyzes whether the claim recites a judicial exception, i.e., whether a law of nature, natural phenomenon, or abstract idea is set forth described in the claim.
Claims 1-4, 7, and 24 recite the following steps which fall within the mental processes and/or mathematical concepts groups of abstract ideas, as noted below.
Independent claim 1 further recites:
computing distance values that reflect a measure of variation between one or more pairs of samples (i.e., mental processes, mathematical concepts);
assigning a minimum inhibitory concentration based on the computed distance values (i.e., mental processes).
Dependent claim 2 further recites:
wherein assigning a minimum inhibitory concentration based on the computed distance values comprises: fitting a curve to a plot of the distance values of the plurality of samples versus corresponding antibiotic concentrations of the plurality of samples; and (i.e., mental processes, mathematical concepts);
assigning a minimum inhibitory concentration based on the fitted curve (i.e., mental processes).
Dependent claim 3 further recites:
wherein the computed distance values are based on probability binning (i.e., mental processes, mathematical concepts; this is further information limiting the judicial exceptions).
Dependent claim 4 further recites:
wherein the probability binning is based on a chi-squared statistic (i.e., mental processes, mathematical concepts; this is further information limiting the judicial exceptions).
Dependent claim 7 further recites:
wherein the curve fitted to the plot of the distance values of the plurality of samples versus corresponding antibiotic concentrations of the plurality of samples is a logistic curve (i.e., mental processes, mathematical concepts; this is further information limiting the judicial exceptions).
Dependent claim 24 further recites:
wherein a susceptibility or resistance of the antibiotic for the bacterial species is determined based on the minimum inhibitory concentration (i.e., mental processes; this is further information limiting the judicial exceptions).
The abstract ideas recited in the claims are evaluated under the broadest reasonable interpretation (BRI) of the claim limitations when read in light of and consistent with the specification. As the claims are currently recited, the method could be performed by drawing out the curve to a plot of distance values between pairs of samples with pen and paper, and determining a minimum inhibitory concentration based on the drawn curve. Drawing out the plot and curve and making decisions using them can be practically performed in the human mind. Additionally, the recited limitations that are identified as judicial exceptions from the mathematical concepts grouping of abstract ideas are abstract ideas irrespective of whether or not the limitations are practical to perform in the human mind. The claims recite computing distance values based on probability binning, which is read as a mathematical measurement of values and therefore a mathematical concept.
Therefore, claims 1-4, 7, and 24 recite an abstract idea.
[Step 2A, Prong One: YES]
Eligibility Step 2A, Prong Two: In determining whether a claim is directed to a judicial exception, further examination is performed that analyzes if the claim recites additional elements that, when examined as a whole, integrates the judicial exception(s) into a practical application (MPEP 2106.04(d)). A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. The claimed additional elements are analyzed to determine if the abstract idea is integrated into a practical application (MPEP 2106.04(d)(I); MPEP 2106.05(a-h)). If the claim contains no additional elements beyond the abstract idea, the claim fails to integrate the abstract idea into a practical application (MPEP 2106.04(d)(III)).
The judicial exceptions identified in Eligibility Step 2A, Prong One are not integrated into a practical application because of the reasons noted below.
Claim 25 recites preparing the plurality of test samples and the control sample. Data gathering steps are extra-solution activity as they collect the data needed to carry out the JE. It does not impose any meaningful limitation on the JE or how the JE is performed (MPEP 2106.04/.05, citing Intellectual Ventures LLC v. Symantee Corp, McRO, TLI communications, OIP Techs. Inc. v. Amason.com Inc., Electric Power Group LLC v. Alstrom S.A.). Therefore, the claimed additional elements do not integrate the abstract ideas into a practical application.
Claim 32 recites wherein obtaining cytometric data from the plurality of test samples and the control sample comprises flow cytometrically analyzing the plurality of test samples and control sample. Data gathering steps are extra-solution activity as they collect the data needed to carry out the JE. It does not impose any meaningful limitation on the JE or how the JE is performed (MPEP 2106.04/.05, citing Intellectual Ventures LLC v. Symantee Corp, McRO, TLI communications, OIP Techs. Inc. v. Amason.com Inc., Electric Power Group LLC v. Alstrom S.A.). Therefore, the claimed additional elements do not integrate the abstract ideas into a practical application.
Claims 1 and 27-28 recite the additional non-abstract elements of data gathering:
obtaining cytometric data for a plurality of test samples and a control sample for the antibiotic and bacterial species (claim 1);
wherein the cytometric data is multi-parametric cytometry data (claim 27; this is further information limiting the data gathered);
wherein the cytometric data comprises light scatter or marker data or a combination thereof (claim 28; this is further information limiting the data gathered).
Data gathering steps are not an abstract idea, they are extra-solution activity, as they collect the data needed to carry out the JE. The data gathering does not impose any meaningful limitation on the JE, or how the JE is performed. The additional limitation (data gathering) must have more than a nominal or insignificant relationship to the identified judicial exception. (MPEP 2106.04/.05, citing Intellectual Ventures LLC v. Symantee Corp, McRO, TLI communications, OIP Techs. Inc. v. Amason.com Inc., Electric Power Group LLC v. Alstrom S.A.).
Thus, the additionally recited elements merely invoke a computer as a tool, and/or amount to insignificant extra-solution data gathering activity, and as such, when all limitations in claims 1-4, 7, 24-25, 27-28, and 32 have been considered as a whole, the claims are deemed to not recite any additional elements that would integrate a judicial exception into a practical application. Claims 1, 25, 27-28, and 32 contain additional elements that would not integrate a judicial exception into a practical application and are further probed for inventive concept in Step 2B.
[Step 2A, Prong Two: NO]
Eligibility Step 2B: Because the claims recite an abstract idea, and do not integrate that abstract idea into a practical application, the claims are probed for a specific inventive concept. The judicial exception alone cannot provide that inventive concept or practical application (MPEP 2106.05). Identifying whether the additional elements beyond the abstract idea amount to such an inventive concept requires considering the additional elements individually and in combination to determine if they amount to significantly more than the judicial exception (MPEP 2106.05A i-vi).
The claims do not include any additional elements that are sufficient to amount to significantly more than the judicial exception(s) because of the reasons noted below.
The additional element of obtaining cytometric data (claim 1), wherein the cytometric data is multi-parametric cytometry data (claim 27), and wherein the cytometric data comprises light scatter or marker data or a combination thereof (claim 28) is conventional. Evidence for conventionality is shown by Givan (Flow Cytometry Protocols, 2010, 3, 1-29). Givan reviews a flow cytometric data file comprising of a list of cells and their respective numbers from forward scatter, side scatter, green fluorescence, orange fluorescence, and red fluorescence photodetectors (pg. 17, Fig. 9). This shows obtaining multi-parametric cytometry data comprising light scatter data.
The additional element of preparing the plurality of test samples and the control sample (claim 25) is conventional. Evidence for conventionality is shown by Mason et al. (Current Protocols in Cytometry, 2001, 8(1), 11.8.1-11.8.9). Mason et al. reviews steps for preparing positive controls for
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uptake and performing
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antibiotic susceptibility test, both of which include incubating broth cultures of test bacterial strains and aseptically diving the cultures to prepare controls and test samples (pg. 11.8.2). This shows preparing test samples and control samples for flow cytometry, which makes it a conventional practice in the art.
The additional element of wherein obtaining cytometric data from the plurality of test samples and the control sample comprises flow cytometrically analyzing the plurality of test samples and control sample (claim 32) is conventional. Evidence for conventionality is shown by Mason et al. (Current Protocols in Cytometry, 2001, 8(1), 11.8.1-11.8.9). Mason et al. reviews flow cytometrically analyzing positive control samples and test samples in steps 7-8 and 14 (pg. 11.8.2). This shows analyzing flow cytometrically collected data of test samples and control samples, which makes it a conventional practice in the art.
[Step 2B: NO]
Therefore, claims 1-4, 7, 24-25, 27-28, and 32 are patent ineligible under 35 U.S.C. § 101.
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 (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 24-25, 27-28, and 32 are rejected under 35 U.S.C. 103 as being unpatentable over Huang et al. (Analytical Chemistry, 2015, 87, 1941-1949), as provided in the IDS filed 2/28/2023, in view of Broeren et al. (Clinical Microbiology and Infection, 2012, 19, 286-291).
With respect to claim 1:
Regarding the recited obtaining cytometric data for a plurality of test samples and a control sample for the antibiotic and bacterial species, Huang et al. discloses monitoring fluorescence and scatter signals by flow cytometry of bacterial strains previously incubated or prepared with 900 nM MH-IR786 and antibiotics at their respective 1x, 1/4x, and 1/16x MIC concentrations (pg. 1944, col. 2, para. 2-3, lines 1-19; pg. 1945, Figure 1). All experiments were performed in triplicate and compared to appropriate paired no-antibiotic controls. This teaches obtaining cytometric data of test samples and control samples for bacterial species and their respective antibiotics.
Regarding the recited computing distance values that reflect a measure of variation between one or more pairs of samples, Huang et al. discloses characterizing 3-dimensional differences between the flow cytometric data of the no-antibiotic treated bacteria and the antibiotic-treated bacteria by probability binning signature quadratic form (PB-sQF) into a 1-dimensional linear distance (pg. 1941, Abstract, lines 15-16; pg. 1945, col. 2, para. 1, lines 5-11). This teaches computing 1-dimensional distance values that reflect differences between pairs of samples.
Huang et al. does not disclose assigning a minimum inhibitory concentration based on the computed distance values.
However, Broeren et al. discloses a comparison of minimum inhibitory concentrations found by different antimicrobial susceptibility testing methods (pg. 288-289, col. 2, para. 1; pg. 288-289, Fig. 1-3; pg. 289, Table 1). Each strain depicts the lowest antibiotic concentration showing respective percentage reduction in cell count as compared with the positive control after incubation. This teaches predicting minimum inhibitory concentrations based on difference between the test samples and control samples.
With respect to claim 24:
Regarding the recited wherein a susceptibility or resistance of the antibiotic for the bacterial species is determined based on the minimum inhibitory concentration, Huang et al. discloses examining a multidrug resistant, clinically isolated E. coli, Mu14S, which was susceptible to gentamicin but was highly resistant to all other tested antibiotics according to the minimum inhibitory concentrations recorded for each antibiotic/bacteria combination in Table 1 (pg. 1944, Table 1; pg. 1946, col. 1, para. 1, lines 1-5). This teaches determining the susceptibility or resistance of the antibiotic for a bacterial species based on minimum inhibitory concentrations.
With respect to claim 25:
Regarding the recited preparing the plurality of test samples and the control sample, Huang et al. discloses incubating bacterial strains with 900 nM MH-IR786 and antibiotics at their respective 1x, 1/4x, and 1/16x MIC concentrations (pg. 1944, col. 2, para. 2; pg. 1944, col. 2, para. 3, lines 5-7 and 12-15). After incubation, bacteria were pelleted, washed 3 times, and resuspended in PBS for cytometry analyses. All experiments were performed in triplicate and compared to appropriate paired no-antibiotic controls. This teaches preparing test samples and control samples.
With respect to claim 27:
Regarding the recited wherein the cytometric data is multi-parametric cytometry data, Huang et al. discloses monitoring fluorescence and scatter signals by flow cytometry, collecting IR786 fluorescence, forward-scattered and side-scattered light for each of 100,000 measured bacterial cells per run and yielding 3-D histograms for each antibiotic concentration (pg. 1944, col. 2, para. 3, lines 1-7; pg. 1946, col. 1, para. 1, lines 1-13; pg. 1946, Fig. 2). This teaches multi-parametric cytometry data.
With respect to claim 28:
Regarding the recited wherein the cytometric data comprises light scatter or marker data or a combination thereof, Huang et al. discloses monitoring fluorescence and scatter signals by flow cytometry, collecting IR786 fluorescence, forward-scattered and side-scattered light for each of 100,000 measured bacterial cells per run and yielding 3-D histograms for each antibiotic concentration (pg. 1944, col. 2, para. 3, lines 1-7; pg. 1946, col. 1, para. 1, lines 1-13; pg. 1946, Fig. 2). This teaches cytometric data comprising light scatter signals.
With respect to claim 32:
Regarding the recited wherein obtaining cytometric data from the plurality of test samples and the control sample comprises flow cytometrically analyzing the plurality of test samples and control sample, Huang et al. discloses monitoring fluorescence and scatter signals by flow cytometry of bacterial strains previously incubated or prepared with 900 nM MH-IR786 and antibiotics at their respective 1x, 1/4x, and 1/16x MIC concentrations (pg. 1944, col. 2, para. 2-3, lines 1-19; pg. 1945, Figure 1). All experiments were performed in triplicate and compared to appropriate paired no-antibiotic controls. This teaches analyzing test samples and control samples by flow cytometry.
It would have been prima facie obvious to one of ordinary skill in the art to modify the antibiotic susceptibility testing method disclosed by Huang et al. to incorporate determining minimum inhibitory concentrations based on variation between samples disclosed by Broeren et al. One would be motivated to incorporate determining minimum inhibitory concentrations because Broeren et al. discloses that bacterial cell count monitoring can be used as a very fast procedure to reliably predict antimicrobial susceptibility (pg. 290, col. 2, para. 1, lines 19-21). Therefore, incorporating minimum inhibitory concentrations based on cell count variation between samples will improve predicting speed of antibiotic susceptibility. There is a likelihood of success, since both methods are of flow cytometry analyses of bacteria, which is well known in the field of microbiology.
Claims 2-4 and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Huang et al. (Analytical Chemistry, 2015, 87, 1941-1949) and Broeren et al. (Clinical Microbiology and Infection, 2012, 19, 286-291) as applied to claims 1, 24-25, 27-28, and 32 above, in view of FCS Express (YouTube, 2020, https://youtu.be/onhcT11rMUY?si=QoV7GRRbhB9-inbn).
Huang et al. and Broeren et al. are applied to claims 1, 24-25, 27-28, and 32 above.
With respect to claim 2:
Huang et al. does not disclose wherein assigning a minimum inhibitory concentration based on the computed distance values comprises: fitting a curve to a plot of the distance values of the plurality of samples versus corresponding antibiotic concentrations of the plurality of samples; and assigning a minimum inhibitory concentration based on the fitted curve.
However, Broeren et al. discloses a comparison of minimum inhibitory concentrations found by different antimicrobial susceptibility testing methods (pg. 288-289, col. 2, para. 1; pg. 288-289, Fig. 1-3; pg. 289, Table 1). Also, further discloses bacterial counts plotted in Excel bar-graphs (pg. 288, col. 1, para. 1, lines 1-3). Each strain depicts the lowest antibiotic concentration showing respective percentage reduction in cell count as compared with the positive control after incubation. Differences in cell count between samples versus corresponding antibiotic concentrations are shown in Figures 1-3. This teaches plots of differences between samples versus antibiotic concentrations of the samples and predicting minimum inhibitory concentrations based on the comparisons.
Broeren et al. does not disclose fitting a curve to the plot of distance values.
However, FCS Express discloses integrated spreadsheet and regression analysis features in the FCS Express software that allows for logistic curve fitting on flow cytometry data (9:59-11:21; “Regression is by default a linear regression, but there are many types of regression and it’s very easy to switch to a different type by formatting this plot … I can change between any of those 19 types of regression … Let’s say that we want a 5-parameter logistic curve”; Description). This teaches fitting a curve to a plot of values. It would be obvious to perform curve fitting using regression analysis to assess cytometry data, such as bacterial counts plotted in Excel.
With respect to claim 3:
Broeren et al. and FCS Express do not disclose wherein the computed distance values are based on probability binning.
However, Huang et al. discloses combining adaptive probability binning with signature quadratic form distances to create a linear statistical metric that more readily scales to multiple dimensions (pg. 1942, col. 1, para. 2, lines 21-31). Also, further discloses characterizing 3-dimensional differences between the flow cytometric data of the no-antibiotic treated bacteria and the antibiotic-treated bacteria by probability binning signature quadratic form (PB-sQF) into a 1-dimensional linear distance (pg. 1941, Abstract, lines 15-16; pg. 1945, col. 2, para. 1, lines 5-11). This teaches computing distance values based on probability binning.
With respect to claim 4:
Broeren et al. and FCS Express do not disclose wherein the probability binning is based on a chi-squared statistic.
However, Huang et al. discloses combining the best attributes of PB-
χ
2
with signature quadratic form distances to create a linear statistical metric that more readily scales to multiple dimensions (pg. 1942, col. 1, para. 2, lines 21-31). Also, further discloses characterizing 3-dimensional differences between the flow cytometric data of the no-antibiotic treated bacteria and the antibiotic-treated bacteria by probability binning signature quadratic form (PB-sQF) into a 1-dimensional linear distance (pg. 1941, Abstract, lines 15-16; pg. 1945, col. 2, para. 1, lines 5-11). This teaches that the probability binning is based on a chi-squared statistic.
With respect to claim 7:
Huang et al. and Broeren et al. do not disclose wherein the curve fitted to the plot of the distance values of the plurality of samples versus corresponding antibiotic concentrations of the plurality of samples is a logistic curve.
However, FCS Express discloses integrated spreadsheet and regression analysis features in the FCS Express software that allows for logistic curve fitting on flow cytometry data (9:59-11:21; “Regression is by default a linear regression, but there are many types of regression and it’s very easy to switch to a different type by formatting this plot … I can change between any of those 19 types of regression … Let’s say that we want a 5-parameter logistic curve”; Description). This teaches fitting a logistic curve to a plot of values. It would be obvious to perform curve fitting using regression analysis to assess cytometry data, such as bacterial counts plotted in Excel.
It would have been prima facie obvious to one of ordinary skill in the art to modify the antibiotic susceptibility testing method disclosed by Huang et al. and Broeren et al. to incorporate curve fitting disclosed by FCS Express. One would be motivated to incorporate curve fitting because FCS Express discloses that analysis of flow cytometry data sets that require curve fitting are made easier with FCS Express with its integrated spreadsheet and regression analysis features (Description). Therefore, incorporating curve fitting will improve efficiency in antibiotic susceptibility testing. There is a likelihood of success, since all methods are of flow cytometry analyses of bacteria or flow cytometry tools, which are well known in the field of microbiology.
Conclusion
No claims are allowed.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Jammy Luo whose telephone number is (571)272-2358. The examiner can normally be reached Monday - Friday, 9:00 AM - 5:00 PM EST.
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/J.N.L./Examiner, Art Unit 1686
/OLIVIA M. WISE/Supervisory Patent Examiner, Art Unit 1685
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