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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 2/6/2026 has been entered.
Information Disclosure Statement
The IDS filed 11/25/2026 has been considered by the Examiner.
Status of Claims
Claims 2-3, 10-11, 16, 21-23 and 25-69 are cancelled;
Claims 1, 4-9, 12-15, 17-20 and 24 are pending and are examined on the merits.
Priority
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, or 365(c) is acknowledged. Priority of US application 62/026,327 filed 05/18/2020 is acknowledged.
Claim Rejections - 35 USC § 112
This is a newly installed rejection.
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1, 4-9, 12-15, 17-20 and 24 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.
Newly amended claim 1 recites “sorting cells of the sample into two or more different containers based on the number and arrangement of the clusters.” Newly amended claim 24 recites “a sorter configured to sort cells of the sample into two or more different containers based on the number and arrangement of the clusters.” However, the disclosure does not support an active step of sorting (or “to sort”) cells into two or more different containers based on the number and arrangement of the clusters.
First the disclosure does not recite the term “containers” or “container”.
Second when the disclosure does recite the terms “sort”” or “sorting”, they only related to general introduction to “sorter”, as outlined here:
[0003] Flow cytometry is a technique used to characterize and often times sort biological material, such as cells of a blood sample or particles of interest in another type of biological or chemical sample.
[0092] In some embodiments, the subject particle sorting systems are flow cytometric systems, such those described in U.S. Pat. Nos. 9,952,076; 9 933,341; 9,726,527; 9,453,789; 9,200,334; 9,097,640; 9,095,494; 9,092,034; 8,975,595; 8,753,573; 8,233,146; 8,140,300; 7,544,326; 7,201,875; 7,129,505; 6,821,740; 6,813,017; 6,809,804; 6,372,506; 5,700,692; 5,643,796; 5,627,040; 5,620,842; 5,602,039; the disclosure of which are herein incorporated by reference in their entirety.
[0093] In some embodiments, particle sorting systems of interest are configured to sort particles with an enclosed particle sorting module, such as those described in U.S. Patent Publication No, 2017/0299493, filed on Mar. 28, 2017, the disclosure of which is incorporated herein by reference.
An explicit, active performance of sorting guided by the data analytical result has never recited in the disclosures. The spec does not describe sorting cells into containers based on the number and arrangement of the clusters. The spec page 46, lines 9-13, does teach:
“In some implementations the processor 1100 can generate a user interface to receive example events for sorting. For example, the user interface can include a control for receiving example events or example images…..”
This does support receiving images and then sorting based on that. However, this is not enough to support applying the abstract idea to determine sorting or use a machine to sort based on the abstract idea. It does not support using the generated clusters to sort cells into containers based on the number and arrangement of clusters.
Therefore, amended claims recite new subject matter.
Claim Rejections - 35 USC § 112
This is a newly installed rejection.
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 1, 4-9, 12-15, 17-20 and 24 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 1 recites the limitation "the resolution indices" in the 6th step. There is insufficient antecedent basis for this limitation in the claim. Claim 1 does recite “a resolution index” in the 5th step.
Same situation happened again in claim 24. Claim 24 recites the limitation "the resolution indices" in the 6th step. There is insufficient antecedent basis for this limitation in the claim. Claim 24 does recite “a resolution index” in the 5th step.
For the same reason, claim 14 recites the limitation "the resolution indices" in the 2nd line without antecedent basis.
Claim 1 recites the limitation "the measured parameter data” in the 6th step. There is insufficient antecedent basis for this limitation in the claim.
Amendments are required.
Claim Rejections - 35 USC § 101
The instant rejection is maintained from the previous Office Action. Modifications are necessitated by claim amendments.
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, 4-9, 12-15, 17-20 and 24 are rejected under 35 USC 101 because the claimed inventions are directed to non-statutory subject matter.
Step 1: The Four Categories of Statutory Subject Matter (MPEP 2106.03)
Claims 1, 4-9, 12-15 and 17-20 are directed to a 101 process, here a "method," for detecting heterogeneity in flow cytometry data.
Claim 24 is directed to a 101 machine or manufacturer, here a "system."
Step 2A, Prong One: Whether the Claims Set Forth or Describe a Judicial Exception (MPEP 2106.04 § II.A.1)
An itemized analysis to the claim elements is set forth:
Calculating a measure of variability for first and second populations from the measured parameter data (claims 1 and 24);
----This step a calculation operation explicitly, which equates to an abstract idea of mathematical concept.
Determining a separation distance for the first and second populations of data from the obtained measures of variability (claims 1 and 24);
----This step calculate the separation distance from two groups of input data, which equates to an abstract idea of mathematical concept.
Calculating a resolution index of the first and second populations of data based on the measures of variability and the separation distance (claims 1 and 24);
----This step recites calculation a resolution index by a formula listed in a later claim, hence the step equates to an abstract idea of mathematical concept.
Applying a dimensionality reduction algorithm to the measured parameter data to determine an optimal number and arrangement of clusters based on resolution indices.
----This step recites applying an algorithm for dimensional reduction, hence the step equates to an abstract idea of mathematical concept.
Above element explicitly or implicitly require mathematical calculations, together with the three mathematical formula explicitly listed in claims 8 and 20, the claims as a whole, reads on data analysis through calculations. Claims are hence directed to mathematical concepts.
Because the steps are directed to the abstract idea of mathematical concepts. The claims must therefore be examined further to determine whether the claims integrate the above-identified abstract ideas into a practical application (MPEP 2106.04(d)).
Step 2A Prong Two: Consideration of Practical Application
The claimed method ends at sorting cells of the sample into two or more different containers based on the number and arrangement of the clusters (claims 1 and 24), which is an additional element. However, this step does nothing more than “apply it” because we don’t know how the clusters, the resolution index and the dimensionality reduction help sorting the cells.
Hence the claims do not include any additional elements that integrate the recited judicial exceptions (abstract ideas and natural correlation) into a practical application.
This judicial exception is not integrated into a practical application because the claims do not meet any of the following criteria:
An additional element reflects an improvement in the functioning of a computer, or an improvement to other technology or technical field;
an additional element that applies or uses a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition;
an additional element implements a judicial exception with, or uses a judicial exception in conjunction with, a particular machine or manufacture U1at is integral to the claim;
an additional element effects a transformation or reduction of a particular article to a different state or thing; and
an additional element applies or uses the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that t!1e claim as a wl1ole is more than a drafting effort designed to monopolize the exception.
Additionally, the courts have also identified limitations that did not integrate a judicial exception into a practical application:
Merely reciting a phrase such as "apply it" (or an equivalent) along with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP 2106.05(f);
Adding insignificant extra-solution activity to the judicial exception, as discussed in MPEP 2106.05(g); and
Generally linking the use of a judicial exception to a particular technological environment or field of use, as discussed in MPEP 2106.05(h).
Step 2B: Consideration of Additional Elements and Significantly More
The claimed methods also recite “additional elements” that are not limitation drawn to an abstract idea. The recited additional elements are drawn to:
Introducing the sample comprising a heterogeneous mixture of the cells into the flow cytometer (claim 1);
Generating parameter data measured from the cells of the sample (claims 1, 24);
Display on a graphic user interface a plot of the arranged clusters (claims 1 and 24);
A flow cytometer configured to produce data by analyzing a biological sample comprising a heterogeneous mixture of cells (claim 24: this step recites technical environment, which equates to additional elements); and
A processor in operable communication with the flow cytometer comprising memory operably coupled to the processor wherein the memory comprises instructions stored thereon (claim 24: this step recites technical environment, which equates to additional elements).
Sorting cells of the sample into two or more different containers based on the number and arrangement of the clusters (claims 1 and 24).
The above additional elements can be divided into five groups: Group 1: a flow cytometer for analyzing a biological sample, and the heterogeneous samples (which include A system comprising: a flow cytometer configured to produce data by analyzing a biological sample (claim 24)); Group 2: data acquired (which includes the elements start with “obtaining…”; Group 3: the computing environment for analyzing the data (which include a processor comprising memory operably coupled to the processor wherein the memory comprises instructions stored thereon (claim 24)); Group 4: report generated from data analysis (display on a GUI); and Group 5: field application of sorting cells. These additional elements are either insignificant extra-solution activities that are well known routine and conventional (a general flow cytometer, data input/output, sorting cells) because they are required for data analysis, or merely provide a computing environment to execute the abstract idea (computer, processor, memory). There is no additional elements that add significantly more to the JE of mathematical calculations.
Hence, the 101 rejection is maintained.
Response to Applicant’s argument:
In the remarks filed 2/6/2026, Applicant argued that (page 7, last para and page 8, 1st para) “the instant claims are not directed to non-statutory subject matter and present specific and concrete limitations that amount to significantly more than an abstract idea.” The argument is not persuasive. As outlined in the 101 rejection above, claims clearly recites abstract ideas in the form of mathematical concepts. Further, the current claims do not recite any additional elements that integrate the abstract idea into a practical application under Step 2A Prong Two or are non-routine, conventional and well understood under Step 2B. Hence there is no integration of the abstract ideas into a practical application.
In the remarks, Applicant argues (page 8, last para) that “claimed concept is
not identified as an abstract idea unless it is similar to at least one concept that the
courts have identified by the court”. Applicant’s argument is not persuasive. The recited mathematical formulas or equations for TaylorIndex (claim 8), TaylorFactor (claim 20) and TaylorScore (claim 20) are analogous to the examples (of the “mathematical concepts” grouping) set forth in MPEP §2106.04(a)(2).I.B:
i. a formula describing certain electromagnetic standing wave phenomena, Mackay Radio & Tel. Co. v. Radio Corp. of America, 306 U.S. 86, 91, 40 USPQ 199, 201 (1939) (50.9(l/lambda<-0.513>);
ii. the Arrhenius equation, Diamond v. Diehr; 450 U.S. 175, 178 n. 2, 179 n.5, 191-92, 209 USPQ at 4-5 (1981) (ln v = CZ + x);
iii. a formula for computing an alarm limit, Parker v. Flook, 437 U.S. 584, 585, 198 USPQ 193, 195 (1978) (B1=B0 (1.0–F) + PVL(F)); and
iv. a mathematical formula for hedging (claim 4), Bilski v. Kappos, 561 U.S. 593, 599, 95 USPQ2d 1001, 1004 (2010) (Fixed Bill Price = Fi + [(Ci + Ti + LDi) x (α + βE(Wi))]).
Therefore, the claims do recite abstract ideas.
Applicants argue (page 9, 2nd para.) that the “claims are directed to a particular process utilized to solve a particular technological problem”. Applicant’s argument seems related to Step 2A/Prong two in the 35 USC 101 analysis.
In response, Applicant’s argument is not persuasive. To be fair, instant claims solved a particular problem in data analysis. We don’t know which technological area benefited from the instant claims, not even the cell sorting technology.
In the remarks, Applicant argues (page 9, last para through page 10, 2nd para) that the instant claims as a whole amount to “significantly more” include "adding a specific limitation other than what is well-understood, routine and conventional in the field, or adding unconventional steps that confine the claim to a particular useful application." Applicant’s argument refers to Step 2B in the 101 analysis, but is not persuasive. As discussed above over the 101 rejection, the additional elements recited in the claims can be divided into five groups: Group 1: a flow cytometer for analyzing a biological sample (which include A system comprising: a flow cytometer configured to produce data by analyzing a biological sample (claim 24)); Group 2: data acquired (which includes the elements start with “obtaining…”; Group 3: the computing environment for analyzing the data (which include a processor comprising memory operably coupled to the processor wherein the memory comprises instructions stored thereon (claim 24)); Group 4: report generated from data analysis (display on a GUI); and Group 5: field application of sorting cells. These additional elements are all well known, routine and conventional (a general flow cytometer, data input/output). There is no additional elements significant enough to integrate claims into a practical application at Step 2B.
Applicants argue (page 9, 2nd para.) that the claims are drawn to an improvement to flow cytometry. In response, what Applicant offered is an improved data analysis. Improvement to data analysis is still part of the abstract ideas. There is no improvement to the flow-cytometry.
In the remarks, Applicant further argues (page 10, 3rd para through page 11, 2nd para) that instant claims are analogous to example 40. The argument is not persuasive. Example 40 is not analogous to the instant claims.. In example 40, the claim recites the combination of additional elements of collecting at least one of network delay, packet loss, or jitter relating to the network traffic passing through the network appliance, and collecting additional Netflow protocol data relating to the network traffic when the collected network delay, packet loss, or jitter is greater than the predefined threshold. Although each of the collecting steps analyzed individually may be viewed as mere pre- or post-solution activity, the claim as a whole is directed to a particular improvement in collecting traffic data. Specifically, the method limits collection of additional Netflow protocol data to when the initially collected data reflects an abnormal condition, which avoids excess traffic volume on the network and hindrance of network performance. The collected data can then be used to analyze the cause of the abnormal condition. This provides a specific improvement over prior systems, resulting in improved network monitoring. The claim as a whole integrates the mental process into a practical application. Thus, the claim is eligible because it is not directed to the recited judicial exception. However, such additional elements are not recited in the instant claims. The instant claims do not recite any additional elements that integrate the abstract idea into a practical application..
Hence, the 101 rejection is maintained.
Claim Rejections - 35 USC § 103
Upon further consideration, the rejection is reinstated.
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.
Claim(s) 1, 4-9, 13, 17 and 24 are rejected under 35 U.S.C. 103 as being unpatentable over Fread ("An updated debarcoding tool for mass cytometry with cell type-specific and cell sample-specific stringency adjustment." PACIFIC SYMPOSIUM ON BIOCOMPUTING 2017. 2017. Cited on the 6/14/2023 PTO-892 form), further in view of Zucker ("Flow cytometry quality assurance." Standardization and Quality Assurance in Fluorescence Measurements II: Bioanalytical and Biomedical Applications (2008): 343-370. Cited on the 6/14/2023 PTO-892 form) and Lux, Markus. ("Efficient Grouping Methods for the Annotation and Sorting of Single Cells." (2018). Newly cited).
Claim 1 is directed to a method for clustering and sorting cells of a sample. The “parameter data” recited in the 2nd step is interpreted as regular data measured in a general flow-cytometry experiment (such as the CD4+ reading , the CD8+ reading). Regarding claim 1, Fread taught acquiring heterogeneous samples and the flow cytometry data (1st para, pg. 589, and Fig 1A, pg. 589). The sample is obvious heterogeneous as both positive and negative barcode channels co-exist. Fread taught separation distance between normalized positive and negative barcode channel measurements (which reads on two different data populations) (last para, line 6-7, pg. 592 and Fig. 4A, pg. 593). Fread does not teach measuring variability or calculating resolution index. Zucker provides (page 343, section “Abstract”) “by comparing the means and standard deviations of the first two peaks, a value can be determined which relates to the sensitivity of the system” and teaches calculating detection efficacy: Rd = M2 – M1/(SD1 + SD2) where M is the mean of the first two peaks and SD is the standard deviation of the first two peaks (last para, line 10-11, pg. 358). The SD implies variability in data. The clusters in claim limitation equates to groups in Zucker. The claim limitation “resolution index” reads on Zucker’s formula for detection efficacy, because (M2-M1) anticipates the separation distance and (SD1 + SD2) anticipates variability. The “detection efficacy” come from Wood’s resolution factor (last para, line 12, pg. 358), and is similar to the TaylorIndex disclosed in the instant invention, which requires comparing the respective measures of variability with the separation distance.
Neither Fread nor Zucker teaches dimensionality reduction.
Lux provides (page 6, 2nd para lines 4-8) “Similar to metagenomic binning, reference-free inspection is enabled by the use of state-of-the-art machine learning techniques that include fast, non-linear dimensionality reduction, and subsequent clustering algorithms that automatically estimate the number of clusters”, which teaches the dimensionality reduction algorithm to facilitate clustering analysis.
Zucker provides Fig. 6 based on the calculation of Rd (page 362, Fig. 6), which teaches displaying on a graphic user interface a plot of the arranged clusters.
Lux teaches an “efficient grouping method for the annotation and sorting of single cells” (page 8, Fig. 1.4). The “grouping method” anticipates clusters in claim 1.
Regarding claim 4, Zucker teaches calculating resolution index (with a formula) as a way to measure separation between the first and the second populations in flow cytometry data (Table 1, pg. 356). Zucker’s formula for “detection efficacy”:
Rd = M2 – M1/(SD1 + SD2)
where M is the mean of the first two peaks and SD is the standard deviation of the first two peaks (last para, line 10-11, pg. 358), is similar to the TaylorIndex disclosed in the instant invention, which requires comparing the respective measures of variability with the separation distance.
Regarding claim 5, Fread taught separation distance between normalized positive and negative barcode channel measurements (which reads on two different data populations) (last para, line 6-7, pg. 592 and Fig. 4A, pg. 593).
Regarding claim 6, Zucker teaches calculating detection efficacy (with a formula) as a way to measure separation between the first and the second populations in flow cytometry data (last para, line 10-11, pg. 358). As revealed in the formula above, Zucker measures of variability comprises calculating the mean centroid position and standard deviation for the first and second populations of data, respectively.
Regarding claim 7, Zucker teaches calculating detection efficacy (aka resolution factor, with a formula) as a ratio between the respective measures of variability for the first and second populations of data and the separation distance (last para, line 10-11, pg. 358).
Regarding claim 8, the TaylorIndex formula is obvious over Zucker’s detection efficacy (aka resolution factor) formula:
Rd = M2 – M1/(SD1 + SD2)
where M is the mean of the first two peaks and SD is the standard deviation of the first two peaks (last para, line 10-11, pg. 358).
Regarding claim 9, it is obvious that the resolution index is calculated for any two populations in a data.
Regarding claim 13, Zucker provides Fig. 6 based on the calculation of Rd (page 362, Fig. 6), which teaches generating an image.
Regarding claim 17, Fread teaches sample multiplexing for fluorescence-based flow cytometry data comprised of multiplexing bar-coding (1st para through 3rd para, pg. 589). Each fluorescence dye reads on a “parameter” in the claim 17.
Claim 24 is the “system” version of the “method” claim 1. Regarding claim 24, since Fread taught computer (Fig. 1, pg. 589; Fig 5, pg. 594), the debarcoding software and pre-compiled executable based on MATLAB for data analysis (2nd para, pg. 595), and Zucker disclosed a flow-cytometer (Fig. 1, pg.345), the art applied to claim 1 also teaches claim 24.
It would have been prima facie obvious to modify the Fread’s mass cytometry data analysis pipeline, with Zucker’s flow cytometry data quality assurance methods including the quantitative resolution index, because Zucker’s quantitative resolution index, detection efficacy, and separation distance over sum of variabilities, enhance Fread’s flow cytometry data processing. One would reasonably expect success because Zucker’s analysis is based on the same data type like Fread’s, they can operate independently to generate more meaningful analytical reports and customers of this analytical tool will enjoy more analytical choices with one data input handing, other than looking for additional tools that might take a different data input format.
It would have been prima facie obvious to modify the combined Fread and Zucker pipeline for flow-cytometry data quality assurance and data analysis, with Lux’s method of dimensionality reduction (page 6, 2nd para lines 4-8) as well as grouping and sorting cells (page 8, Fig. 1.4). Because dimensionality reduction in data pre-processing, will allow subsequent clustering which automatically estimate the number of clusters runs more efficient. It would be obvious to apply grouping and sorting cells are important steps in order to realize the benefit in flow-cytometry data analysis.
One would reasonably expect success because Zucker, Fread and Lux are all about flow-cytometry data analysis, based on the same data type. They can operate independently to generate more meaningful analytical reports in a speeding and efficiently way. Customers of this analytical tool will enjoy more analytical choices with one data input handing, and execute cell sorting under the guidance of the clustering results.
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Fread, Zucker and Lux, as discussed above over claims 1, 4-9, 13, 17 and 24, and further in view of Wallin ("BayesFlow: latent modeling of flow cytometry cell populations." BMC bioinformatics 17.1 (2016): 1-16. Cited on the 6/14/2023 PTO-892 form)
Regarding claim 12, Wallin taught Hartigan’s dip test for modeling flow cytometry data to determine which latent clusters to merge and to indicate confidence in the mergers (penultimate para, pg. 7).
It would have been prima facie obvious to enhance the combined Fread, Zucker and Lux cytometry data analysis pipeline, with Wallin’s teaching of Hartigan’s dip test for modeling the flow cytometry data and to optimize the clustering of populations. Because all of Fread, Zucker, Lux and Wallin are based on the same data type like Fread’s, they can operate independently to generate more meaningful analytical reports. One would reasonably expect success because this would have been an example of combining prior art elements according to known methods to yield predictable results (MPEP §2143.I.A).
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Fread, Zucker and Lux, as discussed above over claims 1, 4-9, 13, 17 and 24, and further in view of Maecker ("Flow cytometry controls, instrument setup, and the determination of positivity." Cytometry Part A: the journal of the International Society for Analytical Cytology 69.9 (2006): 1037-1042. Cited on the 6/14/2023 PTO-892 form).
Regarding claim 18, Maecker teaches maximizing the resolution sensitivity (col2, last para, pg. 1040).
It would have been prima facie obvious to enhance the combined Fread’s, Zucker’s and Lux’s mass cytometry data analysis pipeline, with Maecker to maximize the resolution between populations because maximized resolution allows for better observation on populations in the sample. It is achievable because all of Fread, Zucker Lux and Maecker are based on the same data type like Fread’s, they can operate independently to generate more meaningful analytical reports. The person of ordinary skill in the art would have found it obvious to combine the elements of Fread, Zucker, Lux and Maecker because customers of this analytical tool will enjoy more analytical choices with one data input handing, other than looking for additional tools that might take a different data input format.
Conclusion
No claims are allowed.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GUOZHEN LIU whose telephone number is (571)272-0224. The examiner can normally be reached Monday-Friday 8-5.
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/GL/
Patent Examiner
Art Unit 1686
/Anna Skibinsky/
Primary Examiner, AU 1635
Prosecution Insights