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 .
Status of Claims
Claims 1-20 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 CHINA application 202110495855.6, filed 05/07/2021 is acknowledged
Withdrawn Rejections/Objections
The rejections to claims 1-20 under 35 U.S.C. 112(b) in the Office action posted 6/17/2025 are withdrawn in view of claim amendments filed 9/16/2025.
The objection to claims 5 and 15 in the Office action posted 6/17/2025 are withdrawn in view of claim amendments filed 9/16/2025.
Claim Rejections - 35 USC § 112
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 1-20 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.
Both claim 1 and 11 recite “calculating a first cycle of quantification (Cq) value” at the last step. The disclosure barely mentioned Cq (cycle of quantification) value two times (emphasis added):
“Conventionally, a Cq (cycle of quantification) value (which represents the cycle number at which the fluorescent signal crosses a predetermined threshold value) is often calculated through the growth type curve, to interpret the test result (i.e., positive test result or negative test result). However, the instability of the fluorescent signals often affects the calculation of Cq value, to further affect the interpretation of the nucleic acid testing” [0003].
“For example, a Cq (cycle of quantification) value for interpreting the result of the nucleic acid testing is calculated according to the growth type curve” [0015].
A mathematical formula for calculating the Cq value is not given, the Drawings never mark a point for the Cq value in any figure. Therefore, “calculating a first cycle of quantification (Cq) value” is considered indefinite.
To advance compact prosecution, the recited Cq value is interpreted as the Ct value, which is previously accepted in the real-time PCR analytical community. Ct is also mentioned as “elbow value” or “cycle threshold” in a previously cited art:
“For a typical PCR curve, identifying a transition point at the end of the baseline region, which is referred to commonly as the elbow value or cycle threshold (Ct) value, is extremely useful for understanding characteristics of the PCR amplification process. The Ct value may be used as a measure of efficiency of the PCR process. For example, typically a defined signal threshold is determined for all reactions to be analyzed and the number of cycles (Ct) required to reach this threshold value is determined for the target nucleic acid as well as for reference nucleic acids such as a standard or housekeeping gene. The absolute or relative copy numbers of the target molecule (starting material) can be determined on the basis of the Ct values obtained for the target nucleic acid and the reference nucleic acid (Gibson et al., Genome Research 6:995-1001; Bieche et al., Cancer Research 59:2759-2765, 1999; WO 97/46707; WO 97/46712; WO 97/46714).” (Ronald T. Kurnik (“Universal method to determine real-time PCR cycle threshold values“, US11615863B2, Publication: 2023-03-28. Previously cited. col 1, last para).
Claim Rejections - 35 USC § 101
This rejection is maintained from the previous Office Action filed 6/17/2025 and modified to address amendments filed 9/16/2025.
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 1-20 are rejected under 35 USC 101 because the claimed invention is directed to non-statutory subject matter.
Framework with which to Evaluate Subject Matter Eligibility:
Step 1: Are the claims directed to a process, machine, manufacture, or composition of matter;
Step 2A, Prong One: Do the claims recite a judicially recognized exception, i.e. a law of nature, a natural phenomenon, or an abstract idea;
Step 2A, Prong Two: If the claims recite a judicial exception under Prong One, then is the judicial exception integrated into a practical application (Prong Two); and
Step 2B: If the claims do not integrate the judicial exception, do the claims provide an inventive concept.
Step 1: Are the claims directed to a process, machine, manufacture, or composition of matter?
Claims 1-10 are directed to a process, here a "method," with functional steps like “calculating,” “searching,” “determining,” “obtaining”, “deriving”, “adjusting”, and “calculating”.
Claims 11-20 are drawn to a machine and manufacturer, here an “apparatus", with structural components of a memory and a processor.
[Step 1: claims 1-20 YES. MPEP § 2106.03 pertains].
Step 2A, 1st prong, Do the claims recite a judicially recognized exception, i.e. a law of nature, a natural phenomenon, or an abstract idea?
With respect to Step 2A, Prong One, the claims recite abstract ideas. The MPEP at 2106.04(a)(2) further explains that abstract ideas are defined as:
• mathematical concepts (mathematical formulas or equations, mathematical relationships and mathematical calculations);
• certain methods of organizing human activity (fundamental economic practices or principles, managing personal behavior or relationships or interactions between people); and/or
• mental processes (procedures for observing, evaluating, analyzing/ judging and organizing information).
Mental processes and Mathematical concepts recited in the claims include:
Claims 1, and 11 recite:
calculating a plurality of first derivative values corresponding to the data points;
----this step recites mathematical calculations explicitly with data points as input and a plurality of first derivative values as output, which equates to an abstract idea of mathematical concepts.
searching at least one local maximum value from the first derivative values;
----this step recites a judgement activity (identify at least one local maximum value) based on data observation (“from the first derivative values”), which equates to an abstract idea of mental processes.
determining whether the at least one local maximum value is greater than a first threshold, and
----this step recites a judgement activity based on data comparison, which equates to an abstract idea of mental processes.
determining whether a part of the first derivative values adjacent to the at least one local maximum value are all positive;
----this step recites a judgement activity based on data comparison, which equates to an abstract idea of mental processes.
determining one of the first derivative values after a predetermined effective cycle number or the at least one local maximum value as a target maximum value according to a determination result;
----this step recites a judgement activity based on data comparisons, which equates to an abstract idea of mental processes.
obtaining a target cycle number corresponding to the target maximum value;
----this step recites defining a parameter based on an existing data, which can be achieved in human mind. Hence this step equates to an abstract idea of mental processes.
deriving a basic cycle number according to the first derivative value corresponding to the target cycle number;
----this step recites defining a parameter based on an existing data, which can be achieved in human mind. Hence this step equates to an abstract idea of mental processes.
adjusting the data points according to the basic cycle number to form a baseline of the growth type curve; and
----this step recites data manipulation (adjusting the data points) based on an existing data, which can be achieved in human mind. Hence this step equates to an abstract idea of mental processes.
calculating a first cycle of quantification (Cq) value according to the adjusted growth type curve.
----this step recites mathematical calculations explicitly with adjusted growth type curve as input and a first Cq as output, which equates to an abstract idea of mathematical concepts.
Claims 2 and 12 recite:
calculating a plurality of second derivative values corresponding to the data points;
----this step recites mathematical calculations explicitly with data points as input and a plurality of second derivative values as output, which equates to an abstract idea of mathematical concepts.
multiplying two of the second derivative values corresponding to two adjacent cycle numbers; and
----this step recites mathematical calculations explicitly with two of the second derivative values as input, which equates to an abstract idea of mathematical concepts.
comparing two of the first derivative values corresponding to the two adjacent cycle numbers which have a negative multiplication result, and determining the larger one of the two of the first derivative values corresponding to the two adjacent cycle numbers as the at least one local maximum value.
----this step recites data comparing (two of the first derivative values) and judgement activity (determining the larger one of the two of the first derivative values), which equates to an abstract idea of mental processes.
claims 3 and 13 recite:
checking whether the growth type curve has an abnormal curve characteristic according to the target cycle number or the basic cycle number.
----this step recite a judgement activity based on data observation, which equates to an abstract idea of mental processes.
claims 4 and 14 recite:
when the at least one local maximum value is greater than the first threshold and the part of the first derivative values adjacent to the at least one local maximum value are all positive, determining the at least one local maximum value as the target maximum value.
----this step recites a decision-making activity, which equates to an abstract idea of mental processes.
Claims 5 and 15 recite:
when the at least one local maximum value is not greater than the first threshold or the part of the first derivative values adjacent to the at least one local maximum value are not all positive, determining the one of the first derivative values after the predetermined effective cycle number as the target maximum value.
----this step recites a decision-making activity, which equates to an abstract idea of mental processes.
claims 6 and 16 recite:
searching an incremental part of the first derivative values after the predetermined effective cycle number; and
----this step recites searching some values, which can be achieved in human mind. Therefore, this step equates to an abstract idea of mental processes.
if a last one of the incremental part of the first derivative values is greater than a second threshold, determining the last one of the incremental part of the first derivative values as the target maximum value.
----this step recites a judgement or decision-making activity based on data observation, which equates to an abstract idea of mental processes.
Claims 7 and 17 recite:
adjusting the first threshold or the second threshold to recalculate at least one second Cq value;
----this step recites data manipulation (adjusting the first threshold or the second threshold) and mathematical calculation (to recalculate at least one second Cq value). Therefore, this step equates to an abstract idea of mental processes and mathematical concepts.
if a difference value between the first Cq value and the at least one second Cq value is smaller than a predetermined value, interpreting a test result of the object under test is positive or negative according to the first Cq value; and
----this step recites a judgement activity (interpreting a test result of the object under test is positive or negative according to the first Cq value) based on a condition, which equates to an abstract idea of mental processes.
if the difference value between the first Cq value and the at least one second Cq value is not smaller than the predetermined value, interpreting the test result of the object under test is positive or negative according to the smallest one of the first Cq value and the at least one second Cq value.
----this step recites a judgement activity (interpreting a test result of the object under test is positive or negative according to the first Cq value) based on a condition, which equates to an abstract idea of mental processes.
claims 8 and 18 recite:
setting the data points corresponding to the cycle numbers before the basic cycle number to correspond to the basic data value, to form the baseline.
----this step recites data manipulation (setting the data points ), which equates to an abstract idea of mental processes.
Claims 9 and 19 recite:
searching an incremental part of the first derivative values after the predetermined effective cycle number; and
----this step recites searching data, which can be achieved in human mind. Therefore this step equates to an abstract idea of mental processes.
if a last one of the incremental part of the first derivative values is greater than a second threshold, determining the last one of the incremental part of the first derivative values as the target maximum value.
----this step recites a decision-making activity based on a condition, which equates to an abstract idea of mental processes.
Claims 10 and 20 recite:
adjusting the first threshold or the second threshold to recalculate at least one second Cq value;
----this step recites data manipulation (adjusting the first threshold or the second threshold) and mathematical calculation (to recalculate at least one second Cq value). Therefore, this step equates to an abstract idea of mental processes and mathematical concepts.
if a difference value between the first Cq value and the at least one second Cq value is smaller than a predetermined value, interpreting a test result of the object under test is positive or negative according to the first Cq value; and
----this step recites a judgement activity (interpreting a test result of the object under test is positive or negative according to the first Cq value) based on a condition, which equates to an abstract idea of mental processes.
if the difference value between the first Cq value and the at least one second Cq value is not smaller than the predetermined value, interpreting the test result of the object under test is positive or negative according to the smallest one of the first Cq value and the at least one second Cq value.
----this step recites a judgement activity (interpreting the test result of the object under test is positive or negative according to the smallest one of the first Cq value and the at least one second Cq value) based on a condition, which equates to an abstract idea of mental processes.
Each of which, including all recitation within each listed element above, in at least the simplest embodiment within a BRI, involves mental processes of abstract ideas and mathematical concepts
Hence, the claim explicitly recite elements that, individually and in combination, constitute abstract ideas. The claim must therefore be examined further to determine whether they integrate that abstract idea into a practical application (MPEP 2106.04(d)).
[Step 2A, 1st prong: claims 1-20 YES]
Step 2A, 2nd prong: If the claims recite a judicial exception under Prong One, then is the judicial exception integrated into a practical application?
The claims result in calculating the Cq value, according to the adjusted growth curve, which reads on analyzing data and generating new data. The claims do not recite any additional elements that integrate the abstract idea/judicial exception into a practical application. The identified additional elements (“a memory” and “a processor”) are drawn to no more than merely invoking computers as a tool to perform an existing process (MPEP §2106.05(f)).
This judicial exception is not integrated into a practical application because the claims do not meet any of the following criteria:
An improvement in the functioning of a computer, or an improvement to other technology or technical field, as discussed in MPEP §§ 2106.04(d)(1) and 2106.05(a);
Applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, as discussed in MPEP § 2106.04(d)(2);
Implementing a judicial exception with, or using a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, as discussed in MPEP § 2106.05(b);
Effecting a transformation or reduction of a particular article to a different state or thing, as discussed in MPEP § 2106.05(c); and
Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception, as discussed in MPEP § 2106.05(e).
[Step 2A, 2nd prong: claims 1-20 NO]
Step 2B: Do the claims recite non-conventional arrangement of additional elements in addition to the identified JEs (MPEP 2106.05)?
The claimed methods also recite the following additional elements that are not JEs:
A memory (claim 11); and
A processor (claim 11).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the above identified additional elements are routine and conventional in a research lab. The conventionality of recited subject matter can further be witnessed by the following references:
Liu, Meile, Claudia Udhe‐Stone, and Chetan T. Goudar. "Progress curve analysis of qRT‐PCR reactions using the logistic growth equation." Biotechnology progress 27.5 (2011): 1407-1414.
Ramakers, Christian, et al. "Assumption-free analysis of quantitative real-time polymerase chain reaction (PCR) data." Neuroscience letters 339.1 (2003): 62-66.
Yuan, Joshua S., et al. "Statistical analysis of real-time PCR data." BMC bioinformatics 7.1 (2006): 85.
Pryor, Robert J., and Carl T. Wittwer. "Real-time polymerase chain reaction and melting curve analysis." Clinical applications of PCR. Totowa, NJ: Humana Press, 2006. 19-32.
Liu, Weihong, and David A. Saint. "A new quantitative method of real time reverse transcription polymerase chain reaction assay based on simulation of polymerase chain reaction kinetics." Analytical biochemistry 302.1 (2002): 52-59.
The titles of above listed references clearly demonstrated that claimed methods are conventionally pursued for many years before the instant application is filed. Computers as assistant tools, are used in these studies.
Hence, the combination of the additional elements are not sufficient to be significantly more.
[Step 2B: claims 1-20 No]
Hence, the rejection under 35 U.S.C. 101 to claims 1-20 are maintained.
Response to Applicant’s Arguments
In the Remarks filed 9/16/2025, Applicant argued (page 13, 1st para through page 14, 1st para) that claim elements A1 ~ F1 are not abstract ideas of mental processes. Applicant’s argument is not persuasive. The argued elements are list here:
[A1] searching at least one local maximum value from the first derivative values;
[B1] determining whether the at least one local maximum value is greater than a first threshold, and determining whether a part of the first derivative values adjacent to the at least one local maximum value are all positive;
[C1] determining one of the first derivative values after a predetermined effective cycle number or the at least one local maximum value as a target maximum value according to a determination result;
[D1] obtaining a target cycle number corresponding to the target maximum value;
[E1] deriving a basic cycle number according to the first derivative value corresponding to the target cycle number;
[F1] adjusting the data points according to the basic cycle number to form a baseline of the growth type curve;
These elements, are all drawn to PCR curve analysis. Although recited as a computerized process, nothing would prevent a human mind from performing the claimed steps of “searching …”, “determining …”, “obtaining …”, “deriving …”, and “adjusting …”. These limitations are different from working on a halftone digital image. Human mind is not equipped to work with the intensity values behind the pixels at different positions to output a modified computer data structure and arrive at an improve image. However, human mind is certainly equipped to analyze curves and to draw conclusions.
In the Remarks, Applicant argued (page 14, 2nd para through page 16, 3rd para) that claims are integrated into a practical application due to a technical improvement. Applicant’s argument is not persuasive. The integration should be captured and reflected by additional elements. The claims recite only two additional elements: A memory; and a processor. The memory and processor are generic computing components which merely provide a computing environment for processing abstract ideas (MPEP §2106.05(f)). The technical merits rooted in the judicial exceptions is not applied to the computing components, the computing components do not capture or reflect the technical merits rooted in the judicial exceptions. There is simply no integration. The argued technical solution (page 15, last para through page 16, 1st para), is merely better data analysis. There is no improvement to a technical field.
Hence, the 101 rejection is maintained.
Claim Rejections - 35 USC § 103
This rejection is recycled from the previous Office Action.
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.
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.
Claim(s) 1 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over
Ronald T. Kurnik, Aditya Sane: (“PCR elbow determination using quadratic test for curvature analysis of a double sigmoid“, US20090119020A1, Publication: 2009-05-07. Previously cited. Hereafter Kurnik_1), and Ronald T. Kurnik (“Universal method to determine real-time PCR cycle threshold values“, US11615863B2, Publication: 2023-03-28. Previously cited. Hereafter Kurnik_2).
Regarding claim 1, Kurnik_1 disclosed “a computer implemented method is provided for determining whether data for a growth process exhibits significant growth. The method typically includes receiving a data set representing a growth process, the data set including a plurality of data points, each data point having a pair of coordinate values” (Kurnik_1: [009]), which teaches a data sifting method applied to a processor, wherein the processor is coupled to a memory storing a growth type curve, the growth type curve is generated by performing a polymerase chain reaction on an object under test, the growth type curve comprises a plurality of data points.
Kurnik_1 does not provide curves of a first or a second derivatives. Kurnik_2 provides Fig. 2A, “FIG. 2A shows a plot 200 of the first derivative 230 of PCR curve 110 according to embodiments of the present invention. The x-axis is still cycle number, but the y-axis is in units of change in intensity per cycle, as plot 200 shows the first derivative. First derivative 230 may be determined by taking the first derivative of the function that resulted from a curve fitting process to the data points. As shown, first derivative 230 has a maximum at inflexion point 228 (which corresponds to inflexion point 128)” (col 5, penultimate para), which teaches calculating a plurality of first derivative values corresponding to the datapoints, and search one local maximum value (“a maximum at inflexion point 228”) from the first derivative values.
Kurnik_2 does not teach that the one local maximum value is greater than a first threshold, or “determining whether a part of the first derivative values adjacent to the at least one local maximum value are all positive”. However, one of ordinary skill would know that to avoid wasting time on spurious growth curve and for a successful PCR growth curve and the values derived (instant Fig. 3 and Kurnik_2’s Figs 2A, 2B and 3), these two quality assurance would be obvious. Further, Kurnik_1 provides: “The elbow value in a PCR curve can be determined using several existing methods. For example, various current methods determine the actual value of the elbow as the value where the fluorescence reaches a predetermined level called the AFL (arbitrary fluorescence value). Other current methods might use the cycle number where the second derivative of fluorescence vs. cycle number reaches a maximum. All of these methods have drawbacks. For example, some methods are very sensitive to outlier (noisy) data, and the AFL value approach does not work well for data sets with high baselines. Traditional methods to determine the baseline stop (or end of the baseline) for the growth curve shown in FIG. 1 may not work satisfactorily, especially in a high titer situation. Furthermore, these algorithms typically have many parameters (e.g., 50 or more) that are poorly defined, linearly dependent, and often very difficult, if not impossible, to optimize” ([0005]), which also suggests to apply quality assurance requirements to growth curves and derived growth curves.
Kurnik_2 provides “embodiments use the intersection of a line tangent to the growth curve at the maximum of the second derivative with a baseline of the growth curve. To obtain the point of the maximum of the second derivative of a growth curve, one can obtain a functional approximation (curve fit) to the data points of the particular growth process (e.g., real-time PCR). A second derivative of the function can be computed and analyzed to determine at what cycle (xval) the maximum occurs. The tangent line can then be determined based on the slope of the function at xval. After a baseline of the function is determined, the intersection of the tangent line and the baseline can be calculated. The Ct value is then returned and may be displayed or otherwise used for further processing” (col 5, 2nd para), which teaches obtaining a target cycle number (Ct) corresponding to the xval, Ct value is also a basic cycle number coming from the first derivative value (because the second derivative values are based on the first derivative values).
Kurnik_2 provides “creating a function that approximates the dataset by adjusting parameters of the function to fit the dataset; determining the baseline of the growth curve” (Kurnik_2: claim 1), which teaches adjusting the data points according to the basic cycle number to form a baseline of the growth type curve.
Kurnik_2 provides “identifying an intersection point of the tangent line and the baseline, a cycle number of the intersection point representing a cycle threshold value Ct of the PCR growth process for the biological sample” (Kurnik_2: claim 1), which teaches obtaining a target cycle number corresponding to the target maximum value; deriving a basic cycle number according to the first derivative value corresponding to the target cycle number; and calculating a first Cq value according to the adjusted growth type curve. Because, Kurnik_2’s Ct reads on the Cq value in the instant claim 1.
Claim 11 is the apparatus version for the method of claim 1. Since Kurnik_1 also disclosed “a computer implemented method is provided for determining whether data for a growth process exhibits significant growth. The method typically includes receiving a data set representing a growth process, the data set including a plurality of data points, each data point having a pair of coordinate values” (Kurnik_1: [009]), the art applied to claim 1 also teaches claim 11.
It would have been prima facie obvious to combine two of Kurnik’s methods on real-time PCR data processing to arrive the claimed method on PCR data pre-processing (here “data sifting”), because both methods start with the same growth type curves generated by performing polymerase chain reactions on objects under test, for the same purpose of calculating the Ct values of PCR growth curves, while Kurnik_1 is focused on sigmoidal growth curves (Kurnik_1: Section “Abstract”) and Kurnik_2 “can be used for standard sigmoidal growth curves and for problematic growth curves, such as parabolic curves” (Kurnik_2: Section “Abstract”).
One can reasonably expect success of this combination as Kurnik_2’s first derivative, second derivative corresponding to the PCR growth curve, plus the local maximum value, xval, line tangent to calculate the Ct value, are improvements to the original PCR data analysis framework teaching in Kurnik_1. This combination would be a classic example of “Combining prior art elements according to known methods to yield predictable results” (MPEP §2141.III.(A)).
Response to Applicant’s Arguments
In the Remarks filed 9/16/2025, Applicant argued (page 16, last para through page 18, 2nd para) that the cited reference failed to teach or render obvious every single analytical step recited in both claims 1 and 11.
Applicant’s arguments are not persuasive. Applicants have only emphasized the performance steps (PCR curve analytical steps) and argue that paragraph [0009] from the reference does not teach the terms recited in instant claims 1 and 1, which is not convincing nor persuasive. In claim interpretation, examination applies that standard of BRI. In reference teaching we also apply the figures from the reference, in addition to terms. The art applied in the previous Office Action is deemed proper and the 103 rejections to claims 1 and 11 are maintained.
Conclusion
No claims are allowed.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/GL/
Patent Examiner
Art Unit 1686
/Anna Skibinsky/
Primary Examiner, AU 1635