Response to Arguments
Applicant’s arguments submitted on 2/11/2026 have been fully considered.
First, Applicant argues that the claims are patent eligible, because reading a machine-readable identifier cannot be performed by the human mind. Examiner respectfully disagrees. The broadest reasonable interpretation, in light of the Specification, by a person of ordinary skill in the art of machine-readable identifier comprises mere numbers/numeric identifiers that a human mind can observe and process. Furthermore, the newly claimed “wherein providing the mask comprises reading a machine-readable identifier associated with the microfluidic chip and retrieving the mask corresponding to said identifier, wherein the mask comprises a pre-determined data set generated prior to step (a) that identifies defective partitions” is insignificant pre-solution activity where a person can simply use the observed numeric identifier to retrieve an associated image of a mask for use in other steps. Therefore, this limitation cannot be considered an improvement, and the claims are not currently patent eligible.
Second, Applicant argues that the prior does not disclose the newly added amendments to the independent claims. Examiner cites new prior art herein below that renders obvious the newly added claim amendments.
Claim Interpretation
The claim interpretation under 35 U.S.C. 112(f) is withdrawn in response to Applicant’s amendments.
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.
Claim(s) 1-4, 7-11, and 13 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to the abstract idea of a mental process without significantly more.
Claim 1 recite(s) a “providing” and “applying” steps that can be performed mentally by looking at an image and marking as the mask which partitions are defective; and the “generating” step can be performed mentally by ignoring the defective partitions and judging the results for the non-defective partitions. This judicial exception is not integrated into a practical application because the “generating” step is merely insignificant extra-solution activity of data gathering; and the “partitions of a microfluidic chip” simply link the use of the abstract idea to the environment of microscopic sample processing. Furthermore, the newly claimed “wherein providing the mask comprises reading a machine-readable identifier associated with the microfluidic chip and retrieving the mask corresponding to said identifier, wherein the mask comprises a pre-determined data set generated prior to step (a) that identifies defective partitions” is insignificant pre-solution activity where a person can see and mentally understand a numeric identifier, and then use the numeric identifier to retrieve an associated image of a mask for use in other steps. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception for the same reasons.
Claim 2 recites further steps that can be done mentally.
Claim 3 recites further steps that can be done mentally.
Claim 4 recites further steps that can be done mentally.
Claim 7 recites limitations that simply link the use of the abstract idea to the environment of digital polymerase chain reactions.
Claim 8 recites the insignificant extra-solution activity of storing and/or retrieving data.
Claim 9 recites further steps that can be done mentally.
Claim 10 recites applying the abstract idea with mere generic computer components.
Claim 11 is rejected under the same analysis as claim 1 above, and further recites applying the abstract idea using mere generic computer components, such as a processor and optical sensor.
Claim 13 is rejected under the same analysis as claim 1 above, and further recites applying the abstract idea using mere generic computer components.
Claim Rejections - 35 USC § 102
The rejections under this statute are hereby withdrawn in response to Applicant’s amendments.
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.
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, 2, 4, 10, 11, and 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kurabayashi et al., US 2022/0397528 A1 (hereinafter referred to as “Kurabayashi”) in view of Medoro et al., US 2013/0343966 A1 (hereinafter referred to as “Medoro”) and Chiu et al., US 2021/0308673 A1 (hereinafter referred to as “Chiu”).
Regarding claim 1, Kurabayashi discloses a method for compensating defective partitions of a microfluidic chip, wherein the microfluidic chip comprises at least one array of partitions (see Kurabayashi paras. 0019, 0040, 0117, 0191, 0219, and 0222, where defects in images of partition wells of a microfluidic chip are detected), wherein the method comprises the following steps:
a) generating image data of the microfluidic chip comprising a sample by imaging the microfluidic chip using at least one imaging device (see Kurabayashi paras. 0019, 0032, and 0114, where a camera is used to image the microfluidic chip);
b) providing at least one mask for at least one area of the array of partitions to at least one data processing unit (see Kurabayashi Fig. 25, and paras. 0040, 0117, 0187, 0212, 0222, and 0225-0228, where image masks are used), wherein providing the mask comprises retrieving the mask, wherein the mask comprises a pre-determined data set that identifies defective partitions (see Kurabayashi Fig. 25, and paras. 0040, 0117, 0187, 0212, 0222, and 0225-0228, where image masks are obtained beforehand during CNN training, or during software execution, or during human supervision, and the masks show areas with defects);
c) applying the mask, using the data processing unit, to one or more of the image data, at least one feature extracted from the image data, or at least one value extracted from the image data, thereby generating masked data, wherein the applying of the mask comprises masking each partition of the array depending on the mask (see Kurabayashi Fig.25, and paras. 0040, 0117, 0187, 0212, 0222, and 0225-0228, where image masks are used to remove defects and extract target signals);
d) generating at least one analytical result for the sample using said masked data (see Kurabayashi paras. 0188 and 0235-0239, where statistics and concentrations are generated for the extracted target signal).
Kurabayashi does not explicitly disclose wherein providing the mask comprises reading a machine-readable identifier associated with the microfluidic chip and retrieving the mask corresponding to said identifier, wherein the mask comprises a pre-determined data set generated prior to step (a).
However, Medoro discloses wherein providing the mask comprises retrieving the mask, wherein the mask comprises a pre-determined data set generated prior to step (a) that identifies defective partitions (see Medoro Abstract and paras. 0051-0055, where information comprising a mapping of the faulty areas of the microfluidic device is pre-determined at the time of testing and stored in memory).
It would have been obvious to one of ordinary skill in the art before the effective filing date to the teaching of Medoro of testing and recording faulty areas/partitions on Kurabayashi’s microfluidic chip, because it is predictable that doing so would improve the speed and accuracy of the use of the microfluidic chip by avoiding known faulty areas/partitions.
Furthermore, Chiu discloses wherein providing the data set comprises reading a machine-readable identifier associated with the microfluidic chip and retrieving the data set corresponding to said identifier (see Chiu paras. 0163 and 0304, where a barcode reader reads a barcode attached to the microfluidic cartridge and fetches associated information including defectiveness information).
It would have been obvious to one of ordinary skill in the art before the effective filing date to use the barcodes of Chiu to organize the masks/mappings of Kurabayashi, as modified by Medoro, because it is predictable that organizing the masks/mappings with unique barcode identifiers would improve the speed and accuracy of retrieval by pointing directly to where the correct mask/mapping is stored in memory.
Regarding claim 2, Kurabayashi discloses wherein the mask is a data set for inclusion, exclusion and/or weighting partitions of the array (see Kurabayashi Fig. 25, and paras. 0040, 0117, 0187, 0212, 0222, and 0225-0228, where image masks are used to remove defects and extract target signals).
Regarding claim 4, Kurabayashi discloses wherein the mask is an array specific mask or a mask per lot (see Kurabayashi Fig. 25, and paras. 0040, 0117, 0187, 0212, 0222, and 0225-0228, where image masks are associated with an array).
Regarding claim 10, Kurabayashi discloses wherein the method is computer-implemented (see Kurabayashi paras. 0127-0130, where a computer is used).
Regarding claim 11, Kurabayashi discloses a sample processing system configured for processing a sample on at least one microfluidic chip (see Kurabayashi Abstract, and paras. 0006-0010 and 0019, where samples on a microfluidic chip are processed), wherein the sample processing system is configured for performing the method according to claim 1, wherein the microfluidic chip comprises at least one array of partitions (see Kurabayashi paras. 0019, 0040, 0117, 0191, 0219, and 0222, where defects in images of partition wells of a microfluidic chip are detected), the sample processing system comprising:
a. at least one optical sensor configured for generating image data of the microfluidic chip comprising a sample by imaging the microfluidic chip (see Kurabayashi paras. 0019, 0032, and 0114, where a camera is used to image the microfluidic chip); and
b. at least one processor (see Kurabayashi para. 0229, “CPU: Intel Core i7-8700”) configured for providing at least one mask for the microfluidic chip, wherein the processor is configured to retrieve the mask associated with the microfluidic chip, wherein the mask comprises a pre-determined data set that identifies defective partitions (see Kurabayashi Fig. 25, and paras. 0040, 0117, 0187, 0212, 0222, and 0225-0228, where image masks are obtained beforehand during CNN training, or during software execution, or during human supervision, and the masks show areas with defects), wherein the processor is configured for applying the mask to one or more of the image data, at least one feature extracted from the image data, or at least one value extracted from the image data, thereby generating masked data, and wherein the applying of the mask comprises masking each partition of the array depending on the mask (see Kurabayashi Fig. 25, and paras. 0040, 0117, 0187, 0212, 0222, and 0225-0228, where image masks are used to remove defects and extract target signals);
wherein the sample processing system is further configured for generating at least one analytical result for the sample using said masked data (see Kurabayashi paras. 0188 and 0235-0239, where statistics and concentrations are generated for the extracted target signal).
Kurabayashi does not explicitly disclose the mask based on a machine-readable identifier associated with the microfluidic chip, wherein the mask comprises a pre-determined data set generated prior to generation of the image data.
However, Medoro discloses retrieve the mask, wherein the mask comprises a pre-determined data set generated prior to generation of the image data that identifies defective partitions (see Medoro Abstract and paras. 0051-0055, where information comprising a mapping of the faulty areas of the microfluidic device is pre-determined at the time of testing and stored in memory).
It would have been obvious to one of ordinary skill in the art before the effective filing date to the teaching of Medoro of testing and recording faulty areas/partitions on Kurabayashi’s microfluidic chip, because it is predictable that doing so would improve the speed and accuracy of the use of the microfluidic chip by avoiding known faulty areas/partitions.
Furthermore, Chiu discloses retrieve the data set based on a machine-readable identifier associated with the microfluidic chip (see Chiu paras. 0163 and 0304, where a barcode reader reads a barcode attached to the microfluidic cartridge and fetches associated information including defectiveness information).
It would have been obvious to one of ordinary skill in the art before the effective filing date to use the barcodes of Chiu to organize the masks/mappings of Kurabayashi, as modified by Medoro, because it is predictable that organizing the masks/mappings with unique barcode identifiers would improve the speed and accuracy of retrieval by pointing directly to where the correct mask/mapping is stored in memory.
Regarding claim 13, Kurabayashi discloses a non-transitory computer-readable storage medium comprising instructions which, when the instructions are executed by a sample processing system, cause the sample processing system to perform the method according to claim 1 (see Kurabayashi paras. 0127-0130, where computer software stored in computer readable memory and executed by the computer is disclosed).
Claim(s) 3 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kurabayashi in view of Medoro and Chiu as applied to claim 1 above, and in further view of Unno, US 7,024,281 B1 (hereinafter referred to as “Unno”).
Regarding claim 3, Kurabayashi discloses wherein the mask comprises partitions (see Kurabayashi Fig. 25, and paras. 0040, 0117, 0187, 0212, 0222, and 0225-0228, where image masks are used to show which partitions are defective, and another mask is used to show which partitions are in a valid “On” state).
Kurabayashi does not explicitly disclose a list of partitions and/or a range of partitions.
However, Unno discloses wherein the mask comprises a list of partitions and/or a range of partitions (see Unno Figs. 3, 11, and 12, and col. 6, lls. 11-30, and col. 7, lls. 49-58, and col. 10, lls. 19-50, and col. 28, ll. 30 through col. 30, ll. 28, where the partition mask comprises a list of partitions, and the partition patterns comprise various ranges).
It would have been obvious to one of ordinary skill in the art before the effective filing date to use the partition tracking and ordering technique of Unno to track the defective and/or valid partitions of Kurabayashi, as modified by Medoro and Chiu, and then choose the most optimal order for sample processing, because it is predictable that doing so would improve efficiency and accuracy of the sample processing (see Unno col. 6, lls. 11-30).
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kurabayashi in view of Medoro and Chiu as applied to claim 1 above, and in further view of Gupta et al., US 2020/0087740 A1 (hereinafter referred to as “Gupta”).
Regarding claim 7, Kurabayashi discloses wherein a first fluorescence channel is used for analysis of the sample and a second fluorescence channel is used for pre-determining or generating the mask (see Kurabayashi paras. 0109-0117, where fluorescence tags are used both to detect the presence of a capture agent for a “On” state validity mask, and also to detect the presence of a detection agent for sample analysis).
Kurabayashi does not explicitly disclose wherein the method further comprises conducting a digital polymerase chain reaction assay.
However, Gupta discloses wherein the method further comprises conducting a digital polymerase chain reaction assay (see Gupta para. 0014, where digital PCR is disclosed), wherein a first fluorescence channel is used for analysis of the sample and a second fluorescence channel is used for pre-determining or generating the mask (see Gupta paras. 0084, 0092, and 0123, where fluorescence is used to detect successful amplification for validity, and also fluorescence is used to detect molecule presence and quantity for sample analysis).
It would have been obvious to one of ordinary skill in the art before the effective filing date to apply the masking and processing techniques of Kurabayashi, as modified by Medoro and Chiu, to the dPCR assay of Gupta, because it is predictable that doing so would improve the versatility of Kurabayashi’s sample analysis by permitting both dELISA and dPCR assays to be used in sample analysis on microfluidic chips, and thereby handle many more types of sample analysis.
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kurabayashi in view of Medoro and Chiu as applied to claim 1 above, and in further view of Paczkowski et al., US 2016/0160169 A1 (hereinafter referred to as “Paczkowski”).
Regarding claim 8, Kurabayashi discloses wherein the mask is an algorithmically defined mask, wherein mask parameters and partition indices of the mask are stored in a software of the data processing unit (see Kurabayashi Fig. 25, and paras. 0040, 0117, 0187, 0212, 0222, and 0225-0228, where image masks are used in an algorithm to show which partitions are defective, and another mask is used in an algorithm to show which partitions are in a valid “On” state; see also Kurabayashi paras. 0127-0130, where the software that includes the masks may reside on a computer readable device).
Kurabayashi does not explicitly disclose and at least one corresponding identifier is stored on a barcode of the microfluidic chip, or wherein mask parameters are directly stored in a barcode of the microfluidic chip and indices of the partitions of the mask are calculated by a software of the data processing unit based on a model and the parameters from the barcode.
However, Paczkowski discloses wherein the mask is an algorithmically defined mask (see Paczkowski paras. 0102 and 0133, where “analyte patterns 142 may be detected using multiple wavelengths or imaging/scan modes” where an algorithm for multiplexing patterns is involved in generating and/or reading the mask), wherein mask parameters and partition indices of the mask are stored in a software of the data processing unit and at least one corresponding identifier is stored on a barcode of the microfluidic chip, or wherein mask parameters are directly stored in a barcode of the microfluidic chip and indices of the partitions of the mask are calculated by a software of the data processing unit based on a model and the parameters from the barcode (see Paczkowski Fig. 1B and 1C, and paras. 0070, 0071, 0075-0079, 0102, and 0133, where barcode pattern 142 comprises both itself an identifier of a pattern and/or itself multiple mask parameters forming a pattern, such that an alignment model that may comprise additional mask parameters is used to identify partitions; see also Paczkowski paras. 0185 and 0192 where the algorithms and data are stored in databases and in memory).
It would have been obvious to one of ordinary skill in the art before the effective filing date to use the barcode and image alignment technique of Paczkowski to identify the masks of Kurabayashi, as modified by Medoro and Chiu, because it is predictable that doing so would help ensure and/or confirm the correct mask was used with each partition array by having mask information immediately available and present with each partition array, and cross-referencing the information if confirmation is needed/desired by the user. Paczkowski further states that “[t]hese methods can be helpful in resolving or distinguishing useable data with increased accuracy and improved quantification capabilities from the sample array 122” (see Paczkowski para. 0094).
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kurabayashi in view of Medoro and Chiu as applied to claim 1 above, and in further view of Tzonev, US 2013/0059754 A1 (hereinafter referred to as “Tzonev”).
Regarding claim 9, Kurabayashi discloses number of valid partitions after applying the mask (see Kurabayashi Fig. 25, and paras. 0040, 0117, 0187, 0212, 0222, and 0225-0228, where image masks are used to remove defects and extract target signals).
Kurabayashi does not explicitly disclose wherein the method further comprises flagging an analysis if a fraction and/or number of valid partitions is lower than a pre-defined minimum fraction and/or minimum number of valid partitions.
However, Tzonev discloses wherein the method further comprises flagging an analysis if a fraction and/or number of valid partitions is lower than a pre-defined minimum fraction and/or minimum number of valid partitions (see Tzonev paras. 0016 and 0052, where the result is flagged for a re-run if the preferred conditions are not met, including there being a minimum number of sample partitions and/or preferred concentration present).
It would have been obvious to one of ordinary skill in the art before the effective filing date to use the re-run determination technique of Tzonev in the sample processing of Kurabayashi, as modified by Medoro and Chiu, because it is predictable that doing so would improve the robustness and accuracy of the resulting analysis by ensuring adequate samples and/or concentrations are present, thereby reducing measurement uncertainty (see Tzonev para. 0016).
Conclusion
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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/ANDREW M MOYER/ Supervisory Patent Examiner, Art Unit 2675