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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 6/18/2026 has been entered.
Response to Arguments/Amendments
Applicant’s amendments overcome the previous 112 rejections. Therefore, the previous 112 rejections have been withdrawn.
In light of Applicant’s amendments, after further search and consideration, a new 103 rejection has been made.
Also, in light of Applicant’s amendments since the nonfinal rejection mailed 1/16/2026, claim 7 is now considered as containing allowable subject matter (see below for further details).
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.
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.
Claims 1, 18, 21, 24, 42-45, and 48-52 are rejected under 35 U.S.C. 103 as being obvious over Owsley (US 20200209064 A1; cited by Applicant) in view of Mage (US 20220091017 A1; cited by Applicant).
Regarding claim 1, Owsley teaches a method comprising:
irradiating with a light source particles of a sample comprising a plurality of fluorophores having overlapping fluorescence spectra in a flow stream (paragraphs 59 and 81);
detecting light with a light detection system comprising a plurality of photodetectors from the irradiated particles of the sample (paragraphs 82);
determining a measurement variance comprising a baseline sampling variance and detector signal intensity in the detected light for the sample of particles for each photodetector (paragraph 9 and claims 1-3);
spectrally resolving light from each fluorophore in the sample with a weighted least squares algorithm that uses a weighting component that is calculated from the baseline sampling variance and the detector signal intensity determined for the sample of particles (claims 1-3 and paragraphs 21
detecting light with a light detection system from particles of a sample comprising a plurality of fluorophores having overlapping fluorescence spectra (claim 1);
determining measurement variance in the detected light for each particle (claim 3; figure 2; paragraphs 9 and 33 explain that the variance is determined/estimated; note: as noted on page 48 of Applicant’s specification filed 12/12/2023, measurement variance refers to variations during data acquisition such as variations in light detection, and so it includes variance of the detector that is used for measurements such as described in the cited paragraphs, figures, and claims; regarding “for each particle,” the following two points are noted: 1) since the variance is the variance at every photodetector, including all the photodetectors that detect light from all the particles, this form of measurement variance is for each and every particle; 2) see “for each particle” and “for each cell [particle]” in the claims and in paragraph 39, which describes that the weighted least square algorithm [which includes the variances] is for each particle; also see “the variance of the photodetector is proportional to measured intensity of light by the photodetector” in paragraph 21);
spectrally resolving light from each fluorophore in the sample with a weighted least squares algorithm that uses the measurement variance determined for each particle (claims 1-3).
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Owsley doesn’t explicitly teach the measurement variance baseline sampling variance are changes in the measurement variance baseline sampling variance.
However, Owsley teaches calculating the weighted least square algorithm (which includes the measurement variance) for each particle (paragraphs 169 and 44) and teaches that performing the calculations and algorithms for each particle provides the benefit of sorting particles in real time (paragraphs 8 and 44). Additionally, Mage is directed to a similar invention and teaches determining a change in measurement variance comprising a change in baseline sampling variance (paragraphs 65-66; baseline noise described in paragraphs 65-66 is implicitly a measure of baseline sampling variance, as described in paragraphs 65-66) and spectrally resolving light from each fluorophore in the sample with a weighted least squares algorithm that uses a weighting component that is calculated from the change in baseline sampling variance (paragraphs 67 and 70; figure 1). Additionally, Mage teaches updating the determined variances before repeatedly both before and in between particle measurements (paragraphs 65-67).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the above method such that it comprises determining a change in measurement variance comprising a change in baseline sampling variance and detector signal intensity variance in the detected light for the sample of particles for each photodetector; and spectrally resolving light from each fluorophore in the sample with a weighted least squares algorithm that uses a weighting component that is calculated from the change in baseline sampling variance and the detector signal intensity variance determined for the sample of particles – in order to have updated measures of measurement variance that take into account changing measurement conditions and particle attributes and thus provide more accurate measurements.
Regarding claim 2, Owsley teaches the light detection system comprises a plurality of photodetectors and the measurement variance for each particle is determined for each photodetector (claim 3).
Regarding claim 18, Owsley teaches the fluorescence spectra of each fluorophore overlaps with the fluorescence spectra of at least one other fluorophore in the sample (paragraph 56).
Regarding claim 21, Owsley teaches the fluorescence spectra of at least one fluorophore in the sample overlaps with the fluorescence spectra of two different fluorophores in the sample (paragraphs 56 and 178).
Regarding claim 24, Owsley teaches the method comprises calculating a spectral unmixing matrix for the fluorescence spectra of each fluorophore in the sample using the weighted least squares algorithm (claims 1-2 and 12).
Regarding claim 42, Owsley teaches the weighted least squares algorithm is calculated by matrix decomposition (claim 9).
Regarding claim 43, Owsley teaches the matrix decomposition comprises LU decomposition (claim 9).
Regarding claim 44, Owsley teaches the weight least squares algorithm using the measurement variance is calculated on a field programmable gated array (abstract and figure 1).
Regarding claim 45, Owsley teaches irradiating the sample with a light source (claim 6).
Regarding claim 48, Owsley teaches the light detection system comprises a plurality of photodetectors (claim 3).
Regarding claims 49-52, Owsley teaches the photodetectors comprise one or more photomultiplier tubes; the light detection system comprises a photodetector array; the photodetector array comprises photodiodes; the photodetector array comprises charge coupled devices (paragraph 189).
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Owsley as applied to claim 1 above, and further in view of Ilkov (US 2021/0325289 A1; cited by Applicant).
Regarding claim 3, Owsley doesn’t explicitly teach the measurement variance comprises a change in a photodetector gain parameter in one or more of the photodetectors of the light detection system.
However, Owsley teaches measuring the variance in the photodetector (claim 3). Additionally, Ilkov is directed to a similar flow cytometer and is directed to a similar detection using fluorescence and teaches that the detector related variances that contribute to signa variances include a change in the detector gain parameter in one or more of the photodetectors of the light detection system (paragraph 60).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the above combinaton such that the measurement variance comprises a change in a photodetector gain parameter in one or more of the photodetectors of the light detection system in order to account for additional sources of detector variations that contribute to variations in the signal.
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Owsley as applied to claim 1 above, and further in view of Fox (CN 108027362 A).
Regarding claim 4, Owsley doesn’t explicitly teach the measurement variance comprises a change in a trigger threshold parameter for one or more of the photodetectors of the light detection system.
Like Fox (and like Applicant), Owsley is also directed to optical measurements of particles and to flow cytometry and to fluorescence measurements and teaches that a change of trigger threshold for one or more of the photodetectors of the light detection system leads to changes in measurement variance (pages 5-6 of attached translation).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the above combination such that the measurement variance comprises a change in a trigger threshold parameter for one or more of the photodetectors of the light detection system in order to ensure the determined measurement variance remains accurate after changes in trigger threshold.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Owsley as applied to claim 1 above, and further in view of Lee (CN 101720430 A).
Regarding claim 5, Owsley doesn’t explicitly teach the measurement variance comprises a change in light detection duration parameter for each photodetector for each particle.
Like Owsley (and like Applicant), Lee is also directed to an optical measurement method using fluorescence and teaches that changes in a light detection duration parameter for a photodetector (exposure time) leads to changes in measurement variance (thermal noise; paragraphs 11-12).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the above combination such that the measurement variance comprises a change in light detection duration parameter for each photodetector for each particle in order to ensure the determined measurement variance remains accurate after changes in light detection duration parameter.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Owsley as applied to claim 1 above, and further in view of Kanarowski (US 20140340482 A1).
Regarding claim 6, Owsley doesn’t explicitly teach the measurement variance comprises a change in a photonic shot noise parameter detected by each photodetector for each particle.
However, Owsley teaches the measurement comprises a noise parameter detected by each photodetector for each particle (claim 3). Additionally, like Owsley (and like Applicant), Kanarowski is directed to a method for detecting particles and fluorescent measurements and teaches that when taking into account the noise of photodetectors, taking into a photonic shot noise parameter provides the benefit of being more accurate, especially for sufficiently high photon counts (paragraph 91).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the above combination such that the measurement variance comprises a change in a photonic shot noise parameter detected by each photodetector for each particle in order to obtain a more accurate determination of variance, especially when dealing with high photon counts.
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Owsley as applied to claim 1 above, and further in view of Hsu (US 20140150545 A1).
Regarding claim 17, Owsely doesn’t explicitly teach the measurement variance is determined for each particle for each photodetector in real-time.
However, Owsely teaches performing the algorithms in real time (paragraph 8). Additionally, Hsu is also directed to optical measurements and provides a general teaching of determining measurement variances in real-time (paragraph 76).
It would be obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the above combination such that the measurement variance is determined for each particle for each photodetector in real-time in order to provide accurate, real-time sorting of the particles.
Allowable Subject Matter
Claim 7 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter: The prior art of record (taken alone or in combination) fails to anticipate or render obvious, “irradiating with a light source particles of a sample comprising a plurality of fluorophores having overlapping fluorescence spectra in a flow stream; detecting light with a light detection system comprising a plurality of photodetectors from the irradiated particles of the sample; determining a change in measurement variance comprising a change in baseline sampling variance and detector signal intensity variance in the detected light for the sample of particles for each photodetector; spectrally resolving light from each fluorophore in the sample with a weighted least squares algorithm that uses a weighting component that is calculated from the change in baseline sampling variance and the detector signal intensity variance determined for the sample of particles … the measurement variance is calculated for each particle according to: V= (L x T) + (Q x Y), wherein: L is baseline sampling variance for each photodetector; T is measurement duration for each sampling pulse; Q is a photoelectron scaling factor; and Y is photodetector signal intensity,” in combination with the other claimed limitations.
Additional Prior Art
Novo (US 20130346023 A1) Reads, “[0067] A variety of techniques for unmixing fluorescence emission signals are discussed below including (but limited to) processes that approximate fluorochrome abundances utilizing a percentage error estimation via weighted least squares (WLS),” [0068] In several embodiments, the unmixing process assumes that the observations came from a normal distribution. However, an additional assumption is made that signal variance in the Gaussian model grows with signal intensity. Consequently, measurements with lower variance have proportionally more influence on abundance estimates than measurements with higher variance. In a number of embodiments, the unmixing process involves performing a percentage errors minimization process.
20210325289 reads “variance and coefficient of variation of the signal amplitude. (paragraph 8)
WO 2022117695 A1 reads, “Camera characterization may be done following the approach of Huang et al. [7] and Diekmann et al. [8], For dark pixel offset, and read noise measurements, it is ensured that the camera chip is in darkness during the acquisition of 2000 frames. The baseline (offset) for each pixel is determined by the mean value per pixel and the read noise by the standard deviation over all frames. Single pixel gain is estimated as follows: (a) measuring a sequence of 2000 frames for a series of exposure times by directly shining light on the objective (starting with 1 ms up to 20 ms exposure, (b) for each exposure time, calculating the variance and the mean, (c) calculating the camera gain (e-/grey level) from the variance and the mean (both per pixel) by regression using the following equation: x — offset Gain = - variance — a where x is the mean of the sequence of frames taken at the first step, variance contains the full noise (camera read noise + Poisson shot noise), and a is the variance of the camera read noise, offset relates to the baseline of each pixel as elaborated above. The measured signal is transformed to photoelectrons by subtracting the measured offset value and dividing by the measured camera gain.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RUFUS L PHILLIPS whose telephone number is (571)270-7021. The examiner can normally be reached M-Th, 2 -10 pm.
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/RUFUS L PHILLIPS/ Examiner, Art Unit 2877
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