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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 06/26/2025 has been entered.
Claim Rejections - 35 USC § 102
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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
Claim(s) 16, 18, 20, 22, 24, 26, 30, 33 is/are rejected under 35 U.S.C. 102a1/a2 as being anticipated by Cho et al. (US 2015/0268244).
Regarding claim 16, Cho et al. teach:
16. An apparatus (e.g., microfluidic detector 1600/1600’) capable of calculating a co-localization parameter (e.g., space-time coded output signal or time domain signal 2130, 2132; spacing between peaks 5210a-5210e ¶ 0306; In some embodiments, the peaks 5210a, 5210b are space-time coded signals and establish the reference for the overall fluorescence intensity, so that the fluorescence intensity variations among different particles will not affect its ability to distinguish fluorescent colors. By measuring the time between the first two peaks, the time that the particle P travels from the 1’ detection zone 5012 to the sorting junction can be accurately calculated, enabling for high accuracy sorting. ¶ 0306; intensity values of fluorophores that show fluctuations over a time interval ¶ 0410) for at least two optical signals in a droplet (see i.e., The digital signal then can be processed by a computer processor (e.g., FPGA). Sub-processes 4806, 4807 and 4808 in process 4805 can be carried out by a computer processor. Sub-processes within process 4805 can be carried out as part of Windowed Peak Detection as shown in FIG. 23 in certain embodiments. During signal processing, signals can be processed and waveforms can be analyzed (e.g., all signals and all waveforms can be processed and analyzed). In some embodiments, there can be a threshold calculation phase in which a threshold level is set according to baseline noise (e.g., sub-process 4806). In a second phase, a previously calculated threshold can be used to analyze incoming signals for a waveform/COST signal. The speed of a particle also can be determined based on the location of the peaks (e.g., sub-process 4806). For peak detection, a waveform can be analyzed to identify peaks (e.g., sub-process 4806), and peak parameters (e.g., amplitude, time, area; sub-process 4807). ¶ 0272), comprising:
a detection assembly (e.g., particle detection module 1612/1612’) capable of measuring, for a droplet, at least two optical signals (see ¶ 0186-0188 & Figs. 16A-16C for example), each optical signal capable of being representative of a light intensity spatial distribution in the droplet for an associated wavelength channel (see i.e., a particle in a fluidic channel can interact with light introduced into a channel, and light that has interacted with the particle and can be scattered, reflected or diffracted by the particle can be transmitted from the channel to one or more other components in a microfluidic detector ¶ 0157; see also ¶ 0216-0217, Figs. 21A-21B; The spatial filter can be designed to purposefully coincide with the image plane after magnification. As fluorescent particle passes through detection slits and gets sorted down to the verification slits, the PMT detector is expected to register signals of 3 peaks followed by 2 peaks. ¶ 0244; and Figs. 49A-49B for example), and
a calculator (e.g., computer 1718, computing apparatus 6504) capable of calculating a plurality of parameters from the at least two optical signals (see i.e., The PMT 1714 upon sensing of the light in turn output signals indicative of the sensed light to National Instruments LabView-based software 1716 (available from National Instruments Corp. of Austin, Tex.), which in turn provides data to personal computer 1718 (notwithstanding the representation provided in FIG. 14, the software 1716 can be considered implemented on the personal computer). In the embodiment in FIG. 17 and at least some other embodiments, multiple parameter detection is achieved by applying COlor-Space-Time (COST) coding technology. Multiple parameter detection is of greater interest when it allows for detection of 12 or more different fluorescent wavelengths of light emanating from the microfluidic detector 1710 of any of the embodiments described and illustrated herein. In the embodiment of FIG. 17, it is the microfluidic detector 1710 can support detection of multiple (e.g., 20 or more) fluorescent wavelengths of light emanating from a microfluidic detector using a single detector. ¶ 0197-0198; The digital signal then can be processed by a computer processor (e.g., FPGA). Sub-processes 4806, 4807 and 4808 in process 4805 can be carried out by a computer processor. Sub-processes within process 4805 can be carried out as part of Windowed Peak Detection as shown in FIG. 23 in certain embodiments. During signal processing, signals can be processed and waveforms can be analyzed (e.g., all signals and all waveforms can be processed and analyzed). In some embodiments, there can be a threshold calculation phase in which a threshold level is set according to baseline noise (e.g., sub-process 4806). In a second phase, a previously calculated threshold can be used to analyze incoming signals for a waveform/COST signal. The speed of a particle also can be determined based on the location of the peaks (e.g., sub-process 4806). For peak detection, a waveform can be analyzed to identify peaks (e.g., sub-process 4806), and peak parameters (e.g., amplitude, time, area; sub-process 4807). ¶ 0272; A peak parameter, in some embodiments, can be mapped to a zone in a color filter including zones of overlapping transparency according to one or more peak parameter ratios, which ratios provide for normalized peak parameters (sub-process 4808). Color mapping based on peak parameter ratios (normalized peak parameters) can be applicable to embodiments in which there is one fluorophore or quantum dot per particle (e.g., cell), and to embodiments in which there are multiple fluorophores or quantum dots per particle (e.g., cell), which are described in greater detail herein. Data can be further analyzed and visualized using a visualization tool 4809, which can reside on a personal computer (PC) to ultimately present and identify the fluorescent color(s) and fluorescent intensity emitted from a particle. A visualization tool can be a user interface that permits a user to analyze detection data and/or select certain parameters and functions of a microfluidic detector. A visualization tool in some embodiments allows a user to analyze detection data and identify particular particles or types of particles flowing through the device (e.g., 4811). In some embodiments, a visualization tool allows a user to select parameters for sorting particular particles (e.g., 4810; select gating signal). ¶ 0274; it thereby follows that the trace 5210 can provide at least the following information about the particle P: (1) speed of the particle P. as determined by the spacing between the peaks 5210a-5210e; the faster the particle is moving, the closer the peaks; (2) Overall intensity of the first detection signal, as determined by any combination of the peaks 5210a. 5210b; and (3) Fluorescence information in the first detection signal based on the fluorescence peaks 5210 c-5210 e, such as the fluorescence spectrum of the particle P. It is understood that additional inferences can be drawn from the trace 5210 within embodiments. In some embodiments, the peaks 5210a, 5210b are space-time coded signals and establish the reference for the overall fluorescence intensity, so that the fluorescence intensity variations among different particles will not affect its ability to distinguish fluorescent colors. By measuring the time between the first two peaks, the time that the particle P travels from the 1’ detection zone 5012 to the sorting junction can be accurately calculated, enabling for high accuracy sorting. ¶ 0306; The computing apparatus 6504 includes at least a processor 6512 and a memory 6514, and further includes I/O interfaces 6516 and connection interfaces 6518. The processor 6504 includes an acquisition module 6520, a first detection module 6522, a sorting module 6526, a second detection module 6528, and a verification module 6532. ¶ 0353; the first detection module 6522 is configured to receive a first detection signal from the first detection device 6506 associated with one or more optical characteristics of a particle in a first channel of the channel assembly 6502. ¶ 0355; see also Example 4 Color Compensation for the Color-Space-Time (Cost) Cytometer System [...] ¶ 0397-0410),
wherein the plurality of parameters comprises a distance between a coordinate of a maximum intensity for each of the at least two optical signals, wherein the distance is the co-localization parameter for the at least two optical signals (see i.e., For peak detection, a waveform can be analyzed to identify peaks (e.g., sub-process 4806), and peak parameters (e.g., amplitude, time, area; sub-process 4807). ¶ 0272; In some embodiments, the peaks 5210 a, 5210 b are space-time coded signals and establish the reference for the overall fluorescence intensity, so that the fluorescence intensity variations among different particles will not affect its ability to distinguish fluorescent colors. By measuring the time between the first two peaks, the time that the particle P travels from the 1’ detection zone 5012 to the sorting junction can be accurately calculated, enabling for high accuracy sorting. ¶ 0306; intensity values of fluorophores that show fluctuations over a time interval ¶ 0410);
wherein the calculator comprises a processor and a memory (see i.e., The computing apparatus 6504 includes at least a processor 6512 and a memory 6514 ¶ 0353; see also a processor and a memory of the personal computer 1718 ¶ 0197) comprising software (e.g., 1716 ¶ 0197; real-time signal processing algorithm ¶ 1777; real-time electronic control and signal processing algorithms ¶ 0193; computer-executable instructions ¶ 0321+; a computer storage product with a non-transitory computer-readable medium (also referred to as a non-transitory processor-readable medium) has instructions or computer code thereon for performing various computer-implemented operations ¶ 0435; see also ¶ 0226-0227, 0231+), which when executed by the processor, the calculator is capable of calculating the plurality of parameters for the at least two optical signals, including the co-localization parameter for the at least two optical signals (see i.e., The PMT 1714 upon sensing of the light in turn output signals indicative of the sensed light to National Instruments LabView-based software 1716 (available from National Instruments Corp. of Austin, Tex.), which in turn provides data to personal computer 1718 (notwithstanding the representation provided in FIG. 14, the software 1716 can be considered implemented on the personal computer). In the embodiment in FIG. 17 and at least some other embodiments, multiple parameter detection is achieved by applying COlor-Space-Time (COST) coding technology. Multiple parameter detection is of greater interest when it allows for detection of 12 or more different fluorescent wavelengths of light emanating from the microfluidic detector 1710 of any of the embodiments described and illustrated herein. In the embodiment of FIG. 17, it is the microfluidic detector 1710 can support detection of multiple (e.g., 20 or more) fluorescent wavelengths of light emanating from a microfluidic detector using a single detector. ¶ 0197-0198; The digital signal then can be processed by a computer processor (e.g., FPGA). Sub-processes 4806, 4807 and 4808 in process 4805 can be carried out by a computer processor. Sub-processes within process 4805 can be carried out as part of Windowed Peak Detection as shown in FIG. 23 in certain embodiments. During signal processing, signals can be processed and waveforms can be analyzed (e.g., all signals and all waveforms can be processed and analyzed). In some embodiments, there can be a threshold calculation phase in which a threshold level is set according to baseline noise (e.g., sub-process 4806). In a second phase, a previously calculated threshold can be used to analyze incoming signals for a waveform/COST signal. The speed of a particle also can be determined based on the location of the peaks (e.g., sub-process 4806). For peak detection, a waveform can be analyzed to identify peaks (e.g., sub-process 4806), and peak parameters (e.g., amplitude, time, area; sub-process 4807). ¶ 0272; A peak parameter, in some embodiments, can be mapped to a zone in a color filter including zones of overlapping transparency according to one or more peak parameter ratios, which ratios provide for normalized peak parameters (sub-process 4808). Color mapping based on peak parameter ratios (normalized peak parameters) can be applicable to embodiments in which there is one fluorophore or quantum dot per particle (e.g., cell), and to embodiments in which there are multiple fluorophores or quantum dots per particle (e.g., cell), which are described in greater detail herein. Data can be further analyzed and visualized using a visualization tool 4809, which can reside on a personal computer (PC) to ultimately present and identify the fluorescent color(s) and fluorescent intensity emitted from a particle. A visualization tool can be a user interface that permits a user to analyze detection data and/or select certain parameters and functions of a microfluidic detector. A visualization tool in some embodiments allows a user to analyze detection data and identify particular particles or types of particles flowing through the device (e.g., 4811). In some embodiments, a visualization tool allows a user to select parameters for sorting particular particles (e.g., 4810; select gating signal). ¶ 0274; it thereby follows that the trace 5210 can provide at least the following information about the particle P: (1) speed of the particle P. as determined by the spacing between the peaks 5210a-5210e; the faster the particle is moving, the closer the peaks; (2) Overall intensity of the first detection signal, as determined by any combination of the peaks 5210a. 5210b; and (3) Fluorescence information in the first detection signal based on the fluorescence peaks 5210 c-5210 e, such as the fluorescence spectrum of the particle P. It is understood that additional inferences can be drawn from the trace 5210 within embodiments. In some embodiments, the peaks 5210a, 5210b are space-time coded signals and establish the reference for the overall fluorescence intensity, so that the fluorescence intensity variations among different particles will not affect its ability to distinguish fluorescent colors. By measuring the time between the first two peaks, the time that the particle P travels from the 1’ detection zone 5012 to the sorting junction can be accurately calculated, enabling for high accuracy sorting. ¶ 0306; The computing apparatus 6504 includes at least a processor 6512 and a memory 6514, and further includes I/O interfaces 6516 and connection interfaces 6518. The processor 6504 includes an acquisition module 6520, a first detection module 6522, a sorting module 6526, a second detection module 6528, and a verification module 6532. ¶ 0353; the first detection module 6522 is configured to receive a first detection signal from the first detection device 6506 associated with one or more optical characteristics of a particle in a first channel of the channel assembly 6502. ¶ 0355; see also Example 4 Color Compensation for the Color-Space-Time (Cost) Cytometer System [...] ¶ 0397-0410 for example).
Regarding claim 1, Cho et al. meet all the structural limitations recited by the instant invention. Applicants’ preamble recites “that calculates a co-localization parameter for at least two optical signals in a droplet”. A preamble is generally not accorded any patentable weight where it merely recites the purpose of a process or the intended use of a structure. With regard to limitations in claims 16, 20, 22, 24, 26, 30 (e.g., [...] for a droplet, at least two optical signals, each optical signal being representative of a light intensity spatial distribution in the droplet for an associated wavelength channel, and [...] that calculates a plurality of parameters from the at least two optical signals, wherein the plurality of parameters comprises a distance between a coordinate of a maximum intensity for each of the at least two optical signals, wherein the distance is the co-localization parameter for the at least two optical signals, etc.), these claim limitations are considered process or intended use limitations, which do not further delineate the structure of the claimed apparatus from that of the prior art. The cited prior art teaches all of the positively recited structure of the claimed apparatus. The Courts have held that a statement of intended use in an apparatus claim fails to distinguish over a prior art apparatus. See In re Sinex, 309 F.2d 488, 492, 135 USPQ 302, 305 (CCPA 1962). The Courts have held that the manner of operating an apparatus does not differentiate an apparatus claim from the prior art, if the prior art apparatus teaches all of the structural limitations of the claim. See Ex Parte Masham, 2 USPQ2d 1647 (BPAI 1987). The Courts have held that apparatus claims must be structurally distinguishable from the prior art in terms of structure, not function. See In re Danley, 120 USPQ 528, 531 (CCPA 1959); and Hewlett-Packard Co. V. Bausch and Lomb, Inc., 15 USPQ2d 1525, 1528 (Fed. Cir. 1990) (see MPEP §§ 2114 and 2173.05(g)).
Regarding claims 18, 20, 22, 24, 26, 30, 33, Cho et al. teach:
18. An apparatus according to claim 16, wherein the detection assembly comprises a light source (e.g., 1628/1628’, laser) and at least a visible light sensitive detector (see ¶ 0154, 0179+ for example).
20. An apparatus according to claim 16, wherein the apparatus further comprises a selecting unit (e.g., particle sorter control module 1624/1624’ ¶ 0187+; visualization tool 4809 ¶ 0274; particle sorter 5000 ¶ 0318+) capable of determining a sorting class for the droplet according to at least two parameters of the plurality of parameters (see i.e., In some embodiments, a microfluidic detector includes one or more additional components and/or features. In some embodiments, these can include, for example, an array of integrated lenses that focus light and shorten the interrogation zone to enhance detection throughput. In some embodiments, these features can include flow disturbance minimization, 3D flow confinement and/or cascaded sorting strategies to achieve >1M enrichment factor with minimum cell loss. In some cases these features can include system integration architectures with real-time electronic control and signal processing algorithms to coordinate detection and sorting, enhance sensitivity and minimize sorting error. ¶ 0193; A visualization tool in some embodiments allows a user to analyze detection data and identify particular particles or types of particles flowing through the device (e.g., 4811). In some embodiments, a visualization tool allows a user to select parameters for sorting particular particles (e.g., 4810; select gating signal). ¶ 0274; For some applications, the COST coding method can be applied in two general scenarios according to optical qualities of a sample (e.g., types of fluorophores effectively linked to cells (e.g., via antibodies)). In certain embodiments, a sample contains a mixture of cells or particles and each cell or particle is labeled by one single type of fluorescent dye or quantum dot. For instance, the sample may include a group of antibody-attached beads targeted to a group of specific antigens and each type of antibody-attached bead is uniquely identified by a specific type of fluorophore(s) or quantum dot(s). ¶ 0276; see also the first detection device 5012 can be associated with a larger detection volume (i.e. the first volume) due to more extensive detection techniques, since the first detection signal can form the basis of sorting the particles. The second detection device 5014, on the other hand, can be configured to simply perform a binary classification (i.e., either the particle is present in the second volume, or it is not) ¶ 0332), wherein the at least two parameters comprise the co-localization parameter (see ¶ 0272, 0306, 0410 for example).
22. An apparatus according to claim 18, wherein the apparatus further comprises a selecting unit (e.g., particle sorter control module 1624/1624’ ¶ 0187+; visualization tool 4809 ¶ 0274; particle sorter 5000 ¶ 0318+) capable of determining a sorting class for the droplet according to at least two parameters of the plurality of parameters (see i.e., In some embodiments, a microfluidic detector includes one or more additional components and/or features. In some embodiments, these can include, for example, an array of integrated lenses that focus light and shorten the interrogation zone to enhance detection throughput. In some embodiments, these features can include flow disturbance minimization, 3D flow confinement and/or cascaded sorting strategies to achieve >1M enrichment factor with minimum cell loss. In some cases these features can include system integration architectures with real-time electronic control and signal processing algorithms to coordinate detection and sorting, enhance sensitivity and minimize sorting error. ¶ 0193; A visualization tool in some embodiments allows a user to analyze detection data and identify particular particles or types of particles flowing through the device (e.g., 4811). In some embodiments, a visualization tool allows a user to select parameters for sorting particular particles (e.g., 4810; select gating signal). ¶ 0274; For some applications, the COST coding method can be applied in two general scenarios according to optical qualities of a sample (e.g., types of fluorophores effectively linked to cells (e.g., via antibodies)). In certain embodiments, a sample contains a mixture of cells or particles and each cell or particle is labeled by one single type of fluorescent dye or quantum dot. For instance, the sample may include a group of antibody-attached beads targeted to a group of specific antigens and each type of antibody-attached bead is uniquely identified by a specific type of fluorophore(s) or quantum dot(s). ¶ 0276; see also the first detection device 5012 can be associated with a larger detection volume (i.e. the first volume) due to more extensive detection techniques, since the first detection signal can form the basis of sorting the particles. The second detection device 5014, on the other hand, can be configured to simply perform a binary classification (i.e., either the particle is present in the second volume, or it is not) ¶ 0332), wherein the at least two parameters comprise the co-localization parameter (see ¶ 0272, 0306, 0410 for example).
24. An apparatus according to claim 20, wherein the apparatus further comprises a sorting unit (e.g., particle sorter control module 1624/1624’ ¶ 0187+; visualization tool 4809 ¶ 0274; particle sorter 5000 ¶ 0318+) capable of sorting the droplet according to the sorting class (see i.e., In some embodiments, a microfluidic detector includes one or more additional components and/or features. In some embodiments, these can include, for example, an array of integrated lenses that focus light and shorten the interrogation zone to enhance detection throughput. In some embodiments, these features can include flow disturbance minimization, 3D flow confinement and/or cascaded sorting strategies to achieve >1M enrichment factor with minimum cell loss. In some cases these features can include system integration architectures with real-time electronic control and signal processing algorithms to coordinate detection and sorting, enhance sensitivity and minimize sorting error. ¶ 0193; A visualization tool in some embodiments allows a user to analyze detection data and identify particular particles or types of particles flowing through the device (e.g., 4811). In some embodiments, a visualization tool allows a user to select parameters for sorting particular particles (e.g., 4810; select gating signal). ¶ 0274; For some applications, the COST coding method can be applied in two general scenarios according to optical qualities of a sample (e.g., types of fluorophores effectively linked to cells (e.g., via antibodies)). In certain embodiments, a sample contains a mixture of cells or particles and each cell or particle is labeled by one single type of fluorescent dye or quantum dot. For instance, the sample may include a group of antibody-attached beads targeted to a group of specific antigens and each type of antibody-attached bead is uniquely identified by a specific type of fluorophore(s) or quantum dot(s). ¶ 0276; see also the first detection device 5012 can be associated with a larger detection volume (i.e. the first volume) due to more extensive detection techniques, since the first detection signal can form the basis of sorting the particles. The second detection device 5014, on the other hand, can be configured to simply perform a binary classification (i.e., either the particle is present in the second volume, or it is not) ¶ 0332).
26. An apparatus according to claim 22, wherein the apparatus further comprises a sorting unit (e.g., particle sorter control module 1624/1624’ ¶ 0187+; visualization tool 4809 ¶ 0274; particle sorter 5000 ¶ 0318+) capable of sorting the droplet according to the sorting class (see i.e., In some embodiments, a microfluidic detector includes one or more additional components and/or features. In some embodiments, these can include, for example, an array of integrated lenses that focus light and shorten the interrogation zone to enhance detection throughput. In some embodiments, these features can include flow disturbance minimization, 3D flow confinement and/or cascaded sorting strategies to achieve >1M enrichment factor with minimum cell loss. In some cases these features can include system integration architectures with real-time electronic control and signal processing algorithms to coordinate detection and sorting, enhance sensitivity and minimize sorting error. ¶ 0193; A visualization tool in some embodiments allows a user to analyze detection data and identify particular particles or types of particles flowing through the device (e.g., 4811). In some embodiments, a visualization tool allows a user to select parameters for sorting particular particles (e.g., 4810; select gating signal). ¶ 0274; For some applications, the COST coding method can be applied in two general scenarios according to optical qualities of a sample (e.g., types of fluorophores effectively linked to cells (e.g., via antibodies)). In certain embodiments, a sample contains a mixture of cells or particles and each cell or particle is labeled by one single type of fluorescent dye or quantum dot. For instance, the sample may include a group of antibody-attached beads targeted to a group of specific antigens and each type of antibody-attached bead is uniquely identified by a specific type of fluorophore(s) or quantum dot(s). ¶ 0276; see also the first detection device 5012 can be associated with a larger detection volume (i.e. the first volume) due to more extensive detection techniques, since the first detection signal can form the basis of sorting the particles. The second detection device 5014, on the other hand, can be configured to simply perform a binary classification (i.e., either the particle is present in the second volume, or it is not) ¶ 0332).
30. An apparatus according to claim 16,wherein the software comprises one or more filters (e.g., finite impulse response (FIR) filter ¶ 0226, digital filter 4804 ¶ 0272) that comprise one or more thresholds for a peak width, a peak height, or a peak excursion for one or more of the at least two optical signals (see ¶ 0245, 0272 for example).
33. An apparatus according to claim 16, wherein the memory is a non-transitory memory (¶ 0435).
Claim(s) 16, 18, 20, 22, 24, 26, 30, 33 is/are rejected under 35 U.S.C. 102a1/a2 as being anticipated by Griffiths et al. (WO 2016/059182, rejection referring to English equivalent US 2017/0307626).
Regarding claim 16, Griffiths et al. teach:
16. An apparatus (e.g., 1) comprising:
a detection assembly (e.g., classification assembly) capable of measuring, for a droplet (e.g., 6), at least two optical signals (see ¶ 0117 & Fig. 2 for example), each optical signal capable of being representative of a light intensity spatial distribution in the droplet for an associated wavelength channel (see Figs. 2, 9, 25 for example), and
a calculator (e.g., measurement assembly) capable of calculating a plurality of parameters from the at least two optical signals (see ¶ 0125 for example),
wherein the plurality of parameters comprises a distance between a coordinate of a maximum intensity for each of the at least two optical signals (see i.e., time between two peaks in Figs. 2, 9; see also FIG. 25 represents a histogram of the number of drops counted for a fluorescence signal measured on the channel of the quantification entity. The abscissa represents the fluorescence maximum for the color of the quantification entity, and the ordinate represents the logarithm in base 10 of the number of drops measured at this fluorescence value. The values obtained for the emulsion of primary cells to be screened are plotted in a black solid line. The values obtained for the negative control emulsion are plotted in a gray dotted line. The vertical line of the points with black circles indicates the threshold value above which the drops are selected for the sorting. ¶ 0427), wherein the distance is the co-localization parameter for the at least two optical signals (It is noted that the claim is sufficiently broad to have read on Griffiths et al. since the droplet has been selectively detected, quantified, sorted/classified and plotted. See Figs. 2, 9, 25 & ¶ 0029-0056, 0148, 0150-0154, 0378, 0427 for example.);
wherein the calculator comprises a processor and a memory comprising software (see i.e., A piece of software for controlling the equipment, for example lasers or photomultipliers, is generated for analyzing and sorting out the drops. The sorting system requires an FPGA card for conducting an analysis in real time of the signal. ¶ 0310, a computer/non-transitory memory is required for software controlling the sorting equipment/FPGA card; see also a cited reference in ¶ 0165, PCT/FR2009/051396 Baudry et al. teach a central unit of a computer, a digital electronic circuit, an analog electronic circuit, a microprocessor and/or software means, a screen connected to the unit 6, Google translated version P8), which when executed by the processor, the calculator is capable of calculating the plurality of parameters for the at least two optical signals, including the co-localization parameter for the at least two optical signals (It is noted that the claim is sufficiently broad to have read on Griffiths et al. since the droplet has been selectively detected, quantified, sorted/classified and plotted. See Figs. 2, 9, 25 & ¶ 0029-0056, 0148, 0150-0154, 0378, 0427 for example.).
Regarding claim 1, Griffiths et al. meet all the structural limitations recited by the instant invention. Applicants’ preamble recites “that calculates a co-localization parameter for at least two optical signals in a droplet”. A preamble is generally not accorded any patentable weight where it merely recites the purpose of a process or the intended use of a structure. With regard to limitations in claims 16, 20, 22, 24, 26, 30 (e.g., [...] for a droplet, at least two optical signals, each optical signal being representative of a light intensity spatial distribution in the droplet for an associated wavelength channel, and [...] that calculates a plurality of parameters from the at least two optical signals, wherein the plurality of parameters comprises a distance between a coordinate of a maximum intensity for each of the at least two optical signals, wherein the distance is the co-localization parameter for the at least two optical signals, etc.), these claim limitations are considered process or intended use limitations, which do not further delineate the structure of the claimed apparatus from that of the prior art. The cited prior art teaches all of the positively recited structure of the claimed apparatus. The Courts have held that a statement of intended use in an apparatus claim fails to distinguish over a prior art apparatus. See In re Sinex, 309 F.2d 488, 492, 135 USPQ 302, 305 (CCPA 1962). The Courts have held that the manner of operating an apparatus does not differentiate an apparatus claim from the prior art, if the prior art apparatus teaches all of the structural limitations of the claim. See Ex Parte Masham, 2 USPQ2d 1647 (BPAI 1987). The Courts have held that apparatus claims must be structurally distinguishable from the prior art in terms of structure, not function. See In re Danley, 120 USPQ 528, 531 (CCPA 1959); and Hewlett-Packard Co. V. Bausch and Lomb, Inc., 15 USPQ2d 1525, 1528 (Fed. Cir. 1990) (see MPEP §§ 2114 and 2173.05(g)).
Regarding claims 18, 20, 22, 24, 26, 30, 33, Griffiths et al. teach:
18. An apparatus according to claim 16, wherein the detection assembly comprises a light source (e.g., laser) and at least a visible light sensitive detector (see ¶ 0117, 0143-0146 for example).
20. An apparatus according to claim 16, wherein the apparatus further comprises a selecting unit (e.g., assembly for sorting/sorting system ¶ 0056+; means 98 for directing the drop or a portion of the drop selectively towards a classification area 94, 96, ¶ 0195) capable of determining a sorting class for the droplet according to at least two parameters of the plurality of parameters (see i.e., ¶ 0053-0056, 0195 for example), wherein the at least two parameters comprise the co-localization parameter (It is noted that the claim is sufficiently broad to have read on Griffiths et al. since the droplet has been selectively detected, quantified, sorted/classified and plotted. See Figs. 2, 9, 25 & ¶ 0029-0056, 0148, 0150-0154, 0378, 0427 for example.).
22. An apparatus according to claim 18, wherein the apparatus further comprises a selecting unit (e.g., assembly for sorting/sorting system ¶ 0056+; means 98 for directing the drop or a portion of the drop selectively towards a classification area 94, 96, ¶ 0195) capable of determining a sorting class for the droplet according to at least two parameters of the plurality of parameters (see i.e., ¶ 0053-0056, 0195 for example), wherein the at least two parameters comprise the co-localization parameter (It is noted that the claim is sufficiently broad to have read on Griffiths et al. since the droplet has been selectively detected, quantified, sorted/classified and plotted. See Figs. 2, 9, 25 & ¶ 0029-0056, 0148, 0150-0154, 0378, 0427 for example.).
24. An apparatus according to claim 20, wherein the apparatus further comprises a sorting unit (e.g., assembly for sorting/sorting system ¶ 0056+; means 98 for directing the drop or a portion of the drop selectively towards a classification area 94, 96, ¶ 0195) capable of sorting the droplet according to the sorting class (see i.e., ¶ 0053-0056, 0195 for example).
26. An apparatus according to claim 22, wherein the apparatus further comprises a sorting unit (e.g., assembly for sorting/sorting system ¶ 0056+; means 98 for directing the drop or a portion of the drop selectively towards a classification area 94, 96, ¶ 0195) capable of sorting the droplet according to the sorting class (see i.e., ¶ 0053-0056, 0195 for example).
30. An apparatus according to claim 16,wherein the software comprises one or more filters that comprise one or more thresholds (see i.e., The sorting system requires an FPGA card for conducting an analysis in real time of the signal. ¶ 310; intensity threshold (dashed line) in Fig. 9; and sorting threshold (quantification entity) in Fig. 25) for a peak width, a peak height, or a peak excursion for one or more of the at least two optical signals (see Figs. 9, 25; i.e., selectively filtering optical signals ¶ 0405-0406; The vertical line of the points with black circles indicates the threshold value above which the drops are selected for the sorting. ¶ 0427; cited reference in ¶ 0165, PCT/FR2009/051396 Baudry et al. teach a thresholding and segmentation algorithm, Google translated version P13).
33. An apparatus according to claim 16, wherein the memory is a non-transitory memory (i.e., A piece of software for controlling the equipment, for example lasers or photomultipliers, is generated for analyzing and sorting out the drops. The sorting system requires an FPGA card for conducting an analysis in real time of the signal. ¶ 0310, a computer/non-transitory memory is required for software controlling the sorting equipment/FPGA card).
Response to Arguments
Applicant's arguments filed 06/26/2025 have been fully considered but they are not persuasive.
35 USC § 112 rejections under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph have been withdrawn.
In response to the Applicant's arguments to the process or intended use limitations, a recitation of the intended use of the claimed invention must result in a structural difference between the claimed invention and the prior art in order to patentably distinguish the claimed invention from the prior art. The Courts have held that limitations regarding the contents, intended use or manner of operating an apparatus do not further limit the patentability of apparatus claims. The Courts have held that a statement of intended use in an apparatus claim fails to distinguish over a prior art apparatus. See In re Sinex, 309 F.2d 488,492, 135 USPQ 302, 305 (CCPA 1962). The Courts have held that the manner of operating an apparatus does not differentiate an apparatus claim from the prior art, if the prior art apparatus teaches all of the structural limitations of the claim. See Ex Parte Masham, 2 USPQ2d 1647 (BPAI 1987). The Courts have held that apparatus claims must be structurally distinguishable from the prior art in terms of structure, not function. See In re Danley, 120 USPQ 528, 531 (CCPA 1959); and Hewlett-Packard Co. V. Bausch and Lomb, Inc., 15 USPQ2d 1525, 1528 (Fed. Cir. 1990) (see MPEP §§ 2114 and 2173.05(g)). "Expressions relating the apparatus to contents thereof during an intended operation are of no significance in determining patentability of the apparatus claim." Ex parte Thibault, 164 USPQ 666,667 (Bd. App. 1969). Furthermore, "[i]nclusion of material or article worked upon by a structure being claimed does not impart patentability to the claims." See In re Young, 75 F.2d *>996, 25 USPQ 69 (CCPA 1935) (as restated in In re Otto, 312 F.2d 937, 136 USPQ 458, 459 (CCPA 1963)) (see MPEP § 2115). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
With regard to the capabilities of the apparatus, they have been addressed within the above art rejection. Examiner suggests that the claim be amended to affirmatively recite specific structural elements to positively define the invention in structural terms, and to include the claimed process limitations of the apparatus within the non-transitory memory’s software (instructions). Applicant is thanked for their thoughtful amendments to the claims.
Conclusion
All claims are identical to or patentably indistinct from, or have unity of invention with claims in the application prior to the entry of the submission under 37 CFR 1.114 (that is, restriction (including a lack of unity of invention) would not be proper) and all claims could have been finally rejected on the grounds and art of record in the next Office action if they had been entered in the application prior to entry under 37 CFR 1.114. Accordingly, THIS ACTION IS MADE FINAL even though it is a first action after the filing of a request for continued examination and the submission under 37 CFR 1.114. See MPEP § 706.07(b). 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DEAN KWAK whose telephone number is (571)270-7072. The examiner can normally be reached M-TH, 4:30 am - 2:30 pm EST.
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/DEAN KWAK/Primary Examiner, Art Unit 1798
DEAN KWAK
Primary Examiner
Art Unit 1798