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 .
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: instrument gateway module in claim 47.
Claim 47 recites "an instrument gateway module configured to receive..". Claim invokes 112(f) (placeholder module coupled with functional limitations without any structural limitations) and in view of the specification as software executed by a processing device, performing the tasks described (receive data from lab instruments). The analysis applies to claims 47-56, because none of the claims ever recites structure to execute the module.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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.
Claim(s) 47-66 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 7920736 B2 to Sammak et al., hereinafter, “Sammak” in view of US 2010/0232675 A1 to Ortyn et al., hereinafter, “Ortyn”.
Claim 47. (New) Sammak teaches A system for the classification of one or more specimens, the system comprising: [Abstract] systems for determining characteristics of cellular structures
a controller configured to: [col. 8, line 63-67] The computer means may include…means for control
interface with one or more instruments through an instrument gateway module [col 6, lines 63-66] teaches the classification system may include a user interface operatively associated with the computer. The image analysis and classification modules are preferably implemented as computer readable instructions executable on one or more general or special purpose computers.
configured to receive a plurality of experimental data sets from the one or more instruments, [col 8, lines 63-col. 9, lines 1] teaches the computer means may include: i) a digital frame grabber for receiving the images from the camera, ii) a display for user interaction and display of assay results,
[col 8, lines 47-58] teaches the image input device may include an image capture device in one embodiment. In one implementation, an image capture device may include a microscope or other high magnification optical system having an objective lens…
wherein the plurality of experimental data sets is produced during a plurality of experiments, [col. 31, lines 35-44] …each test run, one need load the saved classifiers instead of retraining.
[col. 24, lines 33-36] Given n feature representations for a problem and m classification methods, n-m different experiments can be run and analyzed to find the optimal pairing of feature representation and classification method
extract one or more feature data sets from the plurality of experimental data sets; [col 9, lines 45-48] teaches the image analysis module receives images from the image input and extracts these images into features which can be used for statistical cellular structure classification.
build one or more classification profiles based on a classification data set comprising at least a portion of the one or more feature data sets; [col 18, lines 57-60] teaches the classification module uses texture and/or border features that are extracted from the image analysis module to classify images of the cellular structure.
and classify one or more specimens of an experiment of the plurality of experiments using the one or more classification profiles. [col 6, lines 53-66] teaches FIG. 1 shows a schematic of a cellular structure classification system ("the classification system") according to an illustrative embodiment of the invention. The classification system includes an image input device, an image analysis module for deriving a plurality of image features from the images input, and a cellular structure classification module ("classification module") for classifying the cellular structure according to a statistical cellular structure model based on the derived image features.
wherein the one or more instruments comprise a multi-spectral imager for fluorescence and bright field detection; [col. 8, lines 59-60] Any optical method may be used, such as bright field, dark field, phase contrast and interference contrast
Sammak teaches the use of bright field and fluorescence (interference contrast) but fails to explicitly teach a multi-spectral imager. Ortyn, in the field of cell analysis using image data teaches [0065] A particularly preferred implementation of imaging system 510 is configured for multi-spectral imaging and can operate with six spectral channels: DAPI fluorescence (400-460 nm), Dark field (460-500 nm), FITC fluorescence (500-560 nm), PE fluorescence (560-595 nm
Sammak teaches analyzing cellular structures. Thus, before the effective filing date of the present application, it would have been obvious to one of ordinary skill in the art to combine the teachings of Sammak with the teachings of Ortyn [page 1, Background] to reduce the long-term experiments and financial cost with analyzing cells.
Claim 48. (New) Sammak teaches wherein the classification data set comprises at least a portion of each feature data set of a plurality of feature data sets, [col. 24, lines 33-36] Given n feature representations for a problem and m classification methods, n-m different experiments can be run and analyzed to find the optimal pairing of feature representation and classification method
wherein a first portion of each feature data set is produced from a first experimental data set of the plurality of experimental data sets, [col. 24, lines 33-36] …n-m different experiments can be run and analyzed to find the optimal pairing of feature representation and classification method
and a second portion of each feature data set is produced from a second experimental data set of the plurality of experimental data sets. [col. 24, lines 33-36] …n-m different experiments can be run and analyzed to find the optimal pairing of feature representation and classification method
Claim 49. (New) Sammak teaches wherein the first experimental data set and the second experimental data set are from different experiments. [col. 24, lines 33-36] Given n feature representations for a problem and m classification methods, n-m different experiments can be run and analyzed to find the optimal pairing of feature representation and classification method
Claim 50. (New) Sammak teaches wherein at least a portion of the first experimental data set and at least a portion of the second experimental data set are from different instruments. [col 8, lines 47-58] teaches the image input device may include an image capture device in one embodiment. In one implementation, an image capture device may include a microscope or other high magnification optical system having an objective lens, an XY stage adapted for holding a plate containing a cell sample or an array of samples, a means for moving the plate to align the samples with the microscope objective and for moving the sample in the direction to effect focusing, a digital camera, a detection system with a light source for directing light to cells in the sample locations, a means for directing light emitted from the cells to the digital camera, and a computer means for receiving and processing digital data from the digital camera. Collecting data from a plurality of instrument for comparison is well-known in the art and therefore not novel.
Claim 51. (New) Sammak teaches wherein the one or more feature data sets comprise measurements of one or more color channels. [col. 30, lines 5-15] [we were provided 77 images of stem cell colonies of varying quality. The colonies were approved National Institutes of Health (NIH) human embryonic stem cells, line HSF-6 from the University of San Francisco. The images were acquired on a Nikon TMS inverted tissue culture microscope with a 10.times. phase contrast objective and a Nikon D100 digital camera. Each image is in RGB format of size 1000.times.1504 pixels. Each RGB image was converted to grayscale via the MATLAB function rgb2gray and scale the resulting 256 grayscale intensity levels to the interval [-1 1] for computational stability.
Claim 52. (New) Sammak teaches wherein the measurements of one or more color channels comprise one or more of intensity, absolute intensity, hue, saturation, and/or spatial changes in intensity. [col. 30, lines 12-15] Each image is in RGB format of size 1000.times.1504 pixels. Each RGB image was converted to grayscale via the MATLAB function rgb2gray and scale the resulting 256 grayscale intensity levels to the interval [-1 1] for computational stability.
Claim 53. (New) Sammak teaches wherein the one or more classification profiles are built using, at least in part, supervised machine learning or unsupervised machine learning. [col. 19, lines 42-44] …in a neural network, the output classification is related to the input point via the hidden layers and the specified activation functions
[col. 32, lines 11-12] The SVM and KLD binary classifications and confidence values calculated across each stem cell colony image
Claim 54. (New) Sammak teaches wherein the one or more feature data sets are extracted based on whether the one or more feature data sets meet or exceed a threshold value. FIG. 16 shows a chart of an individual optimal performance matrix. The feature vector…that yields the highest performance for each category comparison is identified.
Claim 55. (New) Sammak teaches wherein the controller is further configured to display an analysis data set comprising at least a portion of the experimental data sets, FIG. 23 shows a graph of that visually displays classification results
at least a portion of the one or more feature data sets, or at least a portion of the classification data set, FIG. 1 shows a schematic of a cellular structure classification system ("the classification system") according to an illustrative embodiment of the invention. The classification system includes an image input device, an image analysis module for deriving a plurality of image features from the images input
wherein the analysis data set is displayed in real-time, near-real time, or batch mode. [col 19, lines 19-26] teaches kinetic measures could be expanded to real-time sensing of cell state for the purpose of monitoring or controlling cell state.
[col 19, lines 19-26] teaches the benefits of producing an automated system for production of stem cells and their products is critical to overcoming a rate limiting step in cell therapy and tissue engineering, the reproducible, qualified production of stem cells and stem cell products that are difficult to produce manually in large quantities with required consistency from batch to batch and over time.
Claim 56. (New) Sammak teaches wherein the one or more specimens comprises one or more colonies of microbial cells. [Abstract] teaches the invention generally provides methods and systems for determining characteristics of cellular structures. The methods include non-invasive, non-perturbing, automatable, and quantitative methods and may be applied to the examination of cells such as stem cells, embryos, and egg cells.
FIG. 2 shows images of stem cell colonies.
Claim 57. (New) Reviewed and analyzed in the same way as claim 47. See the above analysis and rationale.
Claim 58. (New) Reviewed and analyzed in the same way as claim 48. See the above analysis and rationale.
Claim 59. (New) Reviewed and analyzed in the same way as claim 49. See the above analysis and rationale.
Claim 60. (New) Reviewed and analyzed in the same way as claim 50. See the above analysis and rationale.
Claim 61. (New) Reviewed and analyzed in the same way as claim 51. See the above analysis and rationale.
Claim 62. (New) Reviewed and analyzed in the same way as claim 52. See the above analysis and rationale.
Claim 63. (New) Reviewed and analyzed in the same way as claim 53. See the above analysis and rationale.
Claim 64. (New) Reviewed and analyzed in the same way as claim 54. See the above analysis and rationale.
Claim 65. (New) Reviewed and analyzed in the same way as claim 55. See the above analysis and rationale.
Claim 66. (New) Reviewed and analyzed in the same way as claim 56. See the above analysis and rationale.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claim 47 (and similarly recited claim 57) rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1 of U.S. Patent No. 12125560 B2. Although the claims at issue are not identical, they are not patentably distinct from each other because the claims in the instant application are broader than the claims in the patent.
18/891790
US 12125560 B2
A system for the classification of one or more specimens, the system comprising:
A system for the classification of one or more specimens, the system comprising:
a controller configured to:
a controller configured to:
interface with one or more instruments through an instrument gateway module
interface with one or more instruments through an instrument gateway module
configured to receive a plurality of experimental data sets from the one or more instruments
configured to receive a plurality of experimental data sets from the one or more instruments,
wherein the plurality of experimental data sets is produced during a plurality of experiments,
wherein the plurality of experimental data sets is produced during a plurality of experiments;
wherein the one or more instruments comprise a multi-spectral imager for fluorescence and bright field detection;
wherein the one or more instruments comprise a multi-spectral imager for fluorescence and bright field detection;
extract one or more feature data sets from the plurality of experimental data sets;
extract one or more feature data sets from the plurality of experimental data sets;
build one or more classification profiles based on a classification data set comprising at least a portion of the one or more feature data sets;
build one or more classification profiles based on a classification data set comprising at least a portion of the one or more feature data sets;
and classify one or more specimens of an experiment of the plurality of experiments using the one or more classification profiles.
and classify one or more specimens of an experiment of the plurality of experiments using the one or more classification profiles
Likewise claims 48, 49, 50, 53, 55 and 56 (and respective similarly recited claims 58, 59, 60, 63, 65 and 66) are unpatentable over claims 2, 3, 5, 7, 9 and 10, respectively of U.S. Patent No. 12125560 B2.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. WO 2015/073908 A1 to Silva Ariosto et al. [page 29] Image acquisition. Two different models of fluorescence microscopes were used for the experiments…
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/DELOMIA L GILLIARD/Primary Examiner, Art Unit 2661
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