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 .
Election/Restrictions
Applicant’s election without traverse of Group III (claims 7-10 and 15-18) in the reply filed on 05/04/2015 is acknowledged. Claims 1-6 and 11-14 are withdrawn from further consideration pursuant to 37 CFR 1.142(b), as being drawn to a nonelected invention. Since the restriction requirement properly made, the restriction requirement is now made final.
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 following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 7-10 and 15-18 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Goldberg et al., US 2022/0261990.
Regarding claim 7, Goldberg discloses an apparatus for analyzing cell culture images (fig. 1B, element 100; para 0063; a biological cell analysis system that utilizes machine learning to detect early-stage cellular morphological changes) comprising:
an image processor (para 0064; a processor) for image processing plaque size, clarity, border definition and distribution in cell culture images of a cell culture including a pathogen (fig. 1B; element 102; para 0045-0047 and 0065; the image processing system processes raw image data and generates feature vectors from the captured images of the biological cells. The plaque assay (i.e., plaque assay implies noting plaque size, clarity, border definition, and distribution of the cell monolayer (often termed plaque morphology)) is one of the most important assays in virology. It measures the number of infectious viral particles in a sample by observing the effects of infection on a culture of susceptible cells. This assay counts the number of infectious viral particles in a sample (plaque-forming units or PFUs));
a database for storing image metadata (fig. 1B, elements 101 and 124; para 0064; digital images of cells and associated metadata are stored in a storage device and a database);
a data mining processor (fig. 1B, element 104; para 0067; a machine learning (AI) model) for mining image metadata using machine learning to determine growth and virulence of the pathogen (fig. 1B, element 104; para 0066-0067, 0095, and 0133; the machine learning (AI) model is used with one or more classifier algorithms to classify biological cells and to detect morphological changes of the classified biological cells over time; In the analytical mode, images of biological cell assays can be analyzed to recognize and classify biological cells; During the prediction phase, the selected model is then used to classify cells at a time point corresponding to the selected model. The result is a per-well prediction of the degree of infection (predicted infectivity), being made within a much shorter time period (such as within hours, instead of days)).
Regarding claim 8, the apparatus according to claim 7, Goldberg further discloses comprising a data mining processor for mining the image metadata to optimize plaque assay conditions para 0045-0047, 0067, and 0088).
Regarding claim 9, the apparatus according to claim 8, Goldberg further discloses wherein the cell images comprise a sequence of images taken over a period of time (para 0089 and 0111) and wherein the data mining processor enables a backward time review of to search for the plaques that behave differently from others in backward time (para 0133 and 0145-0146).
Regarding claim 10, the apparatus according to claim 9, Goldberg further discloses wherein the cell culture is unstained (para 0086, 0096, and 0109) and wherein the data mining processor enables the replaying of the images in forward time to display the pathogen attacking a cell (para 0133 and 0145-0146) and permits one to remove a virus sample while it is still alive to see why it behaves differently from others (para 0068, 0073, and 0083).
Regarding claim 15, this claim recites substantially the same limitations that are performed by claim 7 above, and it is rejected for the same reasons.
Regarding claim 16, this claim recites substantially the same limitations that are performed by claim 8 above, and it is rejected for the same reasons.
Regarding claim 17, this claim recites substantially the same limitations that are performed by claim 9 above, and it is rejected for the same reasons.
Regarding claim 18, this claim recites substantially the same limitations that are performed by claim 10 above, and it is rejected for the same reasons.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Ichihashi et al., US 2022/0327694 discloses an area setting unit configured to extract a scratch area that is an area having no cells from a reference image selected from a plurality of images acquired by imaging cells in a time series and set a reference region corresponding to the scratch area in the plurality of images.
Chander et al., US 2018/0239949 discloses evaluating the status of cells in a sample involving imaging of cells, transformation of cell images into biophysical metrics, and transformation of the biophysical metrics into prognostic indications on the cellular and subject levels.
Cao et al., US 2013/0329973 discloses physiological imaging-defined subvolumes of tissues/disease are identified to yield spatially-defined prognostic and/or predictive indicators and/or focal therapy targets within such tissues, in particular tumors, for evaluation over time, for example, prior to and after a therapy treatment.
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/VAN D HUYNH/Primary Examiner, Art Unit 2665
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