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 .
Remarks
In response to communications sent March 12, 2026, claim(s) 1-7, 9, 10, 13-17, 19-21, 23, and 24 is/are pending in this application; of these claim(s) 1 and is/are in independent form. Claim(s) 8, 11, 12, 18, 22, 25-94 is/are cancelled.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 March 12, 2026 has been entered.
Response to Arguments
Applicant’s arguments, see page 5 lines 12-18, filed March 12, 2026, with respect to claims 9, 10, 13, and 16 have been fully considered and are persuasive. The rejection of claims 9, 10, 13, and 16 sent January 15, 2026 has been withdrawn.
Applicant’s arguments, see page 6 lines 1-7, filed March 12, 2026, with respect to claims 1-21 have been fully considered and are persuasive. The rejection of claims 1-21 sent January 15, 2026 has been withdrawn.
Applicant's arguments filed March 12, 2026 have been fully considered but they are not persuasive. As preliminary matters regarding claim interpretation:
See Applicant’s definition of “gates” and “gating” on page 9 lines 3-13. For example, gating “generally refers to the process of classifying the data using a defined gate for a given set of data, where the gate can be one or more regions of interest combined with Boolean logic.” Hence, “gating” is in silico, and does not imply that the gated cells are differentially sorted into separate collection vessels.
Note that the phrase “differentially sorting” in the independent claim by itself does not imply the existence of a plurality of different “collection vessels,” which is described in the Specification on page 5 lines 6-11. This is because the element of two different collection vessels is not in the independent claim and is only in claim 24.
With regarding to claim 24, sorting by the first gate into a first collection vessel does not necessarily occur at the same time with the same equipment as the sortation into the second vessel.
Regarding Applicant’s Arguments pertaining to the independent claim:
Applicant argues that Banville does not teach the element of classification (e.g., sorting decision) based on gates. The Examiner respectfully disagrees. A sorting decision and a classification of the cell (monocyte, lymphocyte, etc.) is described in Para [0087]. The purpose of the invention is to modify the gate boundaries of the test device for better classification for sorting, resulting in a plurality of gate boundaries for gating (i.e. in silico delineation of various sets).
Applicant argues that Banville (US 20130173618 A1) uses a single gate for a particular population. The Examiner respectfully disagrees. See Figure 3 and paragraphs [0106]-[0107] for the perturbed gate boundaries. Each perturbed boundary is evidence that there is not a single gating in Banville. Compare Banville’s Figure 3 to Applicant’s Figure 1. For evidence that multiple gates are used on a single population, see Banville’s Para [0179] and Figure 20, which illustrates various gating regions R1 to R19 (columns) for a particular population (row). The fact that these perturbed gates are evaluated for how well they fit a particular set of data does not negate the fact that the optimized gates are subsequently used for cell sorting.
Applicant argues that the Boolean logic illustrated in Banville’s Figure 22 pertains to a particular set of data points without regard to their membership in a particular region of space. This is not the case. See Banville’s Paragraphs [0179] for examples of how Boolean combinations of regions are used with region identifiers in logical expressions for a given population. The regions used in Boolean combinations are using predefined gating boundaries. Furthermore, Applicant argues that a single gate is used for sorting/classifying cell in Figure 22. Even if, arguendo, the Boolean combinations of regions result in a single gate for sorting, the single gate is “based on” a plurality of gates used to derive a final gate, the final gate is still derived from a Boolean combination of a plurality of gate regions.
Claim Interpretation
Applicant’s Specification at page 53 last paragraph (lines 16-22) attempts to redefine the meaning of 35 U.S.C. § 112(f). However, when the Applicant acts as their own lexicographer, the Applicant does not redefine the statutes promulgated by Congress. Likewise, the definition set forth by the Applicant does not overturn precedential court cases regarding interpretation of the claims under 35 U.S.C. § 112(f). Therefore, the Examiner will interpret the claims in accordance with the statutes and precedent in the usual way, without importing the Applicant’s definitions into the contemplation of law.
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)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-10, 13-17 and 19-24 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US 20130173618 A1 (“Banville”).
As to claim 1, Banville teaches a method comprising:
receiving (Banville Para [0087]: receiving data from the flow cytometer for processing at the gate module):
a first gate comprising a set of vertices (Banville Para [0108]: initial gate boundary 350); and
flow cytometer data (Banville Para [0087]: flow cytometer data);
expanding the first gate to generate a second gate (Banville Para [0108]: expanding/perturbing the initial gate boundary by a specified distance from the centroid of the initial gate boundary);
determining a relationship between sets of flow cytometer data and both of the first gate and the second gate to classify the flow cytometer data (Banville Para [0030]: separating subpopulations of datapoints to separate subpopulations based on gate boundaries of a plurality of gates); and
differentially sorting (the phrase “differentially sorting” in the independent claim by itself does not imply the existence of a plurality of different “collection vessels”) particles in a sample via a sorting flow cytometer based on the first and second gates (Banville Para [0087]: sorting cells using a flow cytometer using the data processing and gating module).
As to claim 2, Banville teaches the method according to Claim 1, wherein expanding the first gate to generate the second gate comprises calculating a centroid of the first gate (Banville Para [0108]: calculations involving a determination of the centroid of the initial gate boundary).
As to claim 3, Banville teaches the method according to Claim 2, further comprising adjusting each vertex of the first gate such that horizontal and vertical differences of the vertices from the centroid is increased by a percentage (Banville Para [0109]: scaling vertices based on a scalar factor).
As to claim 4, Banville teaches the method according to Claim 3, wherein the percentage ranges from 1% to 20% (Banville Para [0109] and Figure 3: the scaling of the vertices based on a scalar factor, as described in Para [0109], is a scaling that is visually between 1% and 20% in Figure 3).
As to claim 5, Banville teaches the method according to Claim 1, wherein expanding the first gate to generate the second gate comprises Minkowski addition (Banville Para [0067]: scaling a gate boundary is a species of the genus of Minkowski addition, based on the definitional plain meaning of Minkowski addition, as understood by one of ordinary skill in the art).
As to claim 6, Banville teaches the method according to Claim 5, wherein the Minkowski addition comprises the summation of the vertices of the first gate with an expansion circle (Banville Para [0067]: scaling a gate boundary by a constant factor; the Examiner argues that scaling by a constant factor is mathematically the same as Minkowski addition of a boundary using an expansion circle).
As to claim 7, Banville teaches the method according to Claim 1, further comprising recording a subset of the classified flow cytometer data (Banville Para [0130]: randomly recording and calculating random points within a shape).
As to claim 9, Banville teaches the method according to Claim 7, wherein the recorded subset of classified flow cytometer data consists of a random sample of the flow cytometer data (Banville Para [0130]: randomly recording and calculating random points within a shape) within a set difference of the set of flow cytometer data encompassed by the second gate and the set of flow cytometer data encompassed by the first gate, and wherein the set difference is a set of flow cytometer data that is encompassed by the second gate but not encompassed by the first cate (Banville Para [0095]: the data of the random sample comprises a region of difference between the initial gate boundary and the perturbed gate boundaries; the data that is stored as a “subset” of the data comprises the “metrics”).
As to claim 10, Banville teaches the method according to Claim 9, wherein the random sample comprises a percentage of the classified flow cytometer data within the set difference (Banville Para [0095]: a portion of the points are drawn from the region of difference between the initial gate boundary and the perturbed gate boundary).
As to claim 13, Banville teaches the method according to Claim 9, wherein the random sample comprises a proportion of the classified flow cytometer data within the set difference determined relative to the number of datapoints within the set of flow cytometer data encompassed by the first gate (Banville Para [0068]: calculating a metric that is a percentage of datapoints within vs. outside of gate boundaries when boundaries are perturbed).
As to claim 14 The method according to Claim 7, wherein the recorded subset of classified flow cytometer data comprises a random sample of the flow cytometer data within a given distance from the first gate (Banville Para [0130]: randomly recording and calculating random points within a scaled distance defined by an elliptical shape).
As to claim 15, Banville teaches the method according to Claim 7, wherein the recorded subset of classified flow cytometer data comprises a random sample of the universal set of flow cytometer data (Banville Para [0165]: the boundary may encompass “all events” observed in a given well).
As to claim 16, Banville teaches the method according to Claim 9, wherein the recorded subset of classified flow cytometer data comprises the set union of the random sample and the set of flow cytometer data encompassed by the first gate (Banville Para [0099]: analyzing data from the gated flow cytometer and a control dataset; both datasets taken together tare the random sample and the data influenced by the gating).
As to claim 17, Banville teaches the method according to Claim 7, further comprising processing the recorded subset of classified flow cytometer with a dimensionality reduction algorithm (Banville Para [0127]: processing the flow cytometer data using eigenvalue and eigenvector determination as a dimension reduction algorithm).
As to claim 19, Banville teaches the method according to Claim 7, further comprising associating the recorded subset of classified flow cytometer data with a phenotype (Banville Para [0165]: associating the data with various biological characteristics that are genetically defined, such as cell surface markers).
As to claim 20, Banville teaches the method according to Claim 7, further comprising adjusting the vertices of the first gate based on the recorded subset of classified flow cytometer data (Banville Para [0175]: iterative adjustment of the gating process based on new data)
As to claim 21, Banville teaches the method according to Claim 7, further comprising adjusting the vertices of the second gate based on the recorded subset of classified flow cytometer data (Banville Para [0167]: adjusting the boundaries based on characteristics of the cells).
As to claim 23, Banville teaches the method according to Claim 1, further comprising sorting particles associated with the set of flow cytometer data encompassed by the first gate into a first collection vessel (Banville Para [0165]: flow cytometry wells).
As to claim 24, Banville teaches the method according to Claim 23, further comprising sorting particles associated with flow cytometer data encompassed by the set difference of the set of flow cytometer data encompassed by the second gate and the set of flow cytometer data encompassed by the first gate into a second collection vessel (Banville Para [0087]: sorting cells using a flow cytometer using the data processing and gating module; sorting by the first gate into a first collection vessel does not necessarily occur at the same time with the same equipment as the sortation into the second vessel).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US-20120245889-A1: pertinent because of gating, thresholding, and modeling
US-20170061657 A1: Pertinent because of Figure 11
Price, Jeffrey H., Edward A. Hunter, and David A. Gough. "Accuracy of least squares designed spatial FIR filters for segmentation of images of fluorescence stained cell nuclei." Cytometry: The Journal of the International Society for Analytical Cytology 25.4 (1996): 303-316. (Year: 1996)
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/JESSE P FRUMKIN/Primary Examiner, Art Unit 1685 May 2, 2026
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