HITACHI, LTD.

Patent Trials and Appeals Board

Aug 25, 2021

2021000043 (P.T.A.B. Aug. 25, 2021)

UNITED STATES PATENT AND TRADEMARK OFFICE
UNITED STATES DEPARTMENT OF COMMERCE
United States Patent and Trademark Office
Address: COMMISSIONER FOR PATENTS
P.O. Box 1450
Alexandria, Virginia 22313-1450
www.uspto.gov
APPLICATION NO. FILING DATE FIRST NAMED INVENTOR ATTORNEY DOCKET NO. CONFIRMATION NO.
14/443,118 05/15/2015 Masataka SHIRAI H&A-9852 1051
24956 7590 08/25/2021
MATTINGLY & MALUR, PC
1800 DIAGONAL ROAD
SUITE 210
ALEXANDRIA, VA 22314
EXAMINER
SKIBINSKY, ANNA
ART UNIT PAPER NUMBER
1631
NOTIFICATION DATE DELIVERY MODE
08/25/2021 ELECTRONIC
Please find below and/or attached an Office communication concerning this application or proceeding.
The time period for reply, if any, is set in the attached communication.
Notice of the Office communication was sent electronically on above-indicated "Notification Date" to the
following e-mail address(es):
ptomail@mmiplaw.com
PTOL-90A (Rev. 04/07)

UNITED STATES PATENT AND TRADEMARK OFFICE
____________

BEFORE THE PATENT TRIAL AND APPEAL BOARD
____________

Ex parte MASATAKA SHIRAI,
HIDEKI KAMBARA, and KIYOMI TANIGUCHI
____________

Appeal 2021-000043
Application 14/443,118
Technology Center 1600
____________

Before DONALD E. ADAMS, RICHARD M. LEBOVITZ, and
ULRIKE W. JENKS, Administrative Patent Judges.

ADAMS, Administrative Patent Judge.

DECISION ON APPEAL
Pursuant to 35 U.S.C. § 134(a), Appellant1 appeals from Examiner’s
decision to reject claims 1 and 3–20 (Appeal Br. 3). We have jurisdiction
under 35 U.S.C. § 6(b).
We AFFIRM.

1 We use the word “Appellant” to refer to “applicant” as defined in 37
C.F.R. § 1.42. Appellant identifies the real party in interest as “Hitachi,
Ltd.” (Appellant’s April 13, 2020, Appeal Brief (Appeal Br.) 3).
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2
STATEMENT OF THE CASE
Appellant’s disclosure “relates to a technique for clustering and
analyzing sample data” (Spec.2 ¶ 1). Appellant’s independent claims 1, 11,
and 12 are reproduced below:
1. An analysis apparatus for clustering and analyzing sample
data, comprising:
[A] a storage medium storing the sample data which
represents a plurality of gene expression values of a plurality of
single cells; and
[B] a processor coupled to the storage medium and
programmed to:
[C] receive an experimental error datum which describes
information about an experimental error of the sample data,
[D] obtain in advance a cluster range parameter for stretching
a cluster boundary during clustering according to a range of the
experimental error which the experimental error datum
describes,
[E] cluster the sample data in a clustering space according to
a temporarily set total cluster number,
[F] determine that an exceptional datum among the sample
data which does not belong to any cluster belongs to a cluster
when an area at a distance determined by the cluster range
parameter from the exceptional datum in the clustering space is
contained in the cluster, and determine that the exceptional
datum forms an independent cluster when the area is not
contained in any cluster, and
[G] output a result of the clustering, and
[H] wherein the processor is further programmed to:
[I] determine an optimal total cluster number by repeating a
process of calculating a first log-likelihood which indicates the
likelihood that the sample data belong to respective clusters
obtained by the clustering and a second log-likelihood which

2 Appellant’s May 15, 2015, Specification.
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indicates the likelihood that the sample data do not belong to
the respective clusters obtained by the clustering until the
clustering result calculated using the first log-likelihood and the
second log-likelihood reaches a preset threshold,
[J] decide a final clustering result of the sample data
according to the obtained optimal total cluster number, and
[K] output the final clustering result of the sample data in
which the single cells are arranged in clusters according to the
obtained optimal total cluster number.
(Appeal Br. 20–21 (annotated to facilitate discussion below).)
11. A data analysis method for clustering and analyzing sample
data, containing:
[A] receiving the sample data which represents a plurality of
gene expression values of a plurality of single cells;
[B] receiving an experimental error datum which describes
information about an experimental error of the sample data;
[C] obtaining a cluster range parameter for stretching a
cluster boundary during clustering according to a range of the
experimental error which the experimental error datum
describes;
[D] clustering the sample data according to a temporarily set
total cluster number;
[E] determining an exceptional datum among the sample data
which does not belong to any cluster belongs to a cluster when
an area at a distance determined by the cluster range parameter
from the exceptional datum in the clustering space is contained
in the cluster, and determining the exceptional datum forms an
independent cluster when the area is not contained in any
cluster; and
[F] outputting a result of the clustering,
[G] wherein an optimal total cluster number is determined by
repeating a process of calculating a first log-likelihood which
indicates the likelihood that the sample data belong to
respective clusters obtained by the clustering and a second log-
likelihood which indicates the likelihood that the sample data
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do not belong to the respective clusters obtained by the
clustering until the clustering result calculated using the first
log-likelihood and the second log-likelihood reaches a preset
threshold,
[H] wherein a final clustering result of the sample data is
decided according to the obtained optimal total cluster number,
and
[I] wherein the final clustering result of the sample data in
which the single cells are arranged in clusters according to the
obtained optimal total cluster number is output.
(Id. at 24–25 (annotated to facilitate discussion below).)
12. An analysis apparatus for clustering and analyzing sample
data, comprising:
[A] a storage medium configured to store the sample data
which represent gene expression levels of a plurality of single
cells and are a measurement result of the plurality of single
cells by single cell analysis; and
[B] a processor coupled to the storage medium and
programmed to:
[C] receive a clustering resolution (CR) value,
[D] wherein the processor is further programmed to perform
a process of clustering the sample data one or more times, the
process including:
[E] performing a provisional clustering of the sample data
into a plurality of ‘k’ clusters, where k is greater than or equal
to 2;
[F] for each cluster in the provisional clustering:
[G] determine whether an exceptional datum is present
in the sample data of the respective cluster;
[H] when the exceptional datum is not present in the
respective cluster:
[I] calculate a cluster center and a standard
deviation of the sample data in the respective
cluster, and normalize the sample data,
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[J] calculate an inverse matrix of a correlation
matrix of the sample data in the respective cluster,
and
[K] calculate a first distance between each of the
sample datum and the cluster center of the respective
cluster;
[L] when the exceptional datum is present in the
respective cluster:
[M] calculate the cluster center of the sample
data in the respective cluster, and normalize the
sample data using the cluster center and the CR
value, and
[N] calculate a second distance between each of
the sample datum and the cluster center of the
respective cluster;
[O] calculate, for each sample datum not in the respective
cluster, a probability that the respective sample datum does not
belong to the respective cluster using a first distribution in
which the probability increases with distance of the respective
sample datum from the cluster center;
[P] calculate, for each sample datum in the respective cluster,
a probability that the respective sample datum belongs to the
respective cluster using a second distribution in which the
probability decreases with distance of the respective sample
datum from the cluster center;
[Q] calculate, for each sample datum, a log-likelihood
value from the calculated probability thereof;
[R] calculate a sum of the log-likelihood values of all
the sample data to determine a likelihood of the respective
cluster; and
[S] sum the log-likelihoods of all of the clusters in the
provisional clustering, and divide the calculated sum by k,
[T] wherein the sample data are repeatedly provisionally
clustered into different k provisional clusters until the summed
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log-likelihood of all of the clusters in the provisional clustering
is less than or equal to a predetermined threshold, and
[U] wherein the processor is further programmed to store and
output the summed log-likelihood of the provisional clustering
which is less than or equal to the predetermined threshold and
the clusters of the sample data corresponding to the summed
log-likelihood of the provisional clustering which is less than or
equal to the predetermined threshold.
(Id. at 25–27 (annotated to facilitate discussion below).)

Claims 1 and 3–20 stand rejected under 35 U.S.C. § 101.

ISSUE
Does the preponderance of evidence of record support Examiner’s
finding that Appellant’s claimed invention is directed to patent-ineligible
subject matter?
PRINCIPLES OF LAW
A. Section 101
An invention is patent-eligible if it claims a “new and useful process,
machine, manufacture, or composition of matter.” 35 U.S.C. § 101.
However, the U.S. Supreme Court has long interpreted 35 U.S.C. § 101 to
include implicit exceptions: “[l]aws of nature, natural phenomena, and
abstract ideas” are not patentable. E.g., Alice Corp. v. CLS Bank Int’l, 573
U.S. 208, 216 (2014).
In determining whether a claim falls within an excluded category, we
are guided by the Court’s two-part framework, described in Mayo and Alice.
Alice, 573 U.S. at 217–18 (citing Mayo Collaborative Servs. v. Prometheus
Labs., Inc., 566 U.S. 66, 75–77 (2012)). In accordance with that framework,
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we first determine what concept the claim is “directed to.” See Alice, 573
U.S. at 219 (“On their face, the claims before us are drawn to the concept of
intermediated settlement, i.e., the use of a third party to mitigate settlement
risk.”); see also Bilski v. Kappos, 561 U.S. 593, 611 (2010) (“Claims 1 and 4
in petitioners’ application explain the basic concept of hedging, or protecting
against risk.”).
Concepts determined to be abstract ideas, and thus patent ineligible,
include certain methods of organizing human activity, such as fundamental
economic practices (Alice, 573 U.S. at 219–20; Bilski, 561 U.S. at 611);
mathematical formulas (Parker v. Flook, 437 U.S. 584, 594–95 (1978)); and
mental processes (Gottschalk v. Benson, 409 U.S. 63, 67 (1972)). Concepts
determined to be patent eligible include physical and chemical processes,
such as “molding rubber products” (Diamond v. Diehr, 450 U.S. 175, 191
(1981)); “tanning, dyeing, making water-proof cloth, vulcanizing India
rubber, smelting ores” (id. at 182 n.7 (quoting Corning v. Burden, 56 U.S.
252, 267–68 (1854))); and manufacturing flour (Benson, 409 U.S. at 69
(citing Cochrane v. Deener, 94 U.S. 780, 785 (1876))).
In Diehr, the claim at issue recited a mathematical formula, but the
Court held that “a claim drawn to subject matter otherwise statutory does not
become nonstatutory simply because it uses a mathematical formula.”
Diehr, 450 U.S. at 187; see also id. at 191 (“We view respondents’ claims as
nothing more than a process for molding rubber products and not as an
attempt to patent a mathematical formula.”). Having said that, the Court
also indicated that a claim “seeking patent protection for that formula in the
abstract . . . is not accorded the protection of our patent laws, and this
principle cannot be circumvented by attempting to limit the use of the
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formula to a particular technological environment.” Id. (citation omitted)
(citing Benson and Flook); see, e.g., id. at 187 (“It is now commonplace that
an application of a law of nature or mathematical formula to a known
structure or process may well be deserving of patent protection.”).
If the claim is “directed to” an abstract idea, we turn to the second
step of the Alice and Mayo framework, where “we must examine the
elements of the claim to determine whether it contains an ‘inventive
concept’ sufficient to ‘transform’ the claimed abstract idea into a patent-
eligible application.” Alice, 573 U.S. at 221 (internal quotation marks
omitted). “A claim that recites an abstract idea must include ‘additional
features’ to ensure ‘that the [claim] is more than a drafting effort designed to
monopolize the [abstract idea].’” Id. (alterations in original) (quoting Mayo,
566 U.S. at 77). “[M]erely requir[ing] generic computer implementation[]
fail[s] to transform that abstract idea into a patent-eligible invention.” Id.
B. USPTO Section 101 Guidance
In January 2019, the U.S. Patent and Trademark Office (USPTO)
published revised guidance on the application of § 101. 2019 Revised Patent
Subject Matter Eligibility Guidance, 84 Fed. Reg. 50 (Jan. 7, 2019)
(“Guidance”).3 “All USPTO personnel are, as a matter of internal agency
management, expected to follow the guidance.” Id. at 51; see also October
2019 Update at 1.

3 In response to received public comments, the Office issued further
guidance on October 17, 2019, clarifying the 2019 Revised Guidance.
USPTO, October 2019 Update: Subject Matter Eligibility (the “October
2019 Update”) (available at https://www.uspto.gov/sites/default/files/
documents/peg_oct_2019_update.pdf).
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Under the Guidance and the October 2019 Update, we first look to
whether the claim recites:
(1) any judicial exceptions, including certain groupings of
abstract ideas (i.e., mathematical concepts, certain methods of
organizing human activity such as a fundamental economic
practice, or mental processes) (“Step 2A, Prong One”); and
(2) additional elements that integrate the judicial exception into
a practical application (see MPEP § 2106.05(a)–(c), (e)–(h) (9th
ed. Rev. 08.2017, Jan. 2018)) (“Step 2A, Prong Two”).4
Guidance, 84 Fed. Reg. at 52–55.
Only if a claim (1) recites a judicial exception and (2) does not
integrate that exception into a practical application, do we then look, under
Step 2B, to whether the claim:
(3) adds a specific limitation beyond the judicial exception that
is not “well-understood, routine, conventional” in the field (see
MPEP § 2106.05(d)); or
(4) simply appends well-understood, routine, conventional
activities previously known to the industry, specified at a high
level of generality, to the judicial exception.
Guidance, 84 Fed. Reg. at 52–56.
ANALYSIS
Appellant’s independent claims 1, 11, and 12 are reproduced above.
Appellant’s claims 3–10 depend directly or indirectly from Appellant’s

4 This evaluation is performed by (a) identifying whether there are any
additional elements recited in the claim beyond the judicial exception, and
(b) evaluating those additional elements individually and in combination to
determine whether the claim as a whole integrates the exception into a
practical application. See Guidance — Section III(A)(2), 84 Fed. Reg. at
54–55.
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claim 1. Appellant’s claims 13–20 depend directly or indirectly from
Appellant’s claim 20.
(Step 1)
We first consider whether the claimed subject matter falls within the
four statutory categories set forth in § 101, namely “[p]rocess, machine,
manufacture, or composition of matter.” Guidance, 84 Fed. Reg. at 53–54;
see 35 U.S.C. § 101. Appellant’s independent claims 1 and 12 are directed
to an apparatus, i.e., a machine. Appellant’s independent claim 11 is
directed to a method, i.e., a process. Thus, Appellant’s claims 1, 11, and 12
are directed to statutory subject matter. Therefore, we proceed to the next
steps of the analysis.
(Step 2A, Prong 1)
The apparatus of Appellant’s claim 1 comprises, inter alia, a
processor [B] and [H] programmed to, inter alia,:
[E] cluster the sample data in a clustering space according to
a temporarily set total cluster number,
[F] determine that an exceptional datum among the sample
data which does not belong to any cluster belongs to a cluster
when an area at a distance determined by the cluster range
parameter from the exceptional datum in the clustering space is
contained in the cluster, and determine that the exceptional
datum forms an independent cluster when the area is not
contained in any cluster,
[I] determine an optimal total cluster number by repeating a
process of calculating a first log-likelihood which indicates the
likelihood that the sample data belong to respective clusters
obtained by the clustering and a second log-likelihood which
indicates the likelihood that the sample data do not belong to
the respective clusters obtained by the clustering until the
clustering result calculated using the first log-likelihood and the
second log-likelihood reaches a preset threshold, and
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[J] decide a final clustering result of the sample data
according to the obtained optimal total cluster number.

The method of Appellant’s claim 11 comprises, inter alia,:
[D] clustering the sample data according to a temporarily set
total cluster number,
[E] determining an exceptional datum among the sample data
which does not belong to any cluster belongs to a cluster when
an area at a distance determined by the cluster range parameter
from the exceptional datum in the clustering space is contained
in the cluster, and determining the exceptional datum forms an
independent cluster when the area is not contained in any
cluster,
[G] wherein an optimal total cluster number is determined by
repeating a process of calculating a first log-likelihood which
indicates the likelihood that the sample data belong to
respective clusters obtained by the clustering and a second log-
likelihood which indicates the likelihood that the sample data
do not belong to the respective clusters obtained by the
clustering until the clustering result calculated using the first
log-likelihood and the second log-likelihood reaches a preset
threshold, and
[H] wherein a final clustering result of the sample data is
decided according to the obtained optimal total cluster number.

The apparatus of Appellant’s claim 12 comprises, inter alia, a
processor [B], [D], and [H] programmed to, inter alia,:
[D] perform a process of clustering the sample data one or
more times,
[E] performing a provisional clustering of the sample data
into a plurality of ‘k’ clusters, where k is greater than or equal
to 2,
[F] for each cluster in the provisional clustering:
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[G] determine whether an exceptional datum is present in the
sample data of the respective cluster,
[H] when the exceptional datum is not present in the
respective cluster:
[I] calculate a cluster center and a standard deviation of the
sample data in the respective cluster, and normalize the sample
data,
[J] calculate an inverse matrix of a correlation matrix of the
sample data in the respective cluster,
[K] calculate a first distance between each of the sample
datum and the cluster center of the respective cluster,
[L] when the exceptional datum is present in the respective
cluster:
[M] calculate the cluster center of the sample data in the
respective cluster, and normalize the sample data using the
cluster center and the CR value,
[N] calculate a second distance between each of the sample
datum and the cluster center of the respective cluster,
[O] calculate, for each sample datum not in the respective
cluster, a probability that the respective sample datum does not
belong to the respective cluster using a first distribution in
which the probability increases with distance of the respective
sample datum from the cluster center,
[P] calculate, for each sample datum in the respective cluster,
a probability that the respective sample datum belongs to the
respective cluster using a second distribution in which the
probability decreases with distance of the respective sample
datum from the cluster center,
[Q] calculate, for each sample datum, a log-likelihood value
from the calculated probability thereof,
[R] calculate a sum of the log-likelihood values of all the
sample data to determine a likelihood of the respective cluster,
[S] sum the log-likelihoods of all of the clusters in the
provisional clustering, and divide the calculated sum by k, and
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[T] wherein the sample data are repeatedly provisionally
clustered into different k provisional clusters until the summed
log-likelihood of all of the clusters in the provisional clustering
is less than or equal to a predetermined threshold.
Determining, deciding, summing, calculating, and clustering of data
steps are mental processes as well as comprising mathematical concepts.
See Guidance, 84 Fed. Reg. at 52; see also Intellectual Ventures I LLC v.
Capital One Fin. Corp., 850 F.3d 1332, 1340 (Fed. Cir. 2017) (“[A]n
invention directed to collection, manipulation, and display of data was an
abstract process”); see also Digitech Image Techs., LLC v. Elecs. for
Imaging, Inc., 758 F.3d 1344, 1351 (Fed. Cir. 2014) (“Without additional
limitations, a process that employs mathematical algorithms to manipulate
existing information to generate additional information is not patent
eligible”); CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1375
(Fed. Cir. 2011) (“The mere manipulation or reorganization of data . . . does
not satisfy the transformation prong”). Alice, 573 U.S. at 221 (“[M]erely
requir[ing] generic computer implementation[] fail[s] to transform that
abstract idea into a patent-eligible invention.”).
Thus, we find no error in Examiner’s finding that Appellant’s claims
1, 11, and 12 recite judicial exceptions (see Ans.5 3–5).
(Step 2A, Prong 2)
Having determined that Appellant’s claims recite a judicial exception,
the Guidance requires an evaluation as to whether the claim as a whole
integrates the recited judicial exception into a practical application of the
exception. See Guidance, 84 Fed. Reg. at 54.

5 Examiner’s July 21, 2020, Answer.
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As discussed above, the determining, deciding, summing, calculating,
and clustering of data steps are abstract ideas, specifically mental processes
and mathematical concepts. Looking, however, at the claim as a whole, we
find that Appellant’s independent claims 1, 11, and 12 comprise the
following additional steps or limitations:
Claim 1:
[A] a storage medium storing the sample data which
represents a plurality of gene expression values of a plurality of
single cells; and
[B] a processor coupled to the storage medium and
programmed to:
[C] receive an experimental error datum which describes
information about an experimental error of the sample data,
[D] obtain in advance a cluster range parameter for stretching
a cluster boundary during clustering according to a range of the
experimental error which the experimental error datum
describes,
[G] output a result of the clustering, and
[H] wherein the processor is further programmed to:
[K] output the final clustering result of the sample data in
which the single cells are arranged in clusters according to the
obtained optimal total cluster number.

Claim 11:
[A] receiving the sample data which represents a plurality of
gene expression values of a plurality of single cells;
[B] receiving an experimental error datum which describes
information about an experimental error of the sample data;
[C] obtaining a cluster range parameter for stretching a
cluster boundary during clustering according to a range of the
experimental error which the experimental error datum
describes;
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[F] outputting a result of the clustering,
[I] wherein the final clustering result of the sample data in
which the single cells are arranged in clusters according to the
obtained optimal total cluster number is output.

Claim 12:
[A] a storage medium configured to store the sample data
which represent gene expression levels of a plurality of single
cells and are a measurement result of the plurality of single
cells by single cell analysis; and
[B] a processor coupled to the storage medium and
programmed to:
[C] receive a clustering resolution (CR) value,
[D] wherein the processor is further programmed to
[U] wherein the processor is further programmed to store and
output the summed log-likelihood of the provisional clustering
which is less than or equal to the predetermined threshold and
the clusters of the sample data corresponding to the summed
log-likelihood of the provisional clustering which is less than or
equal to the predetermined threshold.

The storage medium and processor limitations of Appellant’s
apparatus claims are generic computer limitations and, therefore, fail to
integrate the judicial exception into a practical application. See Alice, 573
U.S. at 221 (“[M]erely requir[ing] generic computer implementation[] fail[s]
to transform that abstract idea into a patent-eligible invention.”); see also
Guidance, 84 Fed. Reg. at 55 (Discussing “examples in which a judicial
exception has not been integrated into a practical application,” include
recitations that “merely includes instructions to implement an abstract idea
on a computer, or merely uses a computer as a tool to perform an abstract
idea”).
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The remaining storing, receiving, obtaining, outputting limitations add
insignificant extra-solution activity to the judicial exception and, thus, are
not sufficient to integrate the judicial exception into a practical application.
See also Guidance, 84 Fed. Reg. at 55; see also Ans. 5–6; MPEP
§ 2106.05(g).
(Step 2B)
Having determined that Appellant’s claims: (1) recite a judicial
exception and (2) do not integrate that exception into a practical application,
the Guidance requires that we evaluate whether Appellant’s claims: (a) add
a specific limitation beyond the judicial exception that is not “well-
understood, routine, conventional” in the field or (b) simply appends well-
understood, routine, conventional activities previously known to the
industry, specified at a high level of generality, to the judicial exception.
Guidance, 84 Fed. Reg. at 52–56.
On this record, we find no additional limitations that are not the
judicial exceptions or insignificant extra-solution activity discussed above
(see Ans. 6 (Examiner finds that Appellant’s “claims do not include
additional elements that are sufficient to amount [to] . . . significantly more
than the judicial exception”)). Thus, we find that Appellant’s claims do not
add a specific limitation beyond the judicial exception that is not “well-
understood, routine, conventional” in this field as required by the Guidance.

Appellant contends that Examiner failed to consider claims 1, 11, and
12 as a whole under the second prong of Step 2A, because Examiner failed
to consider the additional elements together with the judicial exceptions
(Appeal Br. 12–17). We are not persuaded. Claim limitations describing the
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excluded subject matter cannot satisfy the second step of the Alice analysis.
See BSG Tech LLC v. BuySeasons, Inc., 899 F.3d 1281, 1290 (Fed. Cir.
2018) (“It has been clear since Alice that a claimed invention’s use of the
ineligible concept to which it is directed cannot supply the inventive concept
that renders the invention ‘significantly more’ than that ineligible concept.”).
We are not persuaded by Appellant’s contention that Examiner failed
to properly evaluate claims 1, 11, and 12 under Step 2B (see Appeal Br. 17–
18). In support of this assertion, Appellant directs attention to limitations,
which as discussed above, are either abstract ideas or extra-solution activity
(see id.). Claim limitations describing the excluded subject matter cannot
satisfy the second step of the Alice analysis. See SAP Am. Inc. v. InvestPic,
LLC, 898 F.3d 1161, 1163 (Fed. Cir. 2018) (“No matter how much of an
advance in the finance field the claims recite, the advance lies entirely in the
realm of abstract ideas, with no plausibly alleged innovation in the non-
abstract application realm. An advance of that nature is ineligible for
patenting.”); BSG Tech, 899 F.3d at 1290 (“It has been clear since Alice that
a claimed invention’s use of the ineligible concept to which it is directed
cannot supply the inventive concept that renders the invention ‘significantly
more’ than that ineligible concept.”); Berkheimer v. HP Inc., 890 F.3d 1369,
1374 (Fed. Cir. 2018) (Moore, J., concurring) (“Berkheimer. . . leave[s]
untouched the numerous cases from [the Federal Circuit] which have held
claims ineligible because the only alleged ‘inventive concept’ is the abstract
idea.”).
For the foregoing reasons, we are not persuaded by Appellant’s
contention that “Examiner has failed to comply with the requirements of the
Berkheimer Memorandum and MPEP [§] 2106.05(d)” (Appeal Br. 18).
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CONCLUSION
The preponderance of evidence of record supports Examiner’s finding
that Appellant’s claimed invention is directed to patent-ineligible subject
matter.
DECISION SUMMARY
In summary:
Claim(s)
Rejected
35 U.S.C. § Reference(s)/Basis Affirmed Reversed
1, 3–20 101 Eligibility 1, 3–20

TIME PERIOD FOR RESPONSE
No time period for taking any subsequent action in connection with
this appeal may be extended under 37 C.F.R. § 1.136(a). See 37 C.F.R.
§ 1.136(a)(1)(iv) (2019).

AFFIRMED