DETAILED ACTIONS
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 .
Status of the Claims
Claims 1-4, 7-9, 11-15, and 18-25 are pending and examined herein.
Claims 5-6, 10, and 16-17 are canceled.
Priority
As detailed on the 16 February 2022 filing receipt, the application claims priority as early as 28 March 2019. At this point in examination, all claims have been interpreted as being accorded this priority date as the effective filing date.
Withdrawn Objections & Rejections
The objections to claims 2, 8, 18, and 23 are withdrawn based on correction of typographical issues.
The rejection under 35 USC 112(a) is withdrawn in view of the remarks (pg. 8) and amendment reflecting which steps are performed by which models.
The following rejection is the only rejection applied to the instant claims.
35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-4, 7-9, 11-15, and 18-25 are rejected under 35 USC § 101 because the claimed inventions are directed to an abstract idea without significantly more. "Claims directed to nothing more than abstract ideas (such as a mathematical formula or equation), natural phenomena, and laws of nature are not eligible for patent protection" (MPEP 2106.04 § I). Abstract ideas include mathematical concepts, and procedures for evaluating, analyzing or organizing information, which are a type of mental process (MPEP 2106.04(a)(2)). The claims as a whole, considering all claim elements both individually and in combination, do not amount to significantly more than the abstract idea of diagnosing cancer based on peripheral blood T-cell receptor repertoire.
MPEP 2106 organizes JE analysis into Steps 1, 2A (Prong One & Prong Two), and 2B as analyzed below.
Step 1: Are the claims directed to a process, machine, manufacture, or composition of matter (MPEP 2106.03)?
Step 2A, Prong One: Do the claims recite a judicially recognized exception, i.e., a law of
nature, a natural phenomenon, or an abstract idea (MPEP 2106.04(a-c))?
Step 2A, Prong Two: If the claims recite a judicial exception under Prong One, then is the judicial exception integrated into a practical application by an additional element (MPEP 2106.04(d))?
Step 2B: Do the claims recite a non-conventional arrangement of elements in addition to any identified judicial exception(s) (MPEP 2106.05)?
Step 1: Are the claims directed to a 101 process, machine, manufacture, or composition of matter (MPEP 2106.03)?
The claims are directed to a method (claims 1-4, 7-9, 11) a non-transitory computer-readable medium (claims 12-15, 18, and 25), and a computing device (claims 19-24), and each of which falls within one of the categories of statutory subject matter. [Step 1: Yes]
Step 2A, Prong One: Do the claims recite a judicially recognized exception, i.e., a law of nature, a natural phenomenon, or an abstract idea (MPEP 2106.04(a-c))?
With respect to Step 2A, Prong One, the claims recite judicial exceptions in the form of abstract ideas. MPEP § 2106.04(a)(2) further explains that abstract ideas are defined as:
• mathematical concepts (mathematical formulas or equations, mathematical relationships
and mathematical calculations) (MPEP 2106.04(a)(2)(I));
• certain methods of organizing human activity (fundamental economic principles or practices, managing personal behavior or relationships or interactions between people) (MPEP 2106.04(a)(2)(II)); and/or
• mental processes (concepts practically performed in the human mind, including observations, evaluations, judgments, and opinions) (MPEP 2106.04(a)(2)(III)).
The independent claims recite the following steps:
identifying a set of sequencing data,
identifying T cell receptor data associated with a set of antigen specific TCRs,
identifying TCR CDR3 regions within the two data sets,
identifying cancerous and non-cancerous CDR3s,
defining features of the cancerous and non-cancerous CDR3s as amino acid indices,
training a machine learning model using said indices via an adaptive process that selects features of the model to improve performance,
grouping a set of TCR-seq sample data into clusters based on sequence similarity, and
determining a score based on cluster analysis.
Mathematical concepts recited in the independent claims include a machine learning algorithm and determining a score based on the clustering. The terms in the claims are given their broadest reasonable interpretation in light of the specification. The specification discloses "the disclosed framework can utilize any known or to be known machine learning or artificial intelligence (AI) technique, algorithm or mechanism without departing from the scope of the initial disclosure" (pg. 12, paragraph [61]), "any known or to be known deep learning architecture or algorithm is applicable to the disclosed systems and methods discussed herein" (pg. 21, paragraph [108]), and executing a classifier or multiple classifiers by AdaBoost (pg. 13, paragraph [68]). The classifiers underlying AdaBoost are classification and regression trees (pg. 23, paragraph [119]). These classifiers are interpreted as mathematical constructs and thus, under a broadest reasonable interpretation, the machine learning models can be mathematical concepts. Furthermore, the cancer score is disclosed as a numerical determination of the score with confidence intervals (Fig. 5A), which indicates the score is not solely qualitative determination but rather based on mathematical calculations.
Mental processes or steps which the human mind is practically equipped to perform found in the independent claims are identifying RNA-seq data and data associated with a set of antigen-specific T cell receptors and determine a set of amino acid indices. These steps are interpreted as selecting data, identifying patterns (by comparing to amino acid index tables), and interpreting the output of a model, all of which the human mind is practically equipped to do.
Dependent claims 2-4, 7-10, 13-15, 18, and 20-23 recite further details of the mental processes and mathematical concepts found in the independent claims. Claims 2, 13, and 20 recite collecting data, identifying genomic information, analyzing genomic information, and extracting CDR3 sequences, which are interpreted as data analysis and thus mental processes. Claims 3, 14, and 21 recite performing alignment, which is interpreted as data analysis and thus a mental process. Claims 4, 15, and 22 recite generating a connectivity matrix, which is disclosed as grouping alignments with high scores (pg. 19, paragraph [94]), which is data evaluation and thus a mental process. Claims 7, 18, and 23 recite at least minimizing cross-validation errors, which is interpreted as a mathematical concept. Claim 8 recites calculating cross-validation errors, which is interpreted as a mathematical concept. Claim 9 recites further information about calculating the cross-validation errors.
Hence, the claims explicitly recite numerous elements that, individually and in combination,
constitute abstract ideas. The claims must therefore be examined further to determine whether they
integrate that abstract idea into a practical application (MPEP 2106.04(d)). [Step 2A: Yes]
Step 2A, Prong Two: If the claims recite a judicial exception under Prong One, then is the judicial exception integrated into a practical application by an additional element (MPEP 2106.04(d))?
Multiple elements in addition the abstract ideas are recited in the instant claims. Claims 1-4 and 19-24 recite a "computing device." Claim 12-15 and 18 recite a non-transitory computer readable medium. Claims 12-15 and 19-22 recite a processor. Claims 2 and 13 recites a network. Claims 11 and 24-25 recite a deep neural network.
The claims comprising computer components do not describe any specific computational steps by which the computer performs or carries out the abstract idea, nor do they provide any details of how specific structures of the computer are used to implement these functions. The claims state nothing more than that a generic computer performs the functions that constitute the abstract idea. In particular, using the neural network as recited in claims 11 and 24-25 is describing a neural network at a high degree of generality, and so amounts to mere instructions to implement the abstract idea using a computer. MPEP 2106.05(f) provides the following considerations for determining whether a claim simply recites a judicial exception with the words “apply it” (or an equivalent), such as mere instructions to implement an abstract idea on a computer: (1) whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished; (2) whether the claim invokes computers or other machinery merely as a tool to perform an existing process; and (3) the particularity or generality of the application of the judicial exception. Therefore, the limitations merely serve to link the judicial exception of determining a cancer score to the technological environment of a neural network.
None of the dependent claims recite any additional non-abstract elements; they are all directed
to further aspects of the information being analyzed, the manner in which that analysis is performed, or
the mathematical operations performed on the information. [Step 2A Prong Two: No]
Step 2B: Do the claims recite a non-conventional arrangement of elements in addition to any identified judicial exception(s) (MPEP 2106.05)?
Claims found to be directed to a judicial exception are then further evaluated to determine if the claims recite an inventive concept that provides significantly more than the judicial exception itself. Step 2B of 101 analysis determines whether the claims contain additional elements that amount to an inventive concept, and an inventive concept cannot be furnished by an abstract idea itself (MPEP 2106.05).
Claims 1-4 and 19-24 recite a "computing device." Claim 12-15 and 18 recite a non-transitory computer readable medium. Claims 12-15 and 19-22 recite a processor. Claims 2 and 13 recites a network. Claims 11 and 24-25 recite a deep neural network.
The claims recite a general purpose computer, interpreted as instructions to apply the abstract idea using a computer including a broadly recited neural network, where the computer does not impose meaningful limitations on the judicial exceptions, which can be performed without the use of a computer (MPEP 2106.04(d) § I; and MPEP 2106.05(f)). The additional elements recite use of neural networks are interpreted as mere instruction to “apply” the abstract ideas, which cannot provide an inventive concept. See MPEP 2106.05(f). Storing and retrieving data on a computer is a conventional computer activity (Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93; MPEP 2106.05(d)(II)). Transmitting data over a network (Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362; MPEP 2106.05(d)(II)) is a conventional computer activity. Repetitive calculations is a conventional computer activity (Bancorp Services v. Sun Life, 687 F.3d 1266, 1278, 103 USPQ2d 1425, 1433 (Fed. Cir. 2012) (MPEP 2106.05(d)(II)).
Therefore, the recited additional elements, alone or in combination with the judicial exceptions, do not appear to provide an inventive concept. [Step 2B: No]
Conclusion: Claims are Directed to Non-statutory Subject Matter
For these reasons, the claims, when the limitations are considered individually and as a whole,
are directed to an abstract idea and lack an inventive concept. Hence, the claimed invention does not
constitute significantly more than the abstract idea, so the claims are rejected under 35 USC § 101 as
being directed to non-statutory subject matter.
Response to the 12 May 2026 Applicant Remarks
Applicant remarks assert the rejection under 35 USC 101 is as the claims do not recite judicial exceptions (Step 2A Prong One), are not directed to judicial exceptions (Step 2A Prong Two), and include additional elements amounting to significantly more than the abstract ideas (Step 2B) (pg. 9, second paragraph). The stated arguments are unpersuasive.
Regarding Step 2A Prong One, applicant remarks state the claims do not recite mathematical concepts, including the machine learning model (pg. 9, fourth paragraph), which is asserted to involve but not recite math (pg. 10, second paragraph; pg. 13, fourth paragraph).
Applicant remarks state the amended claim 1 does not recite mathematical concepts, and under a broadest reasonable interpretation in light of the specification (MPEP 2111), these can include mathematical concepts. A model and algorithm are both interpreted as verbal descriptions of a mathematical concept; a mathematical relationship may be expressed in words and there is no particular word or set of words that indicates a claim recites a mathematical calculation (MPEP 2106.04(a)(2)). The specification discloses any form of machine learning or AI can be utilized to analyzed T cell, blood, and tumor sample/types (pg. 13, paragraph [69]). The machine learning algorithm is disclosed as executing a classifier or multiple classifiers by AdaBoost (pg. 13, paragraph [68]). The classifiers underlying AdaBoost are classification and regression trees (pg. 23, paragraph [119]). These classifiers are interpreted as mathematical constructs and thus, under a broadest reasonable interpretation, the machine learning models can be mathematical concepts. A neural network, which is highlighted in Example 39 and discussed in Deputy Commission Kim’s memorandum, is an element in addition to the abstract ideas. A neural network is not claimed in the instant claims, and thus the fact pattern is not considered to be analogous. It is noted in a footnote (pg. 13) that the term “algorithm” is not recited in the claims, but the specification discloses the framework is a machine learning algorithm (pg. 3, paragraph [7]) as do the instant remarks – “use of a machine learning algorithm that to predict cancer status based on a patient's peripheral blood TCR repertoire” (pg. 18, second paragraph) – and so the claims are considered to recite an algorithm, which would be understood by one having ordinary skill in the art as math.
Applicant remarks state “as long as a claim contains one or more limitations the cannot be practically performed in the human mind, the claim as a whole does not recite a mental process” (pg. 11, first paragraph), and “it does not matter” if abstract steps are recited because the “proper test” is “a claim does not recite a mental process when it contains limitation(s) that cannot practically be performed in the human mind, for instance when the human mind is not equipped to perform the claim limitation(s)" (pg. 11, second paragraph). This is inconsistent with the guidance from the MPEP.
First, the memo indicates an example of a claim which does not recite a mental process because it cannot be practically performed in the human mind is a specific hardware-based process, an RFID transponder, and a specific data structure (pg. 2-3, Footnote 8). In this example, the claim is entirely comprised of steps which cannot be practically performed by the human mind.
Second, is also notable that the memo notes that Step 2A Prong Two, as opposed to Step 2A Prong One, involves analysis of the claim as a whole (pg. 3, last paragraph), whereas Step 2A Prong One involves analysis of individual limitations. As set forth in MPEP 2106.04(II), Step 2A is a two-prong inquiry, in which examiners determine in Prong 1 whether a claim recites a judicial exception. MPEP 2106.04(I) sets forth that when determining whether a claim recites a judicial exception, it is sufficient to identify the claimed concept which aligns with at least one judicial exception, or, in other words, the specific claim limitations that the examiner believes may recite an exception. That the claim recites limitations which are in addition to those which recite judicial exceptions (i.e., additional elements) does not alter the analysis to determine whether a claim recites a judicial exception performed at Step 2A, Prong 1 (see MPEP 2106.04(II)(A)(1)). Those additional elements are examined at Step 2A, Prong 2, to determine whether the claim is directed to the judicial exceptions (see MPEP 2106.04(II)(A)(2)), which is discussed further below. As set forth in the above rejection, those limitations which are considered to recite a judicial exception are identified at Step 2A, Prong 1, and why they are considered to recite a judicial exception is explained, as is required by the eligibility analysis as outlined in MPEP 2106.04. That is, it does matter whether there are steps performed beyond a machine learning model, which may itself be abstract, because every claim element is analyzed at Step 2A Prong One, and determination that a limitation recites a judicial exception requires further analysis at Step 2A Prong Two.
At Step 2A Prong Two, applicant remarks assert the additional elements are improperly isolated and stated in a conclusory manner (pg. 11, last paragraph). The elements in addition to the abstract ideas are considered to be "computing device" (claims 1-4 and 19-24), a non-transitory computer readable medium (claims 12-15 and 18), recite a processor (claims 12-15 and 19-22), a network (claims 2 and 13), and a deep neural network (claims 11 and 24-25). The computing device is broadly recited to implement the abstract steps. The claims do not describe any specific computational steps by which the computer performs or carries out the abstract idea, nor do they provide any details of how specific structures of the computer are used to implement these functions. The claims state nothing more than that a generic computer performs the functions that constitute the abstract idea. Therefore, these elements are considered to be mere instructions to apply the exceptions using a computer (MPEP 2106.05(f)). The recitations of neural networks are similarly interpreted as describing use of a computer and so amounts to mere instructions to implement the abstract idea using a computer. Example 47 similarly recites using a trained neural network, and is interpreted therein as a field of use or technological environment in which the judicial exception is performed. More specifically, the limitation confines the use of the abstract idea to a particular technological environment – neural networks – and thus fails to add an inventive concept to the claims. MPEP 2106.05(f) pertains.
Applicant remarks state, with respect to the previous Office Action, that use of 3-10 ml of blood to detect cancer signals more accurately should be given patentable weight because the specification discloses this is an improvement to the technology (pg. 12, last paragraph). At Step 2A Prong Two, as stated previously, additional elements are evaluated to determine whether a judicial exception is integrated into a practical application (MPEP 2106.04(d)(I)). The elements in addition to the abstract ideas are considered to be "computing device" (claims 1-4 and 19-24), a non-transitory computer readable medium (claims 12-15 and 18), recite a processor (claims 12-15 and 19-22), a network (claims 2 and 13), and a deep neural network (claims 11 and 24-25). Collection of a blood sample is not required by the claims, and as such a specific volume of blood cannot provide the improvement. The remarks state that starting with a normal amount of blood (3-10 ml), the framework can perform deep TCR sequencing enabling detection, prediction, or determination of cancer-associated TCRs (pg. 16, second paragraph). Respectfully, neither 3-10 ml of blood nor sequencing is required by the claims.
Further regarding Step 2A Prong Two, applicant remarks state, similar to Ex Parte Desjardins, that an improvement to machine learning technology occurs in the instant invention in the form of AdaBoost reducing speed in training, executing a classifier, and reducing dimensionality (pg. 16, last paragraph). Unlike Ex Parte Desjardins, the instant claims are directed to an alleged improvement to a biological idea – determining a score which provides an indication of an immune repertoire being cancerous – rather than improving computer function. Therefore, the fact patterns are not analogous.
At Step 2B, applicant remarks state “it is clear that the claimed elements provide actual improvements in the art” and “as a result, the claims cannot possibly be construed as well-understood, routine, and conventional in this art” (pg. 17, fifth paragraph), asserting even if an additional element does not amount to significantly more on its own, it can still amount to significantly more when considered in combination (pg. 17, last paragraph to pg. 18, first paragraph). Specific examples are given of elements in addition to the abstract ideas (and not abstract idea) providing significantly more, such as the freezing and thawing steps of Rapid Litig. Mgmt. v. CellzDirect and the arrangement of components in BASCOM (pg. 18, first paragraph). Exclusively elements in addition to the abstract ideas are considered. If the machine learning algorithm is considered math – and given it is asserted to be an algorithm in the instant remarks it is still interpreted as math – the elements in addition to the abstract ideas are computer elements for implementing the abstract ideas. The additional elements recite use of neural networks are interpreted as mere instruction to “apply” the abstract ideas, which cannot provide an inventive concept. See MPEP 2106.05(f). Storing and retrieving data on a computer is a conventional computer activity (Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93; MPEP 2106.05(d)(II)). Transmitting data over a network (Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362; MPEP 2106.05(d)(II)) is a conventional computer activity. Repetitive calculations is a conventional computer activity (Bancorp Services v. Sun Life, 687 F.3d 1266, 1278, 103 USPQ2d 1425, 1433 (Fed. Cir. 2012) (MPEP 2106.05(d)(II)). Therefore, the recited additional elements, alone or in combination with the judicial exceptions, do not appear to provide an inventive concept.
Thus, the rejection under 35 USC 101 is maintained.
Conclusion
THIS ACTION IS MADE FINAL. 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.
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/R.J.K./Examiner, Art Unit 1685
/OLIVIA M. WISE/Supervisory Patent Examiner, Art Unit 1685
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