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 .
Status of the Claims
Claims 1-2, 4-9, 12-13, 15-20, 23-24, and 26-31 are pending and examined herein.
Claims 3, 10-11, 14, 21-22, 25, and 32-33 are canceled.
Priority
As detailed on the 25 January 2022 filing receipt, the application claims priority as early as 15 January 2021. At this point in examination, all claims have been interpreted as being accorded this priority date as the effective filing date.
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 1-2, 4-9, 12-13, 15-20, 23-24, and 26-31 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 sensing and classifying cells.
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 computer system (claims 1-2 and 4-9), a method (claims 12-13 and
15-20), and a non-transitory computer-readable medium (claims 23-24 and 26-31), 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 recited limitation of identifying cells based on the sensor data, which is transcriptomic data, is a mental process as the human mind is practically equipped to interpret data.
The recited limitation to “generate... a feature vector representing gene expression values” (claims 1, 12, and 23) is interpreted as a mathematical concept, where a feature vector is disclosed as an array, list, or vector of features (pg. 8, paragraph [25]), interpreted as having a numerical form. Generating such a vector is also interpreted as a step practically performed by the human mind of concatenating data, and thus a mental process.
The recited limitation to “process the feature vector… to generate an output that specifies a cell type for the individual cell” is interpreted as a mathematical process by which the numerical input in the form of the vector is processed to generate a classification value (pg. 9, paragraph [29]), where inputting a number and outputting a number is interpreted as a mathematical process.
The recited limitation to “determine at least some of the cell types as uncommon” is interpreted as a decision or data evaluation step regarding the data. The human mind is practically equipped to perform identifications and classifications based on data and thus this step is considered a mental process.
The recited limitation to generate bootstrap vectors by generating noise and applying the noise is interpreted as mathematical steps as bootstrapping is a mathematical resampling process and the noise is disclosed as mathematical with statistical profiles (pg. 2, paragraph [4]).
The recited limitation to generate a cell-corpus by aggregating the bootstrap vectors and feature vectors is interpreted as a mental step of collecting the generated data, or as a mathematical step of joining them in a mathematical construct, and where the data is abstract. Similarly, updating a corpus is interpreted as a mental step of collecting the generated data and adding to existing such data, or as a mathematical step of joining them in a mathematical construct, and where the data is abstract.
Updating parameters is considered to be a mathematical step of modifying numerical values and thus an abstract idea.
Dependent claims 5, 16, and 27 recite a root node of the decision-tree has a child for
immune cells and a child for non-immune cells, which is considered to be directed to data interpretation and thus a mental process.
Dependent claim 7, 18, and 29 recite steps of identifying a cell as having high entropy, disassociating it from the generated cell type, and classifying it as a novel type, all of which the human mind is practically equipped to perform and thus is a mental process.
Dependent claims 8, 19, and 30 recite steps of identifying a cell as having high entropy and disassociating it from the generated cell type, which the human mind is practically equipped to perform and thus is a mental process.
Dependent claims 9, 20, and 31 recites calculating Shannon entropy, which is a verbal description of a mathematical concept. It is noted that 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)).
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))?
Because the claims recite judicial exceptions, direction under Step 2A Prong Two provides that the claims must be examined further to determine whether they recite elements in addition to the abstract ideas which integrate the judicial exceptions into a practical application (MPEP 2106.04(d)). A claim can be said to integrate a judicial exception into a practical application when it applies, relies on, or uses the judicial exception in a manner that imposes a meaningful limit on the judicial exception. This is performed by analyzing the additional elements of the claim to determine if the judicial exceptions are integrated into a practical application (MPEP 2106.04(d)(I); MPEP 2106.05(a-h)). If the claim contains no additional elements beyond the judicial exceptions, the claim is said to fail to integrate the judicial exceptions into a practical application (MPEP 2106.04(d)(III)).
Claims 1, 12, and 23 recite additional elements that are not abstract ideas: “a cell sampler,” “a sample receiver,” “sensors,” “a microfluidic structure,” “a device controller,” controlling the microfluidic structure to perform single-cell partitioning, measuring signals to characterize cells in the receiver, interpreted as performing single-cell RNA sequencing because single-cell RNA sequencing data is then transmitted to a processing apparatus, one or more processors and memory configured to “receive… the sensor-data,” “using one or more neural network classifiers,” and to “update the neural network classifier parameter values by training the classifiers on an updated corpus.” Additional elements recited in the independent claims also include a computer or processors (claims 1, 12, and 23) and “a computer-readable medium” (claim 23).
Claims 2, 8, 13, 19, 24, and 30 recite at least “storing… cell-corpuses to a data repository.”
Dependent claims 4, 15, and 26 recite the neural network classifiers include classifiers arranged in a hierarchical decision-tree and each node has an ensemble of neural network classifiers configured to vote on classification.
Dependent claims 6, 17, and 28 recite one or more neural network classifies were pre-trained on the initial-corpus of training data.
The cell sampler, comprising a receiver, sensors, microfluidic structure, and controller device are interpreted as required for collecting data for sorting and classifying the cells based on RNA sequencing data.. The data are transmitted and received to perform the classification steps and generating the corpus. Thus, these elements are interpreted as related to insignificant extra-solution activity (MPEP 2106.05(g)). Similarly, the accessing step is a require step gathering the data to generate the bootstrap vectors for the uncommon cell types, and thus also insignificant extra-solution activity.
The memory, processor, and computer-readable medium are presented without 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. Hence, these are mere instructions to apply the abstract idea using a computer, and therefore the claim does not integrate that abstract idea into a practical application (see MPEP 2106.04(d) § I; and MPEP 2106.05(f)).
Using the neural network is considered to be mere instructions to apply the abstract idea because it is done by a computer step (MPEP 2106.05(f)). Additionally, using neural network classifiers indicates a field of use or technological environment in which the judicial exception is performed which limits the processing step determining a cell type to a particular technological environment (neural networks) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h).
Dependent claims 2, 8, 13, 19, 24, and 30 recite storing data. Storing the corpuses is interpreted as occurring after the classification steps and does not materially change the classification, and thus is interpreted as insignificant extra-solution activity (MPEP 2106.05(g)).
Because the claims recite an abstract idea, and do not integrate that abstract idea into a practical application, the claims are directed to that abstract idea. Claims that are directed to abstract ideas must be examined further to determine whether the additional elements besides the abstract idea render the claims significantly more than the abstract idea. Claims that are directed to abstract ideas and that raise a concern of preemption of those abstract ideas must be examined to determine what elements, if any, they recite besides the abstract idea, and whether these additional elements constitute inventive concepts that are sufficient to render the claims significantly more than the abstract idea (MPEP 2106.05). [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, 12, and 23 recite additional elements that are not abstract ideas: “a cell sampler,” “a sample receiver,” “sensors,” “a microfluidic structure,” “a device controller,” controlling the microfluidic structure to perform single-cell partitioning, measuring signals to characterize cells in the receiver, interpreted as performing single-cell RNA sequencing because single-cell RNA sequencing data is then transmitted to a processing apparatus, one or more processors and memory configured to “receive… the sensor-data,” “using one or more neural network classifiers,” and “training the classifiers on an updated corpus.” Additional elements recited in the independent claims also include a computer or processors (claims 1, 12, and 23) and “a computer-readable medium” (claim 23). . Claims 2, 8, 13, 19, 24, and 30 recite at least “storing… cell-corpuses to a data repository.” Dependent claims 4, 15, and 26 recite the neural network classifiers include classifiers arranged in a hierarchical decision-tree and each node has an ensemble of neural network classifiers configured to vote on classification. Dependent claims 6, 17, and 28 recite one or more neural network classifies were pre-trained on the initial-corpus of training data. It is noted that adding information into a corpus may be interpreted as storing information in a database.
Ko (Lab Chip 18: 395-405, 2018; previously cited on the 10 June 2026 PTO-892 form) teaches a review of liquid biopsies, including microfluidics and single-cell RNA sequencing for measuring biomarkers (pg. 395, col. 2, second paragraph). Ko teaches neural networks as increasingly popular including training said algorithm (pg. 400, col. 1, paragraphs 3-4). Ko teaches ensemble for more accurate prediction (pg. 402, col. 1, second paragraph) and bootstrapping classification models (pg. 403, col. 1, first paragraph). Ko teaches iterative training (pg. 397, col. 2, second paragraph), which is interpreted as updating training. Finally, Ko teaches application of these concepts to classifying individual cells (pg. 397, col. 1, last paragraph).
The claims recite a generic computer, interpreted as instructions to apply the abstract idea using a computer, 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)). Storing data on a computer is a conventional computer function (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)). Transmitting and accessing data is conventional (buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014); MPEP 2106.05(d)).
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 09 September 2026 Applicant Remarks
Applicant remarks state the previous office action fails to properly analyze the claims at Step 2A Prong Two of the 101 framework, particularly in view of updated guidance following Desjardins (pg. 11-12). It is noted that the revised guidance is consistent with the MPEP. At Step 2A Prong Two, it is determined whether elements in addition to the abstract ideas integrate the abstract ideas into a practical application (MPEP 2106.04(d)(I)). Additional elements may integrate the abstract ideas into a practical application by an improvement to a computer or technology, a particular treatment, implementation via a particular machine, effecting a transformation, or application beyond generally linking. Limitations involving additional elements that do not integrate into a practical application are application generally stated or using a general purpose computer, insignificant extra-solution activity such as data gathering or output, or generally linking to a technological field or environment.
Claims 1, 12, and 23 recite additional elements that are not abstract ideas: “a cell sampler,” “a sample receiver,” “sensors,” “a microfluidic structure,” “a device controller,” controlling the microfluidic structure to perform single-cell partitioning, measuring signals to characterize cells in the receiver, interpreted as performing single-cell RNA sequencing because single-cell RNA sequencing data is then transmitted to a processing apparatus, one or more processors and memory configured to “receive… the sensor-data,” “using one or more neural network classifiers,” and to “update the neural network classifier parameter values by training the classifiers on an updated corpus.” Additional elements recited in the independent claims also include a computer or processors (claims 1, 12, and 23) and “a computer-readable medium” (claim 23). . Claims 2, 8, 13, 19, 24, and 30 recite at least “storing… cell-corpuses to a data repository.” Dependent claims 4, 15, and 26 recite the neural network classifiers include classifiers arranged in a hierarchical decision-tree and each node has an ensemble of neural network classifiers configured to vote on classification. Dependent claims 6, 17, and 28 recite one or more neural network classifies were pre-trained on the initial-corpus of training data. These elements in addition to the abstract ideas are analyzed to determine if they provide an improvement to a technology or technical field, or whether they recite application generally stated or using a general purpose computer, insignificant extra-solution activity such as data gathering or output, or generally linking to a technological field or environment.
Applicant remarks point out that insignificant extra-solution activity, mere instructions to apply the abstract idea, and a field of use limitation are inconsistent with MPEP analysis. However, at explained above, these considerations are consistent with the MPEP with analyzing whether additional elements provide integration into a practical application. An improvement must be realized at least partly with respect to the additional elements.
It is further noted that adding information to a corpus reads on an abstract data of adding information to a larger pool of information, or as an additional element step of data storage in a database, neither of which would overcome the rejection. Training a neural network is also previously taught, and updating parameters in a classifier is a mathematical step.
Analogy to Desjardins is unpersuasive. As explained in a previous office action, Desjardins is directed to solving a technical problem of catastrophic forgetting, which is an improvement to the computer function (pg. 13, third paragraph). The improvement in the instant claims is directed to cell classification and not a computer system. Regarding MPEP § 2106.05(a) subsection I example xiv, the computer system or system performance is not being improved as in Desjardins; the improvement is to the cell classification. The disclosed improvement is in the data type used and bootstrapping, which is a mathematical function. Using less data to speed up a computer analysis is considered to be within the state of the art. The improvement lies in the abstract steps of data analysis and not the elements in addition to the abstract ideas. Generating an updated corpus for optimizing a classifier is within the state of the art of learning models, where iteratively updating and optimizing is the learning process. Aggregating vectors is a mathematical or mental process of joining the data, which provides the alleged improvement. Applicant remarks states, like Desjardins, there is an improvement to a computer or other technology or technical field. The technology of cell sensing, as evidenced by the elements in addition to the abstract ideas, are known within the state of the art. The technology is not being improved; the improvement is based in the data analysis steps. In Desjardins, as explained in the remarks, the improvement is to the machine learning model and by extension the computer. The instant claims apply the model to cell classification and is an alleged improvement to cell classification, not to the model itself. The type of data being analyzed by the model is not considered analogous.
Regarding Step 2A Prong One, it is agreed that training a neural network is an element in addition to the abstract ideas (pg. 15). Processing the vector is an abstract idea though, where the parameters are used to perform a classification, and thus is a mathematical step using numerical parameters and/or a mental step of data evaluation to perform classification. It is unclear how processing a vector using parameters is not a mathematical concept. The remarks suggesting omission of a neural network. However, the neural network is the technological environment in which the data is processed and the classification is determined. Thus, it is a field of use limitation as exemplified by Example 47, claim 2. Applicant remarks further state generating a vector based cell expression values from sensor data is not an abstract step, where values are derived from sensor-data and not a mental process or mathematical process (pg. 16, third paragraph). It is agreed that controlling the sensors to measure the signals and produce the data are not abstract steps. However, generating a vector based on the data is using the values to form a mathematical structure for data analysis, which may also be done mentally as concatenating the data. Obtaining the data is a separate step from generating the vector based on the data. Because generating and processing vectors are considered to be abstract steps, they were not analyzed at Steps 2A Prong Two or 2B of the 101 framework.
Therefore, 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Robert J Kallal whose telephone number is (571)272-6252. The examiner can normally be reached Monday through Friday 8 AM - 4 PM EST.
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/R.J.K./Examiner, Art Unit 1685
/OLIVIA M. WISE/Supervisory Patent Examiner, Art Unit 1685
