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 .
Applicant's amendments and remarks, filed 01/23/2026, are acknowledged. Rejections and/or objections not reiterated from previous office actions are hereby withdrawn. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
Status of Claims
Claims 1-3, 6-10, 13-17, 20-26 are under presently under examination.
Claims 4, 5, 11, 12, 18, 19 are cancelled.
Claims 21-26 are newly added.
Priority
The instant application does not claim the benefit of priority under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, or 365(c) to any prior applications. Accordingly, the effective priority date for the instant application is the filing date of 11/09/2021.
Withdrawn Rejections
The rejected under 35 U.S.C. 103(a) as being unpatentable over Ren et al. (Reconstruction of cell spatial organization based on ligand-receptor mediated self-assembly, Feb 2020, pp.1-32) is withdrawn in view of applicant’s amendments.
Claim Rejections - 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.
The following rejection is modified in view of applicant’s amendments.
Claims 1-3, 6-10, 13-17, 20-26 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
The United States Patent and Trademark Office published revised guidance on the application of 35 U.S.C. § 101. USPTO’s 2019 Revised Patent Subject Matter Eligibility Guidance (“Guidance”). Under the Guidance, in determining what concept the claim is “directed to,” 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) (Guidance Step 2A, Prong 1); and
(2) additional elements that integrate the judicial exception into a practical application (see MPEP § 2106.05(a)-(c), (e)-(h)) (Guidance Step 2A, Prong 2).
Only if a claim (1) recites a judicial exception and (2) does not integrate that exception into a practical application, do we then look to whether the claim contains an “‘inventive concept’ sufficient to ‘transform’” the claimed judicial exception into a patent-eligible application of the judicial exception. Alice, 573 U.S. at 221 (quoting Mayo, 566 U.S. at 82). In so doing, we thus consider whether the claim:
(3) adds a specific limitation beyond the judicial exception that are not “well-understood, routine and conventional in the field” (see MPEP § 2106.05(d)); or 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50-57 (January 7, 2019).
(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 Step 2B). See Guidance, 84 Fed. Reg. at 54-56.
Guidance Step 1:
The instant invention (claims 1, 8, 15 being representative) is directed to a method, system, and computer program product that performs a process. Thus, the claims are directed to one of the statutory categories of invention. MPEP 2106.03.
A. Guidance Step 2A, Prong 1
The Revised Guidance instructs us first to determine whether any judicial exception to patent eligibility is recited in the claim. The Revised Guidance identifies three judicially-excepted groupings identified by the courts as abstract ideas: (1) mathematical concepts, (2) certain methods of organizing human behavior such as fundamental economic practices, and (3) mental processes. Regarding claim(s) 1, the claimed steps that are part of the abstract idea are as follows:
training, by the processor, an immune response prediction model with a training data set comprising latent space features from scRNA-seg data of a plurality of single cell scRNA-seg datasets in a before treatment condition and a corresponding after treatment condition;
generating, by the processor, vector encodings of features from the scRNA-seg of each cell; generating, by the processor, vector encodings of predicted spatial features of the set of single cellsbased, at least in part, on the scRNA-seq wherein predicting the spatial features of the set of single cells comprises:
predicting a ligand receptor expression of each cell based on the vector encodings of features from the scRNA-seg of the respective cell; generating a cell-by-cell affinity matrix for the set of single cells based on the ligand receptor expression of each cell; identifying a cluster of cells in the set of single cells based on the cell-by-cell affinity matrix; and predicting spatial features of the cluster based on the ligand receptor expression of each cell in the cluster; and predicting, by the processor using the immune response prediction model, an immune response of the patient to a treatment selected for a condition based, at least in part, on the vector encodings of the predicted extracted spatial features.
Mental Processes
In this case, under the BRI, the above italicized steps do not impose any specificity with regards to how they are being performed and generally amount to manipulating and/or analyzing data to achieve the intended results. For example, training a generically recited model broadly reads on adjusting model parameters which could be performed by a scientist with a pen and paper. Similarly, generating vector encodings could also be routinely performed by a scientist with a pen and paper. A review of the specification does not disclose any limiting definition for “training” or “generating” that would serve to take these limitations out of the realm of abstract ideas, but does teach that the model is based on algorithms, i.e. sets of mathematical procedures which describe the relationships between variables and mathematical calculations [0017, 0022, 0024]. Applicant is also reminded that the Office's eligibility guidance does not set limit on the number of calculations that can or cannot be performed mentally. MPEP § 2106.04(a)(2)III. For these reasons, but for the recitation of a processor, the above steps fall within the “mental processes” grouping of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III [Step 2A, Prong 1: YES].
Mathematical Concept
In this case, at least some of the above steps amount to mathematical calculations and/or mathematically relating data. For example, a model based on latent space vectors necessarily requires mathematically relating data; see, e.g. Lotfollahi et al. (Generative Modeling And Latent Space Arithmetics Predict Single-Cell Perturbation Response Across Cell Types, studies and species, RioTxiv, Dec. 2018, pp.1-27). In addition, generating vector encodings and generating an ‘affinity matrix’ are also explicit mathematical concepts that require mathematically relating and/or calculating data. Similarly, the predicting steps also require mathematically relating data (i.e. they are based on vector encodings). The specification also teaches generating spatial features based upon mathematical calculations [0017, 0022]. Therefore, when read in light of applicant’s own specification, the claims are directed to mathematical concepts. See MPEP 2106.04 and 2106.05(II). [Step 2A, Prong 1: YES].
Natural Correlation
Under the broadest reasonable interpretation, the above claims also recite a natural correlation. In particular, the instant claims require determining a naturally occurring relationship between RNA sequence data and an “immune response” (e.g. a disease condition) of a patient to a treatment selected for a condition. See MPEP 2106.04(b). It is noted that even if a claim does recite a law of nature or natural phenomenon, it may still be eligible. For example, claims reciting a naturally occurring relationship between a patient’s genotype and the risk of QTc prolongation (a law of nature) were held eligible as not “directed to” that relationship because they also recited a step of treating the patient with an amount of a particular medication that was tailored to the patient’s genotype. Vanda Pharms., 887 F.3d at 1134-36, 126 USPQ2d at 1279-81. This particular treatment step applied the natural relationship in a manner that integrated it into a practical application. The court’s analysis in Vanda is equivalent to a finding of eligibility at Step 2A Prong Two (Pathway B).
B. Guidance Step 2A, Prong 2
This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception or whether the claim is “directed to” the judicial exception. This evaluation is performed by (1) identifying whether there are any additional steps/elements recited in the claim beyond the judicial exception, and (2) evaluating those additional steps/elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. See MPEP 2106.04(d).
In this case, the additional steps/elements recited in the claim beyond the judicial exception are as follows:
receiving, by a processor, a single cell ribonuclease sequence ("scRNA-seq") for each cell in a set of single cells from a tissue sample from a patient;
With regards to the claimed receiving, this step is not limited to any particular techniques or devices and generally results in collecting data for use by the abstract idea. Therefore, this step amounts to insignificant extra-solution activity and is not indicative of an integration into a practical application. See MPEP 2106.05(g).
With regards to the claimed processor, storage device, and storage media (claims 1, 8, 15), these are recited at high level of generality and generic computer components. Accordingly, these features are merely being used as tools to perform generic computer functions or the abstract idea, and therefore amount to no more than mere instructions to apply the exception using a generic computer. See MPEP 2106.05(f). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application. [Step 2A, Prong 2: NO].
C. Guidance Step 2B:
This part of the eligibility analysis evaluates whether the claim as a whole amount to significantly more than the recited exception i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. See MPEP 2106.05.
As discussed above, the non-abstract steps/elements amount to nothing more than insignificant extra-solution activity. A review of the specification teaches that the collection of scRNA datasets is routine and conventional [0001] as are the computer components for receiving and processing the data [0016, 0017, 0034-0035]. Moreover, Ren et al. (Reconstruction of cell spatial organization based on ligand-receptor mediated self-assembly, Feb 2020, pp.1-32) teaches methods for receiving scRNA sequences from databases as well as samples [pages 2-4]. Therefore, even upon reconsideration, there is nothing unconventional with regards to the above non-abstract elements/steps. See MPEP 2106.05(d)(Part II). Thus, the independent claim(s) as a whole do not amount to significantly more than the exception itself. Therefore, the claim(s) is/are not patent eligible. [Step 2B: NO].
D. Dependent Claims
Dependent claims 2, 3, 6, 7, 9-10, 14, 16, 17, 20-26 have also been considered under the two-part analysis but do not include additional steps/elements appended to the judicial exception that are sufficient to amount to significantly more than the judicial exception(s) for the following reasons. In particular, claims 2, 3, 6, 7, 9-10, 14, 16, 17, 20-26 are directed to limitations that further limit the specificity of the abstract idea or the nature of the data being used by the abstract idea. Accordingly, these claims are also directed to an abstract idea for the reasons set forth above (Step 2A, prong 1 analysis) and because data is abstract. Therefore, the instantly rejected claims are not drawn to eligible subject matter as they are directed to an abstract idea (and/or natural correlation) without significantly more.
Response to Arguments
Applicant’s arguments, filed 01/23/2026, have been fully considered but are not persuasive for the following reasons.
Applicant argues that the amended independent claims recite “significantly more” than the alleged abstract ideas (citing Step 2A, prong 1, analysis). In response, “Step 2B” analysis (not Step 2A, prong 1) evaluates whether the claim as a whole amount to significantly more than the recited exception i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. See MPEP 2106.05. Thus Applicant again appears to have a fundamental misunderstanding of the two-prong inquiry necessary for patentability. See the flowchart in MPEP § 2106, subsection III.
In this case, the only non-abstract step is directed to “receiving” a single cell RNA sequence from a tissue sample. As discussed above (Step 2B analysis), the non-abstract steps/elements amount to nothing more than insignificant extra-solution activity. A review of the specification teaches that the collection of scRNA datasets is routine and conventional [0001] as are the computer components for receiving and processing the data [0016, 0017, 0034-0035]. Moreover, Ren et al. (Reconstruction of cell spatial organization based on ligand-receptor mediated self-assembly, Feb 2020, pp.1-32) teaches methods for receiving scRNA sequences from databases as well as samples [pages 2-4]. Therefore, even upon reconsideration, there is nothing unconventional with regards to the above non-abstract elements/steps and the independent claim(s) as a whole do not amount to significantly more than the exception itself. See MPEP 2106.05(d)(Part II).
Applicant argues the ordered combination of elements is also integrated into a practical application (i.e. Step 2A, prong 2, yes). In response, as discussed above, the receiving step is not limited to any particular techniques or devices and generally results in collecting data for use by the abstract idea. Therefore, this step amounts to insignificant extra-solution activity and is not indicative of an integration into a practical application. See MPEP 2106.05(g). With regards to the claimed processor, storage device, and storage media (claims 1, 8, 15), these are recited at high level of generality and generic computer components. Accordingly, these features are merely being used as tools to perform generic computer functions or the abstract idea, and therefore amount to no more than mere instructions to apply the exception using a generic computer. See MPEP 2106.05(f). Therefore, even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application.
Lastly, in response to applicant’s argument that the combination of claimed steps provides the “improvement” to the technology, neither Applicant nor the specification provides any objective evidence of an improvement to the technology, nor does the specification explain the details of an unconventional technical solution expressed in the claim, or identify technical improvements realized by the claim over the prior art. See MPEP 2106.04(d)(1) and MPEP 2106.05(a). Furthermore, as the training, generating, and predicting steps are part of the abstract idea, applicant is essentially arguing that the inventive concept is the abstract idea. However, 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. BSG Tech LLC v. BuySeasons, Inc., 899 F.3d 1281, 1290 (Fed. Cir. 2018). On this point, the courts have also instructed that “[t]he different use of a mathematical calculation, even one that yields different or better results, does not render patent eligible subject matter.” Board Of Trustees Of Leland Stanford Junior University, 991 F.3d 1245, 1251 (Fed. Cir. 2021). In summary, while applicant’s particular algorithmic approach may be a particular way to predict patient response, the claimed invention is, nevertheless, directed to an improved algorithmic analysis. As such, the claims do not integrate the recited judicial exception into a practical application. For these reasons, the rejection is maintained.
Claim rejections - 35 USC § 112, 1st paragraph
The following is a quotation of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), first paragraph:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same and shall set forth the best mode contemplated by the inventor of carrying out his invention.
The following rejection is modified in view of applicant’s amendments.
Claims 1-3, 6-10, 13-17, 20-26 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement.
The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention.
The written description requirement is separate and distinct from the enablement requirement. The specification must: (1) describe the claimed invention in a manner understandable to a person of ordinary skill in the art, and (2) show that the inventor actually invented the claimed subject matter.
Regarding claim(s) 1, 8, 15, the specification fails to provide written description support for the following steps:
training, by the processor, an immune response prediction model with a training data set comprising latent space features from scRNA-seg data of a plurality of single cell scRNA-seg datasets in a before treatment condition and a corresponding after treatment condition;
generating, by the processor, vector encodings of features from the scRNA-seg of each cell; generating, by the processor, vector encodings of predicted spatial features of the set of single cells based, at least in part, on the scRNA-seq wherein predicting the spatial features of the set of single cells comprises:
predicting a ligand receptor expression of each cell based on the vector encodings of features from the scRNA-seg of the respective cell; generating a cell-by-cell affinity matrix for the set of single cells based on the ligand receptor expression of each cell; identifying a cluster of cells in the set of single cells based on the cell-by-cell affinity matrix; and predicting spatial features of the cluster based on the ligand receptor expression of each cell in the cluster; and predicting, by the processor using the immune response prediction model, an immune response of the patient to a treatment selected for a condition based, at least in part, on the vector encodings of the predicted extracted spatial features.
In particular, the above steps are not limited to any particular acts or operations and amount to functional language specifying desired results and/or specific functions. For example, the claims are not limited to any well-defined model nor are the claims limited to any particular medical condition (or treatment). As such, it is unclear in what way the claimed training and generating steps are being performed and how the “spatial features” are being predicted given the breadth of what is being claimed. A review of the specification teaches a spatial feature extraction module 114 can generate the 3-D model through a non- linear dimensional reduction algorithm (e.g., t-distributed stochastic neighbor embedding, gaussian process latent variable model, etc.) to embed the cell-by-cell matrix into a 3-D model that shows the density of cell types and cell clusters in real space [0024] and a prediction engine that can be a model trained with one or more datasets [0026]. However, this is not commensurate in scope with what is claimed (regarding the extraction module) and it is improper to import narrowing limitations into the claims. MPEP 2111.01. In addition, the specification does not provide any significant structural or functional details with regards to the prediction model, i.e. how it was trained, validated, or other specific details with regards to how this model operates. The specification does teach a model that an generate a cell-by-cell affinity matrix [0023] but fails to provide any limiting definition that would serve to clarify the boundaries of this structure (mathematically). In other words, the claimed model is essentially a black box to achieve the claimed functions. Moreover, the instant claims do not even presently require using any such model and it is improper to import narrowing limitations into the claims. MPEP 2111.01. As such, there is no evidence that applicant has actually disclosed the requisite functionality for achieving the full scope of what is presently embraced by the claims.
Moreover, one of ordinary skill in the art would recognize that computational methods for training and adjusting models for predicting immune response based on RNA data are not trivial.
Ren et al. (Cell Research, 2020, volume 30, pages 763–778) teaches a particular computational tool (CSOmap) for predicting cellular interaction de novo from scRNA-seq data. Unlike the instant claims, Ren teaches that the CSOmap includes specific algorithms and equations associated with ligand-respector pairs [See “Material and Methods”].
Arnol et al. (Cell Reports, 2019, 29, 202–211; IDS filed 11/09/2021) teaches that models for predicting cell-cell interactions must be trained, validated, and optimized for particular diseases under study [pages 203-204, and e3].
Sidey-Gibbons et al. (BMC Medical Research Methodology, 2019, 19:64, pp.1-18) teaches various applications of machine learning in medicine. Unlike the instant claims, Gibbons teaches methods for developing predictive models using specific validation datasets associated with specific real-world diagnostic decisions as well as calculating the accuracy, sensitivity, and specificity of the said models [See, e.g. Abstract, pages 2-3, and Figure 1]. Gibbons also highlights the differences between statistical analysis and machine learning techniques (which are both broadly encompassed by the instant claims). In particular, the goal of statistical methods is inference, i.e. making conclusions or deriving scientific insights about a population from data collected from a representative sample of that population. For example, in order to create a model which describes the relationship between clinical variables and treatment recommendations, one would need to have insight into the specific factors which distinguish the severity of various ‘conditions’ in order to develop appropriate interventions to improve outcomes. Conversely, in machine learning the primary concern is accurate prediction, i.e. the relationship between the individual features and the outcome is of little relevance if the prediction is accurate. Gibbons teaches it is exceptionally difficult to describe in a coherent way the relationships between predictors and outcomes when the relationships are non-linear and when there are a large number of predictors, each of which make a small individual contribution to the model.
Accordingly, given the complexity of genetic-phenotypic relationships, the cited prior art supports the examiner’s position that the specification fails to provide a sufficient disclosure of a model capable of achieving the full scope of what is being claimed. In addition, as set forth above, the claims are not even limited to any specific medical condition or treatments. Therefore, the specification does not establish a reasonable structure-function correlation. “[A] sufficient description of a genus . . . requires the disclosure of either a representative number* of species falling within the scope of the genus or structural features common to the members of the genus so that one of skill in the art can 'visualize or recognize' the members of the genus” (AbbVie, 759 F.3d at 1297, reiterating Eli Lilly, 119 F.3d at 1568-69)(emphasis added). Accordingly, one of ordinary skill in the art would not have understood applicant to have invented a method/system of performing the claimed functions with no more than routine experimentation.
For the reasons discussed above, the specification does not satisfy the written description requirement with respect to the full scope of what is being claimed. For more information regarding the written description requirement, see MPEP §2161.01- §2163.07(b).
Claim rejections - 35 USC § 112, 2nd Paragraph
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
The following rejection is modified in view of applicant’s amendments.
Claims 1-3, 6-10, 13-17, 20-26 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention. Claims that depend directly or indirectly from claim(s) 1, 8, and 15 is/are also rejected due to said dependency.
Claims 1, 8, 15 recite “generating…vector encodings of features from the scRNA-seq of each cell.” It is unclear as to the metes and bounds of the term “features”. Neither the claims nor the specification provides any limitation definition that would serve to clarify the scope. The specification does disclose that the spatial feature extraction module 114 may identify features (i.e., vectors) that correspond to an over expression of the ligand receptor [0022]. However, applicant is reminded that examples are not limiting definitions and it is improper to import narrowing limitations into the claims. MPEP 2111.01. Clarification is requested via amendment.
Claims 1, 8, 15 recite “generating a cell-by-cell affinity matrix based on the ligand receptor expression of each cell”. It is unclear as to the metes and bounds of a “cell-by-cell affinity matrix” such that the artisan would recognize what mathematical structure and/or construct is intended. For example, one of ordinary skill in the art of data analysis would understand that an affinity matrix, i.e. a similarity matrix or kernel, represents the degree of similarity between every pair of items in a dataset represented in terms of rows and columns. However, review of the specification does not provide any limitation definition or mathematical examples that would serve to clarify the scope. The specification [0023] generically describes what this matrix does but fails to provide any limiting definition that would serve to clarify the boundaries of the intended structure. As a result, it is also unclear what computational operations are intended by the claimed “generating”. A review of the specification does not describe, to any appreciable extent, any algorithms, equations, or prose equivalent that correspond to the claimed function. Clarification is requested via amendment.
Cited Prior Art
The following prior art made of record and not relied upon is considered pertinent to applicant' s disclosure.
Lotfollahi et al. (Generative Modeling And Latent Space Arithmetics Predict Single-Cell Perturbation Response Across Cell Types, studies and species, RioTxiv, Dec. 2018, pp.1-27), which teaches a method and model (scGen) combining autoencoders and latent space vector arithmetics for predicting single-cell perturbation response across cell types [Abstract]. In particular, Lotfollahi teaches training their scGen model with genetic data sets comprising latent space vectors in a perturbed (i.e. after treatment condition) and unperturbed (i.e. before treatment condition) [page 3].
Conclusion
No claims are allowed.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 extension fee 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 date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PABLO S WHALEY whose telephone number is (571)272-4425. The examiner can normally be reached between 1pm-9pm EST.
If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Anita Coope can be reached at 571-270-3614. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/PABLO S WHALEY/Primary Examiner, Art Unit 3619
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