DETAILED ACTION
Notice of 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 .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Status of the Claims
Claims 1-17 are pending.
Claims 1, 3-4 and 6-7 are objected to.
Claims 1-17 are rejected.
Priority
This US Application 18/298,640 (04/11/2023) claims priority from Foreign Application IN 202341012638 (02/24/2023), as reflected in the filing receipt mailed on 02/24/2023. The claims to the benefit of priority are acknowledged; and the effective filing date of claims 1-17 is 02/24/2023.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 04/11/2023 considered by the examiner.
Claim objections
Claim 1 is objected to because of the following informalities:
the recited“ predicting… a predefined threshold values" (3rd claim element) does not present proper grammar agreement.
the recited "wherein the one or more feasible cell nucleotide sequences is each assigned" (4th claim element) should read "wherein the one or more feasible cell nucleotide sequences are each assigned"
Claims 3-4 are objected to because of the following informality: the recited "value of biomarkers" (4th line in claim 3 and last line in claim 4) should read either "values of biomarkers" or "a value…"
Claim 4 is objected to because of the following informality: the recited "a feasibility data" should read "feasibility data" without the "a" since the word data is plural.
Claim 6 is objected to because of the following informality: the recited "biomarkers data " should read "biomarker data" since the word data is plural.
Claim 7 is objected to because of the following informality: the recited "the one or more cell characteristics comprises" should read "the one or more cell characteristics comprise" for proper verb-subject agreement.
Claim Rejections - 35 USC § 112(b)
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.
Claims 1-8 and 11 are rejected under 35 U.S.C. 112(b)as being indefinite for failing to particularly point out and distinctly claim the subject matter the invention. Dependent claims are rejected similarly, unless otherwise noted below. The following issues cause the respective claims to be rejected under 112(b) as indefinite:
Claim 1 recites "the one or more cell characteristics for a target cell nucleotide sequence" (3rd claim element) which lacks antecedent basis because there is no previous recitation of "one or more cell characteristics for a target cell nucleotide sequence".
Claim 1 recites " wherein the one or more feasible cell nucleotide sequences is each assigned with a rank to generate a ranked list" which is indefinite because it is unclear if the recited presents a new active step within a wherein clause or not. The rejection may be overcome by amending the claim to clarify the metes and bounds of the limitation. As set forth in MPEP 2111.04.I, “wherein” clauses raise the question as to the limiting effect of the language in a claim.
Claims 3 and 11 recite "an equilibrium dissociation constant (KD) related to binding affinity, value of biomarkers related to at least one of immune evasion and cell fitness using the AI based prediction model." The relationship between the "equilibrium dissociation constant" and the "value of biomarkers…" is unclear. It is unclear if the recited constant is meant to indicate a value of biomarkers or if each "equilibrium dissociation constant" and the "value of biomarkers…" represent separate requirements in the claim. In contrast, the same issue does not exist for claims 4 and 12. For compact prosecution, the latter interpretation is being chosen for this instant examination. The rejection may be overcome by amending the claim to clarify the metes and bounds of the limitation.
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.
Claims 1-17 are rejected under 35 USC § 101 because the claimed inventions are directed to one or more Judicial Exceptions (JEs) without significantly more. Regarding JEs, "Claims directed to nothing more than abstract ideas..., 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)).
101 background
MPEP 2106 organizes JE analysis into Steps 1, 2A (Prong One & Prong Two), and 2B as analyzed below. MPEP 2106 and the following USPTO website provide further explanation and case law citations: uspto.gov/patent/laws-and-regulations/examination-policy/examination-guidance-and-training-materials.
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)?
Analysis of instant claims
Step 1: Are the claims directed to a 101 process, machine, manufacture, or composition of matter (MPEP 2106.03)?
The instant claims are directed to a method (claims 1-8), a system (claims 9-16) and a CRM (claim 17); each of which falls within one of the categories of statutory subject matter.
[Step 1: claims 1-17: 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))?
Background
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)).
Analysis of instant claims
With respect to the instant claims, under the Step 2A, Prong One evaluation, the claims are found to recite abstract ideas that fall into the grouping of mathematical concepts (in particular mathematical relationships and formulas) and mental processes (in particular procedures for observing, analyzing and organizing information) as well as a law of nature or a natural phenomenon are as follows.
Mathematical concepts (in particular mathematical relationships and formulas) include:
• "executing, by the sequence designing system, an … prediction model using vectorized data corresponding to the historical data" (independent claims 1, 9 and 17);
• "predicting, by the sequence designing system, a plurality of cell nucleotide sequences having values of one or more cell characteristics within a predefined threshold values of the one or more cell characteristics for a target cell nucleotide sequence using the … prediction model" (independent claims 1, 9 and 17);
• "performing … one or more pre-processing operations on the historical data for verifying correctness and completeness of the historical data based on the predefined reference information" (claims 2 and 10); and
• "determining, by the sequence designing system, an equilibrium dissociation constant (KD) related to binding affinity, value of biomarkers related to at least one of immune evasion and cell fitness using the … prediction model" (claims 3 and 11).
The claims identified above read on math. The abstract ideas recited in the claims are evaluated under the Broadest Reasonable Interpretation and determined each element performed either in the mind and/or by mathematical operation. Without further detail as to the methodology involved in "executing a model comprising algorithmic rules for nucleotide sequence design", under the BRI, one may simply, for example, use pen and paper to perform mathematical steps to arrive at the described steps. Further support for the mathematical techniques used in the claims is provided in the specification at [0031] which discloses that the sequence designing system may utilize transformer-based self-learning algorithms to predict the plurality of cell nucleotide sequences. Thus, the recited terms correspond to verbal equivalents of mathematical concepts because they constitute actions executed by a group of mathematical steps in a form of a mathematical algorithm; thus mathematical concepts (MPEP 2106.04(a)(2)). A mathematical concept need not be expressed in mathematical symbols, because "words used in a claim operating on data to solve a problem can serve the same purpose as a formula." In re Grams, 888 F.2d 835, 837 and n.1, 12 USPQ2d 1824, 1826 and n.1 (Fed. Cir. 1989). MPEP 2106.04(a)(2) pertains.
Mental processes, defined as concepts or steps practically performed in the human mind such as steps of observations, evaluations, judgments, analysis, opinions or organizing information include:
• "identifying, by the sequence designing system, one or more feasible cell nucleotide sequences among the plurality of cell nucleotide sequences based on predefined reference information, wherein the one or more feasible cell nucleotide sequences is each assigned with a rank to generate a ranked list" (independent claims 1, 9 and 17);
• "generating, by the sequence designing system, an explanation for the ranked list of the one or more feasible cell nucleotide sequences, thereby designing the cell nucleotide sequences" (independent claims 1, 9 and 17);
• "arranging, by the sequence designing system, the historical data in a chronological order based on timestamps associated with the historical data" (claims 2 and 10);
• "extracting, by the sequence designing system, a feasibility data corresponding to feasibility of each of the plurality of cell nucleotide sequences from the predefined reference information, based on an equilibrium dissociation constant (KD) and value of biomarkers related to at least one of immune evasion and cell fitness" (claims 4 and 12);
• "selecting, by the sequence designing system, one or more of the plurality of cell nucleotide sequences within predefined threshold ranges of at least one of immune evasion and cell fitness" (claims 5 and 13); and
• "generating, by the sequence designing system, the ranked list of the one or more feasible cell nucleotide sequences based on an equilibrium dissociation constant (KD)" (claims 5 and 13).
Under the BRI, the recited limitations are mental processes because a human mind is also sufficiently capable of generating an explanation based on data evaluation, arranging data in a chronological order, select/extract feasibility data and sequences within predefined threshold and rank items in a list.
Dependent claims 7-8 and 15-16 recite further steps that limit the judicial exceptions in independent claims 1 and 9 and, as such, also are directed to those abstract ideas. For example, claims 7 and 15 recite further details about the cell characteristics in the predicting step; claims 8 and 16 recite further details about the predefined reference information in the identifying step.
Furthermore, the instant claims recite a natural correlation by correlating cell nucleotide sequences naturally found in the body with a ranking classification (see MPEP 2106.04(b).I).
[Step 2A Prong One: claims 1-17: 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))?
Background
MPEP 2106.04(d).I lists the following example considerations for evaluating whether a judicial exception is integrated into a practical application:
An improvement in the functioning of a computer or an improvement to other technology or another technical field, as discussed in MPEP §§ 2106.04(d)(1) and 2106.05(a);
Applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, as discussed in MPEP § 2106.04(d)(2);
Implementing a judicial exception with, or using a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, as discussed in MPEP § 2106.05(b);
Effecting a transformation or reduction of a particular article to a different state or thing, as discussed in MPEP § 2106.05(c); and
Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception, as discussed in MPEP § 2106.05(e).
Analysis of instant claims
Instant claims 1-13 and 17 recite additional elements that are not abstract ideas:
• "computer-implemented" (claims 1-8);
• "Artificial Intelligence (AI) model (claims 1, 3, 9, 11 and 17);
• "processor" (claims 9-13 and 17);
• "memory" (independent claim 9);
• "receiving, by a sequence designing system, historical data related to results of one or more procedures related to analysis of cell nucleotide sequences from one or more databases" (independent claims 1, 9 and 17).
Dependent claims 6 and 14 recite further details about the historical data received.
Considerations under Step 2A, Prong Two
The recited limitations in claims 1-17 are interpreted as requiring the use of a computer. Hence, the claims explicitly recite steps executed by computers and therefore can be described as computer functions or instructions to implement on a generic computer.
Further steps directed to additional non-abstract elements of a computing device/computer do not describe any specific computational steps by which the "computer parts" perform or carry out the judicial exceptions, 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 a generic computer which performs the functions that constitute the judicial exceptions.
The judicial exceptions in the claims are considered to perform the claimed abstract idea with a computer, which is not sufficient to integrate an abstract idea into a practical application (see MPEP 2106.05(f)); since steps that can be performed mentally and merely performing the mental process in a computer environment do not negate the fact that something that can be carried out in the human mind. See MPEP 2106.04(a)(2).III.C. Additionally, claims 1-10 and 16-20 do not recite an additional element, and therefore there is nothing in the claims to provide a practical application at Step 2A, Prong 2, or significantly more at Step 2B.
Claims directed to "receiving … historical data" read on receiving or transmitting data over a network -Symantec, 838 F.3d at 1321 - MPEP 2106.05(a) pertains; which constitutes just necessary data gathering and therefore correspond to insignificant extra-solution activity.
With respect to claims 1, 3, 9, 11 and 17, the computer-related elements or the general purpose computer and the recited Artificial Intelligence model does not rise to the level of significantly more than the judicial exception. The claims state nothing more than a generic computer which performs the functions that constitute the judicial exceptions. Hence, these are mere instructions to apply the judicial exceptions using a computer, which the courts have found to not provide significantly more when recited in a claim with a judicial exception (Alice Corp., 573 U.S. at225-26, 110 USPQ2d at 1984; see MPEP 2106.05(A)). The specification as published also notes that computer processors and systems, as example, are known and widely used examples of transformer-based self-learning algorithms that may be used without limitation [0031]. The additional elements are set forth at such a high level of generality that they can be met by a general purpose computer. Therefore, the computer components constitute no more than a general link to a technological environment, which is insufficient to constitute an inventive concept that would render the claims significantly more than the judicial exceptions (see MPEP 2106.05(b)I-III).
Further, the limitation reciting "using an Artificial Intelligence model" provides mere instructions to implement an abstract idea on a generic computer. See MPEP 2106.05(f). 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 as a tool to perform an existing process; and (3) the particularity or generality of the application of the judicial exception.
Hence, these are mere instructions to apply the abstract idea using a computer and insignificant extra-solution activity and therefore the claims do not integrate that abstract idea into a practical application (see MPEP 2106.04(d) § I; 2106.05(f); and 2106.05(g)).
In Step 2A, Prong One above, claim steps and/or elements were identified as part of one or more judicial exceptions (JEs).
In this Step 2A, Prong Two immediately above claim steps and/or elements were identified as part of one or more additional elements. Additional elements are further discussed in Step 2B below.
Here in Step 2A, Prong Two, no additional step or element clearly demonstrates integration of the JE(s) into a practical application.
[Step 2A Prong Two: claims 1-17: No]
Step 2B: Do the claims recite a non-conventional arrangement of elements in addition to any identified judicial exception(s) (MPEP 2106.05)?
According to analysis so far, the additional elements described above do not provide significantly more than the judicial exception. A determination of whether additional elements provide significantly more also rests on whether the additional elements or a combination of elements represents other than what is well-understood, routine, and conventional. Conventionality is a question of fact and may be evidenced as: a citation to an express statement in the specification or to a statement made by an applicant during examination that demonstrates a well-understood, routine or conventional nature of the additional element(s); a citation to one or more of the court decisions as discussed in MPEP 2106(d)(II) as noting the well-understood, routine, conventional nature of the additional element(s); a citation to a publication that demonstrates the well-understood, routine, conventional nature of the additional element(s); and/or a statement that the examiner is taking official notice with respect to the well-understood, routine, conventional nature of the additional element(s).
Claims 1-17 recite a computer or computer functions, 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)).
The computer-related elements or the general purpose computer and the artificial intelligence model do not rise to the level of significantly more than the judicial exception. The claims state a generic computer which performs the functions that constitute the judicial exceptions. Hence, these are mere instructions to apply the judicial exceptions using a computer, which the courts have found to not provide significantly more when recited in a claim with a judicial exception (Alice Corp., 573 U.S. at225-26, 110 USPQ2d at 1984; see MPEP 2106.05(A)).
Further, the courts have found that receiving data is a well-understood, routine, and conventional functions of a computer when claimed in a generic manner or as insignificant extra-solution activity (see Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information), buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network), Versa ta Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015), and OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93, as discussed in MPEP 2106.05(d)(Il)(i)).
When the claims are considered as a whole, they do not integrate the abstract idea into a practical application; they do not confine the use of the abstract idea to a particular technology; they do not solve a problem rooted in or arising from the use of a particular technology; they do not improve a technology by allowing the technology to perform a function that it previously was not capable of performing; and they do not provide any limitations beyond generally linking the use of the abstract idea to a broad technological environment. See MPEP 2106.05(a) and 2106.05(h).
The instant claims constitute insignificant extra solution activity, and when considered individually, are insufficient to constitute inventive concepts that would render the claims significantly more than an abstract idea (see MPEP 2106.05(g)). Hence, these elements, when considered individually, are insufficient to constitute inventive concepts that would render the claims significantly more than an abstract idea (see MPEP 2106.05(d)).
[Step 2B: claims 1-17: No]
Conclusion: Instant claims are directed to non-statutory subject matter
For the reasons above, the claims in this instant application, when the limitations are considered individually and as a whole, are directed to an abstract idea and lack an inventive concept not clearly anything significantly more.
Claim Rejections - 35 USC § 103
The following is a quotation of pre-AIA 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained though the invention is not identically disclosed or described as set forth in section 102, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under pre-AIA 35 U.S.C. 103(a) are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
A. Claims 1-2, 6-10 and 14-17 are rejected under 35 U.S.C. 103(a) as being unpatentable over Zhou ("Screening cancer immunotherapy: when engineering approaches meet artificial intelligence." Advanced Science 7(19):2001447 (2020)) in view of Bellazzi ("Predictive data mining in clinical medicine: a focus on selected methods and applications." Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 1(5):416-430 (2011)), as cited on the attached Form PTO-892.
Claim 1 recites a computer-implement method comprising steps. Claim 9 recites a sequence designing system, comprising: a processor; and a memory, communicatively coupled to the processor, wherein the memory stores processor-executable instructions, which, on execution, causes the processor to perform the actions comprising said steps. Claim 17 recites a non-transitory computer readable medium including instructions stored thereon that when processed by at least one processor, cause a sequence designing system to perform operations comprising said steps.
The prior art to Zhou discloses methods and systems as engineering approaches ranging from sequencing and gene editing, to tumor organoids engineering, bioprinted tissues, and organs-on-a-chip systems using artificial intelligence for the development of different immunotherapeutic agents (pg. 1 Abstract); wherein a non-transitory computer-readable medium and memory are provided via computer-based analyses (pg. 6 col. 2 para. 3).
The steps performed by the method of claim 1, a system of claim 9, and a non-transitory computer-readable medium of claim 17 comprise:
receiving, by a sequence designing system, historical data related to results of one or more procedures related to analysis of cell nucleotide sequences from one or more databases;
executing, by the sequence designing system, an Artificial Intelligence (AI) based prediction model using vectorized data corresponding to the historical data;
predicting, by the sequence designing system, a plurality of cell nucleotide sequences having values of one or more cell characteristics within a predefined threshold values of the one or more cell characteristics for a target cell nucleotide sequence using the AI based prediction model
• Zhou teaches engineering approaches ranging from sequencing and gene editing (i.e. reading on designing cell nucleotide sequences), to tumor organoids engineering, bioprinted tissues, and organs-on-a-chip systems (i.e. one or more procedures related to analysis of cell nucleotide sequences from one or more databases) using artificial intelligence (i.e. reading on AI based model) for the development of different immunotherapeutic agents (pg. 1 Abstract); wherein collective analysis of data from sets of patients can inform trends and correlations via supervised machine learning which relies upon labeled datasets to make predictions based on past experience (i.e. receiving historical data and use said data to execute predictions), unsupervised learning, which attempts to identify patterns and trends from previous occurrences, and reinforcement learning, which maximizes reward through making a sequential set of decisions (pg. 14 col. 2 para. 2); wherein given a peptide sequence (i.e. expression product of the design nucleotide sequence – hence reading on a designed nucleotide sequence) and the HLA allele (i.e. immune target cell), the MixMHC2pred program would present an MHC binding score as a metric of peptide-MHC affinity showing an increase in true positives corresponding to the increase in MHCII-presented peptides correctly predicted by the algorithm relative to previous methods ( i.e. the increase in true positives predicted peptide-MHC affinity over previous methods read on the "within predetermined value of the one or more cell characteristics") (pg. 15 col. 1 para. 1).
identifying, by the sequence designing system, one or more feasible cell nucleotide sequences among the plurality of cell nucleotide sequences based on predefined reference information, wherein the one or more feasible cell nucleotide sequences is each assigned with a rank to generate a ranked list; and
generating, by the sequence designing system, an explanation for the ranked list of the one or more feasible cell nucleotide sequences, thereby designing the cell nucleotide sequences
• Zhou does not teach the recitations above. However, Bellazzi teaches main features of predictive clinical data mining and neural network learning models (i.e. reading on AI based model) that deal with temporal data (pg. 416 Abstract); wherein features are ranked on the basis of their predictive capability, measured in terms of a suitable objective function (i.e. identifying, by the sequence designing system, one or more feasible cell nucleotide sequences among the plurality of cell nucleotide sequences based on predefined reference information, wherein the one or more feasible cell nucleotide sequences is each assigned with a rank to generate a ranked list) (pg. 424 col.1 para. 1); wherein in classifying gene expression arrays the number of genes to be included in the final classifier was optimized by sequentially adding five genes from the ordered list and evaluating classification accuracy (i.e. an explanation for the ranked list) through leave-one-out cross-validation (pg. 422 col. 1 para. 1)
Claims 2 and 10 recite:
wherein receiving the historical data further comprises: performing, by the sequence designing system, one or more pre-processing operations on the historical data for verifying correctness and completeness of the historical data based on the predefined reference information; and arranging, by the sequence designing system, the historical data in a chronological order based on timestamps associated with the historical data
• Zhou does not teach the recitation above. However, Bellazzi teaches temporal abstraction of data for temporal reasoning to biomedical problems via the extraction of temporal patterns from time series data (i.e. arranging the historical data in a chronological order based on timestamps associated with the historical data) (pg. 420 col. 1 para. 3); wherein clinical time series need to be preprocessed from raw data to administrative data at a higher conceptual level in order to make them suitable for data mining applications (i.e. reading on verifying correctness and completeness of the historical data) (pg. 419 col. 2 para. 4); wherein processing techniques usually requires time series data to satisfy some assumptions (i.e. predefined reference information) (pg. 420 col. 1 para. 2).
Claims 6 and 14 recite:
wherein the historical data comprises at least one of one or more antigen nucleotide sequences, one or more cell nucleotide sequences, biomarkers data, function-specific biomarkers data, clinical trial progression data, clinical trial outcome data, in-vitro progression data, and in-vitro outcome data
• Zhou teaches engineering approaches ranging from sequencing and gene editing (i.e. reading on designing cell nucleotide sequences), to tumor organoids engineering, bioprinted tissues, and organs-on-a-chip systems (i.e. one or more procedures related to analysis of cell nucleotide sequences from one or more databases) using artificial intelligence (i.e. reading on AI based model) for the development of different immunotherapeutic agents (pg. 1 Abstract); wherein AI models can access databases that comprise characteristic information derived from the TCGA and immune checkpoint blockade clinical trials regarding the immune cells that have infiltrated 20 different types of solid tumors (i.e. historical data comprising clinical trial progression data) (pg. 15 col. 1 para. 2).
Claims 7 and 15 recite:
wherein the one or more cell characteristics comprises at least one of binding affinity, immune evasion, and cell fitness
• Zhou teaches that said designed sequences can be used as checkpoint inhibitors designed to block these pathways to prevent active T cells from binding the inhibitory ligands, thus improving their recognition, amplification, and killing capacity toward cancer cells which varies based on cancer types, diseases stages, and patients (i.e. reading on one of binding affinity, immune evasion, and cell fitness) (pg. 4 col. 1 para. 1).
Claims 8 and 16 recite:
wherein the predefined reference information comprises at least one of a three-dimensional (3D) structure and binding database, a gene regulatory and epigenetic database, a target selectivity database, a signaling pathways database, an inflammatory and Endoplasmic Reticulum (ER) stress database, and a threshold range database
• Zhou teaches the generation of massive databases of analytical images and/or videos from AI platforms to monitor cell systems in new ways to determine efficacy and drug–microscale tissue interactions (i.e. three-dimensional (3D) structure and binding database) (pg. 16 col. 1 para. 1).
Rationale for combining (MPEP §2142-2143)
Regarding claims 1-2, 6-10 and 14-17, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the methods of Zhou in view of Bellazzi because all references disclose methods for the designing of cell nucleotide sequences. The motivation would have been to incorporate temporal data and the efforts performed to translate molecular medicine results into clinically useful data mining (pg. 416 Abstract Bellazzi).
Therefore it would have been obvious to one of ordinary skill in the art to substitute the cell nucleotide sequence design method of Zhou to the methods by Bellazzi because such a substitution is no more than the simple substitution of one known element for another. One of ordinary skill in the art would be able to motivated to combine the teachings in these references with a reasonable expectation of success since the described teachings pertain to methods for designing of cell nucleotide sequences.
B. Claims 3-5 and 11-13 are rejected under 35 U.S.C. 103(a) as being unpatentable over Zhou and Bellazzi as applied to claims 1 and 9 above further in view of Walton ("Prediction of antisense oligonucleotide binding affinity to a structured RNA target." Biotechnology and bioengineering 65(1):1-9 (1999)), as cited on the attached Form PTO-892.
Claims 3 and 11 recite:
wherein predicting the plurality of cell nucleotide sequences comprises: determining, by the sequence designing system, an equilibrium dissociation constant (KD) related to binding affinity, value of biomarkers related to at least one of immune evasion and cell fitness using the AI based prediction model
• Zhou teaches that said designed sequences can be used as checkpoint inhibitors designed to block these pathways to prevent active T cells from binding the inhibitory ligands, thus improving their recognition, amplification, and killing capacity toward cancer cells (i.e. determining value of biomarkers related to at least one of immune evasion and cell fitness using the AI based prediction model) (pg. 4 col. 1 para. 1).
• Zhou does not teach "determining, by the sequence designing system, value of biomarkers related to at least one of immune evasion and cell fitness using the AI based prediction model based on an equilibrium dissociation constant." However, Walton teaches a prediction algorithm to identify oligonucleotide sequences with the highest predicted binding affinity for their target (pg. 1 Abstract); wherein the sequences found to have poor binding affinity experimentally (KD > 10,000 nM) were ranked as 14 of the lowest 20 in free energy among the tested sequences (i.e. determining, by the sequence designing system, value of biomarkers related to at least one of immune evasion and cell fitness using the AI based prediction model based on an equilibrium dissociation constant) (pg. 4 col. 2 para. 2)
Claims 4 and 12 recite:
wherein identifying the one or more feasible cell nucleotide sequences comprises: extracting, by the sequence designing system, a feasibility data corresponding to feasibility of each of the plurality of cell nucleotide sequences from the predefined reference information, based on an equilibrium dissociation constant (KD) and value of biomarkers related to at least one of immune evasion and cell fitness
• Zhou teaches that said designed sequences can be used as checkpoint inhibitors designed to block these pathways to prevent active T cells from binding the inhibitory ligands, thus improving their recognition, amplification, and killing capacity toward cancer cells which varies based on cancer types, diseases stages, and patients (i.e. extracting feasibility data based on value of biomarkers related to at least one of immune evasion and cell fitness - corresponding to feasibility of each of the plurality of cell nucleotide sequences from the predefined reference information – information predefined based on cancer types, diseases stages, and patients) (pg. 4 col. 1 para. 1).
• Zhou does not teach "extracting feasibility data based on an equilibrium dissociation constant - corresponding to feasibility of each of the plurality of cell nucleotide sequences from the predefined reference information – information predefined based on cancer types, diseases stages, and patients." However, Walton teaches a prediction algorithm to identify oligonucleotide sequences with the highest predicted binding affinity for their target (pg. 1 Abstract); wherein the sequences found to have poor binding affinity experimentally (KD > 10,000 nM) were ranked as 14 of the lowest 20 in free energy among the tested sequences (i.e. extracting feasibility data based on an equilibrium dissociation constant - corresponding to feasibility of each of the plurality of cell nucleotide sequences from the predefined reference information – information predefined based on cancer types, diseases stages, and patients) (pg. 4 col. 2 para. 2).
Claims 5 and 13 recite:
wherein identifying the one or more feasible cell nucleotide sequences further comprises: selecting, by the sequence designing system, one or more of the plurality of cell nucleotide sequences within predefined threshold ranges of at least one of immune evasion and cell fitness; and generating, by the sequence designing system, the ranked list of the one or more feasible cell nucleotide sequences based on an equilibrium dissociation constant (KD)
• Zhou teaches that, given a peptide sequence (i.e. expression product of the design nucleotide sequence – hence reading on a designed nucleotide sequence) and the HLA allele (i.e. immune target cell), the MixMHC2pred program would present an MHC binding score as a metric of peptide-MHC affinity showing an increase in true positives (i.e. selecting sequences within a criteria) corresponding to the increase in MHCII-presented peptides correctly predicted by the algorithm relative to previous methods ( i.e. the increase in true positives predicted peptide-MHC affinity over previous methods read on the "within predefined threshold ranges of at least one of immune evasion and cell fitness") (pg. 15 col. 1 para. 1).
• Zhou does not teach " generating, by the sequence designing system, the ranked list of the one or more feasible cell nucleotide sequences based on an equilibrium dissociation constant." However, Walton teaches a prediction algorithm to identify oligonucleotide sequences with the highest predicted binding affinity for their target (pg. 1 Abstract); wherein the sequences found to have poor binding affinity experimentally (KD > 10,000 nM) were ranked as 14 of the lowest 20 in free energy among the tested sequences (i.e. generating, by the sequence designing system, the ranked list of the one or more feasible cell nucleotide sequences based on an equilibrium dissociation constant) (pg. 4 col. 2 para. 2).
Rationale for combining (MPEP §2142-2143)
Regarding claims 3-5 and 11-13, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine, in the course of routine experimentation and with a reasonable expectation of success, the methods of Zhou and Bellazzi in view of Walton because all references disclose methods for the designing of cell nucleotide sequences. The motivation would have been to speed the development of sequences for both research and clinical applications (pg. 1 Abstract Walton).
Therefore it would have been obvious to one of ordinary skill in the art to substitute the method of extracting feasibility data and generating the ranked list of the one or more feasible cell nucleotide sequences of Zhou and Bellazzi to the methods by Walton because such a substitution is no more than the simple substitution of one known element for another. One of ordinary skill in the art would be able to motivated to combine the teachings in these references with a reasonable expectation of success since the described teachings pertain to methods for designing of cell nucleotide sequences.
Conclusion
No claims are allowed.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to FRANCINI A FONSECA LOPEZ whose telephone number is (571)270-0899. The examiner can normally be reached Monday - Friday 8AM - 5PM ET.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Olivia Wise can be reached at (571) 272-2249. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/F.F.L./Examiner, Art Unit 1685
/JANNA NICOLE SCHULTZHAUS/Examiner, Art Unit 1685
Prosecution Insights