The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
Notice to Applicant
In response to the communication received on 03/24/2026, the following is a Final Office Action for Application No. 18134581.
Status of Claims
Claims 1, 3-5 and 7 are pending.
Claims 2 and 6 are cancelled.
Priority
As required by M.P.E.P. 201.14(c), acknowledgement is made of applicant’s claim for priority based on: 18134581 filed 04/14/2023 is a Continuation of PCT/JP2020/047562, filed 12/18/2020.
Response to Amendments
Applicant’s amendments have been fully considered.
Response to Arguments
Applicant’s arguments with respect to the claims have been considered but are moot in light of the new grounds of rejection, as necessitated by amendment.
As per the 101 rejection, Applicant argues that the claims are in favor of eligibility per Prong One of Step 2A, however Examiner respectfully disagrees. Per Prong One of Step 2A, the identified recitation of an abstract idea falls within at least one of the Abstract Idea Groupings consisting of: Mathematical Concepts, Mental Processes, or Certain Methods of Organizing Human Activity. Particularly, the identified recitation falls within the Mental Processes including concepts performed in the human mind (including an observation, evaluation judgment, opinion) and/or Certain Methods of Organizing Human Activity including managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules of instructions). Since the recitation of the claims falls into at least one of the above Groupings, there is a basis for providing further analysis with regard to Prong Two of Step 2A to determine whether the recitation of an abstract idea is deduced to being directed to an abstract idea. Thus, the rejection is maintained.
Applicant argues that the claims are in favor of eligibility per Prong Two of Step 2A, however Examiner respectfully disagrees. Per Prong Two of Step 2A, this judicial exception is not integrated into a practical application because the claim as a whole does not integrate the identified abstract idea into a practical application. The computer, processor and/or memory medium is recited at a high level of generality, i.e., as a generic processor performing a generic computer function of processing/transmitting data. This generic processor server limitation is no more than mere instructions to apply the exception using a generic computer component. Further, computer, processor and/or memory medium to inter alia perform the function of analyzing a reagent that is able to replace a subcompound of the target compound to be analyzed is mere instruction to apply an exception using a generic computer component which cannot integrate a judicial exception into a practical application. Accordingly, this/these additional element(s) does/do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. In other words, the present claims use a generic processing device and memory medium to inter alia perform the function of analyzing a reagent that is able to replace a subcompound of the target compound to be analyzed which is a concept that can be performed in the human mind. The processor is merely used to perform the function(s), and the processor does not integrate the abstract idea into a practical application since there are no meaningful limits on practicing the abstract idea. Thus, since the claims are directed to the determined judicial exception in view of the two prongs of Step 2A, the 2019 PEG flowchart is directed to Step 2B. Thus, the rejection is maintained.
Applicant argues that the claims are in favor of eligibility per Step 2B, however Examiner respectfully disagrees. Therein, the additional elements and combinations therewith are examined in the claims to determine whether the claims as a whole amounts to significantly more than the judicial exception. It is noted here that the additional elements are to be considered both individually and as an ordered combination. In this case, the claims each at most comprise additional elements of: computer, processor and/or memory medium. Taken individually, the additional limitations each are generically recited and thus does not add significantly more to the respective limitations. Further, computer, processor and/or memory medium to inter alia perform the function of analyzing a reagent that is able to replace a subcompound of the target compound to be analyzed is mere instruction to apply an exception using a generic computer component which cannot provide an inventive concept in Step 2B (or, looking back to Step 2A, cannot integrate a judicial exception into a practical application). For further support, the Applicant’s specification supports the claims being directed to use of a generic computer/memory type structure. Taken as an ordered combination, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the limitations are directed to limitations referenced in Alice Corp. that are not enough to qualify as significantly more when recited in a claim with an abstract idea include the non-limiting or non-exclusive examples of MPEP § 2106.05. Thus, the rejection is maintained.
In an effort to further expedite prosecution, see: July 2024 Subject Matter Eligibility Examples, Example 47. Anomaly Detection. Per the analysis of claim 2 Example 47, the analysis refers to MPEP 2106.05(f) which provides the following considerations for determining whether a claim simply recites a judicial exception with the words “apply it” (or an equivalent), such as mere instructions to implement an abstract idea on a computer: (1) whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished; (2) whether the claim invokes computers or other machinery merely as a tool to perform an existing process; and (3) the particularity or generality of the application of the judicial exception. Although the additional elements, e.g. (per Example 47) “using a trained ANN”, limits the identified judicial exceptions, e.g. (per Example 47) “detecting one or more anomalies in a data set using the trained ANN” and, e.g. (per Example 47) “analyzing the one or more detected anomalies using the trained ANN to generate anomaly data,” this type of limitation merely confines the use of the abstract idea to a particular technological environment, e.g. (per Example 47: neural networks) and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h). As an exemplary direction for claim limitations to be eligible, see claims 1 and 3 of Example 47.
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, 3-5 and 7 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 claims fall within statutory class of process or machine or manufacture; hence, the claims fall under statutory category of Step 1.
Step 2 is the two-part analysis from Alice Corp. (also called the Mayo test). The 2019 PEG makes two changes in Step 2A: It sets forth new procedure for Step 2A (called “revised Step 2A”) under which a claim is not “directed to” a judicial exception unless the claim satisfies a two-prong inquiry. The two-prong inquiry is as follows: Prong One: evaluate whether the claim recites a judicial exception (an abstract idea enumerated in the 2019 PEG, a law of nature, or a natural phenomenon). If claim recites an exception, then Prong Two: evaluate whether the claim recites additional elements that integrate the exception into a practical application of the exception. The claim(s) recite(s) the following abstract idea indicated by non-boldface font and additional limitations indicated by boldface font:
non-transitory computer-readable recording medium having stored therein an information processing program that causes a computer to execute a process comprising:executing training of a trained model based on training data defining relations between vectors corresponding to target compounds and vectors respectively corresponding to plural subcompounds included in synthetic pathways for manufacture of the target compounds; and calculating vectors of plural subcompounds corresponding to a target compound to be analyzed by inputting a vector of the target compound to be analyzed into the trained model in a case where the target compound to be analyzed has been received, the vectors of the plural subcompounds being each a result of addition of the vectors of compressed codes of groups composing the plural subcompounds, the vector being assigned according to the embedded position in a Poincare space for each groups composing each of the plural subcompounds; andanalyzing, based on proximity of positions in Poincare space between the vectors of the plural subcompounds and vectors of plural reagents serving as replacement candidates, a reagent that is able to replace a subcompound of the target compound to be analyzed, the vectors of the plural subcompounds having been calculated by the calculating.
[or]
executing training of a trained model based on training data defining relations between vectors of plural subcompounds included in a synthetic pathway for manufacture of a target compound and vectors of common structures representing structures common to structures of the subcompounds and structures of reagents; andcalculating a vector of a common structure corresponding to a subcompound to be analyzed by inputting a vector of the subcompound to be analyzed into the trained model in a case where the subcompound to be analyzed has been received, by using a processor, the vectors of the plural subcompounds being each a result of addition of the vectors of compressed codes of groups composing the plural subcompounds, the vector being assigned according to the embedded position in a Poincare space for each groups composing each of the plural subcompounds; andanalyzing, based on proximity of positions in Poincar6 space between the vectors of the plural subcompounds and vectors of plural reagents serving as replacement candidates, a reagent that is able to replace a subcompound of the target compound to be analyzed, the vectors of the plural subcompounds having been calculated by the calculating.
[or]
a memory; and a processor coupled to the memory and configured to: execute training of a trained model based on training data defining relations between a vector corresponding to a target compound and vectors respectively corresponding to plural subcompounds included in a synthetic pathway for manufacture of the target compound; and calculate vectors of plural subcompounds corresponding to a target compound to be analyzed by inputting a vector of the target compound to be analyzed into the trained model in a case where the target compound to be analyzed has been received, the vectors of the plural subcompounds being each a result of addition of the vectors of compressed codes of groups composing the plural subcompounds, the vector being assigned according to the embedded position in a Poincare space for each groups composing each of the plural subcompounds; andanalyze, based on proximity of positions in Poincare space between the vectors of the plural subcompounds and vectors of plural reagents serving as replacement candidates, a reagent that is able to replace a subcompound of the target compound to be analyzed, the vectors of the plural subcompounds having been calculated by the calculating.
The claim(s) recite(s) the following summarization of the abstract idea which includes calculating vectors of plural subcompounds corresponding to a target compound to be analyzed by inputting a vector of the target compound executed by the additional element(s) of memory medium, computer and/or processor. This falls into at least the Abstract Idea Grouping of Mental Processes since the information can be analyzed by an abstract evaluation judgment process. Thus, the identified recitation of an abstract idea falls within at least one of the Abstract Idea Groupings consisting of: Mathematical Concepts, Mental Processes, or Certain Methods of Organizing Human Activity since the identified recitation falls within the Mental Processes including concepts performed in the human mind (including an observation, evaluation judgment, opinion).
Per Prong One of Step 2A, the identified recitation of an abstract idea falls within at least one of the Abstract Idea Groupings consisting of: Mathematical Concepts, Mental Processes, or Certain Methods of Organizing Human Activity. Particularly, the identified recitation falls within the Mental Processes including concepts performed in the human mind (including an observation, evaluation judgment, opinion).
Per Prong Two of Step 2A, this judicial exception is not integrated into a practical application because the claim as a whole does not integrate the identified abstract idea into a practical application. The computer, processor and/or memory medium is recited at a high level of generality, i.e., as a generic processor performing a generic computer function of processing/transmitting data. This generic computer, processor and/or memory medium limitation is no more than mere instructions to apply the exception using a generic computer component. Further, calculate vectors of plural subcompounds corresponding to a target compound to be analyzed by inputting a vector by a computer, processor and/or memory medium is mere instruction to apply an exception using a generic computer component which cannot integrate a judicial exception into a practical application. Accordingly, this/these additional element(s) does/do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Thus, since the claims are directed to the determined judicial exception in view of the two prongs of Step 2A, the 2019 PEG flowchart is directed to Step 2B.
Per Step 2B, the additional elements and combinations therewith are examined in the claims to determine whether the claims as a whole amounts to significantly more than the judicial exception. It is noted here that the additional elements are to be considered both individually and as an ordered combination. In this case, the claims each at most comprise additional elements of: computer, processor and memory medium. Taken individually, the additional limitations each are generically recited and thus does not add significantly more to the respective limitations. Further, calculate vectors of plural subcompounds corresponding to a target compound to be analyzed by inputting a vector by a computer, processor and/or memory medium is mere instruction to apply an exception using a generic computer component which cannot provide an inventive concept in Step 2B (or, looking back to Step 2A, cannot integrate a judicial exception into a practical application). For further support, the Applicant’s specification supports the claims being directed to use of a generic computer/memory type structure at ¶0139 wherein “As illustrated in FIG. 21, a computer 300 has a CPU 301 that executes various kinds of arithmetic processing.” Taken as an ordered combination, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the limitations are directed to limitations referenced in Alice Corp. that are not enough to qualify as significantly more when recited in a claim with an abstract idea include, as a non-limiting or non-exclusive examples: i. Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp., 134 S. Ct. at 2360, 110 USPQ2d at 1984 (see MPEP § 2106.05(f));
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ii. Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 134 S. Ct. at 2359-60, 110 USPQ2d at 1984 (see MPEP § 2106.05(d));
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iii. Adding insignificant extra-solution activity to the judicial exception, e.g., mere data gathering in conjunction with a law of nature or abstract idea such as a step of obtaining information about credit card transactions so that the information can be analyzed by an abstract mental process, as discussed in CyberSource v. Retail Decisions, Inc., 654 F.3d 1366, 1375, 99 USPQ2d 1690, 1694 (Fed. Cir. 2011) (see MPEP § 2106.05(g)); or
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v. Generally linking the use of the judicial exception to a particular technological environment or field of use, e.g., a claim describing how the abstract idea of hedging could be used in the commodities and energy markets, as discussed in Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1010 (2010) or a claim limiting the use of a mathematical formula to the petrochemical and oil-refining fields, as discussed in Parker v. Flook. The courts have recognized the following computer functions inter alia to be well-understood, routine, and conventional functions when they are claimed in a merely generic manner: performing repetitive calculations; receiving, processing, and storing data (e.g., the present claims); electronically scanning or extracting data; electronic recordkeeping; automating mental tasks (e.g., process/machine/manufacture for performing the present claims); and receiving or transmitting data (e.g., the present claims).
The dependent claims do not cure the above stated deficiencies, and in particular, the dependent claims further narrow the abstract idea without reciting additional elements that integrate the exception into a practical application of the exception or providing significantly more than the abstract idea. Since there are no elements or ordered combination of elements that amount to significantly more than the judicial exception, the claims are not eligible subject matter under 35 USC §101.
Thus, viewed as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself. Therefore, the claim(s) are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
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.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention 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 35 U.S.C. 103 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.
Claims 1, 3-5 and 7 are rejected under 35 U.S.C. 103 as being unpatentable over Takeda et al. (US 20190286791 A1) hereinafter referred to as Takeda in view of Watano et al. (US 20160091756 A1) hereinafter referred to as Watano.
Takeda teaches:
Claim 1. A non-transitory computer-readable recording medium having stored therein an information processing program that causes a computer to execute a process comprising:
executing training of a trained model based on training data defining relations between vectors corresponding to target compounds and vectors respectively corresponding to plural subcompounds included in synthetic pathways for manufacture of the target compounds (¶0020,¶0021 and ¶0050 In block 225, the regression model can be trained using known materials and properties to identify candidate features for a feature vector set and predict the associated target properties. ¶0051 After sufficiently training the regression model, the model can obtain a candidate feature vectors set that can satisfy a user's query for selected properties with targeted values. ¶0052 In block 227 a user can select a chemical or physical property that the user intends to use as a reference for identifying a new chemical structure. The chemical or physical property can be selected from a list of chemical/physical properties. The processing system can receive the selected chemical or physical property and use the property in the search algorithm. One or more properties can be selected by the user. A sum-set of .sup.(j) for all the selected properties y.sub.j can be utilized. ¶0077 In block 275, the newly generated chemical structure can be synthesized for testing and use using various synthetic methods. The new chemical structure can be used to prepare a synthetic pathway for making the new chemical compound. ¶0078 In block 280 the synthesized chemical compound can be tested using various analytical and instrumental methods to determine the actual values for the selected chemical and/or physical properties. The testing can determine if the synthesized compound has the property values utilized in generating the candidate structure(s) and/or identified as the target value(s).); and
calculating vectors of plural subcompounds corresponding to a target compound to be analyzed by inputting a vector of the target compound to be analyzed into the trained model in a case where the target compound to be analyzed has been received (¶0089 To select only the substructures that affect the target property, a feature selection process can be performed on it. By denoting the target property as t, a LASSO (Least Absolute Shrinkage and Selection Operator) regression model custom-character: x.sub.Dcustom-charactery can be created. Tuning the hyperparameter (degree of L.sub.1 penalty term) and setting a threshold w.sub.th for absolute value of regression coefficient |w|, the system selects important substructures. We denote the set of selected substructures as custom-character.sup.Select, and corresponding feature vector as X.sub.D.sup.Select. custom-character.sup.select can be referred to as a data-driven substructure feature set and X.sub.D.sup.Select as the data-driven substructure feature vector. The substructure selection can be accomplished by L1 regularization to select effective substructures. L2 regularization can be utilized for substructure selection for the predefined components of the predefined component set. ¶0090 A final structure set can be a concatenation of a data-driven substructure feature set and a predefined component feature set, x:=(X.sub.D.sup.Select, x.sub.P).);
the vectors of the plural subcompounds being each a result of addition of the vectors of compressed codes of groups composing the plural subcompounds, the vector being assigned according to the embedded position in a Poincare space for each groups composing each of the plural subcompounds; andanalyzing, based on proximity of positions in Poincare space between the vectors of the plural subcompounds and vectors of plural reagents serving as replacement candidates, a reagent that is able to replace a subcompound of the target compound to be analyzed, the vectors of the plural subcompounds having been calculated by the calculating (¶0041 Most chemical properties are affected by substructures included in the chemical structure of a compound (e.g., organic molecules, biological compounds, inorganic compounds, polymers, etc.). Regression analysis and modeling can be used to identify the contribution of separate substructure(s) in a compound to a specific property through analysis of a large data set of chemical compounds including the particular substructure(s). The converting of the chemical structures to feature vectors, regression analysis and modeling, and filtering of new candidate structures can be driven by data and automated analysis rather than human experience, as shown in process algorithm 200. ¶0049 A regression model, F, can be built to predict a target property, y, from an identified set of substructures, where F:custom-charactery, where x is a concatenated feature vector x:=(X.sub.D.sup.Select,x.sub.P), and y is the property. The type of regression model, F, utilized can depend on both the type of material(s) identified and the target properties selected. A regression model can be independently created for each property as F.sub.1:x.sub.1custom-charactery.sub.1, F.sub.2:x.sub.2custom-charactery.sub.2, etc. The regression analysis may utilize any regression method to provide adequate accuracy.. In case that multiple chemical and/or physical properties are targeted, x, is a sum-set of ω for property y.sub.j given as x=x.sup.(j)∪.sup.N.sub.j=1x.sup.(j), where j is an index from 1 to the number of properties selected, and x.sup.(j) for is the j.sup.th substructure that can contribute to the j.sup.th property, y.sub.j ¶0089 To select only the substructures that affect the target property, a feature selection process can be performed on it. By denoting the target property as t, a LASSO (Least Absolute Shrinkage and Selection Operator) regression model custom-character: x.sub.Dcustom-charactery can be created. Tuning the hyperparameter (degree of L.sub.1 penalty term) and setting a threshold w.sub.th for absolute value of regression coefficient |w|, the system selects important substructures. We denote the set of selected substructures as custom-character.sup.Select, and corresponding feature vector as X.sub.D.sup.Select. custom-character.sup.select can be referred to as a data-driven substructure feature set and X.sub.D.sup.Select as the data-driven substructure feature vector. The substructure selection can be accomplished by L1 regularization to select effective substructures. L2 regularization can be utilized for substructure selection for the predefined components of the predefined component set ¶0043 In one or more embodiments, a feature vector can be created for each chemical compound in the data set of materials by counting the number of each of all the possible specific substructure permutations identified in the chemical compound structure. Two different types of feature vectors can be created. The first type of feature vector can include a data-driven substructure count, and the second type of feature vector can include a predefined component count. Each feature vector can include values for the quantity of each identified substructure for a single chemical compound).
Although not explicitly taught by Takeda, Watano teaches in the analogous art of projection image display and projection image display system:
the vector being assigned according to the embedded position in a Poincare space for each groups composing each of the plural subcompounds;and analyzing, based on proximity of positions in Poincare space between the vectors of the plural subcompounds and vectors of plural reagents serving as replacement candidates, a reagent that is able to replace a subcompound of the target compound to be analyzed (¶0039 FIG. 1 is a diagram showing the change in a polarization state of incident light in a member for projection image display in Example 1, by using a Poincare sphere. ¶0040 FIG. 2 is a diagram showing the change in a polarization state of incident light in a member for projection image display in Comparative Example 1, by using a Poincare sphere. ¶0041 FIG. 3 is a diagram showing the change in a polarization state of incident light in a member for projection image display in Example 7, by using a Poincare sphere. ¶0191 When taking, as an example, a configuration of using three cholesteric liquid crystals having different selective reflection central wavelengths for the reflection layer, also in the cases where combinations of dispositions of the reflection central wavelength (6 ways) and dispositions of the rod-like liquid crystal compound and the discotic liquid crystal compound (8 ways), and Re, Rth and the slow axis of the retardation layer are changed, in the same manner as examples of projection image display systems using member for projection image displays in the above Example and Comparative Example, superiority or inferiority of brightness and white degree (tint balance) can be determined by considering the polarization state of incident light on the Poincare sphere.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the projection image display and projection image display system of Watano with the system for creation of new chemical compounds having desired properties using accumulated chemical data to construct a new chemical structure for synthesis of Takeda for the following reasons:
(1) a finding that there was some teaching, suggestion, or motivation, either in the references themselves or in the knowledge generally available to one of ordinary skill in the art, to modify the reference or to combine reference teachings, e.g. Takeda ¶0002 teaches that it is desirable to identify and design new chemical structures that have particular intended properties for synthesis which can be very time consuming and expensive;
(2) a finding that there was reasonable expectation of success since the only difference between the claimed invention and the prior art being the lack of actual combination of the elements in a single prior art reference, e.g. Takeda teaches preparing a data-driven substructure feature vector for each of a plurality of chemical compounds for which a chemical or physical property is known and further includes preparing a predefined component feature vector, creating a regression model to predict a target value for the chemical or physical property, and performing a search algorithm to identify substructure features that affect the target value for the chemical or physical property, and Watano teaches the a member for projection image display, including a reflection layer and a retardation layer, wherein the reflection layer includes a cholesteric liquid crystal layer exhibiting selective reflection in a visible light region; and
(3) whatever additional findings based on the Graham factual inquiries may be necessary, in view of the facts of the case under consideration, to explain a conclusion of obviousness, e.g. Takeda at least the above cited paragraphs, and Watano at least the inclusively cited paragraphs.
Therefore, it would be obvious to one skilled in the art at the time of the invention to combine the projection image display and projection image display system of Watano with the system for creation of new chemical compounds having desired properties using accumulated chemical data to construct a new chemical structure for synthesis of Takeda. The rationale to support a conclusion that the claim would have been obvious is that "a person of ordinary skill in the art would have been motivated to combine the prior art to achieve the claimed invention and whether there would have been a reasonable expectation of success in doing so." DyStar Textilfarben GmbH & Co. Deutschland KG v. C.H. Patrick Co., 464 F.3d 1356, 1360, 80 USPQ2d 1641, 1645 (Fed. Cir. 2006). See MPEP 2143(G).
Takeda teaches:
Claim 3. The non-transitory computer-readable recording medium according to claim 2, wherein the process further includes retrieving information on a rational formula of the reagent as information on the replaceable reagent and outputting a result of the retrieval (¶0049 A regression model, F, can be built to predict a target property, y, from an identified set of substructures, where F:custom-charactery, where x is a concatenated feature vector x:=(X.sub.D.sup.Select,x.sub.P), and y is the property. The type of regression model, F, utilized can depend on both the type of material(s) identified and the target properties selected. A regression model can be independently created for each property as F.sub.1:x.sub.1custom-charactery.sub.1, F.sub.2:x.sub.2custom-charactery.sub.2, etc. The regression analysis may utilize any regression method to provide adequate accuracy).
Takeda teaches:
Claim 4. The non-transitory computer-readable recording medium according to claim 1, wherein the target compound to be analyzed is indicated by information that is a combinationof plural groups, and the process further includes calculating the vector of the target compound to be analyzed by adding up vectors of the plural groups (¶0043 In one or more embodiments, a feature vector can be created for each chemical compound in the data set of materials by counting the number of each of all the possible specific substructure permutations identified in the chemical compound structure. Two different types of feature vectors can be created. The first type of feature vector can include a data-driven substructure count, and the second type of feature vector can include a predefined component count. Each feature vector can include values for the quantity of each identified substructure for a single chemical compound. The identity of each of all the possible specific substructure permutations for a single chemical compound can form a data-driven substructure set.).
As per claims 5 and 7, the method and apparatus tracks the NTCRM medium of claims 1 and 1, respectively, resulting in substantially similar limitations. The same cited prior art and rationale of claims 1and 1 are applied to claims 5 and 7, respectively. Takeda discloses that the embodiment may be found as an apparatus (Figs. 1-5). Additional limitations of claim 5 are as follows however:
Takeda teaches:
vectors of plural subcompounds included in a synthetic pathway for manufacture of a target compound and vectors of common structures representing structures common to structures of the subcompounds and structures of reagents (¶0093 In one or more embodiments, the predicted chemical structure can be synthesized to provide a physical organic molecule, inorganic compound, polymer, or other chemical for testing and review of the resulting properties. The organic molecule(s) may be synthesized using known organic preparatory methods available to chemists. Polymers may be prepared by synthesizing the organic monomer using known organic preparatory methods and polymerizing the resulting monomer to produce the polymer. Inorganic compounds may be synthesized using known inorganic preparatory methods. ¶0096 In one or more embodiments, backbone components of the predefined feature vector can include, for example, substructures: (A) bonded 5-member rings, (B) fused 5-member rings, (C) bonded 6-member rings, (D) fused 6-member rings, (E) linear bonded carbon chains, (F) branched bonded carbons, (G) ether bond, and (H) alcohol groups. FIG. 7 is a block/flow diagram showing a particle swarm optimization algorithm in a chemical space, in accordance with an embodiment of the present invention. Identifying candidate feature vectors that satisfy user-selected target properties can be difficult due to non-linear aspects of an inverse regression model).
Conclusion
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 KURTIS GILLS whose telephone number is (571)270-3315. The examiner can normally be reached on M-F 8-5 PM.
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/KURTIS GILLS/Primary Examiner, Art Unit 3624