DETAILED ACTION
Applicant' s response, filed 11 March 2026, has been fully considered. The following rejections and/or objections are either reiterated or newly applied. They constitute the complete set presently being applied to the instant application.
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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 11 March 2026 has been entered.
Claim Status
Claims 35-50 are pending and examined herein.
Claims 35-50 are rejected.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. JP 2017-171334, filed on 06 September 2017. Claims 35-48 are granted the claim to the benefit of priority to foreign application JP 2017-171334 filed 06 September 2017. Thus, the effective filling date of claims 35-48 is 06 September 2017.
Claim Interpretation
The limitation of “fingerprinting” as set out in the embodiment described in paragraph 48 of the specification as “substructures (fragments) of a molecular structure are assigned to the respective bits to represent the molecular structure; “1” is set to the bit if the corresponding substructure is present in the molecule and “0” is set to the bit if the corresponding substructure is absent. That is, the fingerprinting method can provide a mathematical expression by extracting features of a molecular structure”. Using BRI, fingerprinting in the context of the claims is interpreted to mean a way to characterize molecular structures.
Claim Rejections - 35 USC § 112
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.
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 rejections below are newly recited.
Claim 35-50 is 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 applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. This rejection is newly recited and necessitated by claim amendment.
Claim 35 recites “wherein two kinds or more selected from a plurality of kinds of fingerprinting methods” and “wherein the plurality of kinds of fingerprinting methods comprise an Atom pair type, a Circular type, a Substructure key type, and a Path-based type” which render the metes and bounds of the claim indefinite. MPEP 2173.05(h) states “Markush grouping requires a material selected from an open list of alternatives (e.g., selected from the group "comprising" or "consisting essentially of" the recited alternatives), the claim should generally be rejected under 35 U.S.C. 112(b) as indefinite because it is unclear what other alternatives are intended to be encompassed by the claim. See In re Kiely, 2022 USPQ2d 532 at 2* (Fed. Cir. 2022)”. The indefiniteness arises because group of the plurality of kinds of fingerprinting methods is selected from an open list of alternatives and it is unclear what other alternatives are intended to be encompasses by the claim. Dependent claims 36-50 are rejected by virtue of their dependency on a rejected claim without alleviating the indefiniteness. This rejection may be overcome by amendment of these limitations to “wherein two kinds or more selected from a plurality of kinds of fingerprinting methods are used…” and “wherein the plurality of kinds of fingerprinting methods consist of an Atom pair type, a Circular type…”. For the sake of furthering examination, these limitations will be interpreted as “wherein a plurality of kinds of fingerprinting methods are used…” and “wherein the plurality of kinds of fingerprinting methods consist of an Atom pair type, a Circular type…”.
Claim 50 recites “wherein the mathematical expression notated by one kind of fingerprinting method is connected to the mathematical expression notated by another kind of fingerprinting method in the plurality of kinds of fingerprinting methods” which renders the metes and bounds of the claim indefinite. The indefiniteness arises because it is unclear what the relationship between the mathematical expression of one fingerprinting method connected to the mathematical expression of another kind of fingerprinting method in the plurality kinds of fingerprinting methods is with the system set out in independent claim 35. This rejection may be overcome by amendment of “wherein the expression of the molecular structure is a connection of the mathematical expression notated by one kind of fingerprinting method and the mathematical expression notated by another kind of fingerprinting method in the plurality of kinds of fingerprinting methods”. For the sake of furthering examination, this limitation will be interpreted as wherein the expression of the molecular structure is the connection of the mathematical expression notated by one kind of fingerprinting method and the mathematical expression notated by another kind of fingerprinting method in the plurality of kinds of fingerprinting methods.
112/d
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The rejection below is newly recited.
Claim 46 and 47are rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. Claim 46 does not limit claim 35 in which it depends because the fingerprinting methods are inherently capable of expressing information about a structure featuring a physical property to be predicted. Claim 47 does not limit claim 35 in which it depends because at least one of the fingerprinting methods (i.e., atom pair type, a circular type, a substructure key type, and a path-based type fingerprint) is inherently capable of expressing at least one of a substituent, a substitution position of the substituent, a functional group, the number of elements, kinds of elements, valences of elements, a bond order, and an atomic coordinate. Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements. Further, a possible avenue forward could be to amend to recite “a substructure of the molecular structure featuring a physical property to be predicted” which would be further limiting at least one of the plurality of kinds of fingerprinting methods to a fingerprinting method which captured substructures of the molecular structure (i.e., a Substructure key type).
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 (i.e., changing from AIA to pre-AIA ) 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, 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 rejection below has been modified.
Claims 35-48 are rejected under 35 U.S.C. 103(a)(1) as being unpatentable over Kurokawa (US 20170063351 A1; previously cited) in view of Pyzer-Knapp et al. (Adv. Funct. Mater., 25: 6495-6502 (2015); previously cited).
Claim 35 is directed to a system comprising a data server, an input portion, an arithmetic portion comprising a neural network circuit, an output portion, wherein the neural network circuit comprises a product-sum arithmetic circuit, wherein the product-sum arithmetic circuit comprises a transistor including an oxide semiconductor in a channel formation region
Kurokawa shows to form a neural network using a semiconductor device there needs to be a synapse circuit that stores a connection strength between a first neuron circuit and a second neuron circuit and performs a multiply-accumulate operation (product-sum arithmetic circuit) in which output of the first neuron circuit and the connection strength are multiplied and accumulated (Kurokawa paragraph [010]). Kurokawa shows a semiconductor device including first to fourth circuits. The first circuit includes a first and second charge pump circuit, an analog memory, and a logic circuit. The first and second charge pump circuit each include a first transistor. The first transistor includes an oxide semiconductor in a channel formation region (Kurokawa paragraph [020]). Kurokawa shows an input portion which receives learning data as input and an output portion to provide output from the neural network (Kurokawa paragraphs [0103] - [109] and figure 10).
Kurokawa does not show using molecular structure and a physical property of an organic compound to learn a correlation between them by using a neural network and predict a target physical property from a molecular structure of an object substance input from the input portion on the basis of a result of the learning, wherein the output portion is configured to output the predicted target physical property, wherein two kinds or more selected from a plurality of kinds of fingerprinting methods are used at the same time for expression of the molecular structure of the organic compound at the time of the learning, each of the plurality of kinds of fingerprinting methods providing a mathematical expression by extracting features of the molecular structure, and wherein the plurality of kinds of fingerprinting methods comprise an Atom pair type, a Circular type, a substructure key type, and a Path-based type.
Like Kurokawa, Pyzer-Knapp et al. shows learning correlations utilizing a neural network. Pyzer-Knapp et al. shows using an artificial neural network to learn a correlation between molecular structure and the energy levels of the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) (physical property) (Pyzer-Knapp et al. page 6498 left col.). Pyzer-Knapp et al. shows using artificial neural networks to predict HOMO and LUMO energy levels from a molecular structure (Pyzer-Knapp et al. page 6501 left col.).
Pyzer-Knapp et al. shows a process of learning a correlation between molecular structure and a target property (HOMO or LUMO) which starts with a selection of input feature representation step that tests different fingerprinting methods performance in learning a correlation between molecular structure and a target property (Pyzer-Knapp et al. page 6498 right col.). Pyzer-Knapp et al. shows testing a hashed atom-pair fingerprint (i.e. an atom pair type), a MACCS key-based fingerprint (i.e. a substructure key type), a Morgan circular fingerprint (i.e. a circular type), and a hashed topological torsion fingerprint (i.e. a path-based type) by training neural network models each using one of these fingerprinting methods to predict either HOMO levels or LUMO levels for each molecule in the training set and the analyzing each model to determine the best performing fingerprinting method for predicting the target property (Pyzer-Knapp et al. page 6498 right col. and figure 3). Pyzer-Knapp et al. shows these fingerprinting methods are used at the same time in the process of learning a correlation between a molecular structure and a target property to select the best fingerprinting method to be used (Pyzer-Knapp et al. page 6498 right col. and figure 3).
Claims 36 are directed to wherein two kinds of fingerprinting methods are used as the plurality of kinds of fingerprinting methods. Claims 37 are directed to wherein three kinds of fingerprinting methods are used as the plurality of kinds of finger printing methods. Claims 38 are directed to wherein the two kinds of fingerprinting methods comprise the atom pair type and the circular type. Claims 39 are directed to wherein the two kinds of fingerprinting methods comprise the circular type and the substructure key type. Claims 40 are directed to wherein the two kinds of fingerprinting methods comprise the circular type and the path-based type. Claims 41 are directed to wherein the two kinds of fingerprinting methods comprise the atom pair type and the substructure key type. Claims 42 are directed to wherein the two kinds of fingerprinting methods comprise the atom pair type and the path-based type. Claims 43 are directed to wherein the three kinds of fingerprinting methods comprise the atom pair type and the substructure key type, and the circular type.
Pyzer-Knapp et al. shows testing a hashed atom-pair fingerprint (i.e. an atom pair type), a MACCS key-based fingerprint (i.e. a substructure key type), a Morgan circular fingerprint (i.e. a circular type), and a hashed topological torsion fingerprint (i.e. a path-based type) by training neural network models each using one of these fingerprinting methods to predict either HOMO levels or LUMO levels for each molecule in the training set and the analyzing each model to determine the best performing fingerprinting method for predicting the target property (Pyzer-Knapp et al. page 6498 right col. and figure 3).
Claims 44 are directed to wherein r is greater than or equal to 3 when the Circular type is used for one of the plurality of kinds of fingerprinting methods, and wherein r is the number of bonded elements counted starting from a certain element as 0. Claims 45 are directed to wherein r is greater than or equal to 5 in the Circular type.
Pyzer-Knapp et al. shows using a Morgan circular fingerprint with radius = 2 (Pyzer-Knapp et al. page 6498 right col.). The number of bonded elements is dependent on the number of elements in the molecule, the starting element denoted as 0, and the radius used (a radius of 2 captures information from the central atom itself, atoms 1 bond away, and atoms 2 bonds away). Using a Morgan circular fingerprint on a molecule with greater than or equal to 4 (or 6) elements (with one element being the starting element 0) satisfies this limitation.
Claims 46 are directed to wherein at least one of the plurality of kinds of fingerprinting methods is capable of expressing information about a structure featuring a physical property be predicted.
Pyzer-Knapp et al. shows a process of learning a correlation between molecular structure and a target property (HOMO or LUMO) which starts with a selection of input feature representation step that tests different fingerprinting methods performance in learning a correlation between molecular structure and a target property (Pyzer-Knapp et al. page 6498 right col.). This shows that the fingerprints represent the structure of a molecule which is used for correlating and predicting the molecule’s physical property.
Claims 47 are directed to wherein at least one of the plurality of kinds of fingerprinting methods is capable of expressing at least one of a functional group.
Pyzer-Knapp et al. shows using a fingerprint method of MACCS key-based fingerprint (i.e. a substructure key type) (Pyzer-Knapp et al. page 6498 right col. and figure 3).
Claims 48 are directed to wherein the physical property is any one or more of a HOMO level or LUMO level.
Pyzer-Knapp et al. shows using an artificial neural network to learn a correlation between molecular structure and the energy levels of the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) (physical property) (Pyzer-Knapp et al. page 6498 left col.)
It would have been obvious to one of ordinary skill in the art before the effective filling date to have modified the learning data of the neural network circuit of Kurokawa to be fingerprint data used to learn and predict the correlation between structure and physical property of Pyzer-Knapp et al. because this would allow for the use of specific hardware to implement the software neural network of Pyzer-Knapp et al. which improves computational efficiency. One would have a reasonable expectation of success because Kurokawa shows the learning data (input) of the neural network circuit is represented in binary and the number of neuron circuits to which learning data is input is determined in accordance with the number of bits of the learning data (Kurokawa [0179]) and Pyzer-Knapp et al. uses fingerprints that are fixed-length binary representation with a certain number of bits and the input layer of the neural network having the same number of neurons as the bits of the fingerprint data (Pyzer-Knapp et al. page 6498 right col.).
The rejection below is newly recited.
Claims 49 rejected under 35 U.S.C. 103(a)(1) as being unpatentable over Kurokawa (US 20170063351 A1; previously cited) in view of Pyzer-Knapp et al. (Adv. Funct. Mater., 25: 6495-6502 (2015); previously cited) as applied to claim 35, further in view of Kwak et al. (Organic Light Emitting Materials and Devices XX. Vol. 9941. SPIE, 2016; newly cited).
Kurokawa in view of Pyzer-Knapp et al. does not explicitly show the physical property is a T1 level.
Like Kurokawa in view of Pyzer-Knapp et al., Kwak et al. shows using molecular fingerprinting methods to predict a physical property based on a molecular structure. Kwak et al. shows predicting triplet energies by correlating molecular structure fingerprints to triplet energy calculations which were optimized at the lowest triplet excited state (T1) (Kwak et al. page 5 para. 4, page 6 figure 4 and para. 3, page 7 para. 5-6).
It would have been obvious to one of ordinary skill in the art before the effective filling date of the invention to substitute the predicted physical property of highest occupied molecular orbital and lowest unoccupied molecular orbital of Kurokawa in view of Pyzer-Knapp et al. with the predicted physical property of the lowest triplet excited state (T1) of Kwak et al. because both of these processes utilize models to correlate molecular fingerprints which express the molecular structure with a physical property of based on molecular orbitals.
Response to Arguments
Applicant's arguments filed 11March 2026 have been fully considered but they are not persuasive.
Applicant argues that a learning process to select the method for the best fingerprint in Pyzer-Knapp et al. is not two kinds or more selected from a plurality of kinds of fingerprinting methods are used at the same time for expression of the molecular structure of the organic. Applicant points to MPEP 2111 which states during patent examination, the pending claims must be given their broadest reasonable interpretation consistent with the specification and the broadest reasonable interpretation does not mean the broadest possible interpretation. Rather, the meaning given to a claim term must be consistent with the ordinary and customary meaning of the term (unless the term has been given a special definition in the specification), and must be consistent with the use of the claim term in the specification and drawings. Applicant argues using the broadest reasonable interpretation of the amended claim language consistent with the ordinary and customary meaning and consistent with the specification of the present application, the claimed feature of "two kinds or more selected from a plurality of kinds of fingerprinting methods are used at the same time for expression of the molecular structure of the organic" is not disclosed or suggested in Pyzer-Knapp et al. (Reply 8-9).
These arguments have been fully considered but found to be not persuasive. MPEP 2111.01(II) that "Though understanding the claim language may be aided by explanations contained in the written description, it is important not to import into a claim limitations that are not part of the claim. For example, a particular embodiment appearing in the written description may not be read into a claim when the claim language is broader than the embodiment." Superguide Corp. v. DirecTV Enterprises, Inc., 358 F.3d 870, 875, 69 USPQ2d 1865, 1868 (Fed. Cir. 2004). The breadth of two kinds or more (fingerprinting methods) are used at the same time for expression and the breadth of the limitation at the time of learning encompasses a process of testing multiple fingerprinting methods for a molecular structure which is interpreted as using two kinds or more are used at the same time for expression and selecting the best fingerprinting method is interpreted as “at the time of learning”. The breadth of at the time of learning is encompasses several variations of how the correlation is learned by the neural network circuit and is not limited to the embodiment where the neural network circuit itself receives two kinds or more (fingerprinting methods) at the same time.
Examiners comment
Regarding the 103 rejection above, a possible avenue for overcoming the above rejection is to limit the claim in a manner where the claim recites inputting two kinds or more (fingerprinting methods) as expression into the neural network circuit. Which will limit how the neural network circuit receives input and provide a clear difference between the instant application and prior art of record. An amendment for claim 35 may look like “wherein the arithmetic portion is configured to learn a correlation between the molecular structure and the physical property of the organic compound by inputting an expression of the molecular structure into the neural network circuit” and “wherein the expression of the molecular structure includes two kinds or more selected from a plurality of kinds of fingerprinting methods, wherein each of the plurality of kinds of fingerprinting methods providing a mathematical expression by extracting features of the molecular structure, wherein the plurality of kinds of fingerprinting methods consist of an Atom pair type…”. This amendment would provide that the input to the neural network is required to be an expression that includes two kinds or more fingerprinting methods.
Conclusion
No claims are allowed.
Claim 50 is free of the prior art of record. Pyzer-Knapp et al. is the closest prior art of record which shows utilizing a neural network to predict a physical property of a molecular structure using fingerprinting methods. However, the prior art of record does not show or render obvious the interpretation of claim 50 of wherein the expression of the molecular structure is a connection of the mathematical expression notated by one kind of fingerprinting method and the mathematical expression notated by another kind of fingerprinting method in the plurality of kinds of fingerprinting methods. Thus, claim 50 is free of the prior art of record.
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/J.E.H./Examiner, Art Unit 1685
/KAITLYN L MINCHELLA/Primary Examiner, Art Unit 1685