DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 April 21, 2026, has been entered.
Response to Amendment
Claims 1 and 7 have been amended. Claims 2, 3, 5, and 8-13 have been canceled. Claims 1, 4, 6, and 7 are pending and are provided to be examined upon their merits.
Response to Arguments
Applicant's arguments filed March 23, 2026, have been fully considered but they are not persuasive. A response is provided below in bold where appropriate.
Applicant argues 35 USC §101 Rejection, starting pg. 4 of Remarks:
Rejection under 35 U.S.C. § 101:
The Office Action rejects claims 1, 4, 6 and 7 under 35 U.S.C. § 101 as being directed to an abstract idea without significantly more. This rejection is traversed, for the following reasons:
A. Step 2A - Prong 1: Not a Mental Process
The amended claims include the following specific technical processing steps:
- Generating gene expression information based on a first model trained on drug structure information and drug property information;
- Inputting the gene expression information into a trained second model;
- Adjusting the gene expression information through a gating mechanism based on learned weights trained to reflect co-administration effects;
- Projecting side effect information into a side effect vector space using translating embeddings; and
- Calculating distances between the projected high-dimensional vectors.
In particular, the "gating mechanism using learned weights" and "embedding-based vector space projection" are technical processing operations that presuppose execution by an electronic model and therefore do not constitute mental processes performable by a human.
Respectfully, the above gating mechanism, is based on a mathematical concept (para. [68] and [69]). As taught, the gating mechanism uses a sigmoid function. Even if this were not abstract as a mathematical concept, it is claimed at too high a level.
B. Rebuttal Regarding Mathematical Concepts
The claims define a specific technical architecture comprising a trained model structure, a weight-based gating mechanism, and a translating embedding-based vector space transformation. This is not a mere mathematical formula, but rather a concrete machine learning-based processing architecture for predicting drug-drug interactions. Accordingly, even if the claims involve mathematical operations, the inclusion of mathematical techniques applied within a specific technical architecture cannot, standing alone, render the claims directed to an abstract idea.
Machine learning is not claimed. Learning is recited at a high level of generality. Also, using existing machine learning at a high level of generality has been found not to be enough to make abstract claims statutory.
C. Not a Law of Nature
The Examiner concluded that identifying drug interactions from distances between gene expression information constitutes a law of nature. However, the "distance" recited in the present claims does not refer to any physical distance or biological correlation naturally existing between genes. Rather, it refers to an artificial vector distance computed in an artificially constructed side effect vector space-a space formed by vectors adjusted through a learned gating mechanism and further defined using side effect information. That is, this is not a law existing in nature, but a computational result derived in a learning-based embedding space constructed within an electronic device. Accordingly, the claims are not directed to a law of nature.
Applicant above is arguing the distance is based on an artificial vector distance. However, the basis of the vector is first and second gene expression information.
From Applicant’s specification…
“As the learning data of the first model 400, data obtained by treating multiple cell lines with drugs and measuring gene expression changed after a predetermined time may be used. For example, the standard data set may be a Library of Integrated Network-Based Cellular Signatures (LINCS) LlO00 database. The LINCS data includes gene expression information of compounds, cell lines, genes and response signatures.” [55]
The above is measuring gene expression changed after treating cell lines with drugs. Therefore, a gene expression, for example, protein A changes to protein B after treatment with a drug. Looking at a distance between the two gene expressions is based on the gene itself.
From MPEP 2106.04(b) I…
xi. the natural relationship between a patient’s CYP2D6 metabolizer genotype and the risk that the patient will suffer QTcprolongation after administration of a medication called iloperidone, Vanda Pharmaceuticals Inc. v. West-WardPharmaceuticals, 887 F.3d 1117, 1135-36, 126 USPQ2d 1266, 1281 (Fed. Cir. 2018).<<
Therefore, relationship between geneotype and disease risk with medication. This is similar to what Applicant is claiming with drug-drug interactions (disease risk with medications) and gene expression information.
D. Step 2A - Prong 2: Integrated into a Practical Application
Even assuming arguendo that an abstract concept is partially implicated, the present claims integrate it into a concrete electronic implementation. Specifically, the claims require: trained models stored in memory; model execution by a processor; reflection of co-administration effects through a gating mechanism; and vector space transformation using translating embeddings. Unlike merely performing simple calculations on a general-purpose computer, this constitutes a technical implementation requiring a specific model architecture and processing sequence, and therefore qualifies as a practical application.
Using processors and learning without additional elements are not enough as clamed to make abstract claims statutory. The gating mechanism is recited at a high level of generality.
E. Step 2B: Significantly More
The combination of the trained first model, second model, weight-based gating mechanism, translating embeddings, vector space projection, and distance calculation in the present claims defines a specific machine learning architecture for improving drug-drug interaction prediction accuracy, going well beyond a mere generic computer implementation. Accordingly, the claims include "significantly more" than the judicial exception.
Respectfully, the above includes abstract elements such as vector space projection and distance calculations, which cannot provide the additional elements. Also, elements such as trained models, gating mechanism are recited at a high level.
Accordingly, Applicant respectfully submits that amended independent claims 1 and 7 recite patent-eligible subject matter. The other claims are dependent from one of the independent claims discussed above, and are patent-eligible for at least the same reasons. Applicant, therefore, respectfully submits that the rejection under 35 U.S.C. § 101 is overcome.
In view of the remarks presented hereinabove, reconsideration and withdrawal of the rejection under 35 U.S.C. § 101 are respectfully requested.
The rejection is respectfully maintained but modified for the claim amendments.
Applicant argues 35 USC §112(b) Rejection, pg. 6 of Remarks:
Rejection under 35 U.S.C. § 112(b):
The Office Action rejects claims 1, 4, 6 and 7 under 35 U.S.C. § 112(b) as being indefinite. The Office Action asserts that some features recited in claim 7 are unclear.
In response, the claims are amended to address any noted indefiniteness issue. Applicant submits that there is no unclear expression in the amended claims.
Thus, Applicant submits that the amended claims overcome the rejection under 35 U.S.C. § 112(b). As such, Applicant respectfully requests reconsideration and withdrawal of the rejection under 35 U.S.C. § 112(b).
Withdrawn based on the claim amendments. However the amendments have caused a new 112 rejection.
Applicant argues 35 USC §103 Rejection, starting pg. 6 of Remarks:
Based on the claim amendments and further search and consideration, the prior art rejection is withdrawn, making Applicant’s arguments moot.
Claim Interpretation
Claim 1 recites “calculate gene expression information” and “calculate the information on drug-drug interactions using the gene expression information” where “calculate” is considered the same a “determine.” The recitation “calculate a distance between the projected first gene expression information and the projected second gene expression information” is considered a mathematical calculation that provides a numerical result.
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, 4, 6, and 7 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1, 4, 6, and 7 are directed to a system or method, which are statutory categories of invention. (Step 1: YES).
The Examiner has identified method Claim 7 as the claim that represents the claimed invention for analysis and is similar to system Claim 1.
Claim 7 recites the limitations of:
A control method of an electronic device for predicting drug-drug interactions (DDIs), the control method comprising:
identifying first gene expression information of a first drug and second gene expression information of a second drug based on a first model learned to calculate gene expression information according to drug structures information and drug properties information; and
inputting the first gene expression information and second gene expression information into a second model learned to calculate the information on drug-drug interactions using the gene expression information and information on side effects according to drug combination,
adjust the first gene expression information and the second gene expression information through a gating mechanism configured to reflect co-administration effects between the first drug and the second drug, wherein the gating mechanism is learned to give a weight to the first gene expression information and the second gene expression information,
project the adjusted first gene expression information and the adjusted second gene expression information into a side-effect vector space using translating embedding of the side effects information,
calculating a distance between the projected first gene expression information and the projected second gene expression information in a side-effect vector space, and
identifying information on drug-drug interactions based on the distance.
These above limitations, under their broadest reasonable interpretation, cover performance of the limitation as mental processes. The claim recites elements, highlighted in bold above, which covers performance of the limitation that can be concepts performed in the mind of a person or with pen and paper. A person can identify first and second gene expression information of a first and second drug, calculate drug expression information according to drug structure and properties information, input (write down with pen and paper) first and second gene information to calculate drug-drug interactions using gene expression and side effect information, adjust first and second gene expression information through a gating mechanism to reflect co-administration effects between the first and second drug, to give weight to the first and second expression information, project the adjusted first and second gene expression information into a side-effect vector space using translating embedding of the side effects information, calculate a distance between the projected first and second gene expression information in a vector space (see also paras. [4] and [5] of the specification). If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation as a mental process, then it falls within the “Mental Processes” grouping of abstract ideas. Also, see MPEP 2106.04(a)(2) III C where use of a generic computer was found to be part of mental processes. Accordingly, the claim recites an abstract idea. Claim 1 is also abstract for similar reasons. (Step 2A-Prong 1: YES. The claims are abstract)
In that the claims project the first and second gene expressions into a side-effect vector space (conversion from expressions into vector space, therefore converting numbers from one mathematical form to another), and calculates a distance between the projected first and second gene expression in a side-effect vector space, the claims are also abstract as under mathematical concepts grouping of abstract ideas. See MPEP 2106.04(a)(2) I C where mathematical calculations are found to be abstract.
This judicial exception is not integrated into a practical application. In particular, the claims only recite: electronic device, memory, processor (Claim 1); electronic device (Claim 7). The computer hardware is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. See Applicant’s Fig. 2 where the device appears to be a generic computing device and MPEP 2106.05(f) where applying a computer as a tool is not indicative of significantly more. The first model learned to calculate gene expression and second model learned to calculate the information on drug-drug interactions are recited at a high level of generality. The gating mechanism is recited at a high level of generality, and gating mechanism is learned is recited at a high level of generality, and a person can adjust and give weights to gene expression information to reflect co-administration effects between first and second drugs (see also gating as using sigmoid function (para. [68] and [69] of the specification). Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Therefore claims 1 and 7 are directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application)
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when considered separately and as an ordered combination, they do not add significantly more (also known as an “inventive concept”) to the exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a computer hardware amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The first and second model are generic models recited at a high level of generality. Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Thus claims 1 and 7 are not patent eligible. (Step 2B: NO. The claims do not provide significantly more)
Dependent claims 4 and 6 further define the abstract idea that is present in their independent claim 1 and thus correspond to Mental Processes and Mathematical Concepts and hence are abstract for the reasons presented above. The dependent claims do not include any additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination. Claim4 recites model learned to calculate gene expression information (see para. [69] and use of weight and sigmoid function to calculate gene expression information), information on drug-drug interactions (see paras. [84] – [87] for score of drug pair side effects), which are abstract as Mathematical Concepts. Therefore, the claims 4 and 6 are directed to an abstract idea. Thus, the claims 1, 4, 6, and 7 are not patent-eligible.
Law of Nature
Claims 1, 4, 6, and 7 are also rejected under 35 USC 101 as they recite laws of nature. Claim 1 recites identify information on drug-drug interactions based on the distance, where the distance is between a first gene expression information and second gene expression information. A distance between first and second gene expression information that identifies drug-drug interactions would be a law of nature as identifies drug-drug interaction relies on genetic expression information. Therefore, the drug-drug interaction is based on gene distance, which is a law of nature. See MPEP 2106.04(b) and examples. Claim 7 recites a law of nature for similar reasons.
Similar to the reasons given above for the abstract claims, the claims to not provide a practical application or significantly more under Steps 2A and 2B.
The dependent claims 4 and 6 are rejected as they depend from and further limit their respective independent claim or are themselves reciting laws of nature.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1, 4, 6, and 7 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
An adequate written description for a computer-implemented functional claim limitation contains both the computer and the algorithm that perform the claimed function in sufficient detail such that one of ordinary skill in the art can reasonably conclude that the inventor possessed the claimed subject matter at the time of filing. It is not enough that one skilled in the art could write a program to achieve the claimed function because the specification must explain how the inventor intends to achieve the claimed function to satisfy the written description requirement (MPEP § 2161.01).
Claim 1 recites “adjust the first gene expression information and the second gene expression information through a gating mechanism configured to reflect co-administration effects between the first drug and the second drug, wherein the gating mechanism is learned to give a weight to the first gene expression information and the second gene expression information,…” The instant disclosure fails to adequately disclose the method of performing said gating mechanism learned to give a weight and one of ordinary skill in the art could not reasonably ascertain the methodology for a learned gating mechanism. While the level of detail required to satisfy the written description requirement varies depending on the nature and scope of the claims and on the complexity and predictability of the relevant technology, the claims read in light of the specification fail to disclose the algorithm for gating mechanism is learned in sufficient detail. Claim 7 has a similar problem.
Claims 4 and 6 are further rejected as they depend from their respective independent claims.
Examiner Request
The Applicant is requested to indicate where in the specification there is support for amendments to claims should Applicant amend. The purpose of this is to reduce potential 35 U.S.C. §112(a) or §112 1st paragraph issues that can arise when claims are amended without support in the specification. The Examiner thanks the Applicant in advance.
Prior Art
Based on further search and consideration, the prior art rejection is withdrawn. The best prior art found to date is Mei et al. Mei teaches drug-drug interactions and genes. However, Mei fails to teach or render obvious a gating mechanism learned to give a weight to first and second gene expression and side-effect vector space.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KENNETH BARTLEY whose telephone number is (571)272-5230. The examiner can normally be reached Mon-Fri: 7:30 - 4:00 EST.
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/KENNETH BARTLEY/Primary Examiner, Art Unit 3684
