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 .
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, 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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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, 11 and 13-16 are rejected under 35 U.S.C. 103 as being unpatentable over Lambert (USPAP 2003/0182,101), in view of Tribble et al. (USPAP 2022/0375,579), hereinafter, “Tribble”.
Regarding claim 1 Lambert teaches, to identify a type of an identification target drug from an image obtained by capturing the identification target drug (Please note, figure 1, block 104); and a drug master file including information on one or more appearance attributes for each of a plurality of types of drugs, (Please note, paragraph 0113. As indicated attribute database updater 210 updates drug attribute database 214, which may be any kind of database, including a relational database, object-oriented database, unstructured database or other database; a data file or group of data files; a data stream; and/or any other known or yet-to-be developed structure or technique, whether local or remote, distributed or non-distributed, for providing access to data for use in a computing system.) and the one or more processors are configured to: calculate a first score value indicating likelihood of being a type of the identification target drug, for each of a plurality of types of drugs identifiable from the image (Please note, paragraph 0070. As indicated a processed attribute similarity score (or, as explained below, a severity-weighted similarity score or un-processed attribute similarity score) of 0.5 may be provided for a target-reference pair of drugs A and B, and a similar type of score of 6.2 for the drugs A and C.); identify one or more appearance attributes of the identification target drug from the image (Please note, paragraph 0046. As indicated The drug comparator includes a product attribute comparator that generates one or more product-attribute similarity scores representing a similarity of product attributes of a selected one or more target drugs and a selected one or more reference drugs); acquire from the drug master file, (Please note, paragraph 0113. As indicated attribute database updater 210 updates drug attribute database 214, which may be any kind of database, including a relational database, object-oriented database, unstructured database or other database; a data file or group of data files; a data stream; and/or any other known or yet-to-be developed structure or technique, whether local or remote, distributed or non-distributed, for providing access to data for use in a computing system) information on types of drugs matching the one or more appearance attributes of the identification target drug, and calculate a second score value by using the first score value and values set for the one or more appearance attributes and present candidates for the type of the identification target drug based on the second score value. (Please note, paragraph 0050. As indicated a name attribute comparator that generates name-attribute similarity scores representing a similarity of name attributes of the selected target and reference drugs. The name-attribute similarity scores are a type of attribute similarity scores; that is, the attribute similarity scores may be made up partially, or entirely, of name-attribute similarity scores. In some aspects, the name attribute comparator includes an orthographic analyzer that generates a name-attribute similarity score based at least in part on one or more comparisons between orthographic representations of the names of the selected target and reference drugs.).
Lambert does not expressly teach, utilizing a trained model.
Tribble teaches, trained model utilization. (Please note, paragraph 0035. As indicated the drug configuration module 236 may be configured to utilize one or more machine learned model.).
Lambert & Tribble are combinable because they are from the same field of endeavor.
At the time before the effective filing date, it would have been obvious to a person of ordinary skill in the art to utilize this trained model operation of Tribble in Lambert’s invention.
The suggestion/motivation for doing so would have been as indicated on paragraph 0035, “which are trained to identify drugs from the drug data of the drug management platform 101 based on drug information of the new drug code”.
Therefore, it would have been obvious to combine Tribble with Lambert to obtain the invention as specified in claim 1.
Regarding claim 11 Lambert teaches, wherein the drug master file includes information on a plurality of appearance attributes including an attribute relating to at least one of a shape and a color of a drug, and the one or more processors identify whether the identification target drug matches the plurality of appearance attributes or not. (Please note, paragraph 0037. As indicated comparing pharmaceutical drugs based on multiple attributes of the drugs. Comparisons between or among drugs may be based on the names of the drugs as well as a number of other attributes of the drug product. These other attributes are collectively referred to herein for convenience as "product attributes," as distinguished from a drug's "name attribute." For example, product attributes may include the dosage strengths of the drugs, their route of administration, or their color or shape.).
Regarding claim 13 Lambert teaches, a display configured to display the candidates for the type of the identification target drug. (Please note, paragraph 0108. As indicated a video monitor, printer, audio speaker with a voice synthesis device, or modem. Input-output devices 160 could also include any of a variety of known removable storage devices, including a compact disk drive, a tape drive, a removable hard disk drive, or a diskette drive.).
Regarding claim 14 Lambert teaches, a camera configured to capture the image of the identification target drug. (Please note, paragraph 0103. As indicated as shown in FIG. 1, user computer 110 includes known components such as a processor 105, operating system 120, memory 130, network interface 140, memory storage device 150, and input-output device 160. It will be understood by those skilled in the relevant art that there are many possible configurations of these components and that some components that may typically be included in user computer 110 are not shown, such as a video card, data backup unit, and many other devices.).
Regarding claims 15-16, analysis similar to those presented for claim 1 are applicable.
Allowable Subject Matter
Claims 2-10 and 12 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter: The closest applied Prior Art of record fails to disclose or reasonably suggest wherein the one or more storages store a second trained model trained to identify one or more appearance attributes of the identification target drug from the image, and the one or more processors identify whether or not the identification target drug belongs to a category corresponding to the one or more appearance attributes by using the second trained model.
Examiner’s Note
The examiner cites particular figures, paragraphs, columns and line numbers in the references as applied to the claims for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claims, other passages and figures may apply as well.
It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner.
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/AMIR ALAVI/Primary Examiner, Art Unit 2668 Thursday, September 4, 2025