Prosecution Insights
Last updated: August 15, 2026
Application No. 17/055,447

THERAPY-BASED DATABASE MODEL FOR GENERATING DRUG LIBRARIES

Final Rejection §103
Filed
Nov 13, 2020
Priority
May 15, 2018 — provisional 62/671,424 +1 more
Examiner
DARB, HAMZA A.
Art Unit
3783
Tech Center
3700 — Mechanical Engineering & Manufacturing
Assignee
Fresenius Vial SAS
OA Round
6 (Final)
74%
Grant Probability
Favorable
7-8
OA Rounds
0m
Est. Remaining
99%
With Interview

Examiner Intelligence

Grants 74% — above average
74%
Career Allowance Rate
402 granted / 540 resolved
+4.4% vs TC avg
Strong +31% interview lift
Without
With
+31.3%
Interview Lift
resolved cases with interview
Typical timeline
3y 4m
Avg Prosecution
53 currently pending
Career history
611
Total Applications
across all art units

Statute-Specific Performance

§101
0.6%
-39.4% vs TC avg
§103
50.9%
+10.9% vs TC avg
§102
16.8%
-23.2% vs TC avg
§112
25.2%
-14.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 540 resolved cases

Office Action

§103
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 . Acknowledgment Claim 1 is amended and filed on 5/18/2026. Claim Rejections - 35 USC § 103 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. Claim(s) 1-13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kamen et al. (US. 20140180711A1) (“Kamen”) in view of Lissar et al. (US. 20040088283A1) (“Lissar”). Re claim 1, Kamen discloses a method of generating a database based on a model (¶0076 as the data can be created and edited, and wherein ¶0087 show that the information are related to the drug and therapies and ¶0097-0098 for change that data in the database and link library with database, Abstract, DERS database can be edited/new entry is considered as creating database, Fig. 1, Fig. 56, Fig. 90), comprising: receiving a drug identifier from a user (Fig. 89, Fig. 91-93, ¶0807); storing the drug identifier in a drug entity in the database (¶0806, the drug name only is added to library wherein the drug entity has only drug names and other related names and classification as in Fig. 90-91); receiving drug delivery therapies from the or another user for a plurality of different therapies (Figs. 94-97, Figs. 100-105, ¶0868, the medicament has one to many different therapies as the dose, rate or usage can be different); storing each drug delivery therapy for the drug identifier in a therapy entity in the database, the drug entity having a one-to-many relationship with the therapy entity in the database (Figs. 94-97, Figs. 100-105, ¶0868, the many therapies that can be used for a drug with regards to patient size, age, …etc. Also, Note: the drug can be used for different therapies is drug properties ¶0088); generating a drug library based on the drug entity, the therapy entity (¶0087, ¶0823) and the relationships defined between the drug and therapy entities, and wherein the drug entity does not comprise the drug delivery therapies (drug lists dies does not have any clinical use, and the link between the drug , therapies / clinical use and concentration can be see Fig. 94-105, the user will set up the therapies and does, rate ..etc.); and transmitting the drug library to a medical device for use when programming the medical device to deliver a medicament (Fig. 113, ¶0065, ¶0088, ¶0823, Fig.181 show the infusion manager and link the infusion with the database), but it fails to disclose that the database is generated by an entity relationship model. However, Lissar discloses a database generation (Fig. 7) based on an entity relationship model (¶0074) and wherein the database field is generated by an entity relationship model (entity can be related to drugs, ¶0015, ¶0060). Thus, it would have been prima facie obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modify the model of Kamen so that the database is generated by an entity relationship model as taught by Lissar for the purpose of increasing efficiency and effectiveness of huge data elements database (Lissar, ¶0011). Re claim 2, Kamen discloses wherein each drug delivery therapy comprises at least one clinical protocol selected from a group comprising a bolus, a continuous rate, a ramp rate and a loading dose (rate or loading dose, ¶0657, ¶0708). Re claim 3, Kamen discloses wherein the drug identifier comprises a drug name and a drug concentration (¶0772, ¶0807, drug name, concentration). Re claim 4, Kamen discloses wherein the drug entity comprises the drug name and does not include delivery parameters (¶0801). Re claim 5, Kamen discloses a drug library storage and distribution system (¶0076 as the data can be created and edited, and wherein ¶0087 show that the information are related to the drug and therapies and ¶0097-0098 for change that data in the database and link library with database, Abstract, DERS database can be edited/new entry is considered as creating database, Fig. 1, Fig. 56, Fig. 90), comprising: a processing circuit and non-transitory computer-readable memory configured to generate a drug library database (¶0085) and store the drug library database (¶0085, processor and memory for drug library) comprising: a drug entity specifying a drug name and a drug concentration (¶0801, name and concentration, the drug name only is added to drug lists, wherein the drug entity has only drug names and other related names and classification as in Fig, 91-98); and a therapy entity specifying a clinical protocol for delivery of a drug (¶0087, ¶0823, Fig. 100), the drug entity not specifying the clinical protocol for delivery of the drug (wherein the drug entity has only drug names and other related names and classification and concentration as in Figs. 91-98 and without any admiration protocol), the drug entity having a relationship with a plurality therapy entity (Figs. 94-97, Figs. 100-105, ¶0868, the medicament has one to many different therapies as the dose, rate or usage can be different. Also, Note: the drug can be used for different therapies is drug properties ¶0088), and data from the drug entity and the therapy entity being included in a drug library entity (Fig. 105, ¶0572), wherein the processing circuit is configured to distribute a drug library from the drug library entity to an infusion pump (¶0065, ¶0088, ¶0868, Fig.181 show the infusion manager and link the infusion with the database), but it fails to disclose that the drug library database is generated by an entity relationship model. However, Lissar discloses a database generation (Fig. 7) based on an entity relationship model (¶0074) and wherein the database field is generated by an entity relationship model (entity can be related to drugs, ¶0015, ¶0060). Thus, it would have been prima facie obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modify the model of Kamen so that that the drug library database is generated by an entity relationship model as taught by Lissar for the purpose of increasing efficiency and effectiveness of huge data elements database (Lissar, ¶0011). Re claim 6, Kamen discloses the drug library database further comprising a master drug list entity having a one-to-plurality relationship with the drug entity (medication records, ¶0660, Figs. 94-97, Figs. 100-105, ¶0868, the medicament has one to many different therapies as the dose, rate or usage can be different). Re claim 7, Kamen discloses the drug library database further comprising a pharmacy drug entity (¶0496, Fig. 1) being synchronized with the drug entity (Fig. 1), the pharmacy drug entity specifying data stored in a separate computer associated with a hospital pharmacy (¶0112, can be different/ separate computer), whereby synchronization of the pharmacy drug entity with the drug entity does not modify the therapy entity (¶0492, just consulting or review). Re claim 8, Kamen discloses wherein the drug library comprises a plurality of therapies for the drug name and drug concentration specified in the drug entity (medication records, ¶0660, Figs. 94-97, Figs. 100-105, ¶0868, the medicament has one to many different therapies as the dose, rate or usage can be different, ¶0772, ¶0807, drug name, concentration). Re claim 9, Kamen discloses wherein the clinical protocol of the therapy entity is selected from a group comprising a bolus, a continuous rate, a ramp rate and a loading dose (rate or loading dose, ¶0657, ¶0708). Re claim 10, Kamen discloses wherein the therapy entity may specify a single therapy comprising a combination of different clinical protocols (¶0806, using a secondary infusion ). Re claim 11, Kamen discloses a drug library editing and distribution system (¶0076 as the data can be created and edited, and wherein ¶0087 show that the information are related to the drug and therapies and ¶0097-0098 for change that data in the database and link library with database, Abstract, DERS database can be edited/new entry is considered as creating database, Fig. 1, Fig. 56, Fig. 90), comprising: a non-transitory computer-readable memory (¶0085) configured to store a database of drug records (¶0085-¶0086, drug information), therapy records (classification and use/ delivery ¶0085), and drug libraries (¶0085, processor and memory for drug library), a drug library comprising drug data to be used by software (¶0087-¶0088) on one or more infusion pumps to program one or more infusion pumps to administer a drug to a patient according to a protocol determined at least in part by a user (Fig. 113, ¶0106, 0088, wherein the medical device can be pumps ¶0386); and a processing circuit capable to: receive a drug name and a drug concentration programmed by the or another user (¶0309, ¶0772, ¶0801, wherein the drug entity has only drug names and other related names and classification and concentration as in Figs. 91-98); receive a name of a therapy programmed by the or the another user (¶0088, wherein the medical device can be pumps ¶0828, Fig. 100-105); receive a clinical protocol programmed by the or the another user (rate or loading dose and infusion parameter, ¶0657, ¶0708, or second review and editing before administration ¶0826 ); generate a drug record based on the drug name and the drug concentration (drug library, ¶0070); generate a therapy record separate from the drug record based on the name of the therapy and the clinical protocol (¶0071, Fig. 105), the therapy record being associated with the drug record but the drug record does not comprise the clinical protocol (¶0571, table 8), wherein the drug record is configured to be associated with a plurality of therapy records, each therapy record having a therapy name and a clinical protocol (Figs. 94-97, Figs. 100-105, ¶0868, the medicament has one to many different therapies as the dose, rate or usage can be different); generate a drug library comprising the drug record and the therapy record and relationships between the drug and therapy (¶0087, ¶0098, Abstract, DERS database, Fig. 1, Fig. 56, Fig. 90, 105); and transmit the drug library for distribution to the one or more infusion pumps (¶0390, ¶0070, Fig. 105), but it is fails to disclose that the drug library is generated by an entity relationship model. However, Lissar discloses a database generation (Fig. 7) based on an entity relationship model (¶0074) and wherein the database field (entity can be related to drugs, ¶0015, ¶0060). Thus, it would have been prima facie obvious to one having ordinary skill in the art before the effective filing date of the claimed invention to have modify the model of Kamen so that the drug library database is generated by an entity relationship model as taught by Lissar for the purpose of increasing efficiency and effectiveness of huge data elements database (Lissar, ¶0011). Re claim 12, Kamen discloses one of the one or more infusion pumps comprising operating software, the one of the one or more infusion pumps capable to receive the drug library and constrain operation of the operating software based at least in part on the drug library (¶0070). Re claim 13, Kamen discloses wherein the one of the one or more infusion pumps is a clinician- programmable infusion pump (¶0422). Response to Arguments Applicant's arguments filed 5/18/2026 have been fully considered but they are not persuasive. The applicant argues in last paragraph of page 7 – page 13 that Kamen fails to generate a drug entity using data entry model. This is found not persuasive, as Kamen discloses all events that need to create the drug and drug therapies see ¶0066 and can be sued in hospital see ¶0384, but it uses different model. However, Lissar discloses generating a database for item such as drug see ¶0014-¶0015 and the model can be used an entity relationship model. The applicant argues in page 8-9 with regards to the limitation the drug entity does not comprises the drug delivery therapies. This is found not persuasive as Fig. 98 of Kamen has drug and concentration without include therapies and wherein the therapies is in clinical use in Fig. 100 that send to the pump in Fig. 113 and in ¶0868 discloses that drug without therapies which need from a user to link these to specific medical device and specific patient therapies including does, rate, concentration, time etc. Moreover, in a programming art, show a portion of database / record to generate new database is based on a user selection what need to be entities need to be link to a new database which are generated. The applicant argues with regards to Fig, 98-100 to show that a concentration of drug and clinical use in the drug entity. This is found not persuasive as these screen show the user insertion of the therapies and by linking the drug to the therapies and send them to the medical devices. The applicant argument with regards to the drug entity and therapy entity as claimed is different than the one in the art. there is no clear separation between these two entity as claimed. In the specification. the specific therapy entity is related to delivery protocol setting see ¶0045-¶0059 of the current application . Note: the examiner suggests to further define what portion of the database is shown in the medical devices and clearly further define the drug entity and therapies entity ( see ¶0049-¶0059, to clearly define what the drug entity includes such as name, limits and suggested time ..etc. and what therapies entity includes such as ramp mode, a continuous flow setting, a clinical protocol ..etc. ). The examiner show that a drug entity and then the delivery protocol need to be linked by the user before running the medical device. 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 nonprovisional extension fee (37 CFR 1.17(a)) 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 mailing date of this final action. Any inquiry concerning this communication or earlier communications from the examiner should be directed to HAMZA A. DARB whose telephone number is (571)270-1202. The examiner can normally be reached 8:00-5:00 M-F (EST). Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Chelsea Stinson can be reached at (571) 270-1744. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /HAMZA A DARB/Examiner, Art Unit 3783 /CHELSEA E STINSON/Supervisory Patent Examiner, Art Unit 3783
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Prosecution Timeline

Show 6 earlier events
Oct 17, 2024
Non-Final Rejection mailed — §103
Jan 17, 2025
Response Filed
Mar 26, 2025
Final Rejection mailed — §103
Sep 26, 2025
Request for Continued Examination
Oct 01, 2025
Response after Non-Final Action
Nov 18, 2025
Non-Final Rejection mailed — §103
May 18, 2026
Response Filed
Jun 22, 2026
Final Rejection mailed — §103 (current)

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Prosecution Projections

7-8
Expected OA Rounds
74%
Grant Probability
99%
With Interview (+31.3%)
3y 4m (~0m remaining)
Median Time to Grant
High
PTA Risk
Based on 540 resolved cases by this examiner. Grant probability derived from career allowance rate.

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