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 .
Priority
Acknowledgement 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. GB2009478, filed on 6/22/2020.
Status of Claims
This Office Action is responsive to communications filed 10/29/2025.
Claims 2-3, 6-9, 14-21, 23-24, 27-29 and 33-36 are canceled.
Claims 1, 4-5, 10-13, 22, 25-26, 30-32 and 37-38 are presented for examination.
Response to Arguments
Rejection Under 35 U.S.C. §101
Applicant argues:
Claims 1 and 22 have been amended and as such are no longer directed to an abstract idea without significantly more.
Examiner responds:
The §101 rejection to claims 1-38 are withdrawn.
Rejection Under 35 U.S.C. §112
Applicant argues:
Claims 3 and 24 have been canceled. Claim 12 is amended to recite antecedent basis.
Examiner responds:
The §112 rejection to claims 3, 12 and 24 are withdrawn.
Rejections Under 35 U.S.C §102 and §103
Applicant argues:
Addison fails to anticipate the features of amended claims 1 and 22.
Examiner responds:
Applicant’s arguments have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
Claims 1, 4-5, 10-11, 13, 22, 25-26, 30, 32 and 37-38 are rejected under 35 U.S.C. 103 as being unpatentable over Addison (US20210298635A1)1 in view of Hawes (US20170108840A1).
Regarding claim 1, Addison teaches a system comprising:
an obtaining processor adapted to obtain one or more user factors indicative of a state of the user ([0048]: steps of 600 may be executed by various components such as computing devices; [0049]: at operation 604 images are received; [0050]: at operation 606 a physiological parameter is generated based on the images received in operation 604);
an estimation processor operable to generate a proposed feedback action based upon the one or more obtained user factors ([0051]: at operation 608 a sedation level of the patient is determined based on at least the physiological parameter generated in operation 606; [0064]: at operation 616 an amount of sedative to be administered is determined, the amount of sedative may be based on the patient’s sedation level and/or a rate of change of the patient’s sedation level … based on the change to the patient’s sedation level, a certain amount of sedative that is likely to return the patient to a normal sedation level may be determined)
a feedback processor adapted to cause a modification of one or more operations according to the proposed feedback action ([0065]: patient-monitoring system described may be in communication with a device capable of administering pharmaceutical compound, which may involve sending a signal to a device capable of administering the compound).
Addison is not relied on for wherein the system is an aerosol provisioning system. Addison is not relied on for wherein the feedback action comprises a change in a power supply to a heater for heating aerosolisable material.
However, Hawes in an analogous art teaches:
an aerosol provisioning system ([0061]-[0063]: e-vapor apparatus includes dispensing body and a vaporizer […] vaporizer is configured to heat the pre-vapor formulation to produce a vapor);
a feedback processor adapted to cause a change in a power supply to a heater for heating aerosolisable material ([0121]: “sensor allows vapor drawing strength to be measured and used as feedback to the controller 2105 to adjust the power delivered to the heater of the pod” [emphasis added by examiner]).
Addison teaches a drug delivery system comprising a controller, wherein the controller is configured to: obtain state information about a user using a sensor, generate a feedback instruction to adjust the amount of drug delivery based on state information, and implement the feedback instruction to the drug delivery device. Hawes teaches a drug delivery system comprising an aerosol provision system and a controller configured to: obtain information about a user using a sensor, and using that information generate and implement a feedback action. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art to combine Addison with Hawes in order to produce a device capable of adjusting the amount of drug delivered to a user.
Regarding claim 4, Addison in view of Hawes teaches the elements of claim 1 as outlined above. Addison also teaches wherein the one or more obtained user factors respectively relate to at least one class selected from the group consisting of: historical data providing background information relating to the user; neurological data relating to the user; physiological data relating to the user; contextual data relating to the user; environmental data relating to the user; deterministic data relating to the user; and use-based data relating to the user (Abstract: physiological parameters may include information related to the patients breathing behavior and/or activity).
Regarding claim 5, Addison in view of Hawes teaches the elements of claim 1 as outlined above. Addison also teaches wherein the obtaining processor generates inputs for the estimation processor comprising one or more selected from the group consisting of: one or more individual values based upon one or more respective user factors; one or more combined values based upon two or more respective user factors; and one or more values based upon respective user factors from a single class of data ([0053]: determining a sedation level of the patient involves analysis and combination of two or more generated physiological parameters).
Regarding claim 10, Addison in view of Hawes teaches the elements of claim 1 as outlined above. Addison also teaches wherein the estimation processor does not generate an explicit estimation of user state as an interim operation in the generation of the one or more proposed feedback actions ([0051]: “rate of change of one or more physiological parameters may similarly be compared to one or more rate-of-change thresholds […] physiological parameters and the rate at which they are changing may provide an indication of how a patient is being affected by the sedatives that have been administered”).
Regarding claim 11, Addison in view of Hawes teaches the elements of claim 1 as outlined above. Addison also teaches wherein the estimation processor models a one-operation relationship or a two-operation relationship between the one or more user factors and the one or more generated proposed feedback actions using one or more machine learning systems ([0055]: movement measurements may be determined via machine learning).
Regarding claim 13, Addison in view of Hawes teaches the elements of claim 1 as outlined above. Addison also teaches wherein the estimation processor is operable to generate one or more proposed feedback actions relating to one or more selected from the group consisting of: a behavior feedback action for affecting at least a first behavior of the user; a pharmaceutical feedback action for affecting the consumption of an active ingredient by the user; and a non-consumption feedback action for affecting one or more non-consumption operations of the delivery ecosystem ([0064]: at operation 612 it is determined that the sedation level is outside of the normal or expected range, at operation 616 an amount of sedative to be administered can be determined, based on the patient’s sedation level and/or rate of change; [0065]: determined amount of sedative to be administered may be provided to care provider).
Regarding claim 22, the claim recites a method wherein the limitations of the claim correspond to the limitations of the system of claim 1. Addison also discloses a method (Abstract: systems and methods are provided). The remaining limitations of claim 22 are substantially the same as claim 1 and are rejected due to the reasons outlined above.
Regarding claim 25, Addison in view of Hawes teaches the elements of claim 22 as outlined above. The remaining limitations of claim 25 are substantially the same as claim 4 and are rejected due to the reasons outlined above.
Regarding claim 26, Addison in view of Hawes teaches the elements of claim 22 as outlined above. The remaining limitations of claim 26 are substantially the same as claim 5 and are rejected due to the reasons outlined above.
Regarding claim 30, Addison in view of Hawes teaches the elements of claim 22 as outlined above. The remaining limitations of claim 30 are substantially the same as claim 11 and are rejected due to the reasons outlined above.
Regarding claim 32, Addison in view of Hawes teaches the elements of claim 22 as outlined above. The remaining limitations of claim 32 are substantially the same as claim 13 and are rejected due to the reasons outlined above.
Regarding claim 37, Addison in view of Hawes teaches the elements of claim 22 as outlined above. Addison also teaches a computer system comprising at least one processor and memory (Fig. 2 processor 215 coupled to memory 205 in a computing device 200).
Regarding claim 38, Addison in view of Hawes teaches the elements of claim 22 as outlined above. Addison also teaches a non-transitory computer readable storage medium storing a computer program product comprising instructions ([0036]: “memory 412 includes non-transitory, computer-readable media that stores software that is executed by the processor”).
Claims 12 and 31 are rejected under 35 U.S.C. 103 as being unpatentable over Addison (US20210298635A1) in view of Hawes (US20170108840A1), in further view of Einav (US20210065865A1)2.
Regarding claim 12, Addison in view of Hawes teaches the elements of claim 11 as outlined above. Addison in view of Hawes is not relied on for using different respective machine learning systems responsive to a composition of the one or more factors provided as inputs. However, Einav in an analogous art does teach this claim limitation ([0268]: “assessment tool software includes patient classifiers, pharmaceutical classifiers, physiological classifiers and a classification processing engine […] patient classifiers process patient’s data […] pharmaceutical classifiers process aspects related to pharmaceuticals […] classifiers refer to machine learning systems, e.g. neural networks that have been trained”).
Addison in view of Hawes teaches a drug delivery system comprising processors that receive inputs, processes data, and produce outputs. Einav teaches a drug delivery system comprising processes that receive inputs, processes data, and produce outputs using machine learning systems for respective data classes. Before the effective filing date of the claimed invention, it would have been obvious to a person of ordinary skill in the art to try to improve Addison in view of Hawes with Einav according to known methods to yield predictable results.
Regarding claim 31, Addison in view of Hawes teaches the elements of claim 30 as outlined above. The remaining limitations of claim 31 are substantially the same as claim 12 and are rejected due to the reasons outlined above.
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 Michael V Farina whose telephone number is (571)272-4982. The examiner can normally be reached Mon-Thu 8:00-6:00 EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Thomas Lee can be reached at (571) 272-3667. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/M.V.F./Examiner, Art Unit 2115
/THOMAS C LEE/Supervisory Patent Examiner, Art Unit 2115
1 Addison is a prior art reference cited in the previous office action.
2 Einav is a prior art reference cited in the previous office action.