Prosecution Insights
Last updated: April 19, 2026
Application No. 18/655,659

MULTIFACTORIAL PLANNING FOR AUTONOMIC NERVOUS SYSTEM NEUROMODULATION

Non-Final OA §102
Filed
May 06, 2024
Examiner
BAKKAR, AYA ZIAD
Art Unit
3796
Tech Center
3700 — Mechanical Engineering & Manufacturing
Assignee
Boston Scientific Neuromodulation Corporation
OA Round
1 (Non-Final)
62%
Grant Probability
Moderate
1-2
OA Rounds
3y 0m
To Grant
99%
With Interview

Examiner Intelligence

Grants 62% of resolved cases
62%
Career Allow Rate
111 granted / 179 resolved
-8.0% vs TC avg
Strong +43% interview lift
Without
With
+43.4%
Interview Lift
resolved cases with interview
Typical timeline
3y 0m
Avg Prosecution
38 currently pending
Career history
217
Total Applications
across all art units

Statute-Specific Performance

§101
3.3%
-36.7% vs TC avg
§103
49.4%
+9.4% vs TC avg
§102
22.1%
-17.9% vs TC avg
§112
22.9%
-17.1% vs TC avg
Black line = Tech Center average estimate • Based on career data from 179 resolved cases

Office Action

§102
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 § 102 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. Claim(s) 1-20 are rejected under 35 U.S.C. 102 (a)(1) as being anticipated by US 2019/0009094 Zhang et al., hereinafter “Zhang”. Regarding claim 1, Zhang discloses a data processing system (Abstract and Figure 13 and 14) for planning neurostimulation of a patient (Abstract), comprising: at least one memory device (Para 82) configured to store user input data corresponding to an autonomic condition of a patient (Para 80, 103, and 135; the memory hold the program instructions, which include pain regions inputted by the patient) and mapping data corresponding to a physiological state of one or more anatomical systems or organs of the patient affected by the autonomic condition (Para 6, 103, and 135; Pain syndrome is directly affected by the autonomic nervous system); and at least one processor (Para 82 and Figure 13, element 1316) configured to: identify a configuration of a neurostimulation device and one or more neurostimulation leads and electrodes to the neurostimulation device (Para 67, 69, and 77; determine number of leads and electrodes needed to be used); determine a simulated placement of the one or more neurostimulation leads and electrodes onto one or more neural targets of the patient (Para 58; “receive recommendations regarding neural targets, and/or may select one or more neural targets and receive recommendation for a waveform”, Para 19, 21, 58, and 64), based on the user input data corresponding to the autonomic condition and the mapping data corresponding to the physiological state (Para 58 and 128); and output a graphical representation to depict the simulated placement of the one or more neurostimulation leads and electrodes in the patient, based on a simulated neurostimulation treatment for the autonomic condition (Para 135 and Figure 20). Regarding claim 2, Zhang discloses the one or more neural targets of the patient include one or more spinal neural targets (Para 68), and wherein the neurostimulation includes spinal cord stimulation (SCS) to be provided via the one or more neurostimulation leads and electrodes to the one or more spinal neural targets (Para 77 and 92). Regarding claim 3, Zhang discloses the data processing system (Abstract and Figure 13 and 14) is further configured to: determine one or more stimulation settings to provide the simulated neurostimulation treatment via the one or more neurostimulation leads and electrodes, based on the autonomic condition and the simulated placement of the one or more neurostimulation leads and electrodes (Para 58, 64, and 112; stimulation parameters are set based on user input and are customized based on users condition). Regarding claim 4, Zhang discloses the data processing system is further configured to: output information to depict the one or more stimulation settings to provide the simulated neurostimulation treatment, wherein the information includes: one or more spatial targets, one or more frequencies, and one or more pulse-widths used for the neurostimulation (Para 135 and Figure 20 show a display of a user interface with output information that discuss the spatial target, a recommended frequency and PW, these can be seen in the neural targets image). Regarding claim 5, Zhang discloses the user input data includes data from a symptom questionnaire, and wherein the symptom questionnaire provides a measurement of severity and effects of the autonomic condition from multiple anatomical systems or organs (Para 135 shows a graphical interface that allows the user to highlight areas of pain when prompted, see Also Para 134 and 138). Regarding claim 6, Zhang discloses the mapping data includes a mapping of effects of the autonomic condition at multiple areas corresponding to the one or more neural targets (Para 103, 111, 131). Regarding claim 7, Zhang discloses the graphical representation is further configured to display anatomical maps (Para 134 and Figure 20; Dermatome Map), and wherein the anatomical maps include one or more visceral maps or dermatomal maps (Para 134 and Figure 20; Dermatome Map). Regarding claim 8, Zhang discloses the configuration of the one or more neurostimulation leads and electrodes to a neurostimulation device is based on: type of implantable pulse generator, type of lead, number of leads, and number of electrodes on respective leads (Para 77 and 82); and wherein the simulated placement of the one or more neurostimulation leads and electrodes onto the one or more neural targets of the patient is based on a patient-specific anatomy determined from medical imaging or recorded measurements of the patient (Para 58). Regarding claim 9, Zhang discloses the simulated placement is determined by a planning model that uses a lookup table (Para 58 and 110), and wherein the lookup table provides a correspondence between the anatomical systems or organs and spinal column origins within a stimulation field created by the one or more neurostimulation leads and electrodes (Para 58). Regarding claim 10, Zhang discloses programming circuitry (Figure 14, element 1419) configured to generate programming for an electrostimulator (Para 112), the programming corresponding to the neurostimulation to the one or more neural targets of the patient via the one or more neurostimulation leads and electrodes (Para 112); wherein the programming includes one or more stimulation parameters including: an electrode configuration (Para 6); one or more stimulation pulse parameters including a pulse amplitude (Para 83), a pulse width (Para 83), or a stimulation frequency (Para 83); a stimulation pulse waveform (Para 6); an ON-OFF cycling scheme comprising an ON period for delivering stimulation pulses and a subsequent stimulation-free OFF period (Para 63); or a charge per second (CPS) or a charge per hour (CPH) delivered to a respective neural target. Regarding claim 11, Zhang discloses a method (Abstract and Figure 13 and 14) for planning neurostimulation of a patient (Abstract), comprising: receiving user input data corresponding to an autonomic condition of a patient (Para 80, 103, and 135; pain regions inputted by the patient) and mapping data corresponding to a physiological state of one or more anatomical systems or organs of the patient affected by the autonomic condition (Para 6, 103, and 135; Pain syndrome is directly affected by the autonomic nervous system); identifying a configuration of a neurostimulation device and one or more neurostimulation leads and electrodes to the neurostimulation device (Para 67, 69, and 77; determine number of leads and electrodes needed to be used); determining a simulated placement of the one or more neurostimulation leads and electrodes onto one or more neural targets of the patient (Para 58; “receive recommendations regarding neural targets, and/or may select one or more neural targets and receive recommendation for a waveform”, Para 19, 21, 58, and 64), based on the user input data corresponding to the autonomic condition and the mapping data corresponding to the physiological state (Para 58 and 128); and outputting a graphical representation to depict the simulated placement of the one or more neurostimulation leads and electrodes in the patient, based on a simulated neurostimulation treatment for the autonomic condition (Para 135 and Figure 20). Regarding claim 12, Zhang discloses the one or more neural targets of the patient include one or more spinal neural targets (Para 68), and wherein the neurostimulation includes spinal cord stimulation (SCS) to be provided via the one or more neurostimulation leads and electrodes to the one or more spinal neural targets (Para 77 and 92). Regarding claim 13, Zhang discloses determining one or more stimulation settings to provide the simulated neurostimulation treatment via the one or more neurostimulation leads and electrodes, based on the autonomic condition and the simulated placement of the one or more neurostimulation leads and electrodes (Para 58, 64, and 112; stimulation parameters are set based on user input and are customized based on users condition). Regarding claim 14, Zhang discloses outputting information to depict the one or more stimulation settings to provide the simulated neurostimulation treatment, wherein the information includes: one or more spatial targets, one or more frequencies, and one or more pulse-widths used for the neurostimulation (Para 135 and Figure 20 show a display of a user interface with output information that discuss the spatial target, a recommended frequency and PW, these can be seen in the neural targets image). Regarding claim 15, Zhang discloses the user input data includes data from a symptom questionnaire, and wherein the symptom questionnaire provides a measurement of severity and effects of the autonomic condition from multiple anatomical systems or organs (Para 135 shows a graphical interface that allows the user to highlight areas of pain when prompted, see Also Para 134 and 138). Regarding claim 16, Zhang discloses the mapping data includes a mapping of effects of the autonomic condition at multiple areas corresponding to the one or more neural targets (Para 103, 111, 131). Regarding claim 17, Zhang discloses the graphical representation is further configured to display anatomical maps (Para 134 and Figure 20; Dermatome Map), and wherein the anatomical maps include one or more visceral maps or dermatomal maps (Para 134 and Figure 20; Dermatome Map). Regarding claim 18, Zhang discloses the configuration of the one or more neurostimulation leads and electrodes to a neurostimulation device is based on: type of implantable pulse generator, type of lead, number of leads, and number of electrodes on respective leads (Para 77 and 82); and wherein the simulated placement of the one or more neurostimulation leads and electrodes onto the one or more neural targets of the patient is based on a patient-specific anatomy determined from medical imaging or recorded measurements of the patient (Para 58). Regarding claim 19, Zhang discloses the simulated placement is determined by a planning model that uses a lookup table (Para 58 and 110), and wherein the lookup table provides a correspondence between the anatomical systems or organs and spinal column origins within a stimulation field created by the one or more neurostimulation leads and electrodes (Para 58). Regarding claim 20, Zhang discloses generating programming for an electrostimulator (Para 112), the programming corresponding to the neurostimulation to the one or more neural targets of the patient via the one or more neurostimulation leads and electrodes (Para 112); wherein the programming includes one or more stimulation parameters including: an electrode configuration (Para 6); one or more stimulation pulse parameters including a pulse amplitude (Para 83), a pulse width (Para 83), or a stimulation frequency (Para 83); a stimulation pulse waveform (Para 6); an ON-OFF cycling scheme comprising an ON period for delivering stimulation pulses and a subsequent stimulation-free OFF period (Para 63); or a charge per second (CPS) or a charge per hour (CPH) delivered to a respective neural target. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to AYA ZIAD BAKKAR whose telephone number is (313)446-6659. The examiner can normally be reached on 7:30 am - 5:00 pm M-Th. 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, Carl Layno can be reached on (571) 272-4949. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see https://ppair-my.uspto.gov/pair/PrivatePair. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /AYA ZIAD BAKKAR/ Examiner, Art Unit 3796 /CARL H LAYNO/Supervisory Patent Examiner, Art Unit 3796
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Prosecution Timeline

May 06, 2024
Application Filed
Mar 18, 2026
Non-Final Rejection — §102 (current)

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
62%
Grant Probability
99%
With Interview (+43.4%)
3y 0m
Median Time to Grant
Low
PTA Risk
Based on 179 resolved cases by this examiner. Grant probability derived from career allow rate.

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