Prosecution Insights
Last updated: October 04, 2026

Vektor Medical Inc.

Technology areas: Biotechnology & Pharmaceuticals • Computing & Software • Medical Devices & Mechanical Engineering

4 pending office actions • 3 art units • 4 examiners • 0 of 4 (0%) have an AI response strategy ready • 1 patents granted in the last 365 days

Analysis

Vektor Medical Inc. is managing 4 pending office actions within the Biotechnology & Pharmaceuticals technology area. These actions are distributed among 4 distinct examiners and 3 distinct art units. The involvement of 3 distinct art units indicates a broader technical scope than the busiest examiner's focus on 1 pending office action. This diversity suggests that the company's innovations span several different technical classifications within the biotechnology and pharmaceutical fields, requiring review from multiple specialized examination groups.

JOHN R DOWNEY is the busiest examiner for the company, currently overseeing 1 pending office action. This distribution shows that while the workload is spread across 4 distinct examiners, no examiner is handling more than the pending office action assigned to him. This spread across distinct examiners means that the company's prosecution success is not dependent on any individual. Instead, the company must navigate the different perspectives and requirements of several examiners simultaneously. This multi-examiner environment requires a coordinated strategy to ensure consistency across the 3 distinct art units involved in the prosecution.

Written from this page's own data; every figure is computed from USPTO records and verified before publication.

Portfolio Summary

4
Total Pending OAs
2
Non-Final OAs
2
Final Rejections
0
Advisory / Quayle

Response Deadline Pressure

Based on the USPTO statutory response window for each pending office action. 2 of the docket's apps have a known mailing date; the rest are excluded from the tile counts.

1
Overdue
0
Due this week
1
Due this month
0
Due in next 60 days
0
Due later

Case Difficulty Mix

Difficulty is derived from the rejection statutes on the most recent pending office action. §101-driven and multi-statute cases are graded Hard; §112-only and obviousness-type double-patenting cases are graded Easy; everything else is Medium. "Unknown" means we have not yet parsed a statute for that office action.

3
Hard (75%)
1
Medium (25%)
0
Easy (0%)
0
Unknown (0%)

Rejection Statute Mix

BucketCases
§101 + other1 (25%)
Double-patenting + other1 (25%)
Multi-statute (no §101)2 (50%)

Industry Mix

How the docket's pending cases split across USPTO tech-center bands.

2
Life Sciences
50% of docket
1
Information Tech
25% of docket
0
Communications
0% of docket
0
Semiconductors
0% of docket
1
Mechanical / Eng
25% of docket
0
Business / Other
0% of docket

Time-on-OA Estimate

Manual office-action response work runs about 10 hours per case. The time-saved bands below show what IP Author's prosecution pipeline typically delivers — a conservative 20% on the low end, 35% in the middle, 50% on the high end.

40 h
Manual time on pending OAs
8 h
Time saved (low, 20%)
14 h
Time saved (mid, 35%)
0.3 wks
FTE-weeks freed (mid)

Top Examiners on this docket

ExaminerApps on this docketAllow rateInterview lift
DOWNEY, JOHN R 1 59.7% +23.7%
DEBNATH, NUPUR 1 64.4% +36.8%
CLOW, LORI A 1 64.2% +28.5%
BAILEY, STEVEN WILLIAM 1 31.6% +15.2%

Hard Cases (3)

Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 3 ordered by deadline are shown.

App #TitleExaminerDue in
17110101 MACHINE LEARNING USING SIMULATED CARDIOGRAMS CLOW, LORI A 127d overdue
17809521 DIGESTIVE SYSTEM SIMULATION AND PACING DEBNATH, NUPUR 20d
16042953 GENERATING A MODEL LIBRARY OF MODELS OF AN ELECTROMAGNETIC SOURCE BAILEY, STEVEN WILLIAM —

Interview Candidates (4)

Cases in front of an examiner whose interview lift is 10 percentage points or more — i.e. interviewed cases historically resolve more favorably than non-interviewed ones. The top 4 ordered by deadline are shown.

App #TitleExaminerDue in
17110101 MACHINE LEARNING USING SIMULATED CARDIOGRAMS CLOW, LORI A 127d overdue
17809521 DIGESTIVE SYSTEM SIMULATION AND PACING DEBNATH, NUPUR 20d
18559049 GUIDING IMPLANTATION OF AN ENERGY DELIVERY COMPONENT IN A BODY DOWNEY, JOHN R —
16042953 GENERATING A MODEL LIBRARY OF MODELS OF AN ELECTROMAGNETIC SOURCE BAILEY, STEVEN WILLIAM —

Top Art Units

Art UnitApps
1687 2
3792 1
2186 1

Pending Office Actions

App #TitleExaminerArt UnitStatutesStatusDue inAIFiled
18559049 GUIDING IMPLANTATION OF AN ENERGY DELIVERY COMPONENT IN A BODY DOWNEY, JOHN R 3792 §102§103DP Final Rejection — Pending Nov 04, 2023
17809521 DIGESTIVE SYSTEM SIMULATION AND PACING DEBNATH, NUPUR 2186 §102§103 Final Rejection 20d Pending Jun 28, 2022
17110101 MACHINE LEARNING USING SIMULATED CARDIOGRAMS CLOW, LORI A 1687 §102§112 Non-Final OA 127d overdue Pending Dec 02, 2020
16042953 GENERATING A MODEL LIBRARY OF MODELS OF AN ELECTROMAGNETIC SOURCE BAILEY, STEVEN WILLIAM 1687 §101§102§103§112DP Non-Final OA — Pending Jul 23, 2018

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