Prosecution Insights
Prosecution Insights
Technology areas: Biotechnology & Pharmaceuticals • Medical Devices & Mechanical Engineering
3 pending office actions • 2 art units • 3 examiners • 0 of 3 (0%) have an AI response strategy ready • 5 patents granted in the last 365 days
Industry-Academic Cooperation Foundation Kunsan National University has 2 pending office actions in the Medical Devices & Mechanical Engineering technology area. These actions are assigned to distinct examiners, meaning each matter is being handled by a different individual. This requires the foundation to manage separate examiner relationships for its current pending applications. The use of distinct examiners for only the pending actions shows a lack of examiner concentration in this portfolio.
Both pending office actions are located within 1 distinct art unit, suggesting a unified technical focus despite the involvement of different examiners. GILLIARD, DELOMIA L is the busiest examiner with 1 pending office action. Since the 2 pending office actions are split between distinct examiners, the prosecution workload is balanced. The foundation can focus its strategy on the specific standards of the single art unit involved, which may help in maintaining technical consistency across both pending matters.
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.
| Bucket | Cases |
|---|---|
| §103 only | 1 (33%) |
| Multi-statute (no §101) | 2 (67%) |
How the docket's pending cases split across USPTO tech-center bands.
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.
| Examiner | Apps on this docket | Allow rate | Interview lift |
|---|---|---|---|
| GILLIARD, DELOMIA L | 1 | 89.6% | +10.4% |
| ONDREJCAK, ANDREW DOMENIC | 1 | 40.9% | +29.8% |
| DUNN, MCKENZIE A | 1 | 53.8% | +56.3% |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 2 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18984843 | DEFECT DETECTION SYSTEM AND METHOD USING DEEP NEURAL NETWORK BASED ANALYSIS OF COMPOSITE THERMAL IMAGE DATA | GILLIARD, DELOMIA L | — |
| 18388900 | FIRE EXTINGUISHING DEVICE FOR ELECTRIC VEHICLE BATTERIES | ONDREJCAK, ANDREW DOMENIC | — |
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 3 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18984843 | DEFECT DETECTION SYSTEM AND METHOD USING DEEP NEURAL NETWORK BASED ANALYSIS OF COMPOSITE THERMAL IMAGE DATA | GILLIARD, DELOMIA L | — |
| 18388900 | FIRE EXTINGUISHING DEVICE FOR ELECTRIC VEHICLE BATTERIES | ONDREJCAK, ANDREW DOMENIC | — |
| 18376894 | LIQUID CRYSTAL-BASED MULTIFUNCTIONAL MICRO ROBOT | DUNN, MCKENZIE A | — |
| Art Unit | Apps |
|---|---|
| 3752 | 1 |
| 1678 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18984843 | DEFECT DETECTION SYSTEM AND METHOD USING DEEP NEURAL NETWORK BASED ANALYSIS OF COMPOSITE THERMAL IMAGE DATA | GILLIARD, DELOMIA L | — | §103§112 | Non-Final OA | — | Pending | Dec 17, 2024 |
| 18388900 | FIRE EXTINGUISHING DEVICE FOR ELECTRIC VEHICLE BATTERIES | ONDREJCAK, ANDREW DOMENIC | 3752 | §102§103§112 | Non-Final OA | — | Pending | Nov 13, 2023 |
| 18376894 | LIQUID CRYSTAL-BASED MULTIFUNCTIONAL MICRO ROBOT | DUNN, MCKENZIE A | 1678 | §103 | Non-Final OA | — | Pending | Oct 05, 2023 |
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