Prosecution Insights
Prosecution Insights
Technology area: Transportation, E-Commerce & Mechanical Systems
3 pending office actions • 3 art units • 3 examiners • 0 of 3 (0%) have an AI response strategy ready • 1 patents granted in the last 365 days
Newsbreak Media Networks Inc. is currently managing 3 pending office actions within the Transportation, E-Commerce & Mechanical Systems technology area. These actions are distributed between 2 distinct examiners, which introduces variety in the examination styles the company must address. The prosecution activity is also spread across 2 distinct art units, indicating that the company's technology is being reviewed by two separate technical groups at the USPTO.
TORRICO-LOPEZ, ALAN is the busiest examiner for the portfolio, currently overseeing 2 pending office actions. This means that TORRICO-LOPEZ, ALAN is responsible for 2 of the 3 pending actions, while one other examiner handles the remaining matter. This concentration of work with a single examiner allows the company to develop a consistent relationship and understanding of that official's specific requirements.
The presence of 3 pending office actions across 2 examiners and 2 art units suggests a focused but active prosecution strategy in the Transportation, E-Commerce & Mechanical Systems sector. Practitioners should prioritize the interactions with TORRICO-LOPEZ, ALAN, given his significant role in the current docket. At the same time, they must ensure that the strategy for the third pending action remains aligned with the company's overall goals across both art units.
Based on the USPTO statutory response window for each pending office action. 1 of the docket's apps have a known mailing date; the rest are excluded from the tile counts.
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 |
|---|---|
| §101 + other | 1 (33%) |
| §103 only | 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 |
|---|---|---|---|
| BEKERMAN, MICHAEL | 1 | 32.5% | +31.1% |
| POUNCIL, DARNELL A | 1 | 21.4% | +30.7% |
| TORRICO-LOPEZ, ALAN | 1 | 29.1% | +37.8% |
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 |
|---|---|---|---|
| 18653913 | SYSTEM AND METHOD FOR TARGETING DIGITAL CONTENT AT PRODUCT TERMINALS USING REFERENCE DATA | POUNCIL, DARNELL A | 35d |
| 18207769 | SYSTEM AND METHOD FOR TARGETING DIGITAL CONTENT AT PRODUCT TERMINALS USING REFERENCE DATA | TORRICO-LOPEZ, ALAN | — |
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 |
|---|---|---|---|
| 18653913 | SYSTEM AND METHOD FOR TARGETING DIGITAL CONTENT AT PRODUCT TERMINALS USING REFERENCE DATA | POUNCIL, DARNELL A | 35d |
| 18653921 | SYSTEM AND METHOD FOR TARGETING DIGITAL CONTENT AT PRODUCT TERMINALS USING REFERENCE DATA | BEKERMAN, MICHAEL | — |
| 18207769 | SYSTEM AND METHOD FOR TARGETING DIGITAL CONTENT AT PRODUCT TERMINALS USING REFERENCE DATA | TORRICO-LOPEZ, ALAN | — |
| Art Unit | Apps |
|---|---|
| 3621 | 1 |
| 3622 | 1 |
| 3625 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18653921 | SYSTEM AND METHOD FOR TARGETING DIGITAL CONTENT AT PRODUCT TERMINALS USING REFERENCE DATA | BEKERMAN, MICHAEL | 3621 | §103 | Non-Final OA | — | Pending | May 02, 2024 |
| 18653913 | SYSTEM AND METHOD FOR TARGETING DIGITAL CONTENT AT PRODUCT TERMINALS USING REFERENCE DATA | POUNCIL, DARNELL A | 3622 | §103 | Non-Final OA | 35d | Pending | May 02, 2024 |
| 18207769 | SYSTEM AND METHOD FOR TARGETING DIGITAL CONTENT AT PRODUCT TERMINALS USING REFERENCE DATA | TORRICO-LOPEZ, ALAN | 3625 | §101§103§112 | Final Rejection | — | Pending | Jun 09, 2023 |
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