Technology areas: Computing & Software • Transportation, E-Commerce & Mechanical Systems
2 pending office actions • 2 art units • 2 examiners • 0 of 2 (0%) have an AI response strategy ready
Deep Forest Sciences Inc. currently has 1 pending office action focused in the Computing & Software technology area. The company's active prosecution involves 1 distinct examiner and 1 distinct art unit, indicating a consolidated interaction with the patent office. In the fast-moving computing sector, this singular focus suggests a highly specific patenting goal for the current period. The lack of multiple pending actions or art units implies that the company is not currently pursuing a broad, multi-front prosecution strategy, but is instead focused on a specific software innovation.
The busiest examiner, COYER, RYAN D, is responsible for 1 busiest examiner pending action. This figure matches the total of 1 pending office action for the entire portfolio, placing the current prosecution trajectory under the oversight of this single examiner. For the practitioner, this means that the relationship with this specific examiner is the primary factor in the company's current patent office success. Every response and negotiation must be carefully crafted to address the specific requirements of this examiner, as their decision will determine the immediate fate of the company's active patent filings.
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 (50%) |
| Multi-statute (no §101) | 1 (50%) |
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 |
|---|---|---|---|
| NGUYEN, TRAN N | 1 | 61.8% | +16.9% |
| COYER, RYAN D | 1 | 79.2% | +19.8% |
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 |
|---|---|---|---|
| 18972698 | AI-BASED DRUG SIDE EFFECT PREDICTION | NGUYEN, TRAN N | — |
| 18414136 | TECHNIQUES FOR A CLOUD SCIENTIFIC MACHINE LEARNING PROGRAMMING ENVIRONMENT | COYER, RYAN D | — |
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 2 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18972698 | AI-BASED DRUG SIDE EFFECT PREDICTION | NGUYEN, TRAN N | — |
| 18414136 | TECHNIQUES FOR A CLOUD SCIENTIFIC MACHINE LEARNING PROGRAMMING ENVIRONMENT | COYER, RYAN D | — |
| Art Unit | Apps |
|---|---|
| 3685 | 1 |
| 2191 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18972698 | AI-BASED DRUG SIDE EFFECT PREDICTION | NGUYEN, TRAN N | 3685 | §101§102§103 | Final Rejection | — | Pending | Dec 06, 2024 |
| 18414136 | TECHNIQUES FOR A CLOUD SCIENTIFIC MACHINE LEARNING PROGRAMMING ENVIRONMENT | COYER, RYAN D | 2191 | §102§103§112 | Final Rejection | — | Pending | Jan 16, 2024 |
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Start Free TrialDeep Forest Sciences Inc. has 2 pending office actions as of October 2026, spread across 2 art units and 2 examiners.
Tran N Nguyen has the most, with 1 of Deep Forest Sciences Inc.'s pending office actions.
Mostly Transportation, E-Commerce & Mechanical Systems (USPTO Tech Center 3600), based on where its pending office actions are examined.
