Prosecution Insights
Prosecution Insights
3 pending office actions • 3 art units • 3 examiners • 0 of 3 (0%) have an AI response strategy ready
Based on the USPTO statutory response window for each pending office action. 3 of the docket's apps have a known mailing date; the rest are excluded from the tile counts.
Every pending office action with a known statutory deadline, placed on a days-until-due axis. Dots left of Today are overdue; the further right, the more runway. Cases that share a deadline window stack vertically. 3 of the docket's apps have a known mailing date.
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 | 2 (67%) |
| No statute on record | 1 (33%) |
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 |
|---|---|---|---|
| COONS, LOGAN DOUGLAS | 1 | 100.0% | +0.0% |
| BRAHMACHARI, MANDRITA | 1 | 76.5% | +29.8% |
| AUGER, NOAH ANDREW | 1 | 34.8% | +37.7% |
Cases in front of an examiner with an allow rate of 80%+ where the difficulty is Easy or Medium. The top 1 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18561610 | CALIBRATING AN ELECTRONIC CHEMICAL SENSOR TO GENERATE AN EMBEDDING IN AN EMBEDDING SPACE | COONS, LOGAN DOUGLAS | 12d |
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 |
|---|---|---|---|
| 17429192 | Systems and Methods for Predicting the Olfactory Properties of Molecules Using Machine Learning | AUGER, NOAH ANDREW | 128d overdue |
| 18036707 | MACHINE-LEARNED MODELS FOR SENSORY PROPERTY PREDICTION | BRAHMACHARI, MANDRITA | 3d overdue |
| Art Unit | Apps |
|---|---|
| 2857 | 1 |
| 2144 | 1 |
| 1687 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18561610 | CALIBRATING AN ELECTRONIC CHEMICAL SENSOR TO GENERATE AN EMBEDDING IN AN EMBEDDING SPACE | COONS, LOGAN DOUGLAS | 2857 | §103 | Non-Final OA | 12d | Pending | Nov 16, 2023 |
| 18036707 | MACHINE-LEARNED MODELS FOR SENSORY PROPERTY PREDICTION | BRAHMACHARI, MANDRITA | 2144 | §103 | Non-Final OA | 3d overdue | Pending | May 12, 2023 |
| 17429192 | Systems and Methods for Predicting the Olfactory Properties of Molecules Using Machine Learning | AUGER, NOAH ANDREW | 1687 | Other | Final Rejection | 128d overdue | Pending | Aug 06, 2021 |
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