Prosecution Insights
Prosecution Insights
Technology area: Computing & Software
3 pending office actions • 2 art units • 3 examiners • 0 of 3 (0%) have an AI response strategy ready • 3 patents granted in the last 365 days
Icon Clinical Research Limited currently faces 3 pending office actions within the Computing & Software technology area. These actions are distributed across 3 distinct examiners, suggesting a range of technical examinations despite the shared technology category. The workload spans 2 distinct art units, which indicates that the portfolio's software innovations may touch upon different functional classifications within the patent office. This distribution across 2 art units requires the company to monitor different examination trends simultaneously. Legal teams should coordinate their responses to ensure technical consistency across these different units.
The busiest examiner, MIAN, MUHAMMAD U, is responsible for 1 busiest examiner pending office action. This distribution across 3 distinct examiners requires a multi-faceted approach to prosecution. Practitioners must prepare unique strategies for each of the 3 pending office actions to account for the different perspectives of the examiners involved. The company's strategy in the computing sector is currently divided among these separate examiner interactions. This approach ensures that examiner decisions are distributed across the pending software portfolio.
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 | 1 (33%) |
| Multi-statute (no §101) | 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 |
|---|---|---|---|
| MIAN, MUHAMMAD U | 1 | 67.1% | +22.4% |
| KELLS, ASHER | 1 | 78.9% | +11.6% |
| OBISESAN, AUGUSTINE KUNLE | 1 | 63.6% | +20.8% |
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 |
|---|---|---|---|
| 18680095 | SYSTEMS AND METHODS FOR UTILIZING DATA OBJECT REFERENCES TO ACCESS A TRANSLATED VERSION OF A VALIDATED INSTRUMENT | MIAN, MUHAMMAD U | — |
| 18680113 | SYSTEMS AND METHODS FOR DIRECT INTEGRATION OF A PREVIEW FUNCTION | KELLS, ASHER | — |
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 |
|---|---|---|---|
| 18680095 | SYSTEMS AND METHODS FOR UTILIZING DATA OBJECT REFERENCES TO ACCESS A TRANSLATED VERSION OF A VALIDATED INSTRUMENT | MIAN, MUHAMMAD U | — |
| 18680113 | SYSTEMS AND METHODS FOR DIRECT INTEGRATION OF A PREVIEW FUNCTION | KELLS, ASHER | — |
| 18678419 | SYSTEMS AND METHODS FOR IMPLEMENTING DRUG MECHANISMS OF ACTION WITH MACHINE LEARNING | OBISESAN, AUGUSTINE KUNLE | — |
| Art Unit | Apps |
|---|---|
| 2163 | 1 |
| 2171 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18680095 | SYSTEMS AND METHODS FOR UTILIZING DATA OBJECT REFERENCES TO ACCESS A TRANSLATED VERSION OF A VALIDATED INSTRUMENT | MIAN, MUHAMMAD U | 2163 | §101§112 | Final Rejection | — | Pending | May 31, 2024 |
| 18680113 | SYSTEMS AND METHODS FOR DIRECT INTEGRATION OF A PREVIEW FUNCTION | KELLS, ASHER | 2171 | §102§103 | Non-Final OA | — | Pending | May 31, 2024 |
| 18678419 | SYSTEMS AND METHODS FOR IMPLEMENTING DRUG MECHANISMS OF ACTION WITH MACHINE LEARNING | OBISESAN, AUGUSTINE KUNLE | — | §103 | Non-Final OA | — | Pending | May 30, 2024 |
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