Prosecution Insights
Prosecution Insights
Technology area: Transportation, E-Commerce & Mechanical Systems
4 pending office actions • 4 art units • 4 examiners • 0 of 4 (0%) have an AI response strategy ready • 1 patents granted in the last 365 days
Twin Health, Inc. currently has 4 pending office actions distributed across the Transportation, E-Commerce & Mechanical Systems technology area. The portfolio shows significant diversification in its examination path, as these matters are spread across 4 distinct examiners. This distribution is mirrored in the organizational structure of the patent office, with the 4 pending actions also spanning 4 distinct art units. This one-to-one ratio between actions, examiners, and art units suggests that each filing is being treated as a distinct technical entity.
The workload is evenly distributed among the assigned personnel. SOREY, ROBERT A is identified as the busiest examiner for the company, though they are currently handling only 1 pending office action. This indicates that no single examiner or art unit dominates the company's current prosecution efforts. The parity between the number of pending office actions and the number of distinct examiners suggests that each matter is receiving independent review. For a practitioner, this means the company's patent strategy is currently decentralized, requiring engagement with 4 different examiners across several specialized units.
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 |
|---|---|
| §101 only | 2 (50%) |
| §101 + other | 2 (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 |
|---|---|---|---|
| SOREY, ROBERT A | 1 | 49.3% | +45.2% |
| TOKARCZYK, CHRISTOPHER B | 1 | 43.7% | +23.7% |
| PATEL, JAY M | 1 | 64.6% | +39.2% |
| RUIZ, JOSHUA DAMIAN | 1 | 0.0% | +0.0% |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 4 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 18623790 | DYNAMICALLY MODELING THE EFFECT OF FOOD ITEMS AND ACTIVITY ON A PATIENT'S METABOLIC HEALTH | SOREY, ROBERT A | 59d overdue |
| 18508197 | PRECISION BIOLOGY SEARCH WITH MACHINE LEARNING AND DIGITAL TWIN TECHNOLOGY | TOKARCZYK, CHRISTOPHER B | 44d overdue |
| 17963933 | Generating Instructions for Physical Experiments Using Whole Body Digital Twin Technology | PATEL, JAY M | 23d overdue |
| 17963932 | Generating Patient Cohorts for Simulating Clinical Trials Using Whole Body Digital Twin Technology | RUIZ, JOSHUA DAMIAN | — |
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 |
|---|---|---|---|
| 18623790 | DYNAMICALLY MODELING THE EFFECT OF FOOD ITEMS AND ACTIVITY ON A PATIENT'S METABOLIC HEALTH | SOREY, ROBERT A | 59d overdue |
| 18508197 | PRECISION BIOLOGY SEARCH WITH MACHINE LEARNING AND DIGITAL TWIN TECHNOLOGY | TOKARCZYK, CHRISTOPHER B | 44d overdue |
| 17963933 | Generating Instructions for Physical Experiments Using Whole Body Digital Twin Technology | PATEL, JAY M | 23d overdue |
| Art Unit | Apps |
|---|---|
| 3682 | 1 |
| 3687 | 1 |
| 3681 | 1 |
| 3684 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 18623790 | DYNAMICALLY MODELING THE EFFECT OF FOOD ITEMS AND ACTIVITY ON A PATIENT'S METABOLIC HEALTH | SOREY, ROBERT A | 3682 | §101 | Non-Final OA | 59d overdue | Pending | Apr 01, 2024 |
| 18508197 | PRECISION BIOLOGY SEARCH WITH MACHINE LEARNING AND DIGITAL TWIN TECHNOLOGY | TOKARCZYK, CHRISTOPHER B | 3687 | §101 | Final Rejection | 44d overdue | Pending | Nov 13, 2023 |
| 17963933 | Generating Instructions for Physical Experiments Using Whole Body Digital Twin Technology | PATEL, JAY M | 3681 | §101§112 | Final Rejection | 23d overdue | Pending | Oct 11, 2022 |
| 17963932 | Generating Patient Cohorts for Simulating Clinical Trials Using Whole Body Digital Twin Technology | RUIZ, JOSHUA DAMIAN | 3684 | §101§103 | Non-Final OA | — | Pending | Oct 11, 2022 |
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