Prosecution Insights
Prosecution Insights
Technology area: Transportation, E-Commerce & Mechanical Systems
10 pending office actions • 7 art units • 10 examiners • 0 of 10 (0%) have an AI response strategy ready • 8 patents granted in the last 365 days
Matrixcare Inc. is managing 8 pending office actions within the Transportation, E-Commerce & Mechanical Systems technology area. These actions are distributed across 8 distinct examiners, meaning every pending matter is being reviewed by a different person. These examiners are spread across 5 distinct art units, indicating a variety of technical classifications for the company's filings.
The busiest examiner, HRANEK, KAREN AMANDA, is responsible for 1 pending office action. This shows that the 8 pending office actions are distributed perfectly among the 8 distinct examiners. The involvement of 5 distinct art units suggests that the company's innovations in transportation and e-commerce are being evaluated by five different specialized groups. This spread requires a strategy that can adapt to the diverse technical standards and examiner preferences found across these multiple departments.
Based on the USPTO statutory response window for each pending office action. 6 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. 6 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 | 3 (30%) |
| §101 + other | 5 (50%) |
| §103 only | 2 (20%) |
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 |
|---|---|---|---|
| HRANEK, KAREN AMANDA | 1 | 34.5% | +39.9% |
| KHATTAR, RAJESH | 1 | 36.7% | +35.2% |
| LE, LINH GIANG | 1 | 66.2% | -4.6% |
| HUYNH, EMILY | 1 | 21.9% | +43.6% |
| OBEID, MAMON A | 1 | 46.0% | +33.7% |
| SPRATT, BEAU D | 1 | 78.8% | +24.3% |
| LAGOY, KYRA RAND | 1 | 9.5% | -11.1% |
| HEIN, DEVIN C | 1 | 46.1% | +29.5% |
| HULBERT, AMANDA K | 1 | 84.6% | +4.2% |
| WASEEM, HUMA | 1 | 17.7% | +20.5% |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 8 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 17772909 | SYSTEMS AND METHODS FOR QUANTIFYING HAZARDS IN LIVING SPACES | WASEEM, HUMA | 182d overdue |
| 18618327 | MACHINE LEARNING-BASED SUMMARIZATION AND EVALUATION OF CLINICAL DATA | OBEID, MAMON A | 79d overdue |
| 18086375 | TAGGING PATIENT REFERRALS | HEIN, DEVIN C | 46d overdue |
| 18911784 | MACHINE LEARNING FOR USER GUIDANCE IN CLINICAL SETTINGS | HUYNH, EMILY | 2d overdue |
| 19020616 | MACHINE LEARNING-BASED PREDICTIVE ANALYTICS FOR REFERRAL DIAGNOSES | LE, LINH GIANG | 9d |
| 19020699 | MACHINE LEARNING-BASED DISEASE TRANSMISSION PREDICTIONS AND INTERVENTIONS | KHATTAR, RAJESH | 15d |
| 19169272 | MACHINE LEARNING TO PREDICT PATIENT OUTCOMES BASED ON POSITIONING | HRANEK, KAREN AMANDA | — |
| 18158909 | MODELS TO PREDICT MEDICATION EFFECTIVENESS | LAGOY, KYRA RAND | — |
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 7 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 17772909 | SYSTEMS AND METHODS FOR QUANTIFYING HAZARDS IN LIVING SPACES | WASEEM, HUMA | 182d overdue |
| 18618327 | MACHINE LEARNING-BASED SUMMARIZATION AND EVALUATION OF CLINICAL DATA | OBEID, MAMON A | 79d overdue |
| 18086375 | TAGGING PATIENT REFERRALS | HEIN, DEVIN C | 46d overdue |
| 18911784 | MACHINE LEARNING FOR USER GUIDANCE IN CLINICAL SETTINGS | HUYNH, EMILY | 2d overdue |
| 19020699 | MACHINE LEARNING-BASED DISEASE TRANSMISSION PREDICTIONS AND INTERVENTIONS | KHATTAR, RAJESH | 15d |
| 19169272 | MACHINE LEARNING TO PREDICT PATIENT OUTCOMES BASED ON POSITIONING | HRANEK, KAREN AMANDA | — |
| 18465473 | MACHINE LEARNING TO GENERATE SERVICE RECOMMENDATIONS | SPRATT, BEAU D | — |
| Art Unit | Apps |
|---|---|
| 3686 | 3 |
| 3685 | 2 |
| 3684 | 1 |
| 3683 | 1 |
| 3687 | 1 |
| 3629 | 1 |
| 3792 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19169272 | MACHINE LEARNING TO PREDICT PATIENT OUTCOMES BASED ON POSITIONING | HRANEK, KAREN AMANDA | 3684 | §101§103§112 | Final Rejection | — | Pending | Apr 03, 2025 |
| 19020699 | MACHINE LEARNING-BASED DISEASE TRANSMISSION PREDICTIONS AND INTERVENTIONS | KHATTAR, RAJESH | 3685 | §101 | Final Rejection | 15d | Pending | Jan 14, 2025 |
| 19020616 | MACHINE LEARNING-BASED PREDICTIVE ANALYTICS FOR REFERRAL DIAGNOSES | LE, LINH GIANG | 3686 | §101 | Final Rejection | 9d | Pending | Jan 14, 2025 |
| 18911784 | MACHINE LEARNING FOR USER GUIDANCE IN CLINICAL SETTINGS | HUYNH, EMILY | 3683 | §101§102 | Non-Final OA | 2d overdue | Pending | Oct 10, 2024 |
| 18618327 | MACHINE LEARNING-BASED SUMMARIZATION AND EVALUATION OF CLINICAL DATA | OBEID, MAMON A | 3687 | §101§103 | Non-Final OA | 79d overdue | Pending | Mar 27, 2024 |
| 18465473 | MACHINE LEARNING TO GENERATE SERVICE RECOMMENDATIONS | SPRATT, BEAU D | 3629 | §103 | Final Rejection | — | Pending | Sep 12, 2023 |
| 18158909 | MODELS TO PREDICT MEDICATION EFFECTIVENESS | LAGOY, KYRA RAND | 3685 | §101§103 | Non-Final OA | — | Pending | Jan 24, 2023 |
| 18086375 | TAGGING PATIENT REFERRALS | HEIN, DEVIN C | 3686 | §101 | Non-Final OA | 46d overdue | Pending | Dec 21, 2022 |
| 17785262 | METHOD AND SYSTEM FOR DETECTING MOOD | HULBERT, AMANDA K | 3792 | §101§103 | Non-Final OA | — | Pending | Jun 14, 2022 |
| 17772909 | SYSTEMS AND METHODS FOR QUANTIFYING HAZARDS IN LIVING SPACES | WASEEM, HUMA | 3686 | §103 | Non-Final OA | 182d overdue | Pending | Apr 28, 2022 |
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