Technology area: Biotechnology & Pharmaceuticals
9 pending office actions • 8 art units • 9 examiners • 0 of 9 (0%) have an AI response strategy ready • 18 patents granted in the last 365 days
Recursion Pharmaceuticals Inc. has 9 pending office actions in Biotechnology & Pharmaceuticals. The matters involve 9 distinct examiners and 8 distinct art units. Examiner assignments are fully dispersed, while one art unit contains more than one pending action.
SIOZOPOULOS, CONSTANTINE B is the busiest examiner, with 1 pending action. Counsel should prioritize independent matter review and maintain an art-unit reference for the small amount of technical overlap shown by the data.
Based on the USPTO statutory response window for each pending office action. 1 of the docket's apps have a known mailing date; the rest are excluded from the tile counts.
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 | 1 (11%) |
| §101 + other | 4 (44%) |
| §103 only | 1 (11%) |
| §102 only | 1 (11%) |
| Multi-statute (no §101) | 2 (22%) |
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 |
|---|---|---|---|
| SIOZOPOULOS, CONSTANTINE B | 1 | 57.5% | +39.6% |
| TO, BAOQUOC N | 1 | 89.9% | +7.9% |
| NGUYEN, LEON VIET Q | 1 | 85.2% | +10.2% |
| ROSSI, VY BUI | 1 | 29.5% | +36.4% |
| PARK, HYUN D | 1 | 41.8% | +22.5% |
| ISMAIL, REHANA | 1 | 76.2% | +34.8% |
| VASSELL, MEREDITH ABBOTT | 1 | 29.9% | +45.8% |
| BAILEY, STEVEN WILLIAM | 1 | 31.6% | +15.2% |
| ARIETI, RUTH SOPHIA | 1 | 46.2% | +71.4% |
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 |
|---|---|---|---|
| 18813537 | UTILIZING MASKED AUTOENCODER GENERATIVE MODELS TO EXTRACT MICROSCOPY REPRESENTATION AUTOENCODER EMBEDDINGS | NGUYEN, LEON VIET Q | — |
Multi-statute / §101-driven matters, or cases in front of an examiner with an allow rate under 30%. The top 7 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 17101545 | HIGH THROUGHPUT GENE EDITING SYSTEM AND METHOD | ARIETI, RUTH SOPHIA | 60d overdue |
| 19167738 | COMPUTATIONAL DRUG TARGET SELECTION | SIOZOPOULOS, CONSTANTINE B | — |
| 19270223 | UTILIZING MACHINE LEARNING MODELS TO SYNTHESIZE PERTURBATION DATA TO GENERATE PERTURBATION HEATMAP GRAPHICAL USER INTERFACES | TO, BAOQUOC N | — |
| 18753906 | DETERMINING PHENOMIC RELATIONSHIPS BETWEEN COMPOUNDS AND CELL PERTURBATIONS UTILIZING MACHINE LEARNING MODELS | ROSSI, VY BUI | — |
| 18663991 | SYSTEMS AND METHODS FOR HIGH THROUGHPUT COMPOUND LIBRARY CREATION | PARK, HYUN D | — |
| 18231219 | Drug Optimization by Active Learning | VASSELL, MEREDITH ABBOTT | — |
| 18138705 | Computational Drug Target Selection | BAILEY, STEVEN WILLIAM | — |
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 8 ordered by deadline are shown.
| App # | Title | Examiner | Due in |
|---|---|---|---|
| 17101545 | HIGH THROUGHPUT GENE EDITING SYSTEM AND METHOD | ARIETI, RUTH SOPHIA | 60d overdue |
| 19167738 | COMPUTATIONAL DRUG TARGET SELECTION | SIOZOPOULOS, CONSTANTINE B | — |
| 18813537 | UTILIZING MASKED AUTOENCODER GENERATIVE MODELS TO EXTRACT MICROSCOPY REPRESENTATION AUTOENCODER EMBEDDINGS | NGUYEN, LEON VIET Q | — |
| 18753906 | DETERMINING PHENOMIC RELATIONSHIPS BETWEEN COMPOUNDS AND CELL PERTURBATIONS UTILIZING MACHINE LEARNING MODELS | ROSSI, VY BUI | — |
| 18663991 | SYSTEMS AND METHODS FOR HIGH THROUGHPUT COMPOUND LIBRARY CREATION | PARK, HYUN D | — |
| 18234341 | Heterocycle RMB39 Modulators | ISMAIL, REHANA | — |
| 18231219 | Drug Optimization by Active Learning | VASSELL, MEREDITH ABBOTT | — |
| 18138705 | Computational Drug Target Selection | BAILEY, STEVEN WILLIAM | — |
| Art Unit | Apps |
|---|---|
| 1687 | 2 |
| 3686 | 1 |
| 2154 | 1 |
| 2663 | 1 |
| 1685 | 1 |
| 2857 | 1 |
| 1625 | 1 |
| 1635 | 1 |
| App # | Title | Examiner | Art Unit | Statutes | Status | Due in | AI | Filed |
|---|---|---|---|---|---|---|---|---|
| 19167738 | COMPUTATIONAL DRUG TARGET SELECTION | SIOZOPOULOS, CONSTANTINE B | 3686 | §101 | Non-Final OA | — | Pending | Sep 22, 2025 |
| 19270223 | UTILIZING MACHINE LEARNING MODELS TO SYNTHESIZE PERTURBATION DATA TO GENERATE PERTURBATION HEATMAP GRAPHICAL USER INTERFACES | TO, BAOQUOC N | 2154 | §101§103Other | Non-Final OA | — | Pending | Jul 15, 2025 |
| 18813537 | UTILIZING MASKED AUTOENCODER GENERATIVE MODELS TO EXTRACT MICROSCOPY REPRESENTATION AUTOENCODER EMBEDDINGS | NGUYEN, LEON VIET Q | 2663 | §103 | Final Rejection | — | Pending | Aug 23, 2024 |
| 18753906 | DETERMINING PHENOMIC RELATIONSHIPS BETWEEN COMPOUNDS AND CELL PERTURBATIONS UTILIZING MACHINE LEARNING MODELS | ROSSI, VY BUI | 1685 | §101§102DP | Final Rejection | — | Pending | Jun 25, 2024 |
| 18663991 | SYSTEMS AND METHODS FOR HIGH THROUGHPUT COMPOUND LIBRARY CREATION | PARK, HYUN D | 2857 | §103§112Other | Non-Final OA | — | Pending | May 14, 2024 |
| 18234341 | Heterocycle RMB39 Modulators | ISMAIL, REHANA | 1625 | §102 | Final Rejection | — | Pending | Aug 15, 2023 |
| 18231219 | Drug Optimization by Active Learning | VASSELL, MEREDITH ABBOTT | 1687 | §101§103§112DP | Non-Final OA | — | Pending | Aug 07, 2023 |
| 18138705 | Computational Drug Target Selection | BAILEY, STEVEN WILLIAM | 1687 | §101§102§103 | Non-Final OA | — | Pending | Apr 24, 2023 |
| 17101545 | HIGH THROUGHPUT GENE EDITING SYSTEM AND METHOD | ARIETI, RUTH SOPHIA | 1635 | §103§112 | Non-Final OA | 60d overdue | Pending | Nov 23, 2020 |
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Start Free TrialRecursion Pharmaceuticals Inc. has 9 pending office actions as of October 2026, spread across 8 art units and 9 examiners.
Constantine B Siozopoulos has the most, with 1 of Recursion Pharmaceuticals Inc.'s pending office actions.
Mostly Biotechnology & Pharmaceuticals (USPTO Tech Center 1600), based on where its pending office actions are examined.
