Oral, Direct Factor Xa Inhibitors in Development for the Prevention and Treatment of Thromboembolic Diseases
Bibliographic record
Abstract
Anticoagulants are recommended for the prevention and treatment of a wide variety of thromboembolic events. Although existing anticoagulants are effective, their use is limited by parenteral administration or the requirement for frequent monitoring and subsequent dose adjustment. Therefore, there is an urgent need for novel, oral agents with a predictable anticoagulant action. Because of its key position in the coagulation cascade and its limited roles outside of coagulation, Factor Xa has emerged as an attractive target for novel anticoagulants. As a result, the past decade has witnessed an explosion of research into small-molecule, oral, direct Factor Xa inhibitors, and several are now in clinical development. Rivaroxaban, LY517717, YM150, apixaban, PRT054021, and DU-176b, among others, have shown considerable promise; rivaroxaban is currently furthest ahead in its developmental program, having entered phase III in 3 indications. It is hoped that, before long, these anticoagulants will allow us to enter an era of convenient, oral anticoagulation, without the need for regular monitoring or dose adjustment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".