Tropomyosin receptor kinase inhibitors: an updated patent review for 2010-2016 –<i>Part I</i>
Bibliographic record
Abstract
INTRODUCTION: TrkA/B/C receptor activation supports growth, survival, and differentiation of discrete neuronal populations during development, adult life, and ageing but also plays numerous roles in human disease onset and progression. Trk-specific inhibitors have therapeutic applications in cancer and pain and thus constitute a growing area of interest in oncology and neurology. There has been substantial growth in the number of structural classes of Trk inhibitors and the number of industrial entrants to the Trk inhibitor field over the past six years. Areas covered: In Part II of this two-part review, the discussion of recent patent literature covering Trk family inhibitors is continued from Part I and clinical research with Trk inhibitors is considered. Expert opinion: Trk has been molecularly targeted for over a decade resulting in the progressive evolution of structurally diversified Trk inhibitors arising from scaffold hopping and HTS efforts. Correspondingly, there have been a growing number of clinical investigations utilizing Trk inhibitors in recent years, with a particular focus on the treatment of NTRK-fusion positive cancers and chronic pain. The observed potential of Trk inhibitors to cause adverse CNS side effects however suggests the need for a more rigorous consideration of BBB permeation capabilities during drug development.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".