Type II & III inhibitors of tropomyosin receptor kinase (Trk): a 2020–2022 patent update
Bibliographic record
Abstract
INTRODUCTION: The Trk family proteins are membrane-bound kinases predominantly expressed in neuronal tissues. Activated by neurotrophins, they regulate critical cellular processes through downstream signaling pathways. Dysregulation of Trk signaling can drive a range of diseases, making the design and study of Trk inhibitors a vital area of research. This review explores recent advances in the development of type II and III Trk inhibitors, with implications for various therapeutic applications. AREAS COVERED: . Relevant patents were identified using the Web of Science database, Google, and Google Patents. EXPERT OPINION: While type II and III Trk inhibitor development has advanced more gradually compared to their type I counterparts, they hold significant promise in overcoming resistance mutations and achieving enhanced subtype selectivity - a critical factor in reducing adverse effects associated with pan-Trk inhibition. Recent interdisciplinary endeavors have marked substantial progress in the design of subtype selective Trk inhibitors, with impressive success heralded by the type III inhibitors. Notably, the emergence of mutant-selective Trk inhibitors introduces an intriguing dimension to the field, offering precise treatment possibilities.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.030 | 0.013 |
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".