Bibliographic record
Abstract
<b>Compliance with Ethical Standards</b> <b>Funding</b> The preparation of this review was not supported by any external funding. <b>Conflict of interest</b><b><i> </i></b><b> </b>During the peer review process the manufacturer of the agent under review was offered an opportunity to comment on the article. Changes resulting from any comments received were made by the authors on the basis of scientific completeness and accuracy. Arnold Lee is a salaried employee of Adis International Ltd/Springer Nature, is responsible for the article content and declares no relevant conflicts of interest.<br>Additional information about this Adis Drug Review can be found <b>here</b><br><b>Abstract </b> Tucatinib is an oral, small molecule, selective HER2 inhibitor initially developed by Array BioPharma (a subsidiary of Pfizer) and subsequently developed by Seattle Genetics for the treatment of HER2-positive solid tumours, including breast cancer and colorectal cancer. Tucatinib was approved in the USA in April 2020 and in Switzerland in May 2020 for the treatment of HER2-positive breast cancer, and is pending regulatory review in the EU, Australia, Canada and Singapore. This article summarizes the milestones in the development of tucatinib leading to this first approval in patients with advanced unresectable or metastatic HER2-positive breast cancer.<br>
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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 | 0.000 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.880 | 0.220 |
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; both teacher heads agree on what is shown here.
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".