Enzalutamide and blocking androgen receptor in advanced prostate cancer: lessons learnt from the history of drug development of antiandrogens
Bibliographic record
Abstract
Abstract: Enzalutamide is a nonsteroidal antiandrogen for the treatment of metastatic castration-resistant prostate cancer (mCRPC) both before and after chemotherapy. Enzalutamide is more effective than its predecessor bicalutamide, which was analyzed in head-to-head studies of patients with CRPC. This family of nonsteroidal antiandrogens is now comprised of four drugs approved by the US Food and Drug Administration with two investigational drugs in clinical trials. Antiandrogens have been employed clinically for more than five decades to provide a rich resource of information. Steady-state concentration minimums (C min or trough) in the range of ~1–13 μg/mL are measured in patients at therapeutic doses. Interestingly, enzalutamide which is considered to have strong affinity for the androgen receptor (AR) requires C min levels >10 μg/mL. The sequence of antiandrogens and the clinical order of application in regard to other drugs that target the androgen axis remain of high interest. One novel first-in-class drug, called ralaniten, which binds to a unique region in the N-terminus domain of both the full-length and the truncated constitutively active splice variants of the AR, is currently in clinical trials for patients who previously received abiraterone, enzalutamide, or both. This highlights the trend to develop drugs with novel mechanisms of action and potentially differing mechanisms of resistance compared with antiandrogens. Better and more complete inhibition of the transcriptional activity of the AR appears to continue to provide improvements in the clinical management of mCRPC. Keywords: prostate cancer, enzalutamide, antiandrogens, C min , trough, pharmacology, cross-resistance, clinical trials, PSA response, ralaniten, EPI-002
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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 | 0.003 | 0.003 |
| 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 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".