The Interplay Between Molecular Architecture, Pharmacology, and Suspected Adverse Drug Reactions Associated with Non-Steroidal Androgen Antagonists in The United Kingdom
Bibliographic record
Abstract
Aims: To correlate potential links between the suspected adverse drug reaction (ADR) profile of licensed non-steroidal androgen receptor antagonists (NSARA) with their unique chemical properties and known off-target polypharmacology. Methods: Physiochemical and polypharmacology data was curated from the Electronic Medicines Compendium, FDA New Drug Applications documents, and ChEMBL databases. System organ class (SOC, MedDRA) suspected ADRs and fatalities were curated from the United Kingdom Medicines and Healthcare products Regulatory Authority (MHRA) Yellow card spontaneous reporting scheme for their respective prescribing period; apalutamide (Jan 2019-), bicalutamide (Aug 2018-), enzalutamide (Aug 2018-), flutamide (Aug 2018-) and darolutamide (March 2019-) until Oct 2023. The number of daily doses (dd) was extracted from OpenPrescribing and NHS Digital secondary care medicines data. Data was standardised before comparison to suspected ADRs and fatality reports per 100,000 dd. Results A total of n = 2,480 suspected ADRs were associated with 42,903,000 dd of NSARAs in the United Kingdom. The highest number of ADRs were associated with enzalutamide (n = 1,091) and bicalutamide (n = 749). Enzalutamide was found to have the most off-target pharmacological interactions of the NSARAs studied (n = 5) including potent inhibition of γ-aminobutyric acid, GABA receptor (IC50 = 2.6 µM vs Cmax = 7.7 µM) associated with nervous system disorders (n = 72, accounting for 73% of all NSARA ADRs in this SOC). Apalutamide, the only other GABA inhibitor (IC50 = 3 µM vs Cmax = 2.9 µM) had the highest relative rate of suspected nervous system ADRs at 1.08 per 100,000 dd. Apalutamide was also a modest inhibitor of the human Ether-à-go-go-Related Gene (hERG) ion channel (IC50 = 6 µM vs Cmax = 2.9 µM) and had the highest rate of suspected cardiac arrhythmia ADRs, 30-fold over, enzalutamide, a significantly weaker hERG inhibitor (15.7 µM vs Cmax = 7.7 µM). Darolutamide was the only NSARA to show effects at 5-HT (serotonin) receptor at < 10 µM but did not translate to psychiatric disorders due to low clinical BBB penetration but a an association with hepatobiliary and cardiac disorders was identified based on this inhibitory axis. Suspected skin and subcutaneous SOC ADRs was associated with all NSARAs (except flutamide) but did not reach statistical significance (P = .25). A rationale for epidermis reactions relating to apalutamide containing a masked arylamine was explored but molecular matched pair (MMP) analysis with enzalutamide suggests it may not be a chemical cause. Statistical significance (P < .05) was identified in reported fatalities associated with NSARAs, flutamide had n = 24 or 897.5 fatalities per 100,000 dd which was likely due to both the indication and the small number of dd (n = 3,000) during the time period of the study. Conclusions An investigation of suspected ADRs, standardised to the number of dd for the novel NSARA drug class identified SOCs of potential interest. The highest number of reports related to enzalutamide and bicalutamide. Suspected skin and subcutaneous ADRs approached statistical significance and was interrogated for chemical and pharmacological connections for the first time with the aid of MMP analysis. A potential correlation to nervous system disorders and cardiac arrhythmia for the GABA and hERG inhibitors, enzalutamide and apalutamide, respectively was identified. Darolutamide’s interaction with 5-HT may influence ADRs associated with cardiac and hepatobiliary SOCs. Statistically significant number of suspected fatalities with flutamide was identified.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".