Bioactivation of drugs in the skin: relationship to cutaneous adverse drug reactions
Bibliographic record
Abstract
Drug-induced skin rashes are poorly understood idiosyncratic reactions, and current methods cannot predict their occurrence. Most idiosyncratic drug reactions are thought to be caused by chemically reactive metabolites, and the skin is a frequent site of idiosyncratic reactions; however, the skin has a very limited capacity to metabolize drugs. To balance this, the skin represents a protective barrier with a very active immune response against pathogens and other types of skin injury. Therefore its response to reactive metabolites is quite different from that of the liver. The purpose of this review is to integrate emerging findings into proposed mechanisms of drug and carcinogen metabolism in the skin that are likely responsible for rashes and other immune responses of the skin. Current evidence suggests the skin possesses significant sulfotransferase and flavin monooxygenases activities, but very low cytochromes P450 activity. However, there are skin-specific P450s that are not present in the liver. The manner in which the skin responds to neoantigens through local antigen presentation and innate immune sensing is reviewed with a focus on insights gained from the contact hypersensitivity (CHS) field. The roles of keratinocytes and Langerhans cells, and the emerging function of NOD-like receptors, are highlighted.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 0.003 |
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".