Investigation of the mechanisms of felbamate- and nevirapine-induced idiosyncratic drug reactions
Bibliographic record
Abstract
Idiosyncratic drug reactions represent a major medical problem. The exact mechanisms of idiosyncratic drug reactions are unknown; however, the formation of reactive metabolites and the stimulation of patient's immune system have been implicated. Studying idiosyncratic reactions in patients is virtually impossible; hence, we use animal models. The two drugs that I studied were felbamate and nevirapine. Nevirapine can cause skin rashes in humans. I used an animal model that had previously been developed in our laboratory to further investigate the steps involved in this idiosyncratic reaction. I observed an increase in the total number of T, B, and macrophage cells in the skin. Macrophages were found to infiltrate skin before T cells. Cell activation and ICAM 1 upregulation was observed in parallel to macrophage infiltration. Additionally, on rechallenge, increased serum levels of IFNgamma were observed. Application of either nevirapine or 12-hydroxynevirapine (a precursor to a potential reactive metabolite) to the ears of previously nevirapine-treated rats led to the rapid onset of red ears. This indicates that the T cells activated by previous exposure respond to both the parent drug and to either reactive metabolites or simply structures similar to the parent drug. Generally, various mechanisms can trigger idiosyncratic drug reactions and we hope further studies will enable us to discover most of them. Felbamate can cause liver failure and aplastic anemia. It is known that felbamate is metabolized to reactive 2-phenylpropenal. Attempts to generate an animal model of this adverse reaction by treatment of rats with felbamate along with depletion of glutathione and stimulation of the immune system were unsuccessful. We were unable to detect covalent binding of this reactive metabolite in vivo, either because our antibody is not sufficiently sensitive in rodents (which form less of this metabolite than humans) or because the binding is reversible. I was able to demonstrate the immunogenicity of 2-phenylpropenal. Specifically, injection of a 2-phenylpropenal precursor led to B cell activation, proliferation, and germinal centre formation and stimulated increased IgM, IgG1, IL-4, and IFNgamma production. In contrast, the parent drug and stable metabolites were inactive, demonstrating that reactive metabolites can lead to idiosyncratic reactions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".