Bibliographic record
Abstract
Generic immunosuppressive drugs are available in Europe, Canada, and the United States. Between countries, there are large differences in the market penetration of generic drugs in general, and for immunosuppressive drugs in particular. The registration criteria for generic immunosuppressive drugs are often criticized. However, it is unlikely that the criteria for registration of narrow therapeutic index drugs are going to change, and bioequivalence studies, performed in healthy volunteers, will remain the backbone of the registration process. It would be good if the registration authorities would demand that all generic variants of an innovator drug have the same pill appearance to reduce errors and promote drug adherence.To allow for safe substitution, a number of criteria need to be fulfilled. Generic substitution should not be taken out of the hands of the treating physicians. Generic substitution can only be done safely if initiated by the prescriber, and in well-informed and prepared patients. Payers should refrain from forcing pharmacists to dispense generic drugs in patients on maintenance treatment with innovator drug. Instead, together with transplant societies, they should design guidelines on how to implement generic immunosuppressive drugs into clinical practice. Substitutions must be followed by control visits to check if the patient is taking the medication correctly and if drug exposure remains stable. Inadvertent, uncontrolled substitutions from 1 generic to another, initiated outside the scope of the prescriber, must be avoided as they are unsafe. Repetitive subsequent generic substitutions result in minimal additional cost savings and have an inherent risk of medication errors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.011 | 0.019 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.017 | 0.012 |
| Insufficient payload (model declined to judge) | 0.018 | 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 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".