Generic Medicinal Products in Immunosuppressive Therapy—Should It be a Challenge for Therapeutic Drug Monitoring?
Bibliographic record
Abstract
ABSTRACT: Immunosuppressants have a narrow therapeutic index (NTIDs). Indisputably cyclosporine, tacrolimus, everolimus, and sirolimus have NTIDs, and only in the case of mycophenolic acid, a scientific discussion has not been yet concluded. Their specificities highlight the implications for generics introduced into the drug market, more precisely, with bioequivalence testing. In the European Union, the European Medicines Agency (EMA) released the "Guideline on the Investigation of Bioequivalence." The bioequivalence (BE) of the generic (tested, T) versus original (reference, R) product should be confirmed by obtaining a 90% confidence interval (CI) for the T:R ratio of each of the 2 decisive pharmacokinetic parameters, namely, the area under the curve (AUC) between 90.00% and 111.11%. A similar approach (90.00%-112.00%) for AUC was adopted by the Canadian Agency for Drugs and Technologies in Health (CADTH) for NTIDs; however, the US Food and Drug Administration is still based on classic acceptance criteria: 90% CI between 80.00% and 125.00% but with special requirements of BE testing. A discussion about long-expected global consensus was performed in this study based on the literature concerning BE testing in the case of NTIDs. The narrow acceptance criteria reduce the potential mean difference in bioavailability between generic and original products by a few percent. To identify this problem, special attention has been paid to switching drugs (generic-generic, original-generic) and therapeutic drug monitoring after conversion (TDM). There is no global consensus on the acceptance criteria for the BE of generic drugs; therefore, consensus and harmonization are strictly necessary. This study presents a review of the generic drug market and its classification by manufacturers, drug agencies, and dates of marketing authorization. Guidelines for TDM optimization (during switching/conversion) have been proposed. Physicians and clinical pharmacists should pay special attention to switching immunosuppressive drugs between original versus generic formulations, and generic versus generic formulations. Patients and their families should be educated on the risks associated with uncontrolled conversion.
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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 | 0.023 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".