Loss of response after switching from brand name to generic formulations: three cases and a discussion of key clinical considerations when switching
Bibliographic record
Abstract
Generic formulations of medications are marketed as therapeutically equivalent and less expensive than branded ones. Multiple studies and case reports have described relapses and worsening clinical outcome in patients after a switch from a brand name to a generic medication. Recent studies have shown that generics do not always lead to the expected costs savings, reducing the impetus to proceed with compulsory generic switching. We report on three patients who experienced clinical deterioration after commencing the generic formulation of their previous brand name psychotropic medication. We discuss key clinical differences between original and generic formulations of the same medication. The use of bioequivalence as an indicator of therapeutic and clinical equivalence, the lack of appropriate studies comparing generic and brand name medications and differences in excipients are some of the factors that could explain variation in clinical response between generic and brand name medications. Generic switching should be decided on a case-by-case basis with disclosure of potential consequences to the patient.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.010 | 0.007 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".