Bibliographic record
Abstract
Most antidepressants and other psychotropics in clinical use are available as generic formulations (Table). The availability of lower-priced, generic drugs can benefit patients and third-party payers, but it should not be assumed that all generic drugs are equally beneficial. There are numerous reports in the literature of unexpected and untoward consequences that occur when a generic drug is substituted for the original brand-name drug. A previously stable clinical response may suddenly deteriorate, or the patient may experience new or more severe adverse events (AEs). The United States Food and Drug Administration requires that manufacturers of generic drugs demonstrate that their formulation has pharmacokinetic properties similar (or bioequivalent) to the brand-name drug. Bioequivalency studies are conducted in healthy volunteers, not in patients who would be treated with that drug. Moreover, bioequivalency studies are conducted on a current lot of the branded drug and do not account for variability between lots of the generic formulation. The manufacturer is only required to submit bioequivalency data that support the Abbreviated New Drug Application (ANDA); the FDA does not require disclosure of failed bioequivalence studies. Unlike brand-name drugs, lengthy and costly clinical studies are not required to show that the generic drug is effective and safe. Although the FDA has taken the position that bioequivalence and therapeutic equivalence are equal, many questions related to the use of generic drugs remain unanswered. The following question-and-answer session is an excerpt of an interview with Pierre Blier, MD, PhD, conducted by Diane Sloan, PharmD, which addresses the issue of generic substitution of psychotropic drugs.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.173 | 0.057 |
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".