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Record W2467894892 · doi:10.1017/s1092852900024706

Generic Substitution for Psychotropic Drugs

2009· article· en· W2467894892 on OpenAlexaff
Pierre Blier

Bibliographic record

VenueCNS Spectrums · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicPharmaceutical Economics and Policy
Canadian institutionsMental Health Research Canada
Fundersnot available
KeywordsBioequivalenceDrugGeneric drugMedicineBrand namesFood and drug administrationPharmacologyPharmacokineticsMarketingBusiness

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.059
GPT teacher head0.292
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2009
Admission routes1
Has abstractyes

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