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Record W2969137655 · doi:10.1111/1468-0009.12413

Pharmaceutical Drugs of Uncertain Value, Lifecycle Regulation at the US Food and Drug Administration, and Institutional Incumbency

2019· article· en· W2969137655 on OpenAlexafffund
Matthew Herder

Bibliographic record

VenueMilbank Quarterly · 2019
Typearticle
Languageen
FieldMedicine
TopicBiomedical Ethics and Regulation
Canadian institutionsDalhousie University
FundersCanadian Institutes of Health ResearchCommonwealth Fund
KeywordsMandateContext (archaeology)MedicineFood and drug administrationTransparency (behavior)PoliticsPostmarketing surveillancePublic relationsBusinessPharmacologyPolitical sciencePublic administrationLawAdverse effect

Abstract

fetched live from OpenAlex

Policy Points The US Food and Drug Administration (FDA) has in recent years allowed onto the market several drugs with limited evidence of safety and effectiveness, provided that manufacturers agree to carry out additional studies while the drugs are in clinical use. Studies suggest that these postmarketing requirements (PMRs) frequently lack transparency, are subject to delays, and fail to answer the questions of greatest clinical importance. Yet, none of the literature speaks directly to the challenges that the FDA-as a regulatory institution-encounters in enforcing PMRs. Through a series of interviews with FDA leadership, this article analyzes and situates those challenges in the midst of political threats to the FDA's public health mandate. CONTEXT: Modern pharmaceutical regulation is premised on a rigorous examination of a drug's safety and effectiveness prior to its lawful sale. However, since the 1990s, the US Food and Drug Administration (FDA) has gradually shifted to a model of "lifecycle" regulation that increasingly relies on postmarketing requirements (PMRs) to encourage studies of drug safety and effectiveness following regulatory approval. This article examines the range of legal, institutional, and political challenges that FDA faces in the context of lifecycle regulation. METHODS: Document-based legal and policy analysis was combined with a set of semistructured interviews of current and former FDA officials (n = 23) in order to explore the implications of the FDA's use of PMRs. The median interview time per official was 61 minutes, with a range of 24 to 227 minutes. All of the officials interviewed occupied positions of leadership and influence within the FDA, such as directors of an FDA center or office, key legal counsel on agency-wide policy initiatives, and the commissioner of the FDA. FINDINGS: Insufficient resources and coordination within the FDA, inadequate legal authorities, and the political economy of withdrawing an approved indication in the face of opposition from companies and patients all contribute to the observed shortcomings in the FDA's use and enforcement of PMRs. Further, the FDA is fully aware of these challenges, yet is seemingly resigned to and resistant to criticism of its use of PMRs. CONCLUSIONS: This study of the FDA's shift toward lifecycle regulation reveals not simply an agency in transition, but rather an agency on guard against a set of larger political threats to its mandate. This can be characterized as a state of institutional incumbency in which the agency is engaged in an effort to reproduce key features of the regulatory system-in concert with regulated industries and others-while simultaneously sanctioning significant changes to the regulatory standards the FDA has long applied, to the detriment of public health.

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 imitation

Not 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.

metaresearch head score (Codex)0.038
metaresearch head score (Gemma)0.070
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.202

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.070
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0170.025
Scholarly communication0.0140.013
Open science0.0020.006
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0030.000

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 head0.013
GPT teacher head0.290
Teacher spread0.278 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations42
Published2019
Admission routes2
Has abstractyes

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