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Record W4401691029 · doi:10.18609/cgti.2024.052

Clinical trial applications for investigational medicinal products that contain or consist of genetically modified organisms: industry experiences under the European Union Clinical Trial Regulation (536/2014)

2024· article· en· W4401691029 on OpenAlexaboutno aff
Stuart G. Beattie, Nathalie Lambot, Jacquelyn Awigena-Cook, Martin O’Kane, Caroline Correas, Ine de Goeij, Julien Romanetto, Annelie Persson, Pär Tellner

Bibliographic record

VenueCell and Gene Therapy Insights · 2024
Typearticle
Languageen
FieldMedicine
TopicBiomedical Ethics and Regulation
Canadian institutionsnot available
Fundersnot available
KeywordsEuropean unionClinical trialMedicineGenetically modified organismBusinessBiotechnologyBiologyInternational tradeInternal medicineGenetics

Abstract

fetched live from OpenAlex

The survey reported upon here provides an up to date understanding of industry experiences submitting national GMO applications since the CTR has been in application (January 31, 2022). The survey shows how time- and resource-intensive applications seeking authorizations for use of investigational medicinal products that contain or consist of genetically modified organisms (GMO-IMPs) to EU Member States continue to represent a significant challenge for developers. EU Member State GMO competent authorities presently apply differing interpretations of the European Commission Directives for Deliberate Release of GMOs and/or the Contained Use of GMOs. Survey feedback highlights how varied the different EU Member State GMO competent authority procedures and assessment timeframes are, with differences in adaptation to the timelines dictated by the Clinical Trial Regulation (CTR). Lengthy and uncertain timelines associated with EU Member State GMO competent authority procedures were indicated to have led sponsors to have looked to other regions (USA, Canada, and Australia) to host clinical trials with GMO-IMPs. The benefits of a single clinical trial application submission under the CTR are considerably diminished due to different national GMO procedural and documentation requirements and a lack of formal alignment of timelines between CTA and GMO procedures. EFPIA welcome the proposed improvements for regulation of GMO medicines through revision of the EU General Pharmaceutical Legislation.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.558
Threshold uncertainty score0.842

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.191
GPT teacher head0.399
Teacher spread0.208 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
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

Citations0
Published2024
Admission routes1
Has abstractyes

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