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Record W4394722965 · doi:10.3389/ftox.2024.1353783

ICH S1 prospective evaluation study: weight of evidence approach to predict outcome and value of 2-year rat carcinogenicity studies. A report from the regulatory authorities subgroup

2024· article· en· W4394722965 on OpenAlexaff
Todd Bourcier, Timothy J. McGovern, Tania Cavaliero, Geoffrey Ebere, Akiyoshi Nishikawa, Jihei Nishimura, Kumiko Ogawa, Markku Pasanen, Alisa Vespa, Jan Willem van der Laan

Bibliographic record

VenueFrontiers in Toxicology · 2024
Typearticle
Languageen
FieldMedicine
TopicScience, Research, and Medicine
Canadian institutionsHealth Canada
Fundersnot available
KeywordsMedicineGuidelineProspective cohort studyCarcinogenPharmacologyInternal medicinePathologyBiologyGenetics

Abstract

fetched live from OpenAlex

Introduction: The International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) initiated a process in 2012 to revise the S1B Guideline “Testing for Carcinogenicity of Pharmaceuticals”. Previous retrospective analysis indicated the importance of histopathological risk factors in chronic toxicity studies, evidence of endocrine perturbation, and positive genetic toxicology results as potentially predictive indicators of carcinogenic risk. In addition, a relationship between pharmacodynamic activity and carcinogenicity outcome in long-term rodent studies has been reported. It was postulated that these factors could be evaluated in a Weight-of-Evidence (WoE) approach to predict the outcome of a 2-year rat study. Methods: The ICH S1B(R1) Expert Working Group (EWG) conducted a Prospective Evaluation Study (PES) to determine the regulatory feasibility of this WoE approach. Drug Regulatory Authorities (DRAs) evaluated 49 Carcinogenicity Assessment Documents (CADs), which describe the WoE for submitted pharmaceutical compounds. Each compound was categorized into a carcinogenic risk category including a statement of the value of the 2-year rat study. The outcome of the completed 2-year rat studies was evaluated in relation to the prospective CAD to determine the accuracy of predictions. Results: Based on the results of the PES, the EWG concluded that the evaluation process for assessing human carcinogenic risk of pharmaceuticals described in ICH S1B could be expanded to include a WoE approach. Approximately 27% of 2-year rat studies could be avoided in cases where DRAs and sponsors unanimously agreed that such a study would not add value. Discussion: Key factors supporting a WoE assessment were identified: data that inform carcinogenic potential based on drug target biology and the primary pharmacologic mechanism of the parent compound and major human metabolites; results from secondary pharmacology screens for this compound and major human metabolites that inform carcinogenic risk; histopathology data from repeated-dose toxicity studies; evidence for hormonal perturbation; genotoxicity data; and evidence of immune modulation. The outcome of the PES indicates that a WoE approach can be used in place of conducting a 2-year rat study for some pharmaceuticals. These data were used by the ICH S1B(R1) EWG to write the R1 Addendum to the S1B Guideline published in August 2022.

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)0.340
metaresearch head score (Gemma)0.340
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.660
Threshold uncertainty score0.814

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3400.340
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0070.022
Bibliometrics0.0130.008
Science and technology studies0.0010.002
Scholarly communication0.0070.003
Open science0.0050.005
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0040.001

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 head0.137
GPT teacher head0.409
Teacher spread0.272 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designObservational
DomainMethods
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

Citations10
Published2024
Admission routes1
Has abstractyes

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