Development of the ICH Guidelines for Immunotoxicology Evaluation of Pharmaceuticals Using a Survey of Industry Practices
Bibliographic record
Abstract
An anonymous survey of pharmaceutical industry practices for immunotoxicology evaluation was conducted. This was in support of the development of the guideline on the preclinical evaluation of unintended modulation of the immune system for the International Conference on Harmonization of Technical Requirements for Registration of Pharmaceuticals for Human Use. The survey was conducted in two phases in 2003 and 2004. A total of 64 responses were received of which 45 were included in the formal evaluation. The remaining compounds were excluded because they were cytotoxic anti-neoplastic drugs (N = 7), or due to insufficient information (N = 12). The purpose of the survey was to gather data on the correlation between routine toxicology studies (RTS) and additional immunotoxicological studies (AIS). The results of the survey were evaluated by the Expert Working Group (EWG) and classified as to positive or negative findings in RTS and AIS. The results of the survey showed that for 27 of 45 compounds (60%), the RTS and AIS endpoints were in agreement. In 12 of 45 cases (27%), the RTS endpoints showed immune modulation not observed in the AIS assays. Finally for 6 of 45 drugs (13%) a response was seen with the AIS methods where no significant effect was observed in the RTS endpoints. Length of dosing and the number of tests evaluated were similar in all groups. The groups where RTS detected signs of immunosuppression were more likely to have been dosed at or above MTD. This data contributed to the consensus in the EWG that routine immune function testing as an initial screen for all new drugs is not required. Instead, a weight-of-evidence approach including RTS and other causes for concern is recommended to identify the need for additional immunotoxicity studies.
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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 | 0.096 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
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".