Society of Toxicologic Pathology Neuropathology Interest Group Article: Neuropathologic Findings in Nonhuman Primates Associated With Administration of Biomolecule-Based Test Articles
Bibliographic record
Abstract
The increasing specificity of novel druggable targets coupled with the complexity of emerging therapeutic modalities for treating human diseases has created a growing need for nonhuman primates (NHPs) as models for translational drug discovery and nonclinical safety assessment. In particular, NHPs are critical for investigating potential unexpected/undesired on-target and off-target liabilities associated with administration of candidate biotherapeutics (nucleic acids, proteins, viral gene therapy vectors, etc.) to treat nervous system disorders. Nervous system findings unique to or overrepresented in NHPs administered biomolecule-based ("biologic") test articles include mononuclear cell infiltration in most neural tissues for all biomolecule classes as well as neuronal necrosis with glial cell proliferation in sensory ganglia for certain viral vectors. Such test article-related findings in NHPs often must be differentiated from procedural effects (e.g., local parenchymal or meningeal reactions associated with an injection site or implanted catheter to administer a test article directly into the central nervous system) or spontaneous background findings (e.g., neuronal autophagy in sensory ganglia).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.005 |
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".