Animal‐to‐Human Dose Translation of ANTHRASIL for Treatment of Inhalational Anthrax in Healthy Adults, Obese Adults, and Pediatric Subjects
Bibliographic record
Abstract
Anthrax Immune Globulin Intravenous (AIGIV [ANTHRASIL]), was developed for the treatment of toxemia associated with inhalational anthrax. It is a plasma product collected from individuals vaccinated with anthrax vaccine and contains antitoxin IgG antibodies against Bacillus anthracis protective antigen. A pharmacokinetic (PK) and exposure-response model was constructed to assess the PKs of AIGIV in anthrax-free and anthrax-exposed rabbits, non-human primates and anthrax-free humans, as well as the relationship between AIGIV exposure and survival from anthrax, based on available preclinical/clinical studies. The potential effect of anthrax on the PKs of AIGIV was evaluated and estimates of survival odds following administration of AIGIV protective doses with and without antibiotic co-treatment were established. As the developed PK model can simulate exposure of AIGIV in any species for any dosing scenario, the relationship between the predicted area under the concentration curve of AIGIV in humans and the probability of survival observed in preclinical studies was explored. Based on the simulation results, the intravenous administration of 420 U (units of potency as measured by validated Toxin Neutralization Assay) of AIGIV is expected to result in a > 80% probability of survival in more than 90% of the human population. Additional simulations suggest that exposure levels were similar in healthy and obese humans, and exposure in pediatrics is expected to be up to approximately seven-fold higher than in healthy adults, allowing for doses in pediatric populations that ranged from one to seven vials. Overall, the optimal human dose was justified based on the PK/pharmacodynamic (PD) properties of AIGIV in animals and model-based translation of PK/PD to predict human exposure and efficacy.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".