Pre-clinical study of IRDye800CW-nimotuzumab formulation, stability, pharmacokinetics, and safety
Bibliographic record
Abstract
Abstract Background Epidermal growth factor receptor (EGFR) is a target for cancer therapy as it is overexpressed in a wide variety of cancers. Therapeutic antibodies that bind EGFR are being evaluated in clinical trials as imaging agents for positron emission tomography and image-guided surgery. However, some of these antibodies have safety concerns such as infusion reactions, limiting their use in imaging applications. Nimotuzumab is a therapeutic monoclonal antibody that is specific for EGFR and has been used as a therapy in a number of countries. Methods Formulation of IRDye800CW-nimotuzumab for a clinical trial application was prepared. The physical, chemical, and pharmaceutical properties were tested to develop the specifications to determine stability of the product. The acute and delayed toxicities were tested and IRDye800CW-nimotuzumab was determined to be non-toxic. Non-compartmental pharmacokinetics analysis was used to determine the half-life of IRDye800CW-nimotuzumab. Results IRDye800CW-nimotuzumab was determined to be non-toxic from the acute and delayed toxicity study. The half-life of IRDye800CW-nimotuzumab was determined to be 38 ± 1.5 h. A bi-exponential analysis was also used which gave a t1/2 alpha of 1.5 h and t1/2 beta of 40.8 h. Conclusions Here, we show preclinical studies demonstrating that nimotuzumab conjugated to IRDye800CW is safe and does not exhibit toxicities commonly associated with EGFR targeting antibodies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".