Simulation-Based Software Modeling of CAR T Cell Therapy Efficacy Against Solid Malignant Tumors
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Genetically engineered T cells with Chimeric Antigen Receptors, CAR T cells, are a revolutionary immunotherapy used to treat advanced blood cancers. The purpose of this experiment was to model the destruction process of tumor cells with CAR T cell therapy using Complexity and Organized Behaviour Within Environmental Bounds (COBWEB), an agent-based simulation software. We designated parameter values for abiotic factors, agents (i.e. tumor cells, T cells) and the general environment in our immunotherapy simulation model to illustrate the interactions between tumor cells and cytotoxic components, which described the binding of innate CD8+ T cells or CAR T cells to tumor antigens. The models were used to observe and comparatively analyze the rate of destruction of a solid tumor by CAR T cells and innate CD8+ T cells. The solid tumor developed in a circular island for 60 ticks, representing days; innate CD8+ or CAR T cells were then able to infiltrate the island and the tumor cell population was monitored over 500 days. The CAR T cells exhibited a significantly powerful, efficient immune response against a general solid tumor relative to the innate CD8+ T cells, yet relapse occurred in both models albeit to a lesser extent with CAR T cells. However, further investigations are required to adequately simulate the side effects and realistically-limiting factors of CAR T cell therapy. Similar comparative analyses may help measure and compare the potency of the immune response of CAR T cells compared to standard, or lack of, treatments.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it