Evolution of nanomedicines for the treatment of autoimmune disease: From vehicles for drug delivery to inducers of bystander immunoregulation
Bibliographic record
Abstract
Over the last two decades, the nanomedicine field has witnessed an explosive growth of research on the development of nanoparticle/microparticle (NP/MP)-based compounds for the treatment of autoimmune diseases. Studies have evaluated compounds generated with a broad range of materials with different shapes, sizes, surface chemistries and structures. A number of active pharmaceutical ingredients, including immunosuppressants, cytokines, nucleotides, peptides, proteins and immunomodulators of various types have been encapsulated into or incorporated onto the surface of these compounds, either individually or in combination, and delivered to animal models of autoimmune inflammation via different administration routes. These NP/MP-based compounds can be categorized into four different groups based on their intended mechanisms of action. Here, we review the engineering designs, the pharmacodynamic and therapeutic correlates and the disease specificity of nanomedicines belonging to each of these groups.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".