Molecularly Imprinted Polymer Nanoparticles: An Emerging Versatile Platform for Cancer Therapy
Bibliographic record
Abstract
Molecularly imprinted polymers (MIPs) are chemically synthesized affinity materials with tailor-made binding cavities complementary to the template molecules in shape, size, and functionality. Recently, engineering MIP-based nanomedicines to improve cancer therapy has become a rapidly growing field and future research direction. Because of the unique properties and functions of MIPs, MIP-based nanoparticles (nanoMIPs) are not only alternatives to current nanomaterials for cancer therapy, but also hold the potential to fill gaps associated with biological ligand-based nanomedicines, such as immunogenicity, stability, applicability, and economic viability. Here, we survey recent advances in the design and fabrication of nanoMIPs for cancer therapy and highlight their distinct features. In addition, how to use these features to achieve desired performance, including extended circulation, active targeting, controlled drug release and anti-tumor efficacy, is discussed and summarized. We expect that this minireview will inspire more advanced studies in MIP-based nanomedicines for cancer therapy.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".