Controlling Structure and Function of Polymeric Drug Delivery Nanoparticles Using Microfluidics
Bibliographic record
Abstract
We demonstrate control of multiscale structure and drug delivery function for paclitaxel (PAX)-loaded polycaprolactone-block-poly(ethylene oxide) (PCL-b-PEO) polymeric nanoparticles (PNPs) via synthesis and flow-directed shear processing in a two-phase gas-liquid microfluidic reactor. This strategy takes a page from the engineering of commodity plastics, where processing rather than polymer chemistry provides an experimental handle on properties and function. PNPs formed from copolymers with three different PCL block lengths show sizes, morphologies, and loading efficiencies that depend on both the PCL block length and the microfluidic flow rate. By varying flow rate and comparing with a conventional bulk method of PNP preparation, we show that flow-variable shear processing provides control of PNP sizes and morphologies and enables slower PAX release times (up to 2 weeks) compared to bulk-prepared PNPs. Antiproliferative effects against cultured MCF-7 breast cancer cells were greatest for PNPs formed at an intermediate flow rate, corresponding to small and low-polydispersity spheres formed uniquely at this flow condition. Formation and flow-directed nanoscale shear processing in gas-liquid microfluidic reactors provides a manufacturing platform for drug delivery PNPs that could enable more effective and selective nanomedicines through multiscale structural control.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".