Design and optimization of a microfluidic system for the production of protein drug loadable and magnetically targetable biodegradable microspheres
Bibliographic record
Abstract
The overall goal of this dissertation was to develop a microfluidic system for the production of magnetic and non-magnetic drug-loaded polymer microspheres with narrow size distribution. The size of microspheres is a crucial parameter for their application, as the rate of drug release from the microspheres, the rate of microsphere degradation, and the microsphere biodistribution all correlate with particle size and size distribution. Conventional microsphere production methods generally lead to the formation of particles with broad size distribution. In this work, the conventional emulsification-evaporation method for the production of microspheres was miniaturized into microfluidic flow focusing system. Using a self-designed flow focusing chip, quasi-monodisperse poly (lactic acid) microspheres were prepared. The spherical shape and narrow size distribution of the initial polymer-chloroform droplets generated at the orifice were retained throughout their movement in the channels. After complete solvent removal, the droplets turned into quasi-monosized microspheres with a coefficient of variation between 2% and 16%. To better understand the influence of different parameters on droplet generation, the behavior of the disperse phase and the continuous phase were simulated in a 3D computational multiphase droplet generation model. The experimentally determined droplet sizes correlated well with the computational model and never digressed more than 17% from the simulations. The flow focusing system was then also used directly, for the first time, to produce superparamagnetic microspheres containing 15% magnetic nanoparticles. The microspheres’ thermal properties showed their suitability for magnetic hyperthermia of large tumors in cancer therapy. The microfluidic chip was then further altered into a novel device that is able to encapsulate proteins into the polymer microspheres by integrating flow focusing and passive droplet break up systems into one-chip which contained sections of differing surface properties. With this design, bovine serum albumin-loaded microspheres could be prepared with a protein encapsulation efficiency of up to 96%. The work presented in this dissertation is the first to show that a microfluidic system can be used for the continuous production of quasi-monodisperse magnetic microspheres and protein-drug-loaded polymer microspheres. These microspheres will be useful in hyperthermia treatment, diagnostic imaging, and the targeted and controlled delivery of protein based drugs.
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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".