Abstract 827: Comparative study of calcein encapsulation into nanoparticles using three different micromixers as a model for small drug molecules
Bibliographic record
Abstract
Abstract Background: Liposomes are spherical vesicles made of a lipid bilayer and are effective nanocarriers for drug molecules such as chemotherapeutic agents. Micromixers are devices that allow consistent liposome production while more efficiently controlling their characteristics (size, size distribution (PDI), and zeta potential) than traditional methods. They provide more scalable production and the ability to control variables such as the total flow rate (TFR) that shape the liposomes’ characteristics. Periodic Disturbance Mixer (PDM), Staggered Herringbone Mixer (SHM) and ring micromixer microchannel designs increase the mixing rate and nanoprecipitation. The objective of this study is to compare, between the 3 different micromixer designs, the encapsulation efficiency of calcein and the physicochemical properties of the liposomes. Calcein was chosen due to its similarity in size and fluorescent activity to Doxorubicin, a drug used to treat various forms of cancer. Methods: The devices were designed on SOLIDWORKS 2022, 3D-printed with the Pr110-385 3D printer using photopolymer resin, cleaned and cured. Lipids (DSPC, CHOL and PEG-PE) diluted in ethanol in a consistent molar ratio were injected in one inlet, while PBS 1x with diluted calcein (3 mM) was injected in the other. Flow conditions were set using computer-controlled syringe pumps. The samples including the liposomes were collected at the outlet and centrifugal filtration was performed to remove un-encapsulated calcein. To calculate the encapsulation efficiency, the fluorescence emitted by calcein was used to determine its concentration. Fluorescence was measured using the Qubit 4 Fluorometer. Liposome hydrodynamic diameter, PDI and zeta potential were determined by dynamic light scattering. Empty liposomes were also made to see if there were significant differences in their properties compared to calcein-carrying ones. Results: The PDM, SHM and ring-micromixer were printed to yield to the smallest channel widths possible: 450um, 600um and 280um respectively. All three mixers produced empty and loaded liposomes of a controlled size, proven by the low PDI value of all the samples (PDI<0.2). The mixer’s design did not affect the liposomes’ zeta potential. The PDM, SHM and ring micromixer produced increasingly larger liposomes (loaded). The ring micromixer had the highest encapsulation efficiency, the SHM and PDM were slightly less efficient. Interestingly, the ring micromixer and SHM were most efficient at a higher flow rate (120 ml/h), whereas the PDM encapsulated calcein most efficiently at a lower flow rate (30 ml/h). Conclusions: The three 3D-printed devices tested in this study yielded liposomes of controlled sizes with the PDM making the smallest ones. Additionally, all were successful in encapsulating calcein, but required different flow rate conditions to operate most efficiently. Determining the optimal conditions for encapsulation has major implications in designing new lipid nanoparticle carriers for therapeutics. Citation Format: Armen Erzingatzian, Rubén R. López, Chaymaa Zouggari, Vahé Nerguizian, Julia V. Burnier. Comparative study of calcein encapsulation into nanoparticles using three different micromixers as a model for small drug molecules [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 827.
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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) | 0.000 | 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) | 0.001 | 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 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".