Simplex Lattice Design and Machine Learning Methods for the Optimization of Novel Microemulsion Systems to Enhance
Nayera Nasser1, Rania M Hathout2, Hend Abd-Allah1
1Department of Pharmaceutics and Industrial Pharmacy, Faculty of Pharmacy, Ain Shams University, African Union Organization St., Cairo, 11566, Egypt.
AAPS Pharmscitech
|March 6, 2024
Summary
Novel microemulsion systems significantly improved p-coumaric acid (PCA) absorption and bioavailability. These optimized formulations demonstrated enhanced cytotoxicity against cancer cells and superior in vivo performance compared to PCA suspension.
Area of Science:
- Pharmaceutical Sciences
- Drug Delivery Systems
- Nanotechnology
Background:
- P-coumaric acid (PCA) exhibits promising anti-cancer properties but suffers from poor absorption and bioavailability.
- Developing effective delivery systems is crucial to harness PCA's therapeutic potential.
Purpose of the Study:
- To develop and optimize novel microemulsion systems for p-coumaric acid (PCA).
- To enhance the absorption, bioavailability, and anti-cancer efficacy of PCA.
Main Methods:
- Simplex-lattice mixture design and machine learning were used for formulation optimization.
- In vitro characterization included re-dispersibility and cytotoxicity assays on MCF-7, CaCo2, and HepG2 cell lines.
- In vivo bioavailability studies compared microemulsions to PCA suspension.
Main Results:
- Two stable, optimized microemulsions with ~10 nm droplet size were successfully developed.
- Microemulsions significantly improved PCA re-dispersibility and exhibited 1.5-1.8 times higher bioavailability than suspension.
- Formulations showed markedly enhanced cytotoxicity against tested cancer cell lines.
Conclusions:
- Developed p-coumaric acid microemulsion systems offer a promising approach to overcome bioavailability challenges.
- These novel systems demonstrate potential as effective therapeutic agents for various cancers.
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