Development and optimization of Benjakul microemulsion formulations for enhancing topical anti-inflammatory effect and delivery
Bibliographic record
Abstract
Background and purpose: Benjakul (BJK) is a combination of five botanical herbal constituents widely used in Thai traditional medicine as an anti-inflammatory remedy. This study aimed to develop a novel topical microemulsion containing BJK for clinical use. Experimental approach: The microemulsions were produced by a phase inversion temperature (PIT) methodology. Physicochemical properties and stability were evaluated to determine an optimal formula. The stable BJK-loaded microemulsion formulas were then subjected to in vitro studies for their anti-inflammatory activity, skin cell toxicity, drug permeation, and stability. Finding/Results: Two novel formulations containing isopropyl myristate (ME1-BJK and ME2-BJK) passed the compendial stability test. BJK constituents were completely dissolved in the oil phase and incorporated into the microemulsion base Transcutol® and Labrasol® avoiding the use of alcohol, both microemulsion formulations demonstrated high anti-inflammatory activity with IC 50 values of 3.41 ± 0.36 and 3.95 ± 1.73 μg/mL, respectively. However, dissolution of ME1-BJK showed a superior release profile through both lipophilic and hydrophilic membranes with the highest accumulated amount at 4 h of 25.13% and 38.06%, respectively. All tested formulations of BJK extract demonstrated no apparent skin cell toxicity at concentrations up to 50 μg/mL. After six-month storage under accelerated conditions, there were no significant changes in anti-inflammatory activity. Conclusions and implications: A novel and stable BJK-loaded microemulsion formulation was successfully developed with excellent release and stability properties. Further clinical research to evaluate pain reduction, edema, and skin irritation using this formulation in animal models is ongoing.
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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 | 0.005 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".