Antifungal Efficacy Data for Essential Oil Hydrogels via Monte Carlo Simulation

Adeola Tawakalitu Kola-Mustapha authored this research document on figshare, last updated in April 2026. It details the formulation and testing of clove and lemongrass essential oil hydrogels against Candida albicans. The study includes results from antifungal assays and computational analysis via 10,000 Monte Carlo simulations.

Use Cases

• Analyze Minimum Inhibitory Concentration (MIC) and Minimum Fungicidal Concentration (MFC) values for clove and lemongrass oils against 15 C. albicans isolates.
• Model the synergistic or additive antifungal effects using the Fractional Inhibitory Concentration Index (ΣFIC) data provided for isolate combinations.
• Evaluate the physicochemical and stability properties of hydrogel formulations containing 3% w/w essential oils in a 2:1 ratio.
• Reproduce or validate the Monte Carlo simulation results quantifying the enhanced inhibition from combined essential oils.
• Compare the agar well diffusion method results for different hydrogel formulations to identify the most effective antifungal candidate.

Strengths

• Includes computational validation via 10,000 Monte Carlo simulation runs.
• Tests antifungal efficacy against a standard strain and 14 clinical isolates of Candida albicans.
• Reports specific quantitative metrics: MIC of 100 μL/mL, MFC of 100-200 μL/mL, and a ΣFIC value of 0.75 indicating additive effects.

Limitations

• The dataset is a single 751.3 KB DOCX file, presenting limited scope as a research document rather than a raw data table.
• Sample size for biological testing is limited to 15 Candida albicans isolates.
• No raw, machine-readable data columns or sample rows are provided for direct computational analysis.

Provenance

Source

Adeola Tawakalitu Kola-Mustapha via figshare.

Collection Method

Experimental laboratory assays (macro and checkerboard dilution, agar well diffusion) and computational Monte Carlo simulation.

Freshness

Last updated on 2026-04-07.