Eco – Pharmaceutical Design of a Helianthus Annuus Nanoemulcream: A QbD Optimization Strategy

Eco – Pharmaceutical Design of a Helianthus Annuus Nanoemulcream: A QbD Optimization Strategy | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Eco – Pharmaceutical Design of a Helianthus Annuus Nanoemulcream: A QbD Optimization Strategy Koushik Yetukuri, Mohammad Barakathulla, Morla Siva Prasad, Rama Rao Nadendla This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8291953/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose This study aimed to develop an eco-pharmaceutical Helianthus Annuus (sunflower) oil nanoemulcream using a Quality-by-Design approach integrated with a Central Composite Design to optimize formulation and process variables for improved stability, skin compatibility, and therapeutic performance. Method Sunflower oil was characterized using GC–MS and ATR–FTIR analyses. Nanoemulsions were prepared by high-speed homogenization, and key factors surfactant concentration, homogenization speed, and time were optimized using CCD to minimize particle size. The optimized nanoemulcream was evaluated for physicochemical properties, droplet size, PDI, zeta potential, morphology (SEM), stability, skin irritation, antibacterial activity, in-vitro drug release, and release kinetics. Results The developed nanoemulsion exhibited a mean droplet size of 134.7 ± 34.1 nm, Z-average 166.9 nm, PDI 0.409, and zeta potential − 30.1 ± 2.3 mV, confirming uniform dispersion and electrostatic stability. The nanoemulcream showed suitable pH (6.2 ± 0.1), viscosity (28,500 ± 120 cP), spreadability (12.5 ± 0.5 g·s⁻¹), high drug content (94.2 ± 1.8%), and maintained stability over three months. In-vitro release studies (360 min) demonstrated superior drug release from the nanoemulsion (88%), followed by the nanoemulcream (64.8%), cream with sunflower oil (49%), and plain sunflower oil (30%). Kinetic modeling indicated diffusion-controlled and anomalous transport mechanisms, supported by Korsmeyer–Peppas n values between 0.45–0.89. The formulation was non-irritant in skin studies and showed moderate broad-spectrum antibacterial activity (MIC 110–140 µg/mL). Conclusion The QbD-guided development enabled a stable, skin-compatible, and therapeutically effective sunflower oil nanoemulcream. Enhanced release and controlled kinetics highlight its potential as a sustainable topical delivery system for natural bioactives. Drug Discovery, Design, & Development Antibacterial activity Central Composite Design (CCD) eco-pharmaceutical formulation Helianthus annuus nanoemulcream Quality by Design (QbD) sunflower oil topical drug delivery. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Introduction The increasing focus on eco-pharmaceutical innovation drives the development of sustainable drug delivery systems integrating natural bioactives with advanced formulations. Sunflower oil ( Helianthus annuus ), a renewable and biocompatible resource rich in polyunsaturated fatty acids, tocopherols, and phytosterols, possesses broad therapeutic potential due to its antioxidative and anti-inflammatory and emollient properties [ 1 ]. However, its direct use is characterized by low aqueous solubility, oxidative instability, and low dermal bioavailability. Nanotechnology enables the development of advanced topical systems with improved performance. Nanoemulsions (20–200 nm) enhance solubility, stability, and dermal penetration of lipophilic actives, while their incorporation into semisolid bases forms nanoemulcream’s that combine enhanced permeation with stability and patient acceptability [ 2 ]. Following the QbD approach, formulation development begins with defining the QTPP and identifying CQAs such as droplet size, PDI, zeta potential, viscosity, and spreadability. Risk assessment tools like FMEA and Ishikawa diagrams are used to establish CMAs and CPPs [ 3 ]. A DoE framework using CCD allows efficient optimization of formulation variables, revealing both linear and quadratic effects. In H. annuus nanoemulsions, CCD aids in optimizing oil concentration, S/Cos ratio, and homogenization speed to achieve stability and bioavailability [ 4 ]. High-speed homogenization further supports scalability and sustainability by generating nanosized droplets through mechanical shear with minimal solvent and energy use [ 5 ]. This study integrates QbD with nanotechnology to establish a sustainable strategy for a sunflower oil-based nanoemulcream. Systematic optimization via CCD produced a formulation with enhanced solubilization, dermal permeation, antimicrobial activity, stability, and patient acceptability, providing a reproducible, scalable, and environmentally conscious platform for next-generation topical formulations [ 6 ]. Materials & Methods Materials Sunflower oil ( Helianthus annuus ) was procured from a local vendor in India. Tween 80 and Polyethylene Glycol 400 (PEG 400) were obtained from Loba Chemie Pvt. Ltd. (Mumbai, India). Lanolin was purchased from Fisher Scientific, India. The remaining excipients—Stearic acid, Cetyl alcohol, Propylene glycol, and Potassium hydroxide (KOH)—were also supplied by Loba Chemie Pvt. Ltd. HPLC-grade water was supplied by Thermo Fisher Scientific Pvt. Ltd. (Qualigens), India. Analytical-grade chemicals were employed as obtained from the suppliers. Methods Characterization Studies GC–MS Characterization The compositional profile of sunflower oil was determined using a GC–MS system (Model GCMS-QP2010, Shimadzu, Japan) equipped with an HP-5MS column (30 m × 0.25 mm × 0.25 µm). About 1 µl of oil was injected in splitless mode, with helium served as the carrier gas at a specified flow rate of 1.0 mL/min. The oven temperature was scheduled to ramp from 60°C (2 min) to 280°C at 10°C/min, and maintained for 10 minutes. The injector and detector temperatures were maintained at 250°C and 280°C, respectively. Mass spectra were recorded in electron impact mode (70 eV) over a 50–550 m/z range. Compounds were confirmed through spectral comparison with the NIST reference library. [ 7 ]. ATR–FTIR Spectroscopy Attenuated Total Reflectance–Fourier Transform Infrared (ATR–FTIR) spectroscopy of sunflower oil, Nanoemulsion and the developed nanoemulcream were recorded using a Bruker Alpha II spectrophotometer (Germany). Samples were positioned on the ATR crystal, and spectra were recorded over the range of 4000–400 cm⁻¹ with a resolution of 4 cm⁻¹, averaging 32 scans. [ 8 ]. DSC Analysis Thermal Characterization of crude oil and optimized nanoemulcream was performed using DSC (TA Instruments, USA). Samples (5–10 mg) were sealed in aluminium pans and analyzed under nitrogen (50 mL/min). Heating ranged from 30–300°C at 10°C/min. Thermograms recorded endothermic transitions and degradation peaks to evaluate compatibility and physical stability [ 9 ]. Preparation of Nanoemulcream Formulation The sunflower oil-based nanoemulsion was prepared using high-speed homogenization [ 10 ]. Crude Helianthus annuus oil was mixed with a surfactant/co-surfactant blend of Tween 80 and PEG 400. Deionized water was added dropwise under continuously stirred to obtain a coarse emulsion, which was subsequently processed using high-speed homogenizer using a Digital Ultra-Turrax® T25 (IKA, Germany) to yield a stable oil-in-water nanoemulsion. The resulting nanoemulsion was subsequently incorporated into a cream base to form the nanoemulcream [ 11 , 12 & 13 ]. The oil phase (lanolin, stearic acid, Cetyl alcohol, and the nanoemulsion) and the aqueous phase (propylene glycol, potassium hydroxide, and deionized water) were heated separately to the same appropriate temperature. The aqueous phase was slowly added to the oil phase with continuous stirring followed by homogenization to achieve a uniform cream consistency. The finished formulation was cooled to room temperature and transferred into airtight containers for evaluation. Quality by Design (QbD) Approach The QbD framework guided the systematic, risk-based development of the sunflower oil nanoemulcream [ 3 , 14 ]. The QTPP outlined key formulation characteristics such as dosage form, administration route, strength, pH, appearance, rheological behaviour, and microbiological stability. Based on the QTPP and prior knowledge, CQAs were identified, such as droplet size, zeta potential, pH, viscosity, spreadability, morphology, texture, and washability. Droplet size and zeta potential were emphasized as critical for nanoemulsion stability. Risk assessment utilized an Ishikawa (fishbone) diagram and a REM to categorize and rank formulation and process risks. This process led to the identification of CMAs and CPPs for optimization, while other less impactful parameters were controlled or fixed, ensuring robust formulation development. Optimization of Sunflower Oil Nanoemulcream via DoE DoE-Based Optimization via CCD A CCD with 16 runs and a three-factor, three-level scheme was executed using JMP software (v17.0.0; SAS Institute Inc., Cary, NC, USA). The design enabled evaluation of quadratic response surfaces and development of second-order models to assess main, interaction, and quadratic effects, incorporating factorial, axial, and central points for robustness [ 15 ]. The general polynomial equation generated from the design is expressed as: Y = S 0 + S 1 X 1 +S 2 X 2 +S 3 X 3 +S 4 X 1 X 2 +S 5 X 1 X 3 +S 6 X 2 X 3 +S 7 X 1 2 +S 8 X 2 2 +S 9 X 3 2 where Y represents the response, S₀ denotes the intercept (mean of all runs), S₁–S₉ are regression coefficients, X₁, X₂ , and X₃ represent independent variables, X₁X₂, X₁X₃ , and X₂X₃ indicate interaction terms, and X₁², X₂², X₃² represent quadratic effects. In the present study, the independent variables were the concentration of Tween 80 and PEG 400 (X₁), homogenization time (X₂), and homogenization speed (X₃), with coded levels of − 1 and + 1 representing low and high values, respectively. The response variable (Y₁) was droplet size of the nanoemulsion, determined for all 16 formulations were incorporated into the design model to assess the effects of the independent factors. Optimization was carried out using the Prediction Profiler tool in JMP to identify the best factor settings for minimizing particle size, thereby ensuring formulation stability. [ 16 ] Evaluation of Sunflower Oil Nanoemulcream Physicochemical and Performance Evaluation 1. Physicochemical Characterization The pH of the nanoemulcream was measured at room temperature using a calibrated digital pH meter (Deluxe Model 101, India), standardized with pH 4.01, 7.00, and 10.01 buffers. Approximately 1 g of formulation was dispersed in distilled water, and measurements were performed in triplicate, 24 hours post-preparation. Formulation viscosity was assessed using a Brookfield viscometer (DV II + Pro) with spindle S-64 at 20 rpm and 25°C. Homogeneity and phase separation were evaluated visually and tactilely over 24 hours, while organoleptic properties, including color, odor, and texture, were assessed by observation and application [ 17 , 4 ]. 2. Performance and Application Properties Spreadability was assessed by placing a fixed cream amount between glass slides and measuring the time for the upper slide to move underweight. Washability was tested by rinsing a controlled amount applied to the skin, and after-feel was evaluated by assessing emollience, residue, and slipperiness post-application [ 17 , 18 ]. 3. Particle Size and Zeta Potential Droplet size distribution and zeta potential were measured using Dynamic light scattering (Malvern Zetasizer Nano ZS90, UK). Samples were diluted 1:100 (v/v) in deionized water to reduce multiple scattering. Particle size was reported as Z-average diameter, and zeta potential assessed colloidal stability. Analyses were performed in triplicate [ 19 ]. 4. Safety and Stability Studies Irritancy testing involved applying the formulation to a 1 cm² dorsal hand area and observing for erythema, edema, or irritation over 24 hours; no reactions were observed [ 18 ]. Accelerated stability studies were conducted under room temperature and accelerated conditions (40 ± 2°C / 75 ± 5% RH) for three months., with evaluations at 0, 1, 2, and 3 months, following ICH guidelines [ 20 ]. 5. Drug Content Determination A 1 g sample of nanoemulcream was dissolved in 10 mL ethanol, stirred, filtered, and diluted. Absorbance at 273 nm was recorded using a Systronics Double Beam Spectrophotometer (2202) with ethanol as blank, and the drug content was determined. [ 22 ]. $$\:Drug\:content\:\%=\:\:\left(\frac{Analyzed\:content}{Theoretical\:content}\right)\times\:100$$ In Vitro Drug Release and Kinetic Analysis The release of the drug from the cream formulation was analyzed using a USP Type II (paddle) dissolution apparatus at 37 ± 0.5°C with constant stirring. Aliquots were withdrawn at predetermined intervals, filtered, and replaced with fresh medium to maintain sink conditions. Drug content was quantified using a validated UV–Vis spectrophotometric method at the drug’s absorption maximum (λmax determined from 200–400 nm scan). Calibration curves were prepared, and samples were analyzed in triplicate. Cumulative release data were fitted to kinetic models (zero-order, first-order, Higuchi, Korsmeyer–Peppas, and Hixson–Crowell) to determine release rate constants and elucidate the pathway of drug release.[ 23 ] Antimicrobial Activity The antimicrobial efficacy of the sunflower oil nanoemulcream was assessed by determining its MIC against Staphylococcus aureus , Bacillus subtilis , Escherichia coli , and Pseudomonas aeruginosa using the broth microdilution method in accordance with CLSI guidelines. Two-fold serial dilutions of the formulation (4000–0.125 µg/mL) were prepared in Mueller–Hinton broth and inoculated with standardized bacterial suspensions (0.5 McFarland; ~5 × 10⁵ CFU/mL). Ciprofloxacin and DMSO were used as positive and negative controls, respectively. Plates were incubated at 37 ± 1°C for 24 h, and MIC was defined as the lowest concentration showing no visible bacterial growth. All tests were conducted in triplicate, and results were expressed as mean ± SD [ 24 ]. Scanning Electron Microscopy Analysis Surface morphology of the nanoemulsion formulation was examined using scanning electron microscopy. Samples were mounted on stubs, gold-coated to ensure conductivity, and imaged at a 2 µm scale to observe droplet uniformity and structural features [ 23 ]. The optimized sunflower oil nanoemulcream exhibited excellent physical stability over three months under accelerated conditions. The pH remained consistent (6.2–6.1), within the skin-compatible range, and viscosity showed negligible variation, indicating preserved semisolid consistency. The formulation maintained uniform homogeneity, smooth texture, and stable organoleptic properties, with no phase separation or visible changes observed, confirming its robustness and suitability for topical application. Results & Discussion GC–MS Analysis GC–MS profiling of Helianthus annuus (sunflower) oil identified ten constituents (Rt 0.155–1.220 min), mainly heterocycles, amides, phenolic ketones, and sulphonamides (Fig. 1 ). Major compounds included 1,3,5-Triazine, hexahydro-1,3,5-trimethyl (4.93%) and N,N-Dimethylethanesulfonamide (4.85%), while Topotecan (0.39%) was least abundant. The presence of bioactive components (Table 1 ) such as N, N-Dimethylethanesulfonamide and 1,2,5-Oxadiazole supports the antimicrobial, antioxidant, and skin-protective potential of sunflower oil for nanoemulsion-based topical applications. Table 1 Key bioactive compounds identified in crude sunflower oil by GC-MS. Peak Rt (Min) Compound Name Molecular Formula MW (G/Mol) Peak Area (%) 2 0.155 1,3,5-Triazine, hexahydro-1,3,5-trimethyl- C 6 H 15 N 3 129 4.93 4 0.270 3-tert-Butyl-5-chloro-2-hydroxybenzophenone C 17 H 17 ClO 2 288 2.38 6 0.330 Piperidin-2,6-di-carboxylic acid C 7 H 11 NO 4 173 0.63 7 0.395 N, N-Dimethylethanesulfonamide C 4 H 11 NO 2 S 137 4.85 12 0.555 1,2,5-Oxadiazole C 2 H 2 N 2 O 70 1.76 13 0.620 Propanamide, N-methyl-2-amino- C 4 H 10 N 2 O 102 2.91 18 0.781 3-Pentanone, dimethylhydrazone C 7 H 16 N 2 128 3.47 20 0.900 Topotecan C 23 H 23 N 3 O 5 421 0.39 24 1.085 Propanediamide C 3 H 6 N 2 O 2 102 0.79 28 1.220 N'-Isopropylureidoacetic acid C 6 H 12 N 2 O 3 160 3.44 ATR–FTIR Analysis The ATR–FTIR spectra (Fig. 2 ) confirmed the characteristic functional groups of sunflower oil, nanoemulsion, and nanoemulcream. Peaks at 2956–2854 cm⁻¹ (–CH₂/–CH₃ stretching) and 1743–1735 cm⁻¹ (ester C = O) indicated the triglyceride backbone, while C = C stretching near 1636 cm⁻¹ and = C–H vibrations around 3007 cm⁻¹ confirmed the presence of unsaturated fatty acids, particularly oleic and linoleic acids. Broad O–H bands (3972–3266 cm⁻¹) reflected hydrogen bonding among water and surfactant molecules, and C–O stretching (1234–1030 cm⁻¹) (Table 2 ) verified ester and ether linkages. The nanoemulsion and nanoemulcream exhibited comparable spectral patterns with minor shifts, confirming oil incorporation without chemical modification and overall formulation stability. Table 2 Functional group profile of sunflower oil as determined by ATR–FTIR Observed Wavenumber (cm⁻¹) Functional Group Accepted Range (cm⁻¹) Probable Compound/Class 3972.39–3748.60 O–H stretching (free/broad) 3700–3600 Alcohols, phenols, water 3319.09–3266.02 O–H/N–H stretch (H-bonded) 3400–3200 Hydroxyls from water/surfactant, amines 3007.72 =C–H stretch (cis-alkene) 3020–3000 Unsaturated fatty acids (oleic, linoleic) 2956.20, 2927.06, 2923.41 –CH₃, –CH₂ stretch 2960–2850 Alkanes, fatty acid chains 2854.76, 2854.17 –CH₂ symmetric stretch 2855–2840 Saturated fatty acids 1743.79 C = O stretch (ester) 1750–1735 Triglycerides, ester lipids 1648.99, 1636.01 C = C stretch (alkene) 1680–1620 Unsaturated fatty acids 1460.90, 1454.73 CH₂ bending 1470–1450 Fatty acid chains 1374.06, 1351.22, 1346.24 CH₃ symmetric bending 1390–1340 Methyl groups in lipids 1234.76–1030.16 C–O stretch (esters) 1300–1000 Glycerides, triglyceride esters 1082.79 C–O stretch (weak) 1100–1000 Possibly surfactant or weakened ester band 963.20–843.27 =C–H out-of-plane bending 1000–650 Alkenes (unsaturation) 720.91 –(CH₂) n rocking 750–720 Long alkyl chains 527.95–419.00 Bending vibrations < 600 Fingerprint region (complex bending) DSC Analysis The DSC thermogram (Fig. 3 ) showed an endothermic peak at 198.36°C for sunflower oil and 103.60°C for the nanoemulcream, indicating good thermal stability of the formulation within the processing range. QbD-Based Optimization and Risk Assessment of Nanoemulcream The QbD concept established the QTPP and CQAs for the optimized sunflower oil nanoemulcream (Table 3 ). Target parameters—pH (5.5–7.0), droplet size (< 200 nm), and zeta potential (− 20 to − 30 mV)—ensured stability and skin compatibility, while rheological properties supported smooth application. Risk analysis using RPN and Ishikawa (Fig. 4 ) identified the surfactant blend (Tween 80 + PEG 400) as the highest-risk factor, influencing droplet size, zeta potential, viscosity, and stability. Homogenization time and speed affected particle size and texture, whereas sunflower oil, water, and excipients (Table 4 ) posed moderate risks. This assessment enabled systematic, reproducible, and stable formulation within the QbD framework. Table 3 QTPP and CQAs under the QbD Framework for Sunflower Oil–Based Nanoemulsioncream. QTPP Target CQAs Justification Dosage form Nanoemul cream — Semi-solid emulsion system enhances topical drug delivery Route of administration Topical — Localized delivery, avoids systemic side effects Dosage strength 1.0% w/w of active ingredient — To ensure therapeutic effect Dosage design Oil-in-water nanoemulsion in cream base — Enhances solubility, stability, and skin permeation Appearance White, smooth, homogeneous cream — Impacts patient compliance and product acceptability Odour No objectionable Odor — Improves user acceptability Identification FTIR fingerprint and visual inspection — Confirms identity of active and excipients pH 5.5–7.0 Yes Should match skin pH to avoid irritation Droplet size < 200 nm Yes Key for stability, bioavailability, and skin penetration Zeta potential −20 mV to − 30 mV (target range) Yes Indicator of emulsion stability Rheological aspects Appropriate Spreadability and texture (measured via viscosity, etc.) Yes Influences application, absorption, and patient experience Viscosity Moderate (optimized for Spreadability and retention) Yes Affects in-use performance and stability Spreadability 20–30 g/cm 2 Yes Ensures easy and uniform application Texture Profile Firmness, cohesiveness, adhesiveness, elasticity within acceptable range Yes Impacts consumer acceptance and skin feel Washability Easily washable with water Yes Enhances patient comfort and hygiene Morphological analysis Spherical, non-aggregated droplets in nanoemulsion Yes Ensures nanoscale dispersion, affects performance Particle size Nano-range Yes Reflects formulation integrity post-processing Table 4 RPN Assessment of Formulation and Process Factors Influencing noemulcream Quality Attributes Process Factor Viscosity Spreadability pH Texture Morphology Particle Size Zeta Potential Stability Action Plan Sunflower Oil Medium Medium Low Medium Medium Medium Medium Medium verify purity using GC-MS Surfactant Mixture (Tween 80 + PEG 400) High High Low High Medium High High High Optimize surfactant ratio for stability Deionized Water Medium Medium Low Medium Medium Medium Medium Medium Use ultrapure water Homogenization Time High High Low High Medium High Medium High Maintain at 25 minutes; test ± 5 minutes. Homogenization Speed High High Low High Medium High High High Maintain 12000 rpm; evaluate stability at ± 1000 rpm Cream Base (Lanolin, Cetyl alcohol, Stearic Acid, etc.) Medium Medium Medium Medium Medium Medium Low Medium Balance ingredients for desired texture and stability. DoE Optimization CCD (Table 5 ) was employed to optimize surfactant mix (X₁), Homogenization time (X₂), and Homogenization speed (X₃) for nanoemulsion particle size. The 3D response surface plots (Fig. 5 ) showed that increasing Smix ratio and speed reduced droplet size, while time had a moderate effect. The prediction profiler (Fig. 6 ) indicated an optimized particle size of 165.6 nm with a desirability of 0.83, and the interaction profiler (Fig. 7 ) highlighted synergistic effects of the variables. Statistical validation (Table 6 ) confirmed the model’s significance, good fit, and minimal residual correlation. Table 5 Responses of experimental trials developed via the CCD approach Runs Pattern Smix (1:1) X1 Time (min) X2 Speed (Rpm) X3 R1 Particle size (nm) Y R1 R2 R2 1 00A 4.5 25 12000 179.9 12000 179.2 2 −−− 4 20 10000 204.4 10000 204.7 3 ++− 5 30 10000 182.8 10000 183.2 4 0a0 4.5 20 11000 194.6 11000 195.1 5 000 4.5 25 11000 200.5 11000 200.8 6 00a 4.5 25 10000 196.4 10000 196.5 7 −++ 4 30 12000 174.9 12000 175.1 8 −+− 4 30 10000 196.6 10000 196.8 9 +++ 5 30 12000 187.3 12000 187.5 10 A00 5 25 11000 176.5 11000 176.8 11 a00 4 25 11000 175.3 11000 176.1 12 −−+ 4 20 12000 181.2 12000 181 13 +−+ 5 20 12000 175.2 12000 175.8 14 0A0 4.5 30 11000 209.2 11000 209.5 15 +−− 5 20 10000 207 10000 207.4 16 000 4.5 25 11000 200.6 11000 200.3 Table 6 Statistical Summary of Model Fit, ANOVA, and Durbin–Watson Test Parameter Statistical Value Interpretation R² 0.7883 Indicates that 78.83% of the variation in the response is explained by the model. Adjusted R² 0.7017 Adjusted for degrees of freedom; shows a good model fit. Root Mean Square Error (RMSE) 6.6188 Represents the standard deviation of residuals; smaller value indicates better precision. Mean of Response 190.2563 Average response value across all observations. Observations 32 Total number of experimental runs. Model Sum of Squares 3588.9361 Variation explained by the regression model. Error Sum of Squares 963.7826 Unexplained variation (residual error). F Ratio 9.1026 Indicates model significance. Prob > F < 0.0001 Model is statistically significant (p < 0.05). Durbin–Watson Statistic 2.1204 Suggests no significant autocorrelation (ideal ≈ 2). Autocorrelation −0.0784 Very weak negative correlation between residuals. Prob < DW 0.6720 Confirms independence of residuals. Optimized Nanoemulsion Formulation Design of Experiments (DoE) optimization identified the ideal formulation parameters for the sunflower oil nanoemulcream at an Smix (1:1) ratio of 4, homogenization time of 24.26 min, and speed of 12,000 rpm. The developed model predicted a particle size of 165.57 nm (95% CI: 157.37–173.79 nm), demonstrating strong model accuracy and reproducibility. A desirability value of 0.83 confirmed that the formulation satisfied all QTPP and CQA criteria, ensuring stability, uniformity, and effective topical performance. Optimized Nanoemulsion Characterization The optimized sunflower oil nanoemulsion exhibited a mean droplet size of 134.7 ± 34.1 nm Z-average 166.9 nm, PDI 0.409 (Fig. 8 ). The zeta potential of − 30.1 ± 2.3 mV (Fig. 9 ) indicated strong electrostatic stabilization, preventing aggregation and ensuring long-term stability. These characteristics confirm the formation of a stable, nanosized system suitable for topical nanoemulcream formulation. Physicochemical and Safety Evaluation The sunflower oil nanoemulcream exhibited desirable physicochemical characteristics, including good spreadability, uniform texture, and excellent stability (Table 7 ). SEM images (Fig. 10 ) showed spherical, smooth, and uniformly distributed droplets at a 2 µm scale, confirming nanoscale uniformity, structural integrity, and consistent morphology of the formulation. Skin irritancy testing further demonstrated the nanoemulcream to be non-irritant (Table 8 ), indicating its safety and suitability for topical application. Table 7 Physicochemical characterization of sunflower oil nanoemulcream Parameter Observed Result Acceptable/Standard Range for Creams Inference pH 6.2 ± 0.1 4.5–6.5 (skin-friendly range) Suitable for topical use, non-irritant Viscosity (cP at 25°C) 28,500 ± 120 cP 20,000–50,000 cP (semisolid creams) Provides spreadability & stability Homogeneity Uniform, smooth, no lumps Uniform, smooth Good texture & user acceptability Phase separation None observed after 24 h at RT No separation Stable emulsion system Organoleptic properties White, characteristic Odor, smooth texture Pleasant colour, Odor, smooth feel Patient-compliant Spreadability (gm/s) 12.5 ± 0.5 > 10 gm/s (good spreadability) Easily spreadable on skin Washability Easily washable with tap water Easily washable Convenient for user After-feel Non-greasy, smooth, emollient Non-sticky, emollient Enhances cosmetic acceptability Particle size (nm) 166.9 ± 34.1nm < 200 nm (nano-range) Nanosized, enhances penetration Polydispersity index (PDI) 0.409 ±25 mV (stable colloids) Good electrostatic stability Drug content (%) 94.2 ± 1.8% 90–110% High drug entrapment & uniformity Table 8 Skin Irritancy Test Results of Sunflower Oil Nanoemulcream Parameter Observation (Mean ± SD, n = 3) Guideline Range / Scale Inference Erythema (Redness) 0 (No redness) 0–4 (OECD 404 / Draize scale) Non-irritant Burning / Itching Absent — Safe for skin Mean Irritation Score (MIS) 0 0.0–0.4 = Non-irritant; 0.5–2.0 = Slight; 2.1–5.0 = Moderate; 5.1–8.0 = Severe Safe formulation (Non-irritant) In Vitro Drug Release and Diffusion Kinetics The in vitro drug release study over 360 minutes revealed notable differences among the formulated systems. The nanoemulsion (NE) exhibited the fastest and most extensive drug release, achieving 88% cumulative release, likely due to its nanoscale droplet size, large interfacial area, and improved drug partitioning into the aqueous phase. The nanoemulcream (NEC) showed a moderately sustained release of 64.8%, reflecting the semisolid cream matrix’s mild diffusional barrier, which slows drug migration compared to the freely dispersed nanoemulsion. The conventional cream containing sunflower oil (CMC) displayed a slower release rate (49%), consistent with the restricted drug mobility within the more viscous emulsion base. Plain sunflower oil (SO) showed the lowest release (30%), highlighting the limited diffusion from a hydrophobic, oil-dominant medium (Fig. 11 ). Overall, these findings demonstrate that while nanoemulsions provide rapid and enhanced drug liberation, incorporation into a cream base allows for a more controlled and sustained drug release, making the nanoemulcream a promising platform for topical drug delivery that balances efficacy with practical handling advantages. Dissolution Kinetics The release data were fitted to zero-order, first-order, Higuchi, Korsmeyer–Peppas, and Hixson–Crowell models to elucidate the drug release mechanism. The highest correlation was observed with the Higuchi model (R² = 0.903), suggesting a diffusion-controlled release. Korsmeyer–Peppas equation/model for drug release (n = 0.82, R² = 0.892) suggested anomalous (non-Fickian) diffusion, involving both diffusion and matrix relaxation (Table 9 ). Other models showed lower R² values, indicating less relevance in describing the release kinetics. Table 9 Drug Release Kinetic Model Results — Sunflower Oil Nanoemulcream Kinetic Model Equation R² Interpretation Zero-order Qt = Q 0 + k 0 t 0.832 Does not follow constant-rate release (low R²) First-order log Qt = log Q 0 − k₁t/2.303 0.846 Release depends on concentration; moderate fit Higuchi Qt = k H √t 0.903 Best fit → diffusion-controlled mechanism Korsmeyer–Peppas Mt/M ∞ = ktⁿ 0.892 n = 0.82 → Anomalous (non-Fickian) diffusion involving diffusion + cream matrix relaxation Hixson–Crowell Q₀¹ᐟ³ − Qt¹ᐟ³ = kt 0.811 Weak fit — erosion/dissolution not dominant Antimicrobial Activity The sunflower oil nanoemulcream exhibited moderate antimicrobial action against Gram-positive and Gram-negative organisms (Table 10 ). The MIC values ranged from 110 to 140 µg/mL, with Bacillus subtilis (110 ± 4 µg/mL) showing the greatest susceptibility and Pseudomonas aeruginosa (140 ± 5 µg/mL) the least. Staphylococcus aureus and Escherichia coli recorded MICs of 125 ± 5 and 125 ± 6 µg/mL, respectively. The observed activity demonstrates the effective incorporation and retention of the antimicrobial constituents of sunflower oil within the nanoemulcream matrix. Enhanced efficacy can be attributed to the nanoscale droplet size, which increases surface area and facilitates the interaction of bioactive compounds with bacterial cell membranes. The comparable inhibition against both Gram positive and Gram negative strains further confirms the broad-spectrum antimicrobial potential of the optimized formulation for topical applications. Table 10 Minimum Inhibitory Concentration (MIC) of Sunflower Oil Nanoemulcream Bacterial strain Gram MIC (µg/mL) Interpretation (Based on standard MIC ranges) Staphylococcus aureus (ATCC 25923) Gram + 125 ± 5 Moderate activity (101–500 µg/mL) Bacillus subtilis (ATCC 6633) Gram + 110 ± 4 Moderate activity (101–500 µg/mL) Escherichia coli (ATCC 25922) Gram − 125 ± 6 Moderate activity (101–500 µg/mL) Pseudomonas aeruginosa (ATCC 27853) Gram − 140 ± 5 Moderate activity (101–500 µg/mL) Accelerated Stability Study The optimized sunflower oil nanoemulcream exhibited excellent physical stability over three months under accelerated conditions. The pH remained consistent (6.2–6.1), within the skin-compatible range, and viscosity showed negligible variation, indicating preserved semisolid consistency. The formulation maintained uniform homogeneity, smooth texture, and stable organoleptic properties, with no phase separation or visible changes observed, confirming its robustness and suitability for topical application. Conclusion This study successfully developed a sunflower oil (Helianthus annuus) nanoemulcream using a QbD framework with CCD optimization. The developed nanoemulsion exhibited a mean droplet size of 134.7 ± 34.1 nm, Z-average 166.9 nm, PDI 0.409, and zeta potential − 30.1 ± 2.3 mV, confirming uniform nanoscale dispersion and electrostatic stability. Incorporation into a cream base yielded a physicochemically stable and skin-compatible nanoemulcream with pH 6.2 ± 0.1, viscosity 28,500 ± 120 cP, spreadability 12.5 ± 0.5 g·s⁻¹, and drug content 94.2 ± 1.8%. Accelerated stability studies demonstrated consistent droplet size, viscosity, and drug content over three months, while skin irritancy testing verified its non-irritant behavior. In vitro drug release studies showed enhanced and sustained drug release from the nanoemulcream compared to conventional cream and plain sunflower oil. Kinetic modeling further indicated a combination of diffusion-controlled and anomalous (non-Fickian) transport mechanisms, supporting the formulation’s controlled-release characteristics. The nanoemulcream also displayed moderate broad-spectrum antibacterial activity (MIC 110–140 µg/mL), highlighting its therapeutic potential.Overall, this work establishes a reproducible, environmentally sustainable, and therapeutically effective platform for topical delivery of natural bioactives. The findings underscore the value of QbD-guided nanoemulsion design for next-generation phytopharmaceutical creams with improved stability and safety. Although in vivo animal safety studies were not conducted in the present investigation, the strong in vitro and stability data provide a solid foundation for future preclinical animal studies to further confirm safety and therapeutic performance. Abbreviations ATR FTIR–Attenuated Total Reflectance–Fourier Transform Infrared Spectroscopy CCD Central Composite Design CMAs Critical Material Attributes CPPs Critical Process Parameters CQAs Critical Quality Attributes DMSO Dimethyl Sulfoxide DoE Design of Experiments DSC Differential Scanning Calorimetry GC MS–Gas Chromatography–Mass Spectrometry HPLC High–Performance Liquid Chromatography PDI Polydispersity Index PEG 400 Polyethylene Glycol 400 pH Potential of Hydrogen QbD Quality by Design QTPP Quality Target Product Profile RPN Risk Priority Number MIC minimum inhibitory concentration REM Risk Evaluation Matrix SEM Scanning Electron Microscopy. Declarations Ethical Compliance This research did not include human participants or live animals. All experimental procedures, including in vitro analyses, stability studies, and skin irritation assessments, adhered to institutional safety standards and good laboratory practices. Data and Material Availability All relevant data generated or analyzed during the study are presented within this article and its supplementary information. Additional datasets can be provided by the corresponding author upon reasonable request. Funding Information This work was carried out without any external financial support. Ethical Approval and Participant Consent Not applicable, as the study involved neither human nor animal subjects. Consent for Publication Not applicable. Credit Authorship Contribution Statement (Md Barakathulla): Conceptualization, Methodology, Writing – original draft, Supervision. (Yetukuri Koushik): Methodology, Validation, Writing – review & editing. (Morla Siva Prasad): Data curation, Formal analysis, Writing – review & editing. (Nadendla Rama Rao): Investigation, Visualization, Writing – review & editing. Declaration of Competing Interests The authors declare that there are no financial or personal conflicts of interest that could have influenced the work presented in this study. Acknowledgements The authors express their sincere gratitude to Chalapathi Institute of Pharmaceutical Sciences, Chalapathi Nagar, Lam, Guntur, Andhra Pradesh, India, for providing the facilities and opportunity to carry out this research work. The authors also thank the faculty members, laboratory staff, and their parents for their valuable support and encouragement throughout the study. References Kumari S, Goyal A, Gürer ES, Yapar EA, Garg M, Sood M, Sindhu RK (2022) Bioactive loaded novel nano-formulations for targeted drug delivery and their therapeutic potential. 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Gels 11(6):400. https://doi.org/10.3390/gels11060400 Koushik Y, Rama Rao N, Venkatesh US, Surendra AV, Sreenu T (2025) Formulation and optimization of a Melissa officinalis -loaded nanoemulgel for anti-inflammatory therapy using design of experiments (DoE). Gels 11(10):776. https://doi.org/10.3390/gels11100776 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8291953","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":556093626,"identity":"2749904e-f188-4eb8-86a0-34fe8cd24f07","order_by":0,"name":"Koushik 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1","display":"","copyAsset":false,"role":"figure","size":357412,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eGC–MS Identification of Bioactive Constituents in Sunflower Oil\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 1. \u003c/strong\u003eGC–MS chromatogram of \u003cem\u003eHelianthus annuus\u003c/em\u003e oil displaying the principal bioactive components with antimicrobial, anti-inflammatory, and antioxidant activities relevant for topical formulations.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8291953/v1/a5b67bb7614bcf830464fc23.jpeg"},{"id":97897566,"identity":"9b6664fb-028b-4598-9896-0b93b80c5d2e","added_by":"auto","created_at":"2025-12-10 15:37:57","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":304512,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eATR-FTIR of Sunflower Oil, Nanoemulsion and Nanoemulcream\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 2. \u003c/strong\u003eFTIR spectra of sunflower oil (blue), nanoemulsion (red), and nanoemulcream (black) showing characteristic peaks that confirm successful incorporation of the nanoemulsion into the cream base without any significant chemical interaction.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8291953/v1/43514a092236ff403d42e63a.jpeg"},{"id":97899140,"identity":"68e18563-dc73-497c-866f-9c9236a8ee27","added_by":"auto","created_at":"2025-12-10 15:41:39","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":226988,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDSC Thermograms of Sunflower Oil and Nanoemulcream\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 3. \u003c/strong\u003eDSC thermograms of \u003cem\u003eHelianthus annuus\u003c/em\u003e oil and the optimized \u003cem\u003eHelianthus annuus\u003c/em\u003e nanoemulcream, showing characteristic thermal transitions and stability profiles relevant for topical application.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8291953/v1/5cdd7e1226d7c7c437539c9e.jpeg"},{"id":97898264,"identity":"cba365e2-c40b-4170-94fb-da9d28ed6801","added_by":"auto","created_at":"2025-12-10 15:38:55","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":205432,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIshikawa Diagram of Factors Influencing Nanoemulcream CQAs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 4. \u003c/strong\u003eIshikawa (fishbone) diagram illustrating the potential Variables impacting the Critical Quality Attributes (CQAs) of the nanoemulcream formulation, including personnel, machine, material, method, characterization, and environmental factors.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8291953/v1/180e63aabe09fba77cbee775.jpeg"},{"id":97862192,"identity":"ec033539-1a3d-463d-84c5-cfaa3f14a010","added_by":"auto","created_at":"2025-12-10 09:06:38","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":121086,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e3D Graphs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 5\u003c/strong\u003e: 3D surface plots illustrating the influence of independent factors on particle size (Y): (A) Time vs. Speed, (B) Time vs. Smix, and (C) Speed vs. Smix.\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8291953/v1/56af6bb0c081e7f67381a6a4.jpeg"},{"id":97899462,"identity":"80a3e705-e214-4fd7-9f37-495aaeada3a5","added_by":"auto","created_at":"2025-12-10 15:44:35","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":49919,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrediction Profiler of Nanoemulsion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 6: \u003c/strong\u003ePrediction profiler of the nanoemulsion showing the Impact of the formulation and processing parameters on particle size. The developed conditions predict a droplet dimensions of 165.6 nm with a high desirability of 0.83, indicating good model reliability.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8291953/v1/44448672a6443f7e24bbdca6.png"},{"id":97899005,"identity":"ca0f219c-e903-46f1-84a7-7b1c94d84522","added_by":"auto","created_at":"2025-12-10 15:40:41","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":220622,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eInteraction Profile of optimized Nanoemulsion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 7:\u003c/strong\u003e Interaction profiler showing the combined effects of Smix ratio, homogenization speed, and emulsification time on nanoemulsion particle size, highlighting key variable interactions influencing droplet size and stability.\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8291953/v1/db7d1937d766434f02188df7.jpeg"},{"id":97900350,"identity":"d93f59ea-9af7-4367-b4cb-e07118d81db7","added_by":"auto","created_at":"2025-12-10 15:45:23","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":837296,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eParticle Size Characterization of the Developed Sunflower Oil Nanoemulsion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 8. \u003c/strong\u003eParticle size profile of the developed sunflower-oil-based nanoemulsion exhibiting uniform droplet dimensions appropriate for topical use.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-8291953/v1/bae207104cc51df84f9bd523.png"},{"id":97862207,"identity":"fca2a47d-bddb-42b4-bb77-b5be728ba6e8","added_by":"auto","created_at":"2025-12-10 09:06:38","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":1039919,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eZeta Potential Characterization of the Optimized Sunflower Oil Nanoemulsion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 9. \u003c/strong\u003eZeta-potential profile of the optimized sunflower oil nanoemulsion, demonstrating its stable colloidal behaviour.\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-8291953/v1/030916a1700593afefcd1bc1.png"},{"id":97862205,"identity":"82eec30f-2ebd-4722-92d0-eeff33fe0b4c","added_by":"auto","created_at":"2025-12-10 09:06:38","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":578781,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSEM Characterization of Nanoemulsion Surface Morphology\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 10. \u003c/strong\u003eSEM images of the nanoemulsion formulation at 2 µm scale: (A) and (B) showing surface morphology.\u003c/p\u003e","description":"","filename":"floatimage10.png","url":"https://assets-eu.researchsquare.com/files/rs-8291953/v1/db530070d87c3d65f992f691.png"},{"id":97900728,"identity":"34a4f115-2189-4b2d-b4e6-8a48572f8c80","added_by":"auto","created_at":"2025-12-10 15:45:47","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":72267,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIn Vitro Drug Release and Diffusion Kinetics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 11.\u003c/strong\u003eCumulative drug release (%) versus time (min) for Nanoemulsion (NE), Nanoemulcream (NEC), Cream + Oil (CMC) and Plain Sunflower Oil (SO). Data represent mean values (n = 3). Error bars indicate standard deviation.\u003c/p\u003e","description":"","filename":"floatimage11.png","url":"https://assets-eu.researchsquare.com/files/rs-8291953/v1/42cf83be08782dd67a270429.png"},{"id":98621871,"identity":"7e657f92-f33e-4c9c-aec3-8eb80891335b","added_by":"auto","created_at":"2025-12-19 16:28:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5853308,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8291953/v1/2884f0a7-0182-4262-b2c5-a17497a58168.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eEco – Pharmaceutical Design of a \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eHelianthus Annuus\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e Nanoemulcream: A QbD Optimization Strategy\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe increasing focus on eco-pharmaceutical innovation drives the development of sustainable drug delivery systems integrating natural bioactives with advanced formulations. Sunflower oil (\u003cem\u003eHelianthus annuus\u003c/em\u003e), a renewable and biocompatible resource rich in polyunsaturated fatty acids, tocopherols, and phytosterols, possesses broad therapeutic potential due to its antioxidative and anti-inflammatory and emollient properties [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. However, its direct use is characterized by low aqueous solubility, oxidative instability, and low dermal bioavailability. Nanotechnology enables the development of advanced topical systems with improved performance. Nanoemulsions (20\u0026ndash;200 nm) enhance solubility, stability, and dermal penetration of lipophilic actives, while their incorporation into semisolid bases forms nanoemulcream\u0026rsquo;s that combine enhanced permeation with stability and patient acceptability [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFollowing the QbD approach, formulation development begins with defining the QTPP and identifying CQAs such as droplet size, PDI, zeta potential, viscosity, and spreadability. Risk assessment tools like FMEA and Ishikawa diagrams are used to establish CMAs and CPPs [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. A DoE framework using CCD allows efficient optimization of formulation variables, revealing both linear and quadratic effects. In \u003cem\u003eH. annuus\u003c/em\u003e nanoemulsions, CCD aids in optimizing oil concentration, S/Cos ratio, and homogenization speed to achieve stability and bioavailability [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. High-speed homogenization further supports scalability and sustainability by generating nanosized droplets through mechanical shear with minimal solvent and energy use [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study integrates QbD with nanotechnology to establish a sustainable strategy for a sunflower oil-based nanoemulcream. Systematic optimization via CCD produced a formulation with enhanced solubilization, dermal permeation, antimicrobial activity, stability, and patient acceptability, providing a reproducible, scalable, and environmentally conscious platform for next-generation topical formulations [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e"},{"header":"Materials \u0026 Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eMaterials\u003c/h2\u003e\u003cp\u003eSunflower oil (\u003cem\u003eHelianthus annuus\u003c/em\u003e) was procured from a local vendor in India. Tween 80 and Polyethylene Glycol 400 (PEG 400) were obtained from Loba Chemie Pvt. Ltd. (Mumbai, India). Lanolin was purchased from Fisher Scientific, India. The remaining excipients\u0026mdash;Stearic acid, Cetyl alcohol, Propylene glycol, and Potassium hydroxide (KOH)\u0026mdash;were also supplied by Loba Chemie Pvt. Ltd. HPLC-grade water was supplied by Thermo Fisher Scientific Pvt. Ltd. (Qualigens), India. Analytical-grade chemicals were employed as obtained from the suppliers.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eMethods\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eCharacterization Studies\u003c/h2\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003eGC\u0026ndash;MS Characterization\u003c/h2\u003e\u003cp\u003eThe compositional profile of sunflower oil was determined using a GC\u0026ndash;MS system (Model GCMS-QP2010, Shimadzu, Japan) equipped with an HP-5MS column (30 m \u0026times; 0.25 mm \u0026times; 0.25 \u0026micro;m). About 1 \u0026micro;l of oil was injected in splitless mode, with helium served as the carrier gas at a specified flow rate of 1.0 mL/min. The oven temperature was scheduled to ramp from 60\u0026deg;C (2 min) to 280\u0026deg;C at 10\u0026deg;C/min, and maintained for 10 minutes. The injector and detector temperatures were maintained at 250\u0026deg;C and 280\u0026deg;C, respectively. Mass spectra were recorded in electron impact mode (70 eV) over a 50\u0026ndash;550 m/z range. Compounds were confirmed through spectral comparison with the NIST reference library. [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\n\u003ch3\u003eATR–FTIR Spectroscopy\u003c/h3\u003e\n\u003cp\u003eAttenuated Total Reflectance\u0026ndash;Fourier Transform Infrared (ATR\u0026ndash;FTIR) spectroscopy of sunflower oil, Nanoemulsion and the developed nanoemulcream were recorded using a Bruker Alpha II spectrophotometer (Germany). Samples were positioned on the ATR crystal, and spectra were recorded over the range of 4000\u0026ndash;400 cm⁻\u0026sup1; with a resolution of 4 cm⁻\u0026sup1;, averaging 32 scans. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eDSC Analysis\u003c/h2\u003e\u003cp\u003eThermal Characterization of crude oil and optimized nanoemulcream was performed using DSC (TA Instruments, USA). Samples (5\u0026ndash;10 mg) were sealed in aluminium pans and analyzed under nitrogen (50 mL/min). Heating ranged from 30\u0026ndash;300\u0026deg;C at 10\u0026deg;C/min. Thermograms recorded endothermic transitions and degradation peaks to evaluate compatibility and physical stability [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003ePreparation of Nanoemulcream Formulation\u003c/h3\u003e\n\u003cp\u003eThe sunflower oil-based nanoemulsion was prepared using high-speed homogenization [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Crude \u003cem\u003eHelianthus annuus\u003c/em\u003e oil was mixed with a surfactant/co-surfactant blend of Tween 80 and PEG 400. Deionized water was added dropwise under continuously stirred to obtain a coarse emulsion, which was subsequently processed using high-speed homogenizer using a Digital Ultra-Turrax\u0026reg; T25 (IKA, Germany) to yield a stable oil-in-water nanoemulsion.\u003c/p\u003e\u003cp\u003eThe resulting nanoemulsion was subsequently incorporated into a cream base to form the nanoemulcream [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e \u0026amp; \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The oil phase (lanolin, stearic acid, Cetyl alcohol, and the nanoemulsion) and the aqueous phase (propylene glycol, potassium hydroxide, and deionized water) were heated separately to the same appropriate temperature. The aqueous phase was slowly added to the oil phase with continuous stirring followed by homogenization to achieve a uniform cream consistency. The finished formulation was cooled to room temperature and transferred into airtight containers for evaluation.\u003c/p\u003e\n\u003ch3\u003eQuality by Design (QbD) Approach\u003c/h3\u003e\n\u003cp\u003eThe QbD framework guided the systematic, risk-based development of the sunflower oil nanoemulcream [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The QTPP outlined key formulation characteristics such as dosage form, administration route, strength, pH, appearance, rheological behaviour, and microbiological stability. Based on the QTPP and prior knowledge, CQAs were identified, such as droplet size, zeta potential, pH, viscosity, spreadability, morphology, texture, and washability. Droplet size and zeta potential were emphasized as critical for nanoemulsion stability. Risk assessment utilized an Ishikawa (fishbone) diagram and a REM to categorize and rank formulation and process risks. This process led to the identification of CMAs and CPPs for optimization, while other less impactful parameters were controlled or fixed, ensuring robust formulation development.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eOptimization of Sunflower Oil Nanoemulcream via DoE\u003c/h2\u003e\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\u003ch2\u003eDoE-Based Optimization via CCD\u003c/h2\u003e\u003cp\u003eA CCD with 16 runs and a three-factor, three-level scheme was executed using JMP software (v17.0.0; SAS Institute Inc., Cary, NC, USA). The design enabled evaluation of quadratic response surfaces and development of second-order models to assess main, interaction, and quadratic effects, incorporating factorial, axial, and central points for robustness [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. The general polynomial equation generated from the design is expressed as:\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eY\u0026thinsp;=\u0026thinsp;S\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;S\u003csub\u003e1\u003c/sub\u003eX\u003csub\u003e1\u003c/sub\u003e+S\u003csub\u003e2\u003c/sub\u003eX\u003csub\u003e2\u003c/sub\u003e+S\u003csub\u003e3\u003c/sub\u003eX\u003csub\u003e3\u003c/sub\u003e+S\u003csub\u003e4\u003c/sub\u003eX\u003csub\u003e1\u003c/sub\u003eX\u003csub\u003e2\u003c/sub\u003e+S\u003csub\u003e5\u003c/sub\u003eX\u003csub\u003e1\u003c/sub\u003eX\u003csub\u003e3\u003c/sub\u003e+S\u003csub\u003e6\u003c/sub\u003eX\u003csub\u003e2\u003c/sub\u003eX\u003csub\u003e3\u003c/sub\u003e+S\u003csub\u003e7\u003c/sub\u003eX\u003csub\u003e1\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e+S\u003csub\u003e8\u003c/sub\u003eX\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e+S\u003csub\u003e9\u003c/sub\u003eX\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/h2\u003e\u003cp\u003ewhere \u003cem\u003eY\u003c/em\u003e represents the response, \u003cem\u003eS₀\u003c/em\u003e denotes the intercept (mean of all runs), \u003cem\u003eS₁\u0026ndash;S₉\u003c/em\u003e are regression coefficients, \u003cem\u003eX₁, X₂\u003c/em\u003e, and \u003cem\u003eX₃\u003c/em\u003e represent independent variables, \u003cem\u003eX₁X₂, X₁X₃\u003c/em\u003e, and \u003cem\u003eX₂X₃\u003c/em\u003e indicate interaction terms, and \u003cem\u003eX₁\u0026sup2;, X₂\u0026sup2;, X₃\u0026sup2;\u003c/em\u003e represent quadratic effects.\u003c/p\u003e\u003cp\u003eIn the present study, the independent variables were the concentration of Tween 80 and PEG 400 (X₁), homogenization time (X₂), and homogenization speed (X₃), with coded levels of \u0026minus;\u0026thinsp;1 and +\u0026thinsp;1 representing low and high values, respectively. The response variable (Y₁) was droplet size of the nanoemulsion, determined for all 16 formulations were incorporated into the design model to assess the effects of the independent factors. Optimization was carried out using the Prediction Profiler tool in JMP to identify the best factor settings for minimizing particle size, thereby ensuring formulation stability. [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eEvaluation of Sunflower Oil Nanoemulcream\u003c/h2\u003e\u003cp\u003e\u003cb\u003ePhysicochemical and Performance Evaluation\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003e1. Physicochemical Characterization\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe pH of the nanoemulcream was measured at room temperature using a calibrated digital pH meter (Deluxe Model 101, India), standardized with pH 4.01, 7.00, and 10.01 buffers. Approximately 1 g of formulation was dispersed in distilled water, and measurements were performed in triplicate, 24 hours post-preparation. Formulation viscosity was assessed using a Brookfield viscometer (DV II\u0026thinsp;+\u0026thinsp;Pro) with spindle S-64 at 20 rpm and 25\u0026deg;C. Homogeneity and phase separation were evaluated visually and tactilely over 24 hours, while organoleptic properties, including color, odor, and texture, were assessed by observation and application [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003e2. Performance and Application Properties\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSpreadability was assessed by placing a fixed cream amount between glass slides and measuring the time for the upper slide to move underweight. Washability was tested by rinsing a controlled amount applied to the skin, and after-feel was evaluated by assessing emollience, residue, and slipperiness post-application [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003e3. Particle Size and Zeta Potential\u003c/b\u003e\u003c/p\u003e\u003cp\u003eDroplet size distribution and zeta potential were measured using Dynamic light scattering (Malvern Zetasizer Nano ZS90, UK). Samples were diluted 1:100 (v/v) in deionized water to reduce multiple scattering. Particle size was reported as Z-average diameter, and zeta potential assessed colloidal stability. Analyses were performed in triplicate [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003e4. Safety and Stability Studies\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIrritancy testing involved applying the formulation to a 1 cm\u0026sup2; dorsal hand area and observing for erythema, edema, or irritation over 24 hours; no reactions were observed [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Accelerated stability studies were conducted under room temperature and accelerated conditions (40\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C / 75\u0026thinsp;\u0026plusmn;\u0026thinsp;5% RH) for three months., with evaluations at 0, 1, 2, and 3 months, following ICH guidelines [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003e5. Drug Content Determination\u003c/b\u003e\u003c/p\u003e\u003cp\u003eA 1 g sample of nanoemulcream was dissolved in 10 mL ethanol, stirred, filtered, and diluted. Absorbance at 273 nm was recorded using a Systronics Double Beam Spectrophotometer (2202) with ethanol as blank, and the drug content was determined. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:Drug\\:content\\:\\%=\\:\\:\\left(\\frac{Analyzed\\:content}{Theoretical\\:content}\\right)\\times\\:100$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eIn Vitro Drug Release and Kinetic Analysis\u003c/h2\u003e\u003cp\u003eThe release of the drug from the cream formulation was analyzed using a USP Type II (paddle) dissolution apparatus at 37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u0026deg;C with constant stirring. Aliquots were withdrawn at predetermined intervals, filtered, and replaced with fresh medium to maintain sink conditions. Drug content was quantified using a validated UV\u0026ndash;Vis spectrophotometric method at the drug\u0026rsquo;s absorption maximum (λmax determined from 200\u0026ndash;400 nm scan). Calibration curves were prepared, and samples were analyzed in triplicate.\u003c/p\u003e\u003cp\u003eCumulative release data were fitted to kinetic models (zero-order, first-order, Higuchi, Korsmeyer\u0026ndash;Peppas, and Hixson\u0026ndash;Crowell) to determine release rate constants and elucidate the pathway of drug release.[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eAntimicrobial Activity\u003c/h2\u003e\u003cp\u003eThe antimicrobial efficacy of the sunflower oil nanoemulcream was assessed by determining its MIC against \u003cem\u003eStaphylococcus aureus\u003c/em\u003e, \u003cem\u003eBacillus subtilis\u003c/em\u003e, \u003cem\u003eEscherichia coli\u003c/em\u003e, and \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e using the broth microdilution method in accordance with CLSI guidelines. Two-fold serial dilutions of the formulation (4000\u0026ndash;0.125 \u0026micro;g/mL) were prepared in Mueller\u0026ndash;Hinton broth and inoculated with standardized bacterial suspensions (0.5 McFarland; ~5 \u0026times; 10⁵ CFU/mL). Ciprofloxacin and DMSO were used as positive and negative controls, respectively. Plates were incubated at 37\u0026thinsp;\u0026plusmn;\u0026thinsp;1\u0026deg;C for 24 h, and MIC was defined as the lowest concentration showing no visible bacterial growth. All tests were conducted in triplicate, and results were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003eScanning Electron Microscopy Analysis\u003c/h2\u003e\u003cp\u003eSurface morphology of the nanoemulsion formulation was examined using scanning electron microscopy. Samples were mounted on stubs, gold-coated to ensure conductivity, and imaged at a 2 \u0026micro;m scale to observe droplet uniformity and structural features [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\n\u003cp\u003eThe optimized sunflower oil nanoemulcream exhibited excellent physical stability over three months under accelerated conditions. The pH remained consistent (6.2\u0026ndash;6.1), within the skin-compatible range, and viscosity showed negligible variation, indicating preserved semisolid consistency. The formulation maintained uniform homogeneity, smooth texture, and stable organoleptic properties, with no phase separation or visible changes observed, confirming its robustness and suitability for topical application.\u003c/p\u003e"},{"header":"Results \u0026 Discussion","content":"\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003cdiv id=\"Sec19\" class=\"Section3\"\u003e\u003ch2\u003eGC\u0026ndash;MS Analysis\u003c/h2\u003e\u003cp\u003eGC\u0026ndash;MS profiling of \u003cem\u003eHelianthus annuus\u003c/em\u003e (sunflower) oil identified ten constituents (Rt 0.155\u0026ndash;1.220 min), mainly heterocycles, amides, phenolic ketones, and sulphonamides (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Major compounds included 1,3,5-Triazine, hexahydro-1,3,5-trimethyl (4.93%) and N,N-Dimethylethanesulfonamide (4.85%), while Topotecan (0.39%) was least abundant. The presence of bioactive components (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) such as N, N-Dimethylethanesulfonamide and 1,2,5-Oxadiazole supports the antimicrobial, antioxidant, and skin-protective potential of sunflower oil for nanoemulsion-based topical applications.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eKey bioactive compounds identified in crude sunflower oil by GC-MS.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePeak\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRt (Min)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCompound Name\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMolecular\u003c/p\u003e\u003cp\u003eFormula\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMW (G/Mol)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ePeak Area\u003c/p\u003e\u003cp\u003e(%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.155\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,3,5-Triazine, hexahydro-1,3,5-trimethyl-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eC\u003csub\u003e6\u003c/sub\u003eH\u003csub\u003e15\u003c/sub\u003eN\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e129\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.93\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.270\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3-tert-Butyl-5-chloro-2-hydroxybenzophenone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eC\u003csub\u003e17\u003c/sub\u003eH\u003csub\u003e17\u003c/sub\u003eClO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e288\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.38\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.330\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePiperidin-2,6-di-carboxylic acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eC\u003csub\u003e7\u003c/sub\u003eH\u003csub\u003e11\u003c/sub\u003eNO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e173\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.63\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.395\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eN, N-Dimethylethanesulfonamide\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eC\u003csub\u003e4\u003c/sub\u003eH\u003csub\u003e11\u003c/sub\u003eNO\u003csub\u003e2\u003c/sub\u003eS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e137\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e4.85\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.555\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,2,5-Oxadiazole\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eC\u003csub\u003e2\u003c/sub\u003eH\u003csub\u003e2\u003c/sub\u003eN\u003csub\u003e2\u003c/sub\u003eO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.76\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.620\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePropanamide, N-methyl-2-amino-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eC\u003csub\u003e4\u003c/sub\u003eH\u003csub\u003e10\u003c/sub\u003eN\u003csub\u003e2\u003c/sub\u003eO\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.91\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.781\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3-Pentanone, dimethylhydrazone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eC\u003csub\u003e7\u003c/sub\u003eH\u003csub\u003e16\u003c/sub\u003eN\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e128\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.47\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.900\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTopotecan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eC\u003csub\u003e23\u003c/sub\u003eH\u003csub\u003e23\u003c/sub\u003eN\u003csub\u003e3\u003c/sub\u003eO\u003csub\u003e5\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e421\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.39\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.085\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePropanediamide\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eC\u003csub\u003e3\u003c/sub\u003eH\u003csub\u003e6\u003c/sub\u003eN\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.79\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.220\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eN'-Isopropylureidoacetic acid\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eC\u003csub\u003e6\u003c/sub\u003eH\u003csub\u003e12\u003c/sub\u003eN\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e3\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e160\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eATR\u0026ndash;FTIR Analysis\u003c/h2\u003e\u003cp\u003eThe ATR\u0026ndash;FTIR spectra (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) confirmed the characteristic functional groups of sunflower oil, nanoemulsion, and nanoemulcream. Peaks at 2956\u0026ndash;2854 cm⁻\u0026sup1; (\u0026ndash;CH₂/\u0026ndash;CH₃ stretching) and 1743\u0026ndash;1735 cm⁻\u0026sup1; (ester C\u0026thinsp;=\u0026thinsp;O) indicated the triglyceride backbone, while C\u0026thinsp;=\u0026thinsp;C stretching near 1636 cm⁻\u0026sup1; and =\u0026thinsp;C\u0026ndash;H vibrations around 3007 cm⁻\u0026sup1; confirmed the presence of unsaturated fatty acids, particularly oleic and linoleic acids. Broad O\u0026ndash;H bands (3972\u0026ndash;3266 cm⁻\u0026sup1;) reflected hydrogen bonding among water and surfactant molecules, and C\u0026ndash;O stretching (1234\u0026ndash;1030 cm⁻\u0026sup1;) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) verified ester and ether linkages. The nanoemulsion and nanoemulcream exhibited comparable spectral patterns with minor shifts, confirming oil incorporation without chemical modification and overall formulation stability.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFunctional group profile of sunflower oil as determined by ATR\u0026ndash;FTIR\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eObserved Wavenumber (cm⁻\u0026sup1;)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFunctional Group\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAccepted Range (cm⁻\u0026sup1;)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eProbable Compound/Class\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3972.39\u0026ndash;3748.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eO\u0026ndash;H stretching (free/broad)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3700\u0026ndash;3600\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAlcohols, phenols, water\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3319.09\u0026ndash;3266.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eO\u0026ndash;H/N\u0026ndash;H stretch (H-bonded)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3400\u0026ndash;3200\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHydroxyls from water/surfactant, amines\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3007.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e=C\u0026ndash;H stretch (cis-alkene)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3020\u0026ndash;3000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnsaturated fatty acids (oleic, linoleic)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2956.20, 2927.06, 2923.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ndash;CH₃, \u0026ndash;CH₂ stretch\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2960\u0026ndash;2850\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAlkanes, fatty acid chains\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2854.76, 2854.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ndash;CH₂ symmetric stretch\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2855\u0026ndash;2840\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSaturated fatty acids\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1743.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cb\u003eC\u0026thinsp;=\u0026thinsp;O stretch (ester)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1750\u0026ndash;1735\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTriglycerides, ester lipids\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1648.99, 1636.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eC\u0026thinsp;=\u0026thinsp;C stretch (alkene)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1680\u0026ndash;1620\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eUnsaturated fatty acids\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1460.90, 1454.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCH₂ bending\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1470\u0026ndash;1450\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFatty acid chains\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1374.06, 1351.22, 1346.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCH₃ symmetric bending\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1390\u0026ndash;1340\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMethyl groups in lipids\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1234.76\u0026ndash;1030.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eC\u0026ndash;O stretch (esters)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1300\u0026ndash;1000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGlycerides, triglyceride esters\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1082.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eC\u0026ndash;O stretch (weak)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1100\u0026ndash;1000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePossibly surfactant or weakened ester band\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e963.20\u0026ndash;843.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e=C\u0026ndash;H out-of-plane bending\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1000\u0026ndash;650\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAlkenes (unsaturation)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e720.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ndash;(CH₂) n rocking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e750\u0026ndash;720\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLong alkyl chains\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e527.95\u0026ndash;419.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBending vibrations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;600\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFingerprint region (complex bending)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eDSC Analysis\u003c/h2\u003e\u003cp\u003eThe DSC thermogram (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) showed an endothermic peak at 198.36\u0026deg;C for sunflower oil and 103.60\u0026deg;C for the nanoemulcream, indicating good thermal stability of the formulation within the processing range.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003eQbD-Based Optimization and Risk Assessment of Nanoemulcream\u003c/h2\u003e\u003cp\u003eThe QbD concept established the QTPP and CQAs for the optimized sunflower oil nanoemulcream (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Target parameters\u0026mdash;pH (5.5\u0026ndash;7.0), droplet size (\u0026lt;\u0026thinsp;200 nm), and zeta potential (\u0026minus;\u0026thinsp;20 to \u0026minus;\u0026thinsp;30 mV)\u0026mdash;ensured stability and skin compatibility, while rheological properties supported smooth application. Risk analysis using RPN and Ishikawa (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e4\u003c/span\u003e) identified the surfactant blend (Tween 80\u0026thinsp;+\u0026thinsp;PEG 400) as the highest-risk factor, influencing droplet size, zeta potential, viscosity, and stability. Homogenization time and speed affected particle size and texture, whereas sunflower oil, water, and excipients (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) posed moderate risks. This assessment enabled systematic, reproducible, and stable formulation within the QbD framework.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eQTPP and CQAs under the QbD Framework for Sunflower Oil\u0026ndash;Based Nanoemulsioncream.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eQTPP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTarget\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCQAs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eJustification\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDosage form\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNanoemul cream\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSemi-solid emulsion system enhances topical drug delivery\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRoute of administration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTopical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLocalized delivery, avoids systemic side effects\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDosage strength\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.0% w/w of active ingredient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTo ensure therapeutic effect\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDosage design\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOil-in-water nanoemulsion in cream base\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eEnhances solubility, stability, and skin permeation\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAppearance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWhite, smooth, homogeneous cream\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eImpacts patient compliance and product acceptability\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOdour\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo objectionable Odor\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eImproves user acceptability\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIdentification\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFTIR fingerprint and visual inspection\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eConfirms identity of active and excipients\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003epH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.5\u0026ndash;7.0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eShould match skin pH to avoid irritation\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDroplet size\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;200 nm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eKey for stability, bioavailability, and skin penetration\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZeta potential\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;20 mV to \u0026minus;\u0026thinsp;30 mV (target range)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eIndicator of emulsion stability\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRheological aspects\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAppropriate Spreadability and texture (measured via viscosity, etc.)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInfluences application, absorption, and patient experience\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eViscosity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerate (optimized for Spreadability and retention)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eAffects in-use performance and stability\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSpreadability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20\u0026ndash;30 g/cm\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eEnsures easy and uniform application\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTexture Profile\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFirmness, cohesiveness, adhesiveness, elasticity within acceptable range\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eImpacts consumer acceptance and skin feel\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWashability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEasily washable with water\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eEnhances patient comfort and hygiene\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMorphological analysis\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpherical, non-aggregated droplets in nanoemulsion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eEnsures nanoscale dispersion, affects performance\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParticle size\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNano-range\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eReflects formulation integrity post-processing\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eRPN Assessment of Formulation and Process Factors Influencing noemulcream Quality Attributes\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"10\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProcess Factor\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eViscosity\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSpreadability\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003epH\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTexture\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMorphology\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eParticle Size\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eZeta Potential\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eStability\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c10\"\u003e\u003cp\u003eAction Plan\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSunflower Oil\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003everify purity using GC-MS\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSurfactant Mixture (Tween 80\u0026thinsp;+\u0026thinsp;PEG 400)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eOptimize surfactant ratio for stability\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDeionized Water\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eUse ultrapure water\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHomogenization Time\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eMaintain at 25 minutes; test\u0026thinsp;\u0026plusmn;\u0026thinsp;5 minutes.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHomogenization Speed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eHigh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eMaintain 12000 rpm; evaluate stability at \u0026plusmn;\u0026thinsp;1000 rpm\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCream Base (Lanolin, Cetyl alcohol, Stearic Acid, etc.)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eMedium\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003eBalance ingredients for desired texture and stability.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003ch2\u003eDoE Optimization\u003c/h2\u003e\u003cp\u003eCCD (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) was employed to optimize surfactant mix (X₁), Homogenization time (X₂), and Homogenization speed (X₃) for nanoemulsion particle size. The 3D response surface plots (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e5\u003c/span\u003e) showed that increasing Smix ratio and speed reduced droplet size, while time had a moderate effect. The prediction profiler (Fig.\u0026nbsp;\u003cspan refid=\"Fig11\" class=\"InternalRef\"\u003e6\u003c/span\u003e) indicated an optimized particle size of 165.6 nm with a desirability of 0.83, and the interaction profiler (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e7\u003c/span\u003e) highlighted synergistic effects of the variables. Statistical validation (Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) confirmed the model\u0026rsquo;s significance, good fit, and minimal residual correlation.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eResponses of experimental trials developed via the CCD approach\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRuns\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePattern\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSmix\u003c/p\u003e\u003cp\u003e(1:1) X1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eTime\u003c/p\u003e\u003cp\u003e(min) X2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSpeed\u003c/p\u003e\u003cp\u003e(Rpm) X3\u003c/p\u003e\u003cp\u003eR1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eParticle size (nm) Y\u003c/p\u003e\u003cp\u003eR1\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eR2\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eR2\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e00A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e12000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e179.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e12000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e179.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;\u0026minus;\u0026minus;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e204.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e10000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e204.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e++\u0026minus;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e182.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e10000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e183.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0a0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e11000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e194.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e11000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e195.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e11000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e200.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e11000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e200.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e00a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e196.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e10000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e196.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;++\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e12000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e174.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e12000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e175.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;+\u0026minus;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e196.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e10000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e196.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+++\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e12000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e187.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e12000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e187.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eA00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e11000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e176.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e11000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e176.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ea00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e11000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e175.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e11000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e176.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;\u0026minus;+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e12000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e181.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e12000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e181\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u0026minus;+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e12000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e175.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e12000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e175.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0A0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e11000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e209.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e11000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e209.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e+\u0026minus;\u0026minus;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e10000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e207\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e10000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e207.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e11000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e200.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e11000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e200.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eStatistical Summary of Model Fit, ANOVA, and Durbin\u0026ndash;Watson Test\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"3\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eStatistical Value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eInterpretation\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eR\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.7883\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIndicates that 78.83% of the variation in the response is explained by the model.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAdjusted R\u0026sup2;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.7017\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAdjusted for degrees of freedom; shows a good model fit.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRoot Mean Square Error (RMSE)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.6188\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRepresents the standard deviation of residuals; smaller value indicates better precision.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean of Response\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e190.2563\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAverage response value across all observations.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eObservations\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eTotal number of experimental runs.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eModel Sum of Squares\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3588.9361\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eVariation explained by the regression model.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eError Sum of Squares\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e963.7826\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUnexplained variation (residual error).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eF Ratio\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.1026\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eIndicates model significance.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProb\u0026thinsp;\u0026gt;\u0026thinsp;F\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eModel is statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDurbin\u0026ndash;Watson Statistic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.1204\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSuggests no significant autocorrelation (ideal\u0026thinsp;\u0026asymp;\u0026thinsp;2).\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAutocorrelation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026minus;0.0784\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eVery weak negative correlation between residuals.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProb\u0026thinsp;\u0026lt;\u0026thinsp;DW\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.6720\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eConfirms independence of residuals.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003eOptimized Nanoemulsion Formulation\u003c/h2\u003e\u003cp\u003eDesign of Experiments (DoE) optimization identified the ideal formulation parameters for the sunflower oil nanoemulcream at an Smix (1:1) ratio of 4, homogenization time of 24.26 min, and speed of 12,000 rpm. The developed model predicted a particle size of 165.57 nm (95% CI: 157.37\u0026ndash;173.79 nm), demonstrating strong model accuracy and reproducibility. A desirability value of 0.83 confirmed that the formulation satisfied all QTPP and CQA criteria, ensuring stability, uniformity, and effective topical performance.\u003c/p\u003e\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\u003ch2\u003eOptimized Nanoemulsion Characterization\u003c/h2\u003e\u003cp\u003eThe optimized sunflower oil nanoemulsion exhibited a mean droplet size of 134.7\u0026thinsp;\u0026plusmn;\u0026thinsp;34.1 nm Z-average 166.9 nm, PDI 0.409 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e8\u003c/span\u003e). The zeta potential of \u0026minus;\u0026thinsp;30.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3 mV (Fig.\u0026nbsp;\u003cspan refid=\"Fig12\" class=\"InternalRef\"\u003e9\u003c/span\u003e) indicated strong electrostatic stabilization, preventing aggregation and ensuring long-term stability. These characteristics confirm the formation of a stable, nanosized system suitable for topical nanoemulcream formulation.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec26\" class=\"Section3\"\u003e\u003ch2\u003ePhysicochemical and Safety Evaluation\u003c/h2\u003e\u003cp\u003eThe sunflower oil nanoemulcream exhibited desirable physicochemical characteristics, including good spreadability, uniform texture, and excellent stability (Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). SEM images (Fig.\u0026nbsp;\u003cspan refid=\"Fig13\" class=\"InternalRef\"\u003e10\u003c/span\u003e) showed spherical, smooth, and uniformly distributed droplets at a 2 \u0026micro;m scale, confirming nanoscale uniformity, structural integrity, and consistent morphology of the formulation. Skin irritancy testing further demonstrated the nanoemulcream to be non-irritant (Table\u0026nbsp;\u003cspan refid=\"Tab8\" class=\"InternalRef\"\u003e8\u003c/span\u003e), indicating its safety and suitability for topical application.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePhysicochemical characterization of sunflower oil nanoemulcream\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eObserved Result\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eAcceptable/Standard Range for Creams\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInference\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003epH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.5\u0026ndash;6.5 (skin-friendly range)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSuitable for topical use, non-irritant\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eViscosity (cP at 25\u0026deg;C)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28,500\u0026thinsp;\u0026plusmn;\u0026thinsp;120 cP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20,000\u0026ndash;50,000 cP (semisolid creams)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eProvides spreadability \u0026amp; stability\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHomogeneity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUniform, smooth, no lumps\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eUniform, smooth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGood texture \u0026amp; user acceptability\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePhase separation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNone observed after 24 h at RT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNo separation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eStable emulsion system\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOrganoleptic properties\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWhite, characteristic Odor, smooth texture\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePleasant colour, Odor, smooth feel\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePatient-compliant\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSpreadability (gm/s)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e12.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;10 gm/s (good spreadability)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eEasily spreadable on skin\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWashability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEasily washable with tap water\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eEasily washable\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eConvenient for user\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAfter-feel\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNon-greasy, smooth, emollient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eNon-sticky, emollient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eEnhances cosmetic acceptability\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParticle size (nm)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e166.9\u0026thinsp;\u0026plusmn;\u0026thinsp;34.1nm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;200 nm (nano-range)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNanosized, enhances penetration\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePolydispersity index (PDI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.409\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.5 (moderately narrow distribution)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHomogeneous size distribution\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZeta potential (mV)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ndash;30.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3 mV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026gt;\u0026plusmn;25 mV (stable colloids)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGood electrostatic stability\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDrug content (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e94.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e90\u0026ndash;110%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHigh drug entrapment \u0026amp; uniformity\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab8\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 8\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSkin Irritancy Test Results of Sunflower Oil Nanoemulcream\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameter\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eObservation (Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, n\u0026thinsp;=\u0026thinsp;3)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGuideline Range / Scale\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInference\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eErythema (Redness)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (No redness)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0\u0026ndash;4 (OECD 404 / Draize scale)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon-irritant\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBurning / Itching\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAbsent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u0026mdash;\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eSafe for skin\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean Irritation Score (MIS)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.0\u0026ndash;0.4\u0026thinsp;=\u0026thinsp;Non-irritant; 0.5\u0026ndash;2.0\u0026thinsp;=\u0026thinsp;Slight; 2.1\u0026ndash;5.0\u0026thinsp;=\u0026thinsp;Moderate; 5.1\u0026ndash;8.0\u0026thinsp;=\u0026thinsp;Severe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003eSafe formulation (Non-irritant)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec27\" class=\"Section3\"\u003e\u003ch2\u003eIn Vitro Drug Release and Diffusion Kinetics\u003c/h2\u003e\u003cp\u003eThe in vitro drug release study over 360 minutes revealed notable differences among the formulated systems. The nanoemulsion (NE) exhibited the fastest and most extensive drug release, achieving 88% cumulative release, likely due to its nanoscale droplet size, large interfacial area, and improved drug partitioning into the aqueous phase. The nanoemulcream (NEC) showed a moderately sustained release of 64.8%, reflecting the semisolid cream matrix\u0026rsquo;s mild diffusional barrier, which slows drug migration compared to the freely dispersed nanoemulsion. The conventional cream containing sunflower oil (CMC) displayed a slower release rate (49%), consistent with the restricted drug mobility within the more viscous emulsion base. Plain sunflower oil (SO) showed the lowest release (30%), highlighting the limited diffusion from a hydrophobic, oil-dominant medium (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e11\u003c/span\u003e). Overall, these findings demonstrate that while nanoemulsions provide rapid and enhanced drug liberation, incorporation into a cream base allows for a more controlled and sustained drug release, making the nanoemulcream a promising platform for topical drug delivery that balances efficacy with practical handling advantages.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec28\" class=\"Section2\"\u003e\u003ch2\u003eDissolution Kinetics\u003c/h2\u003e\u003cp\u003eThe release data were fitted to zero-order, first-order, Higuchi, Korsmeyer\u0026ndash;Peppas, and Hixson\u0026ndash;Crowell models to elucidate the drug release mechanism. The highest correlation was observed with the Higuchi model (R\u0026sup2; = 0.903), suggesting a diffusion-controlled release. Korsmeyer\u0026ndash;Peppas equation/model for drug release (n\u0026thinsp;=\u0026thinsp;0.82, R\u0026sup2; = 0.892) suggested anomalous (non-Fickian) diffusion, involving both diffusion and matrix relaxation (Table\u0026nbsp;\u003cspan refid=\"Tab9\" class=\"InternalRef\"\u003e9\u003c/span\u003e). Other models showed lower R\u0026sup2; values, indicating less relevance in describing the release kinetics.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab9\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 9\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDrug Release Kinetic Model Results \u0026mdash; Sunflower Oil Nanoemulcream\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKinetic Model\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEquation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eR\u0026sup2;\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInterpretation\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZero-order\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQt\u0026thinsp;=\u0026thinsp;Q\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;k\u003csub\u003e0\u003c/sub\u003et\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.832\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eDoes not follow constant-rate release (low R\u0026sup2;)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFirst-order\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003elog Qt\u0026thinsp;=\u0026thinsp;log Q\u003csub\u003e0\u003c/sub\u003e\u0026thinsp;\u0026minus;\u0026thinsp;k₁t/2.303\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.846\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRelease depends on concentration; moderate fit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHiguchi\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQt\u0026thinsp;=\u0026thinsp;k\u003csub\u003eH\u003c/sub\u003e \u0026radic;t\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.903\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eBest fit \u0026rarr; diffusion-controlled mechanism\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKorsmeyer\u0026ndash;Peppas\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMt/M\u0026thinsp;\u0026infin;\u0026thinsp;=\u0026thinsp;ktⁿ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.892\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;0.82 \u0026rarr; Anomalous (non-Fickian) diffusion involving diffusion\u0026thinsp;+\u0026thinsp;cream matrix relaxation\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHixson\u0026ndash;Crowell\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eQ₀\u0026sup1;ᐟ\u0026sup3; \u0026minus; Qt\u0026sup1;ᐟ\u0026sup3; = kt\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.811\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eWeak fit \u0026mdash; erosion/dissolution not dominant\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec29\" class=\"Section2\"\u003e\u003ch2\u003eAntimicrobial Activity\u003c/h2\u003e\u003cp\u003eThe sunflower oil nanoemulcream exhibited moderate antimicrobial action against Gram-positive and Gram-negative organisms (Table\u0026nbsp;\u003cspan refid=\"Tab10\" class=\"InternalRef\"\u003e10\u003c/span\u003e). The MIC values ranged from 110 to 140 \u0026micro;g/mL, with \u003cem\u003eBacillus subtilis\u003c/em\u003e (110\u0026thinsp;\u0026plusmn;\u0026thinsp;4 \u0026micro;g/mL) showing the greatest susceptibility and \u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e (140\u0026thinsp;\u0026plusmn;\u0026thinsp;5 \u0026micro;g/mL) the least. \u003cem\u003eStaphylococcus aureus\u003c/em\u003e and \u003cem\u003eEscherichia coli\u003c/em\u003e recorded MICs of 125\u0026thinsp;\u0026plusmn;\u0026thinsp;5 and 125\u0026thinsp;\u0026plusmn;\u0026thinsp;6 \u0026micro;g/mL, respectively. The observed activity demonstrates the effective incorporation and retention of the antimicrobial constituents of sunflower oil within the nanoemulcream matrix. Enhanced efficacy can be attributed to the nanoscale droplet size, which increases surface area and facilitates the interaction of bioactive compounds with bacterial cell membranes. The comparable inhibition against both Gram positive and Gram negative strains further confirms the broad-spectrum antimicrobial potential of the optimized formulation for topical applications.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab10\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 10\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMinimum Inhibitory Concentration (MIC) of Sunflower Oil Nanoemulcream\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBacterial strain\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGram\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMIC (\u0026micro;g/mL)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInterpretation (Based on standard MIC ranges)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStaphylococcus aureus (ATCC 25923)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGram \u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e125\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModerate activity (101\u0026ndash;500 \u0026micro;g/mL)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eBacillus subtilis\u003c/em\u003e (ATCC 6633)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGram \u003csup\u003e+\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e110\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModerate activity (101\u0026ndash;500 \u0026micro;g/mL)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEscherichia coli (ATCC 25922)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGram \u003csup\u003e\u0026minus;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e125\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModerate activity (101\u0026ndash;500 \u0026micro;g/mL)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePseudomonas aeruginosa\u003c/em\u003e (ATCC 27853)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eGram \u003csup\u003e\u0026minus;\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e\u003cp\u003e140\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eModerate activity (101\u0026ndash;500 \u0026micro;g/mL)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eAccelerated Stability Study\u003c/h3\u003e\u003cp\u003eThe optimized sunflower oil nanoemulcream exhibited excellent physical stability over three months under accelerated conditions. The pH remained consistent (6.2–6.1), within the skin-compatible range, and viscosity showed negligible variation, indicating preserved semisolid consistency. The formulation maintained uniform homogeneity, smooth texture, and stable organoleptic properties, with no phase separation or visible changes observed, confirming its robustness and suitability for topical application.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study successfully developed a sunflower oil (Helianthus annuus) nanoemulcream using a QbD framework with CCD optimization. The developed nanoemulsion exhibited a mean droplet size of 134.7\u0026thinsp;\u0026plusmn;\u0026thinsp;34.1 nm, Z-average 166.9 nm, PDI 0.409, and zeta potential \u0026minus;\u0026thinsp;30.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3 mV, confirming uniform nanoscale dispersion and electrostatic stability. Incorporation into a cream base yielded a physicochemically stable and skin-compatible nanoemulcream with pH 6.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1, viscosity 28,500\u0026thinsp;\u0026plusmn;\u0026thinsp;120 cP, spreadability 12.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 g\u0026middot;s⁻\u0026sup1;, and drug content 94.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8%. Accelerated stability studies demonstrated consistent droplet size, viscosity, and drug content over three months, while skin irritancy testing verified its non-irritant behavior. In vitro drug release studies showed enhanced and sustained drug release from the nanoemulcream compared to conventional cream and plain sunflower oil. Kinetic modeling further indicated a combination of diffusion-controlled and anomalous (non-Fickian) transport mechanisms, supporting the formulation\u0026rsquo;s controlled-release characteristics. The nanoemulcream also displayed moderate broad-spectrum antibacterial activity (MIC 110\u0026ndash;140 \u0026micro;g/mL), highlighting its therapeutic potential.Overall, this work establishes a reproducible, environmentally sustainable, and therapeutically effective platform for topical delivery of natural bioactives. The findings underscore the value of QbD-guided nanoemulsion design for next-generation phytopharmaceutical creams with improved stability and safety. Although in vivo animal safety studies were not conducted in the present investigation, the strong in vitro and stability data provide a solid foundation for future preclinical animal studies to further confirm safety and therapeutic performance.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eATR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eFTIR\u0026ndash;Attenuated Total Reflectance\u0026ndash;Fourier Transform Infrared Spectroscopy\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCCD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCentral Composite Design\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCMAs\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCritical Material Attributes\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCPPs\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCritical Process Parameters\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCQAs\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCritical Quality Attributes\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDMSO\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDimethyl Sulfoxide\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDoE\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDesign of Experiments\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDSC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDifferential Scanning Calorimetry\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eGC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMS\u0026ndash;Gas Chromatography\u0026ndash;Mass Spectrometry\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHPLC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHigh\u0026ndash;Performance Liquid Chromatography\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePDI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePolydispersity Index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePEG 400\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePolyethylene Glycol 400\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003epH\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePotential of Hydrogen\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eQbD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eQuality by Design\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eQTPP\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eQuality Target Product Profile\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eRPN\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eRisk Priority Number\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMIC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eminimum inhibitory concentration\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eREM\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eRisk Evaluation Matrix\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSEM Scanning Electron\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMicroscopy.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Compliance\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not include human participants or live animals. All experimental procedures, including in vitro analyses, stability studies, and skin irritation assessments, adhered to institutional safety standards and good laboratory practices.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData and Material Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll relevant data generated or analyzed during the study are presented within this article and its supplementary information. Additional datasets can be provided by the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was carried out without any external financial support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval and Participant Consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable, as the study involved neither human nor animal subjects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCredit Authorship Contribution Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(Md Barakathulla): Conceptualization, Methodology, Writing – original draft, Supervision. (Yetukuri Koushik): Methodology, Validation, Writing – review \u0026amp; editing. (Morla Siva Prasad): Data curation, Formal analysis, Writing – review \u0026amp; editing. (Nadendla Rama Rao): Investigation, Visualization, Writing – review \u0026amp; editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of Competing Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there are no financial or personal conflicts of interest that could have influenced the work presented in this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors express their sincere gratitude to Chalapathi Institute of Pharmaceutical Sciences, Chalapathi Nagar, Lam, Guntur, Andhra Pradesh, India, for providing the facilities and opportunity to carry out this research work. The authors also thank the faculty members, laboratory staff, and their parents for their valuable support and encouragement throughout the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKumari S, Goyal A, G\u0026uuml;rer ES, Yapar EA, Garg M, Sood M, Sindhu RK (2022) Bioactive loaded novel nano-formulations for targeted drug delivery and their therapeutic potential. Pharmaceutics 14:1091. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/pharmaceutics14051091\u003c/span\u003e\u003cspan address=\"10.3390/pharmaceutics14051091\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDuarte J, Sharma A, Sharifi E, Damiri F, Berrada M, Khan MA, Singh SK, Dua K, Veiga F, Mascarenhas-Melo F, Pires PC, Paiva-Santos AC (2023) Topical delivery of nanoemulsions for skin cancer treatment. 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Gels 11(10):776. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/gels11100776\u003c/span\u003e\u003cspan address=\"10.3390/gels11100776\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Chalapathi Institute of Pharmaceutical Sciences","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Antibacterial activity, Central Composite Design (CCD), eco-pharmaceutical formulation Helianthus annuus, nanoemulcream, Quality by Design (QbD), sunflower oil, topical drug delivery.","lastPublishedDoi":"10.21203/rs.3.rs-8291953/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8291953/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e\u003cp\u003eThis study aimed to develop an eco-pharmaceutical \u003cem\u003eHelianthus Annuus\u003c/em\u003e (sunflower) oil nanoemulcream using a Quality-by-Design approach integrated with a Central Composite Design to optimize formulation and process variables for improved stability, skin compatibility, and therapeutic performance.\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e\u003cp\u003eSunflower oil was characterized using GC\u0026ndash;MS and ATR\u0026ndash;FTIR analyses. Nanoemulsions were prepared by high-speed homogenization, and key factors surfactant concentration, homogenization speed, and time were optimized using CCD to minimize particle size. The optimized nanoemulcream was evaluated for physicochemical properties, droplet size, PDI, zeta potential, morphology (SEM), stability, skin irritation, antibacterial activity, in-vitro drug release, and release kinetics.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThe developed nanoemulsion exhibited a mean droplet size of 134.7\u0026thinsp;\u0026plusmn;\u0026thinsp;34.1 nm, Z-average 166.9 nm, PDI 0.409, and zeta potential \u0026minus;\u0026thinsp;30.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3 mV, confirming uniform dispersion and electrostatic stability. The nanoemulcream showed suitable pH (6.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1), viscosity (28,500\u0026thinsp;\u0026plusmn;\u0026thinsp;120 cP), spreadability (12.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5 g\u0026middot;s⁻\u0026sup1;), high drug content (94.2\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8%), and maintained stability over three months. In-vitro release studies (360 min) demonstrated superior drug release from the nanoemulsion (88%), followed by the nanoemulcream (64.8%), cream with sunflower oil (49%), and plain sunflower oil (30%). Kinetic modeling indicated diffusion-controlled and anomalous transport mechanisms, supported by Korsmeyer\u0026ndash;Peppas n values between 0.45\u0026ndash;0.89. The formulation was non-irritant in skin studies and showed moderate broad-spectrum antibacterial activity (MIC 110\u0026ndash;140 \u0026micro;g/mL).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThe QbD-guided development enabled a stable, skin-compatible, and therapeutically effective sunflower oil nanoemulcream. Enhanced release and controlled kinetics highlight its potential as a sustainable topical delivery system for natural bioactives.\u003c/p\u003e","manuscriptTitle":"Eco – Pharmaceutical Design of a Helianthus Annuus Nanoemulcream: A QbD Optimization Strategy","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-10 09:06:33","doi":"10.21203/rs.3.rs-8291953/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"68364bca-c2f8-4c43-b08c-e4340afe9b4d","owner":[],"postedDate":"December 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":59189572,"name":"Drug Discovery, Design, \u0026 Development"}],"tags":[],"updatedAt":"2025-12-10T09:06:33+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-10 09:06:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8291953","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8291953","identity":"rs-8291953","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}