Optimization of oil-in-water nanoemulsion system of <i>Ananas comosus</i> peels extract by D-optimal mixture design and its physicochemical properties

Yahya, Nur Azzanizawaty; Wahab, Roswanira Abdul; Attan, Nursyafreena; Hashim, Siti Ernieyanti; Hamid, Mariani Abdul; Noor, Norhayati Mohamed; Rahman, Amin Ur

doi:10.1080/01932691.2020.1839485

Cited by 8 publications

(6 citation statements)

References 65 publications

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“…The final optimal composition of variables suggested was used to confirm the predicted optimum values of the model. Finally, the percentage prediction error (PPE) of VCO-based nanoemulsion is calculated using equation ( 2 ) to assess the adequacy of the final reduced model [ 20 ].

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Section: Methodsmentioning

confidence: 99%

“…Furthermore, it has been used in conjunction with nanoparticles to improve the efficacy of doxorubicin, tacrine, loperamide, tubocurarine, and hexapeptide dalargin [ 19 ]. The presence of surfactants in the system, in turn, reduces the surface tension of the O/W phase to enable droplet formation, where their finite size makes it easy to penetrate through lipid membranes and deposit the bioactive compounds on the targeted site [ 20 ].…”

Section: Introductionmentioning

confidence: 99%

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Development and Optimization of Nanoemulsion from Ethanolic Extract of Centella asiatica (NanoSECA) Using D-Optimal Mixture Design to Improve Blood-Brain Barrier Permeability

Jusril

Imran

Khalil

et al. 2022

Evidence-Based Complementary and Alternative Medicine

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The evidence on the neuroprotective impact of Centella asiatica (C. asiatica) has been greatly documented in recent years. However, a major obstacle that remains to be overcome is the capacity of the active molecules in C. asiatica to cross the blood-brain barrier (BBB). In this study, we explored the possibilities of using a D-optimal mixture design to fabricate nanoemulsion of C. asiatica (NanoSECA) for better brain bioavailability. The parameters for optimization were the percentage of water (10–80% w/v) and virgin coconut oil (VCO) (10–80% w/v). Nanoemulsions were formulated using a high-pressure homogenization approach and were characterized for their physicochemical properties. The optimal VCO-based nanoemulsion (VBN: F2) conditions were found at 80% (w/v) of water and 10% (w/v) of VCO. Subsequently, viability tests were conducted on neuroblastoma (SH-SY5Y) and macrophage (RAW 264.7) cell lines. NanoSECA was distinguished for its antioxidant, acetylcholinesterase (AChE), anti-inflammatory, and parallel artificial membrane permeability assay (PAMPA) activities in vitro. The NanoSECA has a particle size of 127.833 ± 8.280 nm, zeta potential (ZP) of −24.9 ± 0.011 mV, polydispersity index (PDI) of 0.493 ± 4.681, percentage prediction error (PPE) of −12.02%, and pH of 6.0 ± 0.006 and is also stable under different storage conditions. Cell viability was improved in a dose-dependent manner on SH-SY5Y and RAW 264.7 cell lines. In addition, NanoSECA significantly reduced the AChE activity, suppressing the level of proinflammatory mediators and oxidative stress. Moreover, NanoSECA showed high BBB permeation with a high value of experimental permeability to cross the BBB. Thus, NanoSECA could efficiently potentiate the central nervous system (CNS) therapeutic activities through enhanced penetration of BBB. These nano-delivery systems are crucial to unlock the full potential of C. asiatica for treating numerous CNS disorders.

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…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Development and Optimization of Nanoemulsion from Ethanolic Extract of Centella asiatica (NanoSECA) Using D-Optimal Mixture Design to Improve Blood-Brain Barrier Permeability

Jusril

Imran

Khalil

et al. 2022

Evidence-Based Complementary and Alternative Medicine

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“…A D-optimal design is often selected because the concept of minimizing regression coefficient variance is intuitively appealing. 30 It allows for fewer experimental runs compared to any classical design available. The D-optimal design is a useful alternative when classical symmetrical designs are not applicable.…”

Section: Partitioningmentioning

confidence: 99%

Investigating and Optimizing Insulin Partitioning with Conjugated Au Nanoparticles in Aqueous Two-Phase Systems Using Response Surface Methodology

Saki Norouzi,

Rahimpour

2024

ACS Omega

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This study investigated the impact of bioconjugation on the partitioning of insulin, a clinically valuable protein, in an aqueous two-phase system. Gold nanoparticles of different sizes were synthesized and conjugated with insulin. Analysis of the conjugated insulin showed that the insulin remains fully active. Conjugated gold nanoparticles (AuNPs/insulin) were used in polyethylene glycol (PEG)−dextran aqueous two-phase systems to investigate the effect of pH, PEG and dextran molecular weights, PEG and dextran concentrations, AuNPs/insulin dosage, and nanoparticle size on the partition coefficient. These systems were chosen for their biocompatibility and low toxicity. Response surface methodology with D-optimal design was used to model and optimize these systems and their affected parameters. At the optimum condition of a pH = 8 system containing 21% PEG 4000, 5% dextran 100,000, and 100 IU AuNPs/insulin, the partition coefficient of AuNPs/insulin was found to be 192.96, which is in agreement with the empirical partition coefficient of 189.2. This is significantly higher than the partition coefficient of free insulin in a similar system. This approach could be used to overcome limitations in the feasibility of aqueous two-phase systems for industrial-scale purification of biomolecules and biopharmaceuticals.

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“…The main benefit of the D-optimal RSM lies in the fact that it can potentially fit a range of models (e.g., first order, second order, quadratic and cubic) with a smaller number of supporting experimental studies. Hence, it is not surprising that D-optimal design is frequently selected by the cosmetic and pharmaceutical industries, especially when formulating emulsion systems—from nanoemulsions to creams [ 16 , 17 , 18 ].…”

Section: Introductionmentioning

confidence: 99%

Efficient Development of Green Emulsifier/Emollient-Based Emulsion Vehicles: From RSM Optimal Experimental Design to Abridged In Vivo Assessment

et al. 2023

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Since natural-origin, sustainable ingredients are preferred by modern consumers, novel emulsifiers and emollients keep entering the market. This study hypothesizes that a combination of in silico, instrumental tools and simplified sensory studies could be used to efficiently characterize emulsions in a shorter timeframe. A total of 22 rather simple o/w emulsions were prepared by a time/energy-saving emulsification process. A natural mixed emulsifier (Lauryl Glucoside/Myristyl Glucoside/Polyglyceryl-6 Laurate) and two emollients (both with INCI name C15–19 Alkane) were used. The performed D-optimal experimental design within the response surface method (RSM) significantly narrowed down the number of samples about to enter the stage of texture, friction and sensory studies to the samples comprising 30% of a respective Emogreen emollient and 2% or 3% of the emulsifier. The sample comprising 2% emulsifier/30% Emogreen® L15 showed significantly higher firmness (42.12 mN) when compared to the one with 2% emulsifier/30% Emogreen® L19 (33.62 mN), which was somewhat unexpected considering the emollients’ inherent viscosity values (4.5 mPa·s for L15 and 9 mPa·s for L19). The sample with 2% emulsifier/30% Emogreen® L19 managed to maintain the lowest friction, while the one with 3% emulsifier/30% Emogreen® L19 released its full lubricating potential in the second part of the measurement (30–60 s). The obtained results revealed the strengths and weaknesses of each formulation, narrowing down their possible applications in the early development stage.

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Optimization of oil-in-water nanoemulsion system of Ananas comosus peels extract by D-optimal mixture design and its physicochemical properties

Cited by 8 publications

References 65 publications

Development and Optimization of Nanoemulsion from Ethanolic Extract of Centella asiatica (NanoSECA) Using D-Optimal Mixture Design to Improve Blood-Brain Barrier Permeability

Development and Optimization of Nanoemulsion from Ethanolic Extract of Centella asiatica (NanoSECA) Using D-Optimal Mixture Design to Improve Blood-Brain Barrier Permeability

Investigating and Optimizing Insulin Partitioning with Conjugated Au Nanoparticles in Aqueous Two-Phase Systems Using Response Surface Methodology

Efficient Development of Green Emulsifier/Emollient-Based Emulsion Vehicles: From RSM Optimal Experimental Design to Abridged In Vivo Assessment

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