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Assessment of Fractional Factorial Design for the Selection and Screening of Appropriate Components of a Self-nanoemulsifying Drug Delivery System Formulation.

ABSTRACT: Purpose: Recently, a self-nanoemulsifying drug delivery system (SNEDDS) has shown great improvement in the enhancement of drug bioavailability. The selection of appropriate compositions in the SNEDDS formulation is the fundamental step towards developing a successful formulation. This study sought to evaluate the effectiveness of fractional factorial design (FFD) in the selection and screening of a SNEDDS composition. Furthermore, the most efficient FFD approach would be applied to the selection of SNEDDS components. Methods: The types of oil, surfactant, co-surfactant, and their concentrations were selected as factors. 2⁶ full factorial design (FD) (64 runs), 2^6-1 FFD (32 runs), 2^6-2 FFD (16 runs), and 2^6-3 FFD (8 runs) were compared to the main effect contributions of each design. Ca-pitavastatin (Ca-PVT) was used as a drug model. Screening parameters, such as transmittance, emulsification time, and drug load, were selected as responses followed by particle size along with zeta potential for optimized formulation. Results: The results indicated that the patterns of 2⁶ full FD and 2^6-1 for both main effects and interactions were similar. 2^6-3 FFD lacked adequate precision when used for screening owing to the limitation of design points. In addition, capryol, Tween 80, and transcutol P were selected to be developed in a SNEDDS formulation with a particle size of 69.7± 5.3 nm along with a zeta potential of 33.4± 2.1 mV. Conclusion: Herein, 2^6-2 FFD was chosen as the most efficient and adequate design for the selection and screening of SNEDDS composition. The optimized formulation fulfilled the requirement of a quality target profile of a nanoemulsion.

SUBMITTER: Kuncahyo I

PROVIDER: S-EPMC6912180 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Assessment of Fractional Factorial Design for the Selection and Screening of Appropriate Components of a Self-nanoemulsifying Drug Delivery System Formulation.

Kuncahyo Ilham I Choiri Syaiful S Fudholi Achmad A Martien Ronny R Rohman Abdul A

Advanced pharmaceutical bulletin 20191024 4

<i><b>Purpose:</b></i> Recently, a self-nanoemulsifying drug delivery system (SNEDDS) has shown great improvement in the enhancement of drug bioavailability. The selection of appropriate compositions in the SNEDDS formulation is the fundamental step towards developing a successful formulation. This study sought to evaluate the effectiveness of fractional factorial design (FFD) in the selection and screening of a SNEDDS composition. Furthermore, the most efficient FFD approach would be applied to ...[more]

PMID: 31857965

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Project description:The development of self-nanoemulsifying drug delivery systems (SNEDDS) to enhance the oral bioavailability of lipophilic drugs is usually based on traditional one-factor-at-a-time approaches. These approaches may be inadequate to analyse the effect of each excipient and their potential interactions on the emulsion droplet size formed when dispersing the SNEDDS in an aqueous environment. The current study investigates the emulsion droplet sizes formed from SNEDDS containing different levels of the natural surfactant monoacyl phosphatidylcholine to reduce the concentration of the synthetic surfactant polyoxyl 40 hydrogenated castor oil (Kolliphor® RH40). Monoacyl phosphatidylcholine was used in the form of Lipoid S LPC 80 (LPC, containing approximately 80% monoacyl phosphatidylcholine, 13% phosphatidylcholine and 4% concomitant components). The investigated SNEDDS comprised of long-chain or medium-chain glycerides (40% to 75%), Kolliphor® RH40 (5% to 55%), LPC (0 to 40%) and ethanol (0 to 10%). D-optimal design, multiple linear regression, and partial least square regression were used to screen different SNEDDS within the investigated excipient ranges and to analyse the effect of each excipient on the resulting droplet size of the dispersed SNEDDS measured by dynamic light scattering. All investigated formulations formed nano-emulsions with droplet sizes from about 20 to 200?nm. The use of medium-chain glycerides was more likely to result in smaller and more monodisperse droplet sizes compared to the use of long-chain glycerides. Kolliphor® RH40 exhibited the most significant effect on reducing the emulsion droplet sizes. Increasing LPC concentration increased the emulsion droplet sizes, possibly because of the reduction of Kolliphor® RH40 concentration. A higher concentration of ethanol resulted in an insignificant reduction of the emulsion droplet size. The study provides different ternary diagrams of SNEDDS containing LPC and Kolliphor® RH40 as a reference for formulation developers.

Project description:BackgroundPretreatments are one of the main bottlenecks for the lignocellulose conversion process and the search for cheaper and effective pretreatment methodologies for each biomass is a complex but fundamental task. Here, we used a 2ν5-1 fractional factorial design (FFD) to optimize five pretreatment variables: milling time, temperature, double treatment, chemical concentration, and pretreatment time in acid-alkali (EA) and acid-organosolv (EO) pretreatments, applied to elephant grass leaves.ResultsFFD allowed optimization of the pretreatment conditions using a reduced number of experiments and allowed the identification of secondary interactions between the factors. FFD showed that the temperature can be kept at its lower level and that the first acid step can be eliminated in both pretreatments, without significant losses to enzymatic hydrolysis. EA resulted in the highest release of reducing sugars (maximum of 205 mg/g substrate in comparison to 152 mg/g in EO and 40 mg/g in the untreated sample), using the following conditions in the alkali step: [NaOH] = 4.5% w/v; 85 °C and 100 min after ball milling the sample. The factors statistically significant (P < 0.05) in EA pretreatment were NaOH concentration, which contributes to improved hydrolysis by lignin and silica removal, and the milling time, which has a mechanical effect. For EO samples, the statistically significant factors to improved hydrolysis were ethanol and catalyst concentrations, which are both correlated to higher cellulose amounts in the pretreated substrates. The catalyst is also correlated to lignin removal. The detailed characterization of the main hemicellulosic sugars in the solids after pretreatments revealed their distinct recalcitrance: glucose was typically more recalcitrant than xylose and arabinose, which could be almost completely removed under specific pretreatments. In EA samples, the removal of hemicellulose derivatives was very dependent on the acid step, especially arabinose removal.ConclusionThe results presented herewith contribute to the development of more efficient and viable pretreatments to produce cellulosic ethanol from grass biomasses, saving time, costs and energy. They also facilitate the design of enzymatic cocktails and a more appropriate use of the sugars contained in the pretreatment liquors, by establishing the key recalcitrant polymers in the solids resulting from each processing step.

Project description:The 3D printing techniques have been explored extensively in recent years for pharmaceutical manufacturing and drug delivery applications. The current investigation aims to explore 3D printing for the design and development of a nanomedicine-based oral solid dosage form of a poorly water-soluble drug. A self-nanoemulsifying tablet formulation of dapagliflozin propanediol monohydrate was developed utilizing the semisolid pressure-assisted microsyringe (PAM) extrusion-based 3D printing technique. The developed formulation system consists of two major components (liquid and solid phase), which include oils (caproyl 90, octanoic acid) and co-surfactant (PEG 400) as liquid phase while surfactant (poloxamer 188) and solid matrix (PEG 6000) as solid-phase excipients that ultimately self-nanoemulsify as a drug encapsulated nanoemulsion system on contact with aqueous phase/gastrointestinal fluid. The droplet size distribution of the generated nanoemulsion from a self-nanoemulsifying 3D printed tablet was observed to be 104.7 ± 3.36 nm with polydispersity index 0.063 ± 0.024. The FT-IR analysis of the printed tablet revealed that no drug-excipients interactions were observed. The DSC and X-RD analysis of the printed tablet revealed that the loaded drug is molecularly dispersed in the crystal lattice of the tablet solid matrix and remains solubilized in the liquid phase of the printed tablet. SEM image of the drug-loaded self-nanoemulsifying tablets revealed that dapagliflozin propanediol monohydrate was completely encapsulated in the solid matrix of the printed tablet, which was further confirmed by SEM-EDS analysis. The in vitro dissolution profile of dapagliflozin-loaded self-nanoemulsifying tablet revealed an immediate-release drug profile for all three sizes (8 mm, 10 mm, and 12 mm) tablets, exhibiting >75.0% drug release within 20 min. Thus, this study has emphasized the capability of the PAM-based 3D printing technique to print a self-nanoemulsifying tablet dosage form with an immediate-release drug profile for poorly water-soluble drug.

Project description:BackgroundAudit and feedback aims to improve patient care by comparing healthcare performance against explicit standards. It is used to monitor and improve patient care, including through National Clinical Audit (NCA) programmes in the UK. Variability in effectiveness of audit and feedback is attributed to intervention design; separate randomised trials to address multiple questions about how to optimise effectiveness would be inefficient. We evaluated different feedback modifications to identify leading candidates for further "real-world" evaluation.MethodsUsing an online fractional factorial screening experiment, we randomised recipients of feedback from five UK NCAs to different combinations of six feedback modifications applied within an audit report excerpt: use effective comparators, provide multimodal feedback, recommend specific actions, provide optional detail, incorporate the patient voice, and minimise cognitive load. Outcomes, assessed immediately after exposure to the online modifications, included intention to enact audit standards (primary outcome, ranked on a scale of -3 to +3, tailored to the NCA), comprehension, user experience, and engagement.ResultsWe randomised 1241 participants (clinicians, managers, and audit staff) between April and October 2019. Inappropriate repeated participant completion occurred; we conservatively excluded participant entries during the relevant period, leaving a primary analysis population of 638 (51.4%) participants. None of the six feedback modifications had an independent effect on intention across the five NCAs. We observed both synergistic and antagonistic effects across outcomes when modifications were combined; the specific NCA and whether recipients had a clinical role had dominant influences on outcome, and there was an antagonistic interaction between multimodal feedback and optional detail. Among clinical participants, predicted intention ranged from 1.22 (95% confidence interval 0.72, 1.72) for the least effective combination in which multimodal feedback, optional detail, and reduced cognitive load were applied within the audit report, up to 2.40 (95% CI 1.88, 2.93) for the most effective combination including multimodal feedback, specific actions, patient voice, and reduced cognitive load.ConclusionPotentially important synergistic and antagonistic effects were identified across combinations of feedback modifications, audit programmes, and recipients, suggesting that feedback designers must explicitly consider how different features of feedback may interact to achieve (or undermine) the desired effects.Trial registrationInternational Standard Randomised Controlled Trial Number: ISRCTN41584028.

Dataset Information

Assessment of Fractional Factorial Design for the Selection and Screening of Appropriate Components of a Self-nanoemulsifying Drug Delivery System Formulation.

Publications

Assessment of Fractional Factorial Design for the Selection and Screening of Appropriate Components of a Self-nanoemulsifying Drug Delivery System Formulation.

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