Formulation and Evaluation of Herbal Shampoo: A Comparative Study By DoE/QbD Approach

Some ancient medications were used to make the hair care herbal shampoo powder. Organoglytics, powder characteristics, foam test, and physical evaluation were performed on Tulsi, Shikakai, Heena, Bahera, Amla, Neem, and Brahmi. Existing inspections will assist set standards and assessment criteria, which will undoubtedly aid to standardise the quality and purity of these herbal powder shampoos, due to the selection of drugs once the drugs are used together or jointly. We optimise the formula with the help of the Design of Experiments as per the Quality by Design approach. This paper illustrates broad theoretical as well as practical view of advanced screening design. In addition to the statistical concept‟s regression analysis, parato chart, residual diagnosis, main effect plot, interaction effect plot, design space and multiple response prediction.

Resveratrol Nanocrystal Incorporated into Mesoporous Material: Rational Design and Screening through Quality-by-Design Approach

Bioflavonoids from grape seeds feature powerful antioxidant and immunostimulant activities, but they present problems related to solubility and bioavailability. Nanocrystal (NC) incorporated into a mesoporous carrier is a promising strategy to address these issues. However, the preparation of this formulation involves the selection of factors affecting its critical quality attributes. Hence, this study aimed to develop an NC formulation incorporating resveratrol into a soluble mesoporous carrier based on rational screening design using a systematic and continuous development process, the quality-by-design paradigm. A mesoporous soluble carrier was prepared by spray-drying mannitol and ammonium carbonate. The NC was obtained by introducing the evaporated solvent containing a drug/polymer/surfactant and mesoporous carrier to the medium. A 26−2 fractional factorial design (FFD) approach was carried out in the screening process to understand the main effect factors. The type and concentration of polymer and surfactant, resveratrol loading, and solvent were determined on the NC characteristics. The results indicated that drug loading, particle size, and solubility were mainly affected by RSV loading, PEG concentration, and Kolliphor EL concentration. The polymer contributed dominantly to reducing the particle size and enhancing solubility in this screening design. The presence of surfactants in this system made it possible to prolong the supersaturation process. According to the 26−2 FFD, the factors selected to be further developed using a statistical technique according to the quality-by design-approach, Box Behnken Design, were Kolliphor EL, PEG400, and RSV loading.

Response Surface Optimization for Simultanous Estimation of Sofosbuvir and Velpatasvir in Human Plasma Sample

An efficient column friendly, buffer free, highly sensitive, cost effective RP-HPLC method was developed by considering the criticality of different method parameters on analytical attributes like tailing factor, resolution and retention time in preliminary risk analysis and screening designs. The Pareto analysis of screening design highlighted the need for optimization of resolution and its influencers (capacity factor and theoretical plates) for both the drugs to imbibe quality in the method. The suggested method of optimization design was developed using ZODIAC C18 ODS (250 mm × 4.6 mm, 5 μm) column in isocratic mode using mobile phase acetonitrile : methanol : water in the ratio of 60:10:30 at a flow rate of 0.8 mL/min and UV detection wavelength of 262 nm. The retention times of drugs were found to be 3.488 minutes for sofosbuvir, 5.387 minutes for velpatasvir. The linear regression analysis data for the calibration plots showed good linear relationship with r2=0.997 for sofosbuvir, r2=0.988 for velpatasvir, in the working concentration range of 1000-5000 ng/mL, 250-1250 ng/mL respectively. The AQbD devised method was applied for quantification of drugs in plasma and validated as suggested in ICH M10 guidelines.

Clever Experimental Designs: Shortcuts for Better iPSC Differentiation

For practical use of pluripotent stem cells (PSCs) for disease modelling, drug screening, and regenerative medicine, the cell differentiation process needs to be properly refined to generate end products with consistent and high quality. To construct and optimize a robust cell-induction process, a myriad of cell culture conditions should be considered. In contrast to inefficient brute-force screening, statistical design of experiments (DOE) approaches, such as factorial design, orthogonal array design, response surface methodology (RSM), definitive screening design (DSD), and mixture design, enable efficient and strategic screening of conditions in smaller experimental runs through multifactorial screening and/or quantitative modeling. Although DOE has become routinely utilized in the bioengineering and pharmaceutical fields, the imminent need of more detailed cell-lineage specification, complex organoid construction, and a stable supply of qualified cell-derived material requires expedition of DOE utilization in stem cell bioprocessing. This review summarizes DOE-based cell culture optimizations of PSCs, mesenchymal stem cells (MSCs), hematopoietic stem cells (HSCs), and Chinese hamster ovary (CHO) cells, which guide effective research and development of PSC-derived materials for academic and industrial applications.

ChemSpaX: Exploration of Chemical Space by Automated Functionalization of Molecular Scaffold

Exploration of the local chemical space of molecular scaffolds by post-functionalization (PF) is a promising route to discover novel molecules with desired structure and function. PF with rationally chosen substituents based on known electronic and steric properties is a commonly used experimental and computational strategy in screening, design and optimization of catalytic scaffolds. Automated generation of reasonably accurate geometric representations of post-functionalized molecular scaffolds is highly desirable for data-driven applications. However, automated PF of transition metal (TM) complexes remains challenging. In this work a Python-based workflow, ChemSpaX, that is aimed at automating the PF of a given molecular scaffold with special emphasis on TMcomplexes, is introduced. In three representative applications of ChemSpaX by comparing with DFT and DFT-B calculations, we show that the generated structures have a reasonable quality for use in computational screening applications. Furthermore, we show thatChemSpaXgenerated geometries can be used in machine learning applications to accurately predict DFT computed HOMO-LUMO gaps for transition metal complexes.ChemSpaXis open-source and aims to bolster and democratize the efforts of the scientific community towards data-driven chemical discovery.

Targeting the energy-coupling factor (ECF) transporters: identification of new tool compounds

The energy-coupling factor (ECF) transporters are a family of transmembrane proteins involved in the uptake of vitamins in a wide range of bacteria. Inhibition of the activity of these proteins could reduce the viability of pathogens that depend on vitamin uptake. Their central role in the metabolism of bacteria and absence in humans make the ECF transporters a potential antibacterial target, which can be further investigated making use of a selective chemical probe. Here, we report on the virtual screening, design, synthesis, structure–activity relationships (SARs) and coarse-grained molecular dynamics simulations of the first class of inhibitors of the ECF transporters. We investigated the mechanism of action of this chemical class and profiled the best hit compounds regarding their pharmaceutical properties. The optimized hit has a minimum inhibitory concentration (MIC) value of 2 µg/mL against Streptococcus pneumoniae, which opens up the possibility to use this chemical class to investigate the role of the ECF transporters in health and disease.

Application of Plackett-Burman design for screening of factors affecting pitavastatin nanoparticle formulation development

Introduction: Nanoparticle formulation of pitavastatin calcium is a potential alternative to solve the solubility related problem. However, the formulation of nanoparticle involves various parameters that affect product quality. Plackett-Burman design could facilitate an economical experimental plan that focuses on determining the relative significance of many. Aim: The objective of this study was to screen the variables which could significantly affect the pitavastatin nanoparticle formulation. Materials and methods: The pitavastatin nanoparticles were formulated by preparing nanosuspension using the emulsion solvent evaporation technique followed by freeze-drying. A Plackett-Burman screening design methodology was employed in which seven factors at two levels were tested at 12 runs to study the effect of formulation and process variables on particle size and polydispersity index of nanoparticles. The surface morphology and crystalline nature of nanoparticle were also evaluated. Results: The particle size and polydispersity index of nanosuspension was found in the range of 113.1 to 768.5 nm and 0.068 to 0.508, respectively. Statistical analysis of various variables revealed that stabilizer concentration, injection flow rate, and stirring rate were the most influential factors affecting the particle size and polydispersity index of the formulation. X-ray diffraction (XRD) and scanning electron microscopy (SEM) study suggested the amorphous nature of nanoparticles. Conclusions: This study concluded that the Plackett-Burman design was an efficient tool for screening the process and formulation variables affecting the properties of pitavastatin nanoparticles and also for the identification of the most prominent factor.