Optimizing Biodegradable Starch-Based Composite Films Formulation for Wound-Dressing Applications.

This paper utilizes response surface methodology (RSM) design-based analyses to optimize starch-based wound dressings that were characterized based on weight loss (WL%), swelling index (SI%), and mechanical strength (TS). The wound-dressing materials were prepared by employing a modified casting method, using various concentrations of starch (0.5-2 w/w%), polyvinyl alcohol (PVA) (0.5-2 weight%), citric acid (1.5-4 weight%), and glycerol (1.5-4 weight%) to yield wound-dressing films with appropriate combinations of in vitro degradation, swelling index, and tensile strength. As a result of the response surface method-based analysis, the swelling index, in vitro degradation, and tensile strength were linearly related to variations in the formulation of organic components. Based on our experimental investigations, the optimized film (formulation: 1 weight% PVA, 2 weight% starch, 1.5 weight% citric acid, and 1.5 weight% glycerol) exhibited an outstanding swelling index (343.52%), suitable in vitro degradation (53.22%), and excellent tensile strength (8.82 MPa). The response surface plots for the dependent variables, swelling index (SI%), weight loss (WL%), and mechanical strength (TS), showed that in all dual relations, the PVA-starch combination significantly affected all dependent variables; however, the PVA-citric acid interaction showed the most excellent effect on the swelling index. As a result, every component of the resulting film had a lesser amount of all ingredients to achieve better properties at a lower material cost. Starch-based/PVA films have been identified in this paper as optimal and more affordable wound-dressing films.

Comparative Evaluation of Artificial Neural Networks and Data Analysis in Predicting Liposome Size in a Periodic Disturbance Micromixer.

Artificial neural networks (ANN) and data analysis (DA) are powerful tools for supporting decision-making. They are employed in diverse fields, and one of them is nanotechnology; for example, in predicting silver nanoparticles size. To our knowledge, we are the first to use ANN to predict liposome size (LZ). Liposomes are lipid nanoparticles used in different biomedical applications that can be produced in Dean-Forces-based microdevices such as the Periodic Disturbance Micromixer (PDM). In this work, ANN and DA techniques are used to build a LZ prediction model by using the most relevant variables in a PDM, the Flow Rate Radio (FRR), and the Total Flow Rate (TFR), and the temperature, solvents, and concentrations were kept constant. The ANN was designed in MATLAB and fed data from 60 experiments with 70% training, 15% validation, and 15% testing. For DA, a regression analysis was used. The model was evaluated; it showed a 0.98147 correlation coefficient for training and 0.97247 in total data compared with 0.882 obtained by DA.

Parametric Study of the Factors Influencing Liposome Physicochemical Characteristics in a Periodic Disturbance Mixer.

Liposomes encapsulate different substances ranging from drugs to genes. Control over the average size and size distribution of these nanoparticles is vital for biomedical applications since these characteristics determine to a high degree where liposomes will accumulate in the human body. Micromixers enable the continuous flow synthesis of liposomes, improving size control and reproducibility. Recently, Dean flow dynamics-based micromixers, such as the periodic disturbance mixer (PDM), have been shown to produce controlled-size liposomes in a scalable and reproducible way. However, contrary to micromixers based on molecular diffusion or chaotic advection, their production factors and their influence over liposome properties have not yet been addressed thoroughly. In this work, we present a comprehensive parametric study of the effects of flow conditions and molecular changing factors such as concentration, lipid type, and temperature on the physicochemical characteristics of liposomes. Numerical models and confocal images are used to quantitatively and qualitatively evaluate mixing performance under different liposome production conditions and their relationship with vesicle properties. The total flow rate (TFR) and, to a lesser extent, the flow rate ratio (FRR) control the liposome size and size distribution. Effects on liposome size are also observed by changing the molecular factors. Moreover, the liposome ζ potential is independent of the factors studied here. The micromixer presented in this work enables the production of liposomes as small as 24 nm, with monodispersed to low or close to low polydispersed liposome populations as well as a production rate as high as 41 mg/h.

Surface Response Based Modeling of Liposome Characteristics in a Periodic Disturbance Mixer.

Liposomes nanoparticles (LNPs) are vesicles that encapsulate drugs, genes, and imaging labels for advanced delivery applications. Control and tuning liposome physicochemical characteristics such as size, size distribution, and zeta potential are crucial for their functionality. Liposome production using micromixers has shown better control over liposome characteristics compared with classical approaches. In this work, we used our own designed and fabricated Periodic Disturbance Micromixer (PDM). We used Design of Experiments (DoE) and Response Surface Methodology (RSM) to statistically model the relationship between the Total Flow Rate (TFR) and Flow Rate Ratio (FRR) and the resulting liposomes physicochemical characteristics. TFR and FRR effectively control liposome size in the range from 52 nm to 200 nm. In contrast, no significant effect was observed for the TFR on the liposomes Polydispersity Index (PDI); conversely, FRR around 2.6 was found to be a threshold between highly monodisperse and low polydispersed populations. Moreover, it was shown that the zeta potential is independent of TFR and FRR. The developed model presented on the paper enables to pre-establish the experimental conditions under which LNPs would likely be produced within a specified size range. Hence, the model utility was demonstrated by showing that LNPs were produced under such conditions.