Electrospun polylactic acid and polyvinyl alcohol fibers as efficient and stable nanomaterials for immobilization of lipases

Electrospinning was applied to create easy-to-handle and high- surface-area membranes from continuous nanofibers of polyvinyl alcohol (PVA) or polylactic acid (PLA). Lipase PS from Burkholderia cepacia and Lipase B from Candida antarctica (CaLB) could be immobilized effectively by adsorption onto the fibrous material as well as by entrapment within the electrospun nanofibers. The biocatalytic performance of the resulting membrane biocatalysts was evaluated in the kinetic resolution of racemic 1-phenylethanol (rac-1) and 1-phenylethyl acetate (rac- 2). Fine dispersion of the enzymes in the polymer matrix and large surface area of the nanofibers resulted in an enormous increase in the activity of the membrane biocatalyst compared to the non-immobilized crude powder forms of the lipases. PLA as fiber-forming polymer for lipase immobilization performed better than PVA in all aspects. Recycling studies with the various forms of electrospun membrane biocatalysts in ten cycles of the acylation and hydrolysis reactions indicated excellent stability of this forms of immobilized lipases. PLA-entrapped lipases could preserve lipase activity and enantiomer selectivity much better than the PVA-entrapped forms. The electrospun membrane forms of CaLB showed high mechanical stability in the repeated acylations and hydrolyses than commercial forms of CaLB immobilized on polyacrylamide beads (Novozyme 435 and IMMCALB- T2-150). © 2016 Springer-Verlag Berlin Heidelber

Film Coating as a New Approach to Prepare Tablets Containing Long-Term Stable Lactobacillus acidophilus

This work presents a study of film coating with the vaginal strain of Lactobacillus acidophilus, the aim of which was to manufacture administrable probiotic tablets in one step and to enhance the survival rate of bacteria and their viability during storage. The results show that the film coated lactose-based tablets contained viable bacteria and the survival rate after the process was 21%, which could be enhanced up to 59% by applying protective media (trehalose, sucrose, reconstituted skim milk (RSM) during dehydration. Additionally, protective agents improved the viability of bacteria during storage too. After one year, 20% of the embedded bacteria were active when stored at –20°C, and viability dropped only one order of magnitude when stored at 7°C. It was verified that the bacteria in film coated tablets were not sensitive to higher levels of humidity owing to the moisture-moderating PVA-based coating composite

Data-driven linear parameter-varying modelling of the steering dynamics of anautonomous car

Developing automatic driving solutions and driver support systems requires accurate vehicle specific models to describe and predict the associated motion dynamics of the vehicle. Despite of the mature understanding of ideal vehicle dynamics, which are inherently nonlinear, modern cars are equipped with a wide array of digital and mechatronic components that are difficult to model. Furthermore, due to manufacturing, each car has its personal motion characteristics which change over time. Hence, it is important to develop data-driven modelling methods that are capable to capture from data all relevant aspects of vehicle dynamics in a model that is directly utilisable for control. In this paper, we show how Linear Parameter-Varying (LPV) modelling and system identification can be applied to reliably capture personalised model of the steering system of an autonomous car based on measured data. Compared to other nonlinear identification techniques, the obtained LPV model is directly utilisable for powerful controller synthesis methods of the LPV framework

Identification of the nonlinear steering dynamics of an autonomous vehicle

Automated driving applications require accurate vehicle specific models to precisely predict and control the motion dynamics. However, modern vehicles have a wide array of digital and mechatronic components that are difficult to model, manufactures do not disclose all details required for modelling and even existing models of subcomponents require coefficient estimation to match the specific characteristics of each vehicle and their change over time. Hence, it is attractive to use data-driven modelling to capture the relevant vehicle dynamics and synthesise model-based control solutions. In this paper, we address identification of the steering system of an autonomous car based on measured data. We show that the underlying dynamics are highly nonlinear and challenging to be captured, necessitating the use of data-driven methods that fuse the approximation capabilities of learning and the efficiency of dynamic system identification. We demonstrate that such a neural network based subspace-encoder method can successfully capture the underlying dynamics while other methods fall short to provide reliable results

Downstream processing of polymer-based amorphous solid dispersions to generate tablet formulations

Application of amorphous solid dispersions (ASDs) is considered one of the most promising approaches to increase the dissolution rate and extent of bioavailability of poorly water soluble drugs. Such intervention is often required for new drug candidates in that enablement, bioavailability is not sufficient to generate a useful product. Importantly, tableting of ASDs is often complicated by a number of pharmaceutical and technological challenges including poor flowability and compressibility of the powders, compression-induced phase changes or phase separation and slow disintegration due to the formation of a gelling polymer network (GPN). The design principles of an ASD-based system include its ability to generate supersaturated systems of the drug of interest during dissolution. These metastable solutions can be prone to precipitation and crystallization reducing the biopharmaceutical performance of the dosage form. The main aim of the research in this area is to maintain the supersaturated state and optimally enhance bioavailability, meaning that crystallization should be delayed or inhibited during dissolution, as well as in solid phase (e.g., during manufacturing and storage). Based on the expanding use of ASD technology as well as their downstream processing, there is an acute need to summarize the results achieved to this point to better understand progress and future risks. The aim of this review is to focus on the conversion of ASDs into tablets highlighting results from various viewpoints