An Adaptive Finite Time Sliding Mode Observer

This chapter develops a novel adaptive ?nite time observer which can achieve ?nite time unmatched parameter estimation and ?nite time system state observation. The proposed approach has strong robustness and rapid convergence. A step by step proof is given which employs ?nite time stability and sliding mode principles. It is seen that the method also enables lumped matched uncertainty to be estimated. An illustrative example is used to validate the effectiveness of the proposed approach

Quality by design: Scale-up of freeze-drying cycles in pharmaceutical industry

This paper shows the application of mathematical modeling to scale-up a cycle developed with lab-scale equipment on two different production units. The above method is based on a simplified model of the process parameterized with experimentally determined heat and mass transfer coefficients. In this study, the overall heat transfer coefficient between product and shelf was determined by using the gravimetric procedure, while the dried product resistance to vapor flow was determined through the pressure rise test technique. Once model parameters were determined, the freeze-drying cycle of a parenteral product was developed via dynamic design space for a lab-scale unit. Then, mathematical modeling was used to scale-up the above cycle in the production equipment. In this way, appropriate values were determined for processing conditions, which allow the replication, in the industrial unit, of the product dynamics observed in the small scale freeze-dryer. This study also showed how inter-vial variability, as well as model parameter uncertainty, can be taken into account during scale-up calculations

MYOD-SKP2 axis boosts tumorigenesis in fusion negative rhabdomyosarcoma by preventing differentiation through p57Kip2 targeting.

Rhabdomyosarcomas (RMS) are pediatric mesenchymal-derived malignancies encompassing PAX3/7-FOXO1 Fusion Positive (FP)-RMS, and Fusion Negative (FN)-RMS with frequent RAS pathway mutations. RMS express the master myogenic transcription factor MYOD that, whilst essential for survival, cannot support differentiation. Here we discover SKP2, an oncogenic E3-ubiquitin ligase, as a critical pro-tumorigenic driver in FN-RMS. We show that SKP2 is overexpressed in RMS through the binding of MYOD to an intronic enhancer. SKP2 in FN-RMS promotes cell cycle progression and prevents differentiation by directly targeting p27Kip1 and p57Kip2, respectively. SKP2 depletion unlocks a partly MYOD-dependent myogenic transcriptional program and strongly affects stemness and tumorigenic features and prevents in vivo tumor growth. These effects are mirrored by the investigational NEDDylation inhibitor MLN4924. Results demonstrate a crucial crosstalk between transcriptional and post-translational mechanisms through the MYOD-SKP2 axis that contributes to tumorigenesis in FN-RMS. Finally, NEDDylation inhibition is identified as a potential therapeutic vulnerability in FN-RMS

Emerging Freeze-Drying Process Development and Scale-up Issues

Although several guidelines do exist for freeze-drying process development and scale-up, there are still a number of issues that require additional attention. The objective of this review article is to discuss some emerging process development and scale-up issue with emphasis on effect of load condition and freeze-drying in novel container systems such as syringes, Lyoguard trays, ampoules, and 96-well plates. Understanding the heat and mass transfer under different load conditions and for freeze-drying in these novel container systems will help in developing a robust freeze-drying process which is also easier to scale-up. Further research and development needs in these emerging areas have also been addressed