The development of predictive engines based on pharmacokinetic-physiological mathematical models for personalised dosage recommendations is an immature field. Nevertheless, these models are extensively applied during the design of new drugs. This study presents new advances in this subject, through a stable population of patients who underwent kidney transplantation and were prescribed tacrolimus. We developed 2 new population pharmacokinetic models based on a compartmental approach, with one following the physiologically based pharmacokinetic approach and both including circadian modulation of absorption and clearance variables. One of the major findings was an improved predictive capability for both models thanks to the consideration of circadian rhythms, both in estimating the population and in Bayesian individual customisation. This outcome confirms a plausible mechanism suggested by other authors to explain circadian patterns of tacrolimus concentrations. We also discovered significant intrapatient variability in tacrolimus levels a week after the conversion from a fast-release (Prograf) to a sustained-release formulation (Advagraf) using adaptive optimisation techniques, despite high adherence and controlled conditions. We calculated the intrapatient variability through parametric intrapatient variations, which provides a method for quantifying the mechanisms involved. We present a first application for the analysis of bioavailability changes in formulation conversion. The 2 pharmacokinetic models have demonstrated their capability as predictive engines for personalised dosage recommendations, although the physiologically based pharmacokinetic model showed better predictive behaviour.

Serial plates are not reasonable in material saving and stress dispersion. To design orthopedic plates ideally and conveniently, this paper proposes a method to optimize plates through editing semantic parameters based on average bone model. Firstly, for the reasonable distribution of serial plates in number and size, an average bone model is created from the existing bones, among which each bone has a contribution to the average model. Secondly, a common orthopedic plate with semantic parameters is constructed on average bone model and it can be conveniently modified. Lastly, optimizing the thickness of the plate through finite element analysis and genetic algorithm to meet the stress condition and use as little material as possible. The simulation results indicate that the method can save material and disperse the stress of the plates so that it can effectively optimize the orthopedic plates.

Despite the intense research in the last decade with the aim of developing a reliable solution for fall detection in the elderly and other risk populations, it can be asserted that the diffusion of fall detectors in the geriatric practice is near null. This scenario is similar to the very scarce use of telemedicine in healthcare. The present work begins analyzing why fall detectors have not achieved to permeate the industry. That road is used to know the drawbacks of current devices and systems, besides to allow studying several important concepts underlying the principles of fall detection. A novel smart detection system based on that survey is finally briefly presented. The design of this device is founded on the experience and results obtained by an earlier device that was designed in the framework of the thesis of one of the authors.

The emergence of computer-aided design (CAD) has propelled the evolution of the sheet metal engineering field. Sheet metal design software tools include parameters associated to the part’s forming process during the pattern drawing calculation. Current methods avoid the calculation of a first pattern drawing of the flattened part’s neutral surface, independent of the forming process, leading to several methodological limitations. The study evaluates the reliability of the Computer Extended Descriptive Geometry (CeDG) approach to surpass those limitations. Three study cases that cover a significative range of sheet metal systems are defined and the associated solid models and patterns’ drawings are computed through Geogebra-based CeDG and two selected CAD tools (Solid Edge 2020, LogiTRACE v14), with the aim of comparing their reliability and accuracy. Our results pointed to several methodological lacks in LogiTRACE and Solid Edge that prevented to solve properly several study cases. In opposition, the novel CeDG approach for the computer parametric modeling of 3D geometric systems overcame those limitations so that all models could be built and flattened with accuracy and without methodological limitations. As additional conclusion, the success of CeDG suggests the necessity to recover the relevance of descriptive geometry as a key core in graphic engineering.

No abstract