A Framework for Interactive Structural Design Exploration

Rapid advances in additive manufacturing and topology optimization enable unprecedented levels of design freedom for realizing complex structures. The challenge is that the increasing design freedom is accompanied by increasing complexity, such that it can become difficult for either computational algorithms or human designers alone to search these expansive design spaces effectively. Our goal is to establish an interactive design framework that is both data-driven and designer-guided so that human designers can work together with computational algorithms to search structural design spaces more effectively. The framework builds upon classical topology optimization techniques to build a library of designs for a class of problems. A conditional generative adversarial network (cGAN) is trained to establish a latent representation of the library and to support rapid exploration of candidate designs. The library of designs is clustered based on visual similarity. The user selects clusters with desirable features, and the underlying latent representation is manipulated to generate visually similar candidate designs with adjustable levels of diversity or similarity to the selected clusters. The framework enables designers to use their expertise and intuition to guide the algorithm towards promising solutions by screening designs quickly and eliminating clusters of designs that may not be desirable for reasons that are difficult to embed within the optimization itself but are recognizable and significant to a human designer (e.g., secondary functionality, aesthetics).

Experimental Design: Approaches and Applications in Development of Pharmaceutical Drug Delivery System

Conventionally, all the delivery systems have been prepared by methodology of trial and error concept by manipulating one variable at a Time, but attainment of optimal formulation is not achievable. The systematic approach Design of Experiments (DoE) enables researchers to provide appropriate outline to develop a best optimized delivery system. Optimization techniques using DoE helps to provide effective and economical analytical tools to find the perfect solution for a particular problem. In screening designs, there is large number of screening factors in minimum number of experiments and beneficial to minimize the variables in a desired size therefore further experimentation may be performed easily by using these variables. Experimental designs and optimization techniques are the tools which are systematically used to categorize various types of problems that may influence development of pharmaceutical delivery system. Use of experimental design is the best approach to the screening and optimization of experimental factors. In the present review article we have focused on application of practically applicable experimental designs and optimization techniques for the development of quality and efficacious of pharmaceutical formulations such as, nanoparticles, Phytosomes, microspheres, liposomes, micells, films, nanostructured lipid carriers and tablets and which type of factors to be considered while optimization are also discussed. Keywords: Experimental design, Optimization, Applications, Drug delivery, Phytosomes, Nano delivery System.

Liquid biopsy in lung cancer: tertiary prevention potential

Background In the era of personalized therapy liquid biopsy is considered an important diagnostic tool in the clinical management of cancer patients. Tissue specimen represents “gold standard” for molecular evaluation of specific gene targets alterations that lead cancer patients to benefit of a “tailed therapy” based on molecular features of the tumor. This innovative source of nucleic acids was introduced in clinical setting only for NSCLC patients to test Epidermal Grow Factor Receptor (EGFR) mutations when tissue is not available or to monitor acquired resistance mutation after a first line of treatment. The study aimed at assessing the diagnostic potential of liquid biopsy in balanced tertiary screening modeling. Methods The cases relating to 5 years of activity regarding to molecular diagnostics performed on liquid biopsy specimens in the Predictive Diagnostic laboratory of AOU Federico II were reviewed. Laboratory data were collected in SPSS. Non parametric analysis were performed in order to test the differences between patients WILD TYPE or not. A multivariate logistic model was performed in order to assess the effect of mutation, age and sex, on the tumor progression. The results of the revision concern 515 total cases (almost of all plasma or peripheral blood) allowed to evaluate the liquid biopsies for women and men. The average age of the Patients is 66.3 years, and the 25 percentile is 59 years. Results The cases are 221 basal and 294 by progression. The cases with mutation, as expected, have an OR 4,15 compared to the basal to have a tumor progression (95% IC: 2,7 - 6,3) regardless of sex and age. The mutations detected were 131 from different types of pulmonary carcinomas. Conclusions Working on case data, specifying the characteristics of the Patients with mutations will drive a further estimate in tertiary prevention screening designs. Key messages In the last five years, the liquid biopsy has been used for different purposes in oncology. To specify the characteristics of the Patients with mutations will drive a further estimate in tertiary prevention screening designs.