Optimization of production of anti-cancer vaccines based on dendritic cells

Cancer remains as one of the top killing diseases in first world countries. It’s not a single, but a set of various diseases for which different treatment approaches have been taken over the years. Cancer immunotherapy comes as a “new” breath on cancer treatment, taking use of the patients’ immune system to induce anti-cancer responses. Dendritic Cell (DC) vaccines use the extraordinary capacity of DCs’ antigen presentation so that specific T cell responses may be generated against cancer. In this work, we report the ex vivo generation of DCs from precursors isolated from clinical-grade cryopreserved umbilical cord blood (UCB) samples. After the thawing protocol for cryopreserved samples was optimized, the generation of DCs from CD14+ monocytes, i.e., moDCs, or CD34+ hematopoietic stem cells (HSCs), i.e, CD34-derived DCs, was followed and their phenotype and function evaluated. Functional testing included the ability to respond to maturation stimuli (including enzymatic removal of surface sialic acids), Ovalbumin-FITC endocytic capacity, cytokine secretion and T cell priming ability. In order to evaluate the feasibility of using DCs derived from UCB precursors to induce immune responses, they were compared to peripheral blood (PB) moDCs. We observed an increased endocytosis capacity after moDCs were differentiated from monocyte precursors, but almost 10-fold lower than that of PB moDCs. Maturation markers were absent, low levels of inflammatory cytokines were seen and T cell stimulatory capacity was reduced. Sialidase enzymatic treatment was able to mature these cells, diminishing endocytosis and promoting higher T cell stimulation. CD34-derived DCs showed higher capacity for both maturation and endocytic capacity than moDCs. Although much more information was acquired from moDCs than from CD34-derived DCs, we conclude the last as probably the best suited for generating an immune response against cancer, but of course much more research has to be performed.

Optimization of wastewater quality in the Sines refinery

In order to address and resolve the wastewater contamination problem of the Sines refinery with the main objective of optimizing the quality of this stream and reducing the costs charged to the refinery, a dynamic mass balance was developed nd implemented for ammonia and polar oil and grease (O&G) contamination in the wastewater circuit. The inadequate routing of sour gas from the sour water stripping unit and the kerosene caustic washing unit, were identified respectively as the major source of ammonia and polar substances present in the industrial wastewater effluent. For the O&G content, a predictive model was developed for the kerosene caustic washing unit, following the Projection to Latent Structures (PLS) approach. Comparison between analytical data for ammonia and polar O&G concentrations in refinery wastewater originating from the Dissolved Air Flotation (DAF) effluent and the model predictions of the dynamic mass balance calculations are in a very good agreement and highlights the dominant impact of the identified streams for the wastewater contamination levels. The ammonia contamination problem was solved by rerouting the sour gas through an existing clogged line with ammonia salts due to a non-insulated line section, while for the O&G a dynamic mass balance was implemented as an online tool, which allows for prevision of possible contamination situations and taking the required preventive actions, and can also serve as a basis for establishing relationships between the O&G contamination in the refinery wastewater with the properties of the refined crude oils and the process operating conditions. The PLS model developed could be of great asset in both optimizing the existing and designing new refinery wastewater treatment units or reuse schemes. In order to find a possible treatment solution for the spent caustic problem, an on-site pilot plant experiments for NaOH recovery from the refinery kerosene caustic washing unit effluent using an alkaline-resistant nanofiltration (NF) polymeric membrane were performed in order to evaluate its applicability for treating these highly alkaline and contaminated streams. For a constant operating pressure and temperature and adequate operating conditions, 99.9% of oil and grease rejection and 97.7% of chemical oxygen demand (COD) rejection were observed. No noticeable membrane fouling or flux decrease were registered until a volume concentration factor of 3. These results allow for NF permeate reuse instead of fresh caustic and for significant reduction of the wastewater contamination, which can result in savings of 1.5 M€ per year at the current prices for the largest Portuguese oil refinery. The capital investments needed for implementation of the required NF membrane system are less than 10% of those associated with the traditional wet air oxidation solution of the spent caustic problem. The operating costs are very similar, but can be less than half if reusing the NF concentrate in refinery pH control applications. The payback period was estimated to be 1.1 years. Overall, the pilot plant experimental results obtained and the process economic evaluation data indicate a very competitive solution through the proposed NF treatment process, which represents a highly promising alternative to conventional and existing spent caustic treatment units.

Modeling and optimization of extracellular polysaccharides production by Enterobacter A47

Polysaccharides are gaining increasing attention as potential environmental friendly and sustainable building blocks in many fields of the (bio)chemical industry. The microbial production of polysaccharides is envisioned as a promising path, since higher biomass growth rates are possible and therefore higher productivities may be achieved compared to vegetable or animal polysaccharides sources. This Ph.D. thesis focuses on the modeling and optimization of a particular microbial polysaccharide, namely the production of extracellular polysaccharides (EPS) by the bacterial strain Enterobacter A47. Enterobacter A47 was found to be a metabolically versatile organism in terms of its adaptability to complex media, notably capable of achieving high growth rates in media containing glycerol byproduct from the biodiesel industry. However, the industrial implementation of this production process is still hampered due to a largely unoptimized process. Kinetic rates from the bioreactor operation are heavily dependent on operational parameters such as temperature, pH, stirring and aeration rate. The increase of culture broth viscosity is a common feature of this culture and has a major impact on the overall performance. This fact complicates the mathematical modeling of the process, limiting the possibility to understand, control and optimize productivity. In order to tackle this difficulty, data-driven mathematical methodologies such as Artificial Neural Networks can be employed to incorporate additional process data to complement the known mathematical description of the fermentation kinetics. In this Ph.D. thesis, we have adopted such an hybrid modeling framework that enabled the incorporation of temperature, pH and viscosity effects on the fermentation kinetics in order to improve the dynamical modeling and optimization of the process. A model-based optimization method was implemented that enabled to design bioreactor optimal control strategies in the sense of EPS productivity maximization. It is also critical to understand EPS synthesis at the level of the bacterial metabolism, since the production of EPS is a tightly regulated process. Methods of pathway analysis provide a means to unravel the fundamental pathways and their controls in bioprocesses. In the present Ph.D. thesis, a novel methodology called Principal Elementary Mode Analysis (PEMA) was developed and implemented that enabled to identify which cellular fluxes are activated under different conditions of temperature and pH. It is shown that differences in these two parameters affect the chemical composition of EPS, hence they are critical for the regulation of the product synthesis. In future studies, the knowledge provided by PEMA could foster the development of metabolically meaningful control strategies that target the EPS sugar content and oder product quality parameters.

Quadratic programming versus second order con programming in portfolio optimization

Despite the extensive literature in finding new models to replace the Markowitz model or trying to increase the accuracy of its input estimations, there is less studies about the impact on the results of using different optimization algorithms. This paper aims to add some research to this field by comparing the performance of two optimization algorithms in drawing the Markowitz Efficient Frontier and in real world investment strategies. Second order cone programming is a faster algorithm, appears to be more efficient, but is impossible to assert which algorithm is better. Quadratic Programming often shows superior performance in real investment strategies.

Millennium BCP: Optimization of the branches closure process

Nowadays, a significant number of banks in Portugal are facing a bank-branch restructuring problem, and Millennium BCP is not an exception. The closure of branches is a major component of profit maximization through the reduction in operational and personnel costs but also an opportunity to approach the idea of “baking of future” and start thinking on the benefits of the digital era. This dissertation centers on a current high-impact organizational problem addressed by the company and consists in a proposal of optimization to the model that Millennium BCP uses. Even though measures of performance are usually considered the most important elements in evaluating the viability of branches, there is evidence suggesting that other general factors can be important to assess branch potential, such as the influx on branches, business dimensions of a branch and its location, which will be addressed in this project.

Customer service process optimization at Sonae e MC

Sonae MC is constantly innovating and keeping up with the new market trends, being increasingly focused on E-commerce due to its growing importance. In that area, a telephone line is available to support customers with their problems. However, rare were the cases in which those problems were solved in the first contact. Therefore, the goal of this work was to reengineer these processes to improve the service performance and consequently the customer’s satisfaction. Following an evolutionary approach, improvement opportunities were suggested and if correctly implemented the cases resolution time could decrease 1 day and Sonae MC will save €7.750 per month.