Cross-Seminars - 2 July 16h30 - 4x short on climate change, bioprocesses and cells

1 julho 2021, 10:29 • Ana Almeida Matos

SEMINAR 3 – 2 July / 16.30h
This session will be composed of 4 short seminars:

1. Tittle: What (really) drives corporations to issue debt that has to be applied in environmental-friendly projects?
   Presenter: Rodrigo Graça, PhD student    CANCELLED
   Abstract:
   Climate change is one of the greatest challenges of our contemporary society. The modifications of Earth’s climate carries potentially high economic and social costs. These consequences can be significantly mitigated, but only with a fast and extensive transition of the current economic system towards a greener and less carbon-intensive model, as urged by the Intergovernmental Panel on Climate Change (IPCC) of the United Nations in their most recent report. This ambitious endeavour is solely feasible with the involvement of both public and private sectors. Positive Impact Fixed Income products, such as the Green Bonds are valuable tools to mobilize and direct private funds into projects that actively contribute to a more sustainable economy, and hence complementing and enhancing the actions conducted by Governments towards this direction. These products have been reporting a fast growth since their emergence in 2007, suggesting the priorities’ redefinition by investors and consumers towards higher accountability for environmental, social and governance (ESG) aspects. The PhD research proposal is still going to be developed, although it is expected to aim around the following questions. First, how effective are these financial products concerning their impact on the environmental and social factors that they were designed to achieve? Second, what is added value for the issuers and the investors that include these products in their portfolios?
   
   
2. Title: Use of Dynamic Optimization Algorithms for the development of bioprocesses
   Presenter: João Antunes 
   Abstract:
   The dynamic optimization or open-loop optimal control of a bioprocess is a procedure by which the optimal control variables are ascertained through the application of an optimization algorithm to a given model of the bioprocess in question, usually described in form of differential and algebraic equations (DAEs) and subsequent constraints on state and control variables. This optimization procedure is an important tool that can give a better understanding of a process as its complex, and usually non-linear, nature can obscure the procedure by which the processes optimal production might be reached. I study the effect of different optimization methods applied in the development of hybrid semiparametric modelling to develop a batch-to-batch control of a given biological process.
   
   
3. Title: A novel symbolic framework for hybrid semiparametric modelling of bioprocesses
   Presenter: José Pinto
   Abstract:
   In this project a hybrid modelling toolbox to integrate machine learning and mechanistic biological models was developed in MATLAB/OCTAVE. Symbolic calculus is adopted to “fuse” physical mathematical equations with machine learning equations. Furthermore, this tool obeys the Systems Biology Markup Language (SBML). The compliance with the SBML standard enables it to easily adapt existing mechanistic SBML models to hybrid semiparametric versions. In addition, the storage of hybrid SBML models in public databases becomes possible.          
   
   
4. Title: Dynamic models describing cell growth, central carbon metabolism and virus production in animal cells? 
   Presenter: João Ramos, SBE research group, NOVA University Lisbon
   Abstract:
   Currently large number of datasets are being generated and more complex, leading to a need for model-based data integration and analysis for process optimization. However, currently few models exist that describes both cell growth and intracellular metabolism of animal cell lines using dynamic mechanistic models.
   We have developed dynamic mathematical models of cell growth, virus production and metabolism and show their applications for different cell lines. In this approach our models use ordinary differential equations to simulate changes in viable cell concentration, and volume, virus titer, concentration of extracellular substrates, and intracellular concentrations of key metabolites from the central carbon metabolism.
   We show that such models allow accurate estimation of the release of metabolic by-products such as lactate and ammonium directly from the intracellular reactions and model simulations hints at the existence of distinct cellular physiological states. Furthermore, we use this approach to study metabolism during virus replication and showed that there is no significant changes comparing metabolism of infected and non-infected cells. Finally, we demonstrate the usage of this modeling approach for media optimization.

Link to entire session: https://videoconf-colibri.zoom.us/j/89214599997