One of the main aims of the Mathematical Modeling component is to establish mathematical models of cell functions and of separation processes in bioengineering systems of importance to industrial biotechnology.
Some of our recent developments in mathematical modelling include a Mathematical Model of the Dynamics of Red Tide in order to be able to understand and predict this environmentally very harmful phenomena of the Red Tide in the South of Chile. These models include a large range of different mathematical elements ranging from satellite images to computational fluid dynamics and all the biological elements of the harmful algal blooms (HAB) and have recently introduced the use of multispectral satellite information. An important variable also recently introduced is the effect of parameter related to “historical” wheather conditions.

 

Other projects in this field include Mathematical models for tumor growth coupled with tumor angiogenesis where we have predicted cancer drug resistance through modeling gastrointestinal stromal (GIST) metastasis to the liver and also Genome-scale models for Wolbachia’s metabolism which include metabolic reconstructions on the genomes of 4 sequenced Wolbachia strains. Another interesting project is patient response classification, modeling and parameter estimation of the glycemia-insulinemia control during an oral glucose tolerance test and also Mathematical models for tumor growth coupled with tumor angiogenesis which will be used in the design of new therapeutic strategies that minimize drug resistance.

 

We have also worked in the Modelling, Simulation and Optimization of a Multiproduct Batch plant in biotechnology using MILP reformulations with continuous equipment sizes and discrete host selection. This is a new approach and its main advantage is its scalability that allows to solve, within reasonable precision requirements, realistic instances. It was used to optimize the equipment sizes of a new biotechnological multi-product plant, based on information of real processes for the production of 4 diferent recombinant proteins in a plant composed of 44 unit operations showing that in the case studied it is possible to save up to a 66% of the capital investment in equipment.