Sysoft Center for Systems Biology and Bioengineering develops complex dynamic models for biomedical applications. The biomedical pathways are quantified with multiple parameters that can change depending on clinical in-vivo or in-vitro conditions. A standard relational database model holds all the objects of the quantitative model. An optimization algorithm matches the aggregate model with the clinical datasets. It automatically adjusts all the parameters till it can find the best solution. Multivariate analysis (MVA) aims to create a derived aggregate model reducing the complexity of multi-dimensional data to a few latent variables that express the majority of the variance of the data set. MVA is also utilized to perform nonlinear multiple regression analysis between large data sets. Our dynamic model can interface with external data sets and other models using Systems Biology Markup Language (SBML). It is a computer-readable format for representing models of biochemical reaction network in software.