Systems Pharmacology in Modelling Complex Scenarios: Opportunities and Challenges

Abstract

The treatment of complex diseases represents currently a major challenge. In this context systems pharmacology (SP) is an emergent discipline that provides an opportunity to get deeper insights in this type of diseases by integrating different areas of knowledge including biology, pharmacology, pharmacometrics, statistics, and computational modelling. Nowadays, SP has relevance throughout the entire process of drug development, since it has been able to show that systems computational models allow increasing the understanding of different mechanisms of action and regulatory processes, demonstrating their usefulness for organizing large biological data sets and extracting significant information. These models are useful for (i) the identification and validation of new therapeutic targets, (ii) the discovery of new biomarkers, (iii) patient stratification, (iv) dose individualization, (v) the identification of new sources of variability and (vi) the prediction of toxicity and adverse effects. In this thesis, different types of mechanistic models were explored showing its capabilities and drawbacks. The Introduction section provides a brief description and uses of systems pharmacology models. Chapter 1 presents a systems pharmacology model for Systemic Lupus Erythematosus. This model, based in Boolean equations, allows identifying different patient subpopulations according to their molecular alterations, predicting the variability in the progression of the disease and designing individualized drug therapies with a high likelihood of success. In Chapter 2 two systems pharmacology models for coagulation cascade published in the literature are implemented and reproduced. Then, experimental data obtained from the literature was incorporated in both models to reproduce coagulation tests. Finally, a semi-mechanistic pharmacokinetic/pharmacodynamic (PKPD) model was built to fit this experimental data. Chapter 1 and Chapter 2 provide an overview of the characteristics of the disease or biological system and their therapeutic alternatives as well as the description of the information and methodology used to develop the SP models, together with the corresponding results. On the other hand, Chapter 3 discusses the impact of considering exposure at the target site with regard to systemic concentrations, a piece of information that usually remains forgotten in mechanistic modelling. The General Discussion highlights the most relevant aspects of the three chapters, followed by the Conclusions section, which summarizes the main findings of this thesis. Finally, in the Annex, an article of a systems pharmacology model developed for inflammatory bowled disease, recently published in PLOS ONE journal is enclosed.