2011 - Athens - Greece

PAGE 2011: Other topics - Methodology
Bruno Bieth

Using a Systems Biology Approach to Explore Clinical Diversity and Investigate Mechanism of Drug Action: Example of the RAAS System in Hypertension

B. Bieth(1), A. Soubret(1), H. Schmidt(1), A. Georgieva(2), M. Hallow(2), A. Sarkar(2), R. Sarangapani(2)

Modeling & Simulation (M&S), Novartis, Basel, Switzerland (1), East Hanover, US (2)

Objectives: The complexity of the biological and pathophysiological mechanisms of disease, and the impact of therapies on disease progression, motivates the development and use of computational models as a way to integrate quantitative physiological knowledge.

Using biological and physiological prior knowledge, a detailed representation of the Renin-Angiotensin-Aldosterone System (RAAS) as well as the effect of anti-hypertensive therapies on long-term blood pressure regulation has been implemented into a large complex mathematical model to explore clinical variability in different populations and investigate mechanism of drug action.

Methods: The Systems Biology – Population software package (SBPOP) aims at providing a flexible computational framework in support of such model-based drug development. Virtual populations are created within this large-scale model to represent real patient subpopulations by matching the underlying individual characteristics to the observed clinical and pre-clinical data.

Different calibration methodologies have been developed to generate diverse phenotype of virtual populations. They consist in using different sampling algorithms of the model parameter space along with several physiological criteria for population selection (depending on the type of data available, e.g. longitudinal data with few patients typical of phase I-II, or few data points in large population typical of phase III).

Results: We will demonstrate how the RAAS platform combines with a set of virtual populations can describe: diverse baseline characteristics that correspond to inclusion criteria of patients recruited in clinical trials; disease progression patterns that take into account pathophysiological diversity of hypertensive and diabetic subjects; drugs therapy effects such angiotensin-converting enzyme inhibitors, angiotensin II Receptor Blockers and Renin inhibitor.

Conclusions: The platform provides a framework for integrating data in the context of the Hypertension disease, focusing on understanding and anticipating clinical responses to potential treatment through the generation of virtual populations.

Reference: PAGE 20 (2011) Abstr 2030 [www.page-meeting.org/?abstract=2030]
Poster: Other topics - Methodology