What can systems pharmacology contribute to drug development? Disease modelling as a predictive tool

Abstract

The paper "The Apoe-/-Mouse PhysioLab ® Platform: A Validated Physiologically-based Mathematical Model of Atherosclerotic Plaque Progression in the Apoe-/-Mouse" by Jason Chan and colleagues [1] published in BioDiscovery 2012; 3: 2 is significant for several reasons. The pharmaceutical and biotechnology industries have become quite proficient at rational drug design, but rational drug development has not progressed as quickly (and development costs represent at least 70% of the billion dollar cost of taking a new chemical entity from conception to market). The reasons are clear: with the possible exception of antiinfectives, drugs for most therapeutic indications involve perturbations of complex interactive systems, our preclinical models all involve sweeping simplifications, and clinical trials usually involve heterogeneous groups of patients. Systems pharmacology approaches present one approach to addressing this complexity. Genetically engineered animal models offer useful approximations to human disease, but an animal model supplemented by a computational disease model greatly increases the range of questions that can be asked. Atherosclerosis presents a case in point: its aetiology is complex, it is affected by environmental and behavioural factors, including diet and smoking, and it may take several decades for the condition to progress to clinical disease. The Apoe-/-mouse reflects many of the features of human atherosclerosis, but there are important differences: in humans the dominant circulating atherogenic particles consist of LDL, while in the Apoe-/-mouse VLDL and IDL predominate. How do these differences affect the ability of the mouse model to predict the outcome of drug treatment or lifestyle changes in humans? Another limitation of the mouse model is that, despite its biological similarities with human atherosclerosis, it does not lead to the same clinical outcomes of angina and heart attack. Why is that? Given these limitations of the mouse model, can it still guide the development of prevention and treatment regimens to reduce the incidence of human heart disease? Chan et al have presented a computational model of atherosclerotic progression that has the potential to improve the predictive power of animal models of the disease, and (when the model is extended from mice to humans) to enable in silico clinical trials.The Chan et al. model, based upon the Apoe-/-mouse, includes elements of cholesterol and macrophage trafficking, inflammation, oxidative stress, endothelial function, and thrombosis. It has the ability to predict relationships between biomarker data, pharmacodynamic effects and clinical outcomes. The model is the outcome of a collaboration between Entelos, an in silico modelling and simulation company, and Philip Morris, a tobacco company. A primary motive for developing the model appears to have been a desire to explore the relationship between smoking (and smoking cessation) and heart disease. However, the scope of the model is broad enough to enable it to be used