TPMS technology to infer biomarkers of macular degeneration prognosis in in silico simulated prototype-patients under the study of heart failure treatment with sacubitril and valsartan

Abstract

Unveiling the mechanism of action of a drug is key to understand the benefits and adverse reactions of drug(s) in an organism. However, in complex diseases such as heart diseases there is not a unique mechanism of action but a wide range of different responses depending on the patient. Exploring this collection of mechanisms is one of the clues for a future personalised medicine. The Therapeutic Performance Mapping System (TPMS) is a Systems Biology approach that generates multiple models of the mechanism of action of a drug. This is achieved by (1) modelling the responses in human with an accurate description of the protein networks and (2) applying a Multilayer Perceptron-like and sampling method strategy to find all plausible solutions. In the present study, TPMS is applied to explore the diversity of mechanisms of action of the drug combination sacubitril/valsartan. We use TPMS to generate a range of mechanism of action models explaining the relationship between sacubitril/valsartan and heart failure (the indication), as well as evaluating their relationship with macular degeneration (a common/recurrent adverse effect). We found that a lower response in terms of heart failure treatment is more associated to macular degeneration development, although good response mechanisms can also associate to the adverse effect. A set of 30 potential biomarkers are proposed to identify mechanisms (or patients) more prone to suffering macular degeneration when presenting good heart failure response. As each molecular mechanism can be particular not only of cells but also individuals, we conclude that the study of the collection of models generated using TPMS technology can be used to detect adverse effects personalized to patients.