ArticlePloS one2020
In-silico simulated prototype-patients using TPMS technology to study a potential adverse effect of sacubitril and valsartan.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.
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Who cites it
35 citing papers in PubMed.
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- Digital patient modeling identifies predictive biomarkers of regorafenib response in elderly metastatic colorectal cancer.Frontiers in systems biology · 2025Article
- Synergistic effects of vedolizumab and JAK 1,2,3 inhibitors in Crohn's disease: insights from a systems biology and artificial intelligence-based approach.Frontiers in immunology · 2025Article
- In Silico Modeling of Fabry Disease Pathophysiology for the Identification of Early Cellular Damage Biomarker Candidates.International journal of molecular sciences · 2024Article
- Machine Learning-Driven Biomarker Discovery for Skeletal Complications in Type 1 Gaucher Disease Patients.International journal of molecular sciences · 2024Article
- Aflibercept Off-Target Effects in Diabetic Macular Edema: An In Silico Modeling Approach.International journal of molecular sciences · 2024Article
- MMPred: a tool to predict peptide mimicry events in MHC class II recognition.Frontiers in genetics · 2024Article
- A decision support system based on artificial intelligence and systems biology for the simulation of pancreatic cancer patient status.CPT: pharmacometrics & systems pharmacology · 2023Article
- Application of systems biology to identify pharmacological mechanisms of thrombotic microangiopathy evoked by combined activated prothrombin complex concentrate and emicizumab.Scientific reports · 2023Article
- AnMolecular genetics and metabolism reports · 2023Article
- Neuronal Prosurvival Role of Ceramide Synthase 2 by Olidogendrocyte-to-Neuron Extracellular Vesicle Transfer.International journal of molecular sciences · 2023Article
- Neprilysin Inhibitors in Heart Failure: The Science, Mechanism of Action, Clinical Studies, and Unanswered Questions.JACC. Basic to translational science · 2023Review
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- A quantitative systems pharmacology model for certolizumab pegol treatment in moderate-to-severe psoriasis.Frontiers in immunology · 2023Article
- Identification of the Potential Molecular Mechanisms Linking RUNX1 Activity with Nonalcoholic Fatty Liver Disease, by Means of Systems Biology.Biomedicines · 2022Article
- Data mining analyses for precision medicine in acromegaly: a proof of concept.Scientific reports · 2022Article
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Unveiling the mechanism of action of a drug is key to understand the benefits and adverse reactions of a medication 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 personalized medicine. The Therapeutic Performance Mapping System (TPMS) is a Systems Biology approach that generates multiple models of the mechanism of action of a drug. Each molecular mechanism generated could be associated to particular individuals, here defined as prototype-patients, hence the generation of models using TPMS technology may be used for detecting adverse effects to specific patients. TPMS operates by (1) modelling the responses in humans with an accurate description of a protein network and (2) applying a Multilayer Perceptron-like and sampling 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 wide range of models explaining the relationship between sacubitril/valsartan and heart failure (the indication), as well as evaluating their association with macular degeneration (a potential adverse effect). Among the models generated, we identify a set of mechanisms of action associated to a better response in terms of heart failure treatment, which could also be associated to macular degeneration development. Finally, a set of 30 potential biomarkers are proposed to identify mechanisms (or prototype-patients) more prone of suffering macular degeneration when presenting good heart failure response. All prototype-patients models generated are completely theoretical and therefore they do not necessarily involve clinical effects in real patients. Data and accession to software are available at http://sbi.upf.edu/data/tpms/.
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