Nonsteroidal anti-inflammatory drugs (NSAIDs) are consumed by tens of millions worldwide. Although they relieve pain and inflammation, we understand poorly their mechanism of action. They also cause serious gastrointestinal and cardiovascular adverse effects and are thought to have caused thousands of deaths. Despite enrolling more than 100,000 patients in randomized trials, we still do not know the NSAID of choice for patients with arthritis and heart disease or if NSAIDs differ in clinical efficacy. Here we propose a paradigm shifting, strategic approach to harvest benefit and manage risk by personalizing therapy with NSAIDs. Data from studies from yeast, mammalian cells, zebrafish, mice and humans will be integrated to develop signaling networks that reflect perturbation by model NSAIDs and that generate hypotheses ultimately addressed by prospective, randomized trials in humans. Our hope is that these iteratively refined models, progressively informed by human data, will lead to algorithms of incremental value to clinicians in the prediction of efficacy and adverse effects. This interdisciplinary strategy will deliver innovative tools and technologies, quantitative models and biomarkers of drug response and if successful will allow more rational prescription of NSAIDs to minimize risk and maximize benefit to individuals, creating a novel paradigm for the development and approval of drugs, the design of randomized trials and the treatment of chronic disease.

Public Health Relevance

Drugs are prescribed based on detection of large average signals of effectiveness and hazard. This proposal attempts to refine the use of nonsteroidal anti-inflammatory drugs so that they are used in patients individually most likely to benefit and least likely to suffer adverse effects.

National Institute of Health (NIH)
National Heart, Lung, and Blood Institute (NHLBI)
Specialized Center--Cooperative Agreements (U54)
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Special Emphasis Panel (ZGM1)
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Srinivas, Pothur R
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University of Pennsylvania
Schools of Medicine
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Aldrovandi, Maceler; Hinz, Christine; Lauder, Sarah N et al. (2017) DioxolaneA3-phosphatidylethanolamines are generated by human platelets and stimulate neutrophil integrin expression. Redox Biol 11:663-672
Mesaros, Clementina; Arroyo, Alejandro D; Blair, Ian A et al. (2017) Coenzyme A thioester formation of 11- and 15-oxo-eicosatetraenoic acid. Prostaglandins Other Lipid Mediat 130:1-7
Crescenzi, Rachelle; DeBrosse, Catherine; Nanga, Ravi P R et al. (2017) Longitudinal imaging reveals subhippocampal dynamics in glutamate levels associated with histopathologic events in a mouse model of tauopathy and healthy mice. Hippocampus 27:285-302
Bhatt, Deepak L; Grosser, Tilo; Dong, Jing-Fei et al. (2017) Enteric Coating and Aspirin Nonresponsiveness in Patients With Type 2 Diabetes Mellitus. J Am Coll Cardiol 69:603-612
Torng, Wen; Altman, Russ B (2017) 3D deep convolutional neural networks for amino acid environment similarity analysis. BMC Bioinformatics 18:302
Li, Ruizhi; Grosser, Tilo; Diamond, Scott L (2017) Microfluidic whole blood testing of platelet response to pharmacological agents. Platelets 28:457-462
Jin, Yu; Xie, Yi; Ostriker, Allison C et al. (2017) Opposing Actions of AKT (Protein Kinase B) Isoforms in Vascular Smooth Muscle Injury and Therapeutic Response. Arterioscler Thromb Vasc Biol 37:2311-2321
Grosser, Tilo; Ricciotti, Emanuela; FitzGerald, Garret A (2017) The Cardiovascular Pharmacology of Nonsteroidal Anti-Inflammatory Drugs. Trends Pharmacol Sci 38:733-748
Zemski Berry, Karin A; Murphy, Robert C; Kosmider, Beata et al. (2017) Lipidomic characterization and localization of phospholipids in the human lung. J Lipid Res 58:926-933
FitzGerald, Garret A (2017) Imprecision: Limitations to Interpretation of a Large Randomized Clinical Trial. Circulation 135:113-115

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