The objective of the Pharmacology Core is to enable the projects in this Center to develop new classes of host-targeting antiviral therapeutics for the Priority viruses. The overall goal of this core is to provide the infrastructure that will enable compounds for each project to advance in pre-clinical development. This core will establish capabilities and a Center-focused collection of expertise and advisors, which are not available on the Stanford University campus or commercially. To achieve the above goals, the pharmacology core will accomplish the following specific aims, which are to provide: (i) Medicinal chemistry capabilities to produce compound series required for: characterization of lead compounds, their structure-activity-relationships, design and synthesis of pro-drugs, and analysis of drug metabolites. (ii) In vitro characterization of drug metabolism in murine and human systems. (iii) In vivo analysis of drug metabolism in conventional mice and in mice with humanized livers. (iv) In vivo analysis of drug efficacy in mice with humanized livers. (v) Biostatistical support for analysis of all data produced by the Program's projects and by the Pharmacology Core.

Public Health Relevance

In summary, we seek to develop new classes of host-targeting antiviral therapeutics that are capable of treating multiple NIAID Emerging and Re-emerging Priority Pathogen viruses, when used alone or in combination with other available agents.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Program--Cooperative Agreements (U19)
Project #
1U19AI109662-01
Application #
8643874
Study Section
Special Emphasis Panel (ZAI1-LR-M (J1))
Project Start
2014-04-10
Project End
2019-03-31
Budget Start
2014-04-10
Budget End
2015-03-31
Support Year
1
Fiscal Year
2014
Total Cost
$1,095,972
Indirect Cost
$372,905
Name
Stanford University
Department
Type
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
Vallania, Francesco; Tam, Andrew; Lofgren, Shane et al. (2018) Leveraging heterogeneity across multiple datasets increases cell-mixture deconvolution accuracy and reduces biological and technical biases. Nat Commun 9:4735
Bongen, Erika; Vallania, Francesco; Utz, Paul J et al. (2018) KLRD1-expressing natural killer cells predict influenza susceptibility. Genome Med 10:45
Dovey, Cole M; Diep, Jonathan; Clarke, Bradley P et al. (2018) MLKL Requires the Inositol Phosphate Code to Execute Necroptosis. Mol Cell 70:936-948.e7
Pu, Szu-Yuan; Xiao, Fei; Schor, Stanford et al. (2018) Feasibility and biological rationale of repurposing sunitinib and erlotinib for dengue treatment. Antiviral Res 155:67-75
Xiao, Fei; Wang, Stanley; Barouch-Bentov, Rina et al. (2018) Interactions between the Hepatitis C Virus Nonstructural 2 Protein and Host Adaptor Proteins 1 and 4 Orchestrate Virus Release. MBio 9:
Sweeney, Timothy E; Azad, Tej D; Donato, Michele et al. (2018) Unsupervised Analysis of Transcriptomics in Bacterial Sepsis Across Multiple Datasets Reveals Three Robust Clusters. Crit Care Med 46:915-925
Schor, Stanford; Einav, Shirit (2018) Repurposing of Kinase Inhibitors as Broad-Spectrum Antiviral Drugs. DNA Cell Biol 37:63-69
Cheung, Peggie; Vallania, Francesco; Warsinske, Hayley C et al. (2018) Single-Cell Chromatin Modification Profiling Reveals Increased Epigenetic Variations with Aging. Cell 173:1385-1397.e14
Haynes, Winston A; Tomczak, Aurelie; Khatri, Purvesh (2018) Gene annotation bias impedes biomedical research. Sci Rep 8:1362
Sweeney, Timothy E; Thomas, Neal J; Howrylak, Judie A et al. (2018) Multicohort Analysis of Whole-Blood Gene Expression Data Does Not Form a Robust Diagnostic for Acute Respiratory Distress Syndrome. Crit Care Med 46:244-251

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