Absorption, distribution, metabolism and elimination (collectively called pharmacokinetics, PK), and time-dependent drug actions in target organs (pharmacodynamics, PD) play critical roles in efficacy and toxicity of all drugs. We will develop and implement new methods for modeling PK-PD at multiple scales from cells to patients, new methods for measuring PK at the cellular and subcellular levels, and new cell culture systems that better mimic the tumor environment, thus increasing our ability to predict patient responses from cell culture data. Our translational goal is to create new single-cell resolution methods to integrate a molecular understanding of drug-target interaction with measures of target engagement and induction of drug response in tissues and organisms.
Aim 3. 1 involves technology development for sub-cellular resolution PK measurement by fluorescence imaging of Companion Imaging Drugs (CIDs), small molecule or protein drugs tagged with a fluorophore for imaging in a manner that retains the bioactivity and pharmacokinetics of the parent compound. The properties of CIDs will be optimized (Aim 3.1.1) and the compounds used for intravital imaging of drug distribution and response in living mice (Aim 3.1.2). CIDs will be used to directly assay drug-target interaction in single cells by fluorescence correlation microscopy (Aim 3.1.3).
Aim 3. 2 will develop a novel quantitative, multiplexed mass spectrometry method for assaying structure-activity relationships at a cellular and sub-cellular level based on covalent modification of target proteins. This will involve creation of novel chemical drug-like probes (Aim 3.2.1) that will then be subjected to systematic chemical modification to explore the impact of physic0-chemical properties such as cLogP, pKa etc.
(Aim 3. 2.2).
Aim 3. 3 will involve development of methods for integrating pathway-level knowledge and biomarkers (both predictive and response) into the kind of PK-PD models that are routinely used for translational pharmacology and clinical trial design in industry.
Aim 3. 4 will attempt to recreate key features of the tumor microenvironment in culture to increase the predictivity of cell culture models. This will involve reproducing time-varying drug exposure as observed in animals and patients (Aim 3.4.1), systematic variation of the soluble environment (Aim 3.4.2), manipulation of the physical environment through changes in substrate elasticity (Aim 3.4.3) and direct assessment of the relationship between drug response in culture and patients across all the data collected Aims 1-3.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Specialized Center (P50)
Project #
1P50GM107618-01A1
Application #
8769537
Study Section
Special Emphasis Panel (ZGM1)
Project Start
Project End
Budget Start
2014-09-01
Budget End
2015-05-31
Support Year
1
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Harvard Medical School
Department
Type
DUNS #
City
Boston
State
MA
Country
United States
Zip Code
02115
Wang, Rui-Sheng; Loscalzo, Joseph (2018) Network-Based Disease Module Discovery by a Novel Seed Connector Algorithm with Pathobiological Implications. J Mol Biol 430:2939-2950
Weinstein, Zohar B; Kuru, Nurdan; Kiriakov, Szilvia et al. (2018) Modeling the impact of drug interactions on therapeutic selectivity. Nat Commun 9:3452
Leopold, Jane A; Loscalzo, Joseph (2018) Emerging Role of Precision Medicine in Cardiovascular Disease. Circ Res 122:1302-1315
Spady, Emma S; Wyche, Thomas P; Rollins, Nathanael J et al. (2018) Mammalian Cells Engineered To Produce New Steroids. Chembiochem 19:1827-1833
Cheng, Feixiong; Desai, Rishi J; Handy, Diane E et al. (2018) Network-based approach to prediction and population-based validation of in silico drug repurposing. Nat Commun 9:2691
Vinegoni, Claudio; Feruglio, Paolo Fumene; Gryczynski, Ignacy et al. (2018) Fluorescence anisotropy imaging in drug discovery. Adv Drug Deliv Rev :
Oldham, William M; Oliveira, Rudolf K F; Wang, Rui-Sheng et al. (2018) Network Analysis to Risk Stratify Patients With Exercise Intolerance. Circ Res 122:864-876
Sampattavanich, Somponnat; Steiert, Bernhard; Kramer, Bernhard A et al. (2018) Encoding Growth Factor Identity in the Temporal Dynamics of FOXO3 under the Combinatorial Control of ERK and AKT Kinases. Cell Syst 6:664-678.e9
Monteiro, Maria B; Ramm, Susanne; Chandrasekaran, Vidya et al. (2018) A High-Throughput Screen Identifies DYRK1A Inhibitor ID-8 that Stimulates Human Kidney Tubular Epithelial Cell Proliferation. J Am Soc Nephrol 29:2820-2833
Cokol-Cakmak, Melike; Bakan, Feray; Cetiner, Selim et al. (2018) Diagonal Method to Measure Synergy Among Any Number of Drugs. J Vis Exp :

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