We are requesting funds to upgrade our mass spectrometry capabilities. Until this year, Dr Nagar's and Korzekwa's laboratories have used two standard resolution mass spectrometers (Sciex API 4000s) for all LCMSMS quantitation. Although these instruments are excellent for routine quantitation of drugs and metabolites from in vitro and plasma samples, they are not high-resolution instruments and are not ideal for protein quantitation. Unexpectedly, we have recently acquired a Bruker Solarix 7T FT-ICR mass spectrometer (< two years old). This instrument has a 7-tesla magnet and is an ultra-high-resolution instrument capable of measuring molecular masses with 1 in 2.5 million resolution. This instrument is equipped with both MALDI and API interfaces, which allows identification and quantification of both small molecules and proteins. In addition to exact-mass analysis and quantitation of drugs and metabolites from in vitro and plasma samples, this instrument can perform mass spectrometry imaging, the spatial quantitation of drugs and metabolites directly from tissues 1,2. We are requesting two upgrades for the Bruker Solarix 7T FT-ICR mass spectrometer. First, we are requesting funds to purchase an HTX M5 Sprayer MALDI matrix deposition system and second, an Agilent 1290 high performance HPLC. These upgrades will be used for sample preparation and introduction into the FT-ICR mass spectrometer through the MALDI imaging and API interfaces, respectively. The requested upgrade to this instrument will allow us to greatly expand our analytical capabilities and generate unanticipated datasets that will help achieve our Specific Aims outlined in the abstract above for NIH grant 2R01GM104178 `Predicting intracellular concentrations in the presence of transporters'.

Public Health Relevance

We are requesting funds to upgrade a high-resolution mass spectrometer capable of tissue imaging as part of our NIH grant 2R01GM104178 `Predicting intracellular concentrations in the presence of transporters'. The overall goal of this research is to better predict drug efficacy and safety in humans. Biophysical methods, in vitro, in situ, and in vivo data will be used to develop models that incorporate membrane partitioning, permeability-limited diffusion, blood flow, active transport, and metabolism in order to predict intracellular and extracellular drug concentration- time profiles.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
3R01GM104178-06S1
Application #
10154888
Study Section
Program Officer
Garcia, Martha
Project Start
2013-01-15
Project End
2022-07-31
Budget Start
2019-08-01
Budget End
2020-07-31
Support Year
6
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Temple University
Department
Pharmacology
Type
Schools of Pharmacy
DUNS #
057123192
City
Philadelphia
State
PA
Country
United States
Zip Code
19122
Guo, Yingying; Chu, Xiaoyan; Parrott, Neil J et al. (2018) Advancing Predictions of Tissue and Intracellular Drug Concentrations Using In Vitro, Imaging and Physiologically Based Pharmacokinetic Modeling Approaches. Clin Pharmacol Ther 104:865-889
Yadav, Jaydeep; Korzekwa, Ken; Nagar, Swati (2018) Improved Predictions of Drug-Drug Interactions Mediated by Time-Dependent Inhibition of CYP3A. Mol Pharm 15:1979-1995
Pham, Chuong; Nagar, Swati; Korzekwa, Ken (2017) Numerical analysis of time dependent inhibition kinetics: comparison between rat liver microsomes and rat hepatocyte data for mechanistic model fitting. Xenobiotica :1-28
Nagar, Swati; Korzekwa, Richard C; Korzekwa, Ken (2017) Continuous Intestinal Absorption Model Based on the Convection-Diffusion Equation. Mol Pharm 14:3069-3086
Nagar, Swati; Korzekwa, Ken (2017) Drug Distribution. Part 1. Models to Predict Membrane Partitioning. Pharm Res 34:535-543
Korzekwa, Ken; Nagar, Swati (2017) On the Nature of Physiologically-Based Pharmacokinetic Models -A Priori or A Posteriori? Mechanistic or Empirical? Pharm Res 34:529-534
Korzekwa, Ken; Nagar, Swati (2017) Drug Distribution Part 2. Predicting Volume of Distribution from Plasma Protein Binding and Membrane Partitioning. Pharm Res 34:544-551
Ye, Min; Nagar, Swati; Korzekwa, Ken (2016) A physiologically based pharmacokinetic model to predict the pharmacokinetics of highly protein-bound drugs and the impact of errors in plasma protein binding. Biopharm Drug Dispos 37:123-41
Barnaba, Carlo; Yadav, Jaydeep; Nagar, Swati et al. (2016) Mechanism-Based Inhibition of CYP3A4 by Podophyllotoxin: Aging of an Intermediate Is Important for in Vitro/in Vivo Correlations. Mol Pharm 13:2833-43
Kulkarni, Priyanka; Korzekwa, Kenneth; Nagar, Swati (2016) Intracellular Unbound Atorvastatin Concentrations in the Presence of Metabolism and Transport. J Pharmacol Exp Ther 359:26-36

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