Quantitative Systems Pharmacology Approaches Applied to Microphysiological Systems (MPS): Data Interpretation and Multi-MPS Integration
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Quantitative Systems Pharmacology.pdf
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Author(s) • • • • • • • • •
Large, E. M.
Hughes, D. J.
Stokes, C. L.
Yu, Jiajie
Cilfone, Nicholas A.
Sarkar, Ujjal
Tannenbaum, Steven R
Lauffenburger, Douglas A
Griffith, Linda G
Cirit, Murat
Date Issued
October 2015
Journal
CPT: Pharmacometrics & Systems Pharmacology
Publisher
Nature Publishing Group
Citation
Yu, J, NA Cilfone, EM Large, U Sarkar, JS Wishnok, SR Tannenbaum, DJ Hughes, et al. “Quantitative Systems Pharmacology Approaches Applied to Microphysiological Systems (MPS): Data Interpretation and Multi-MPS Integration.” CPT: Pharmacometrics & Systems Pharmacology 4, no. 10 (October 2015): 585–594. © 2017 American Society for Clinical Pharmacology and Therapeutics
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Final published version
Abstract
Our goal in developing Microphysiological Systems (MPS) technology is to provide an improved approach for more predictive preclinical drug discovery via a highly integrated experimental/computational paradigm. Success will require quantitative characterization of MPSs and mechanistic analysis of experimental findings sufficient to translate resulting insights from in vitro to in vivo. We describe herein a systems pharmacology approach to MPS development and utilization that incorporates more mechanistic detail than traditional pharmacokinetic/pharmacodynamic (PK/PD) models. A series of studies illustrates diverse facets of our approach. First, we demonstrate two case studies: a PK data analysis and an inflammation response––focused on a single MPS, the liver/immune MPS. Building on the single MPS modeling, a theoretical investigation of a four-MPS interactome then provides a quantitative way to consider several pharmacological concepts such as absorption, distribution, metabolism, and excretion in the design of multi-MPS interactome operation and experiments.
MIT Department
Massachusetts Institute of Technology. Center for Gynepathology Research
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Biology
Massachusetts Institute of Technology. Department of Chemistry
Massachusetts Institute of Technology. School of Engineering
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DOI of Published Version
https://doi.org/10.1002/psp4.12010