A Systems Approach for Tumor Pharmacokinetics
Name
Thurber-2011-A systems approach f.pdf
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802.63 KB
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Adobe PDF
Checksum (MD5)
9dd9cc8b4b3c24664baa761f379efe98
Author(s)
Thurber, Greg Michael
Weissleder, Ralph
Date Issued
September 2011
Journal
PLoS ONE
Publisher
Public Library of Science
Citation
Thurber, Greg Michael, and Ralph Weissleder. “A Systems Approach for Tumor Pharmacokinetics.” Ed. C. Andrew Boswell. PLoS ONE 6.9 (2011): e24696. Web. 27 Apr. 2012.
Version
Final published version
Abstract
Recent advances in genome inspired target discovery, small molecule screens, development of biological and nanotechnology have led to the introduction of a myriad of new differently sized agents into the clinic. The differences in small and large molecule delivery are becoming increasingly important in combination therapies as well as the use of drugs that modify the physiology of tumors such as anti-angiogenic treatment. The complexity of targeting has led to the development of mathematical models to facilitate understanding, but unfortunately, these studies are often only applicable to a particular molecule, making pharmacokinetic comparisons difficult. Here we develop and describe a framework for categorizing primary pharmacokinetics of drugs in tumors. For modeling purposes, we define drugs not by their mechanism of action but rather their rate-limiting step of delivery. Our simulations account for variations in perfusion, vascularization, interstitial transport, and non-linear local binding and metabolism. Based on a comparison of the fundamental rates determining uptake, drugs were classified into four categories depending on whether uptake is limited by blood flow, extravasation, interstitial diffusion, or local binding and metabolism. Simulations comparing small molecule versus macromolecular drugs show a sharp difference in distribution, which has implications for multi-drug therapies. The tissue-level distribution differs widely in tumors for small molecules versus macromolecular biologic drugs, and this should be considered in the design of agents and treatments. An example using antibodies in mouse xenografts illustrates the different in vivo behavior. This type of transport analysis can be used to aid in model development, experimental data analysis, and imaging and therapeutic agent design.
MIT Department
Harvard University--MIT Division of Health Sciences and Technology
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Creative Commons Attribution
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DOI of Published Version
https://doi.org/10.1371/journal.pone.0024696
