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Design of Optimized Hypoxia-Activated Prodrugs Using Pharmacokinetic/Pharmacodynamic Modeling

Overview of attention for article published in Frontiers in oncology, January 2013
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

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1 X user
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2 patents
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1 Wikipedia page

Citations

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37 Dimensions

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56 Mendeley
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Title
Design of Optimized Hypoxia-Activated Prodrugs Using Pharmacokinetic/Pharmacodynamic Modeling
Published in
Frontiers in oncology, January 2013
DOI 10.3389/fonc.2013.00314
Pubmed ID
Authors

Annika Foehrenbacher, Timothy W. Secomb, William R. Wilson, Kevin O. Hicks

Abstract

Hypoxia contributes to resistance of tumors to some cytotoxic drugs and to radiotherapy, but can in principle be exploited with hypoxia-activated prodrugs (HAP). HAP in clinical development fall into two broad groups. Class I HAP (like the benzotriazine N-oxides tirapazamine and SN30000), are activated under relatively mild hypoxia. In contrast, Class II HAP (such as the nitro compounds PR-104A or TH-302) are maximally activated only under extreme hypoxia, but their active metabolites (effectors) diffuse to cells at intermediate O2 and thus also eliminate moderately hypoxic cells. Here, we use a spatially resolved pharmacokinetic/pharmacodynamic (SR-PK/PD) model to compare these two strategies and to identify the features required in an optimal Class II HAP. The model uses a Green's function approach to calculate spatial and longitudinal gradients of O2, prodrug, and effector concentrations, and resulting killing in a digitized 3D tumor microregion to estimate activity as monotherapy and in combination with radiotherapy. An analogous model for a normal tissue with mild hypoxia and short intervessel distances (based on a cremaster muscle microvessel network) was used to estimate tumor selectivity of cell killing. This showed that Class II HAP offer advantages over Class I including higher tumor selectivity and greater freedom to vary prodrug diffusibility and rate of metabolic activation. The model suggests that the largest gains in class II HAP antitumor activity could be realized by optimizing effector stability and prodrug activation rates. We also use the model to show that diffusion of effector into blood vessels is unlikely to materially increase systemic exposure for realistic tumor burdens and effector clearances. However, we show that the tumor selectivity achievable by hypoxia-dependent prodrug activation alone is limited if dose-limiting normal tissues are even mildly hypoxic.

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
France 1 2%
Unknown 53 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 18%
Researcher 8 14%
Student > Bachelor 7 13%
Student > Doctoral Student 5 9%
Other 4 7%
Other 14 25%
Unknown 8 14%
Readers by discipline Count As %
Chemistry 10 18%
Biochemistry, Genetics and Molecular Biology 8 14%
Medicine and Dentistry 8 14%
Agricultural and Biological Sciences 5 9%
Pharmacology, Toxicology and Pharmaceutical Science 3 5%
Other 9 16%
Unknown 13 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 October 2020.
All research outputs
#5,395,320
of 25,576,801 outputs
Outputs from Frontiers in oncology
#1,892
of 22,703 outputs
Outputs of similar age
#52,782
of 289,927 outputs
Outputs of similar age from Frontiers in oncology
#28
of 328 outputs
Altmetric has tracked 25,576,801 research outputs across all sources so far. Compared to these this one has done well and is in the 78th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 22,703 research outputs from this source. They receive a mean Attention Score of 3.0. This one has done particularly well, scoring higher than 91% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 289,927 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 328 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.