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Tumor Static Concentration Curves in Combination Therapy

Overview of attention for article published in The AAPS Journal, September 2016
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Title
Tumor Static Concentration Curves in Combination Therapy
Published in
The AAPS Journal, September 2016
DOI 10.1208/s12248-016-9991-1
Pubmed ID
Authors

Tim Cardilin, Joachim Almquist, Mats Jirstrand, Alexandre Sostelly, Christiane Amendt, Samer El Bawab, Johan Gabrielsson

Abstract

Combination therapies are widely accepted as a cornerstone for treatment of different cancer types. A tumor growth inhibition (TGI) model is developed for combinations of cetuximab and cisplatin obtained from xenograft mice. Unlike traditional TGI models, both natural cell growth and cell death are considered explicitly. The growth rate was estimated to 0.006 h(-1) and the natural cell death to 0.0039 h(-1) resulting in a tumor doubling time of 14 days. The tumor static concentrations (TSC) are predicted for each individual compound. When the compounds are given as single-agents, the required concentrations were computed to be 506 μg · mL(-1) and 56 ng · mL(-1) for cetuximab and cisplatin, respectively. A TSC curve is constructed for different combinations of the two drugs, which separates concentration combinations into regions of tumor shrinkage and tumor growth. The more concave the TSC curve is, the lower is the total exposure to test compounds necessary to achieve tumor regression. The TSC curve for cetuximab and cisplatin showed weak concavity. TSC values and TSC curves were estimated that predict tumor regression for 95% of the population by taking between-subject variability into account. The TSC concept is further discussed for different concentration-effect relationships and for combinations of three or more compounds.

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Geographical breakdown

Country Count As %
Unknown 20 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 40%
Student > Ph. D. Student 5 25%
Student > Bachelor 2 10%
Other 1 5%
Professor > Associate Professor 1 5%
Other 0 0%
Unknown 3 15%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 4 20%
Mathematics 4 20%
Medicine and Dentistry 3 15%
Engineering 2 10%
Psychology 1 5%
Other 2 10%
Unknown 4 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 17 December 2016.
All research outputs
#15,387,502
of 22,893,031 outputs
Outputs from The AAPS Journal
#917
of 1,288 outputs
Outputs of similar age
#204,100
of 322,613 outputs
Outputs of similar age from The AAPS Journal
#21
of 35 outputs
Altmetric has tracked 22,893,031 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,288 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.0. This one is in the 19th percentile – i.e., 19% of its peers scored the same or lower than it.
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 322,613 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.