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Bench to bedside translation of antibody drug conjugates using a multiscale mechanistic PK/PD model: a case study with brentuximab-vedotin

Overview of attention for article published in Journal of Pharmacokinetics and Pharmacodynamics, November 2012
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Title
Bench to bedside translation of antibody drug conjugates using a multiscale mechanistic PK/PD model: a case study with brentuximab-vedotin
Published in
Journal of Pharmacokinetics and Pharmacodynamics, November 2012
DOI 10.1007/s10928-012-9276-y
Pubmed ID
Authors

Dhaval K. Shah, Nahor Haddish-Berhane, Alison Betts

Abstract

To build a multiscale mechanism based pharmacokinetic-pharmacodynamic (PK/PD) model for antibody drug conjugates (ADCs), using brentuximab-vedotin as an example, for preclinical to clinical translation of ADC efficacy. Brentuximab-vedotin experimental data, collected from diverse publications, were employed in the following steps to build and validate the model: (1) characterization of ADC and payload PK at the cellular level, (2) characterization of payload PK in plasma and tumor tissue of xenograft mouse, (3) characterization of ADC PK in mouse plasma, (4) prediction of the tumor payload concentrations in xenograft mouse by integrating parameters obtained from steps 1-3 with the novel tumor disposition model for ADC, (5) characterization of preclinical brentuximab-vedotin tumor growth inhibition data using the novel PK/PD model, (6) characterization of ADC and payload PK in cancer patients, and (7) prediction of clinical responses of brentuximab-vedotin using the PK/PD model, by integrating PK parameters obtained from step 6, and translated mouse parameters from step 5; and comparing them with clinical trial results. The tumor disposition model was able to accurately predict xenograft tumor and plasma payload concentrations. PK/PD model predicted progression free survival rates and complete response rates for brentuximab-vedotin in patients were comparable to the observed clinical results. It is essential to understand and characterize the disposition of ADC and payload, at the cellular and physiological level, to predict the clinical outcome of ADC. A first of its kind mechanistic model has been developed for ADCs, which can integrate preclinical biomeasures and PK/PD data, to predict clinical response.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 123 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 3%
United Kingdom 1 <1%
Unknown 118 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 49 40%
Student > Ph. D. Student 22 18%
Other 14 11%
Student > Master 7 6%
Student > Bachelor 4 3%
Other 10 8%
Unknown 17 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 26 21%
Pharmacology, Toxicology and Pharmaceutical Science 18 15%
Biochemistry, Genetics and Molecular Biology 16 13%
Medicine and Dentistry 15 12%
Chemistry 8 7%
Other 17 14%
Unknown 23 19%
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 11 December 2012.
All research outputs
#17,285,036
of 25,373,627 outputs
Outputs from Journal of Pharmacokinetics and Pharmacodynamics
#328
of 477 outputs
Outputs of similar age
#125,340
of 192,216 outputs
Outputs of similar age from Journal of Pharmacokinetics and Pharmacodynamics
#1
of 1 outputs
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