Dose-Esc/Exp RMC4630 & Cobi in Relapsed/Refractory Solid Tumors & RMC4630& Osi in EGFR+ Locally Adv/Meta NSCLC
Ontology highlight
ABSTRACT:
DISEASE(S): Solid Tumor,Cervical Cancer,Gastrointestinal Cancer,Colorectal Cancer,Bladder Cancer,Pancreatic Cancer,Lung Neoplasms,Neoplasms,Carcinoma, Squamous Cell,Ovarian Cancer,Nsclc,Advanced Solid Tumor,Carcinoma, Non-small-cell Lung,Lung Diseases
PROVIDER: 2308561 | ecrin-mdr-crc |
REPOSITORIES: ECRIN MDR
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Project description:This a model from the article:
Population-based analysis of methadone distribution and metabolism using an
age-dependent physiologically based pharmacokinetic model.
Yang F, Tong X, McCarver DG, Hines RN, Beard DA. J Pharmacokinet Pharmacodyn
2006 Aug;33(4):485-518 16758333
,
Abstract:
Limited pharmacokinetic (PK) and pharmacodynamic (PD) data are available to use
in methadone dosing recommendations in pediatric patients for either opioid
abstinence or analgesia. Considering the extreme inter-individual variability of
absorption and metabolism of methadone, population-based PK would be useful to
provide insight into the relationship between dose, blood concentrations, and
clinical effects of methadone. To address this need, an age-dependent
physiologically based pharmacokinetic (PBPK) model has been constructed to
systematically study methadone metabolism and PK. The model will facilitate the
design of cost-effective studies that will evaluate methadone PK and PD
relationships, and may be useful to guide methadone dosing in children. The PBPK
model, which includes whole-body multi-organ distribution, plasma protein
binding, metabolism, and clearance, is parameterized based on a database of
pediatric PK parameters and data collected from clinical experiments. The model
is further tailored and verified based on PK data from individual adults, then
scaled appropriately to apply to children aged 0-24 months. Based on measured
variability in CYP3A enzyme expression levels and plasma orosomucoid (ORM2)
concentrations, a Monte-Carlo-based simulation of methadone kinetics in a
pediatric population was performed. The simulation predicts extreme variability
in plasma concentrations and clearance kinetics for methadone in the pediatric
population, based on standard dosing protocols. In addition, it is shown that
when doses are designed for individuals based on prior protein expression
information, inter-individual variability in methadone kinetics may be greatly
reduced.
This model was taken from the CellML repository
and automatically converted to SBML.
The original model was:
Yang F, Tong X, McCarver DG, Hines RN, Beard DA. (2006) - version=1.0
The original CellML model was created by:
Catherine Lloyd
c.lloyd@auckland.ac.nz
The University of Auckland
This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team.
To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication
for more information.
In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not..
To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
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This model is described in the article:
Systems pharmacology models
can be used to understand complex
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Demin O, Karelina T, Svetlichniy D,
Metelkin E, Speshilov G, Demin O Jr, Fairman D, van der Graaf PH,
Agoram BM.
CPT Pharmacometrics Syst Pharmacol
2013; 2: e74
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modulation.CPT: Pharmacometrics & Systems Pharmacology
(2013) 2, e74; doi:10.1038/psp.2013.49; advance online
publication 11 September 2013.
This model is hosted on
BioModels Database
and identified by:
BIOMD0000000490.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
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