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BIOMD0000000234 - Tham2008 - PDmodel, Tumour shrinkage by gemcitabine and carboplatin

 

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Reference Publication
Publication ID: 18594002
Tham LS, Wang L, Soo RA, Lee SC, Lee HS, Yong WP, Goh BC, Holford NH.
A pharmacodynamic model for the time course of tumor shrinkage by gemcitabine + carboplatin in non-small cell lung cancer patients.
Clin. Cancer Res. 2008 Jul; 14(13): 4213-4218
Department of Hematology-Oncology, National University Hospital, Singapore. Tham_lai_san@lilly.com  [more]
Model
Original Model: CellML logo
Submitter: Nick Holford
Submission ID: MODEL0911120001
Submission Date: 15 Nov 2009 18:46:45 UTC
Last Modification Date: 17 Mar 2015 11:24:15 UTC
Creation Date: 16 Nov 2009 12:37:34 UTC
Encoders:  Vijayalakshmi Chelliah
   Lai-San Tham
   Geoffrey Nunns
set #1
bqbiol:hasProperty ICD C34
OMIM LUNG CANCER
Human Disease Ontology lung cancer
set #2
bqbiol:isVersionOf Gene Ontology defense response to tumor cell
set #3
bqbiol:hasTaxon Taxonomy Homo sapiens
Notes
Tham2008 - PDmodel, Tumour shrinkage by gemcitabine and carboplatin

This model is described in the article:

Tham LS, Wang L, Soo RA, Lee SC, Lee HS, Yong WP, Goh BC, Holford NH.
Clin. Cancer Res. 2008 Jul; 14(13): 4213-4218

Abstract:

PURPOSE: This tumor response pharmacodynamic model aims to describe primary lesion shrinkage in non-small cell lung cancer over time and determine if concentration-based exposure metrics for gemcitabine or that of its metabolites, 2',2'-difluorodeoxyuridine or gemcitabine triphosphate, are better than gemcitabine dose for prediction of individual response. EXPERIMENTAL DESIGN: Gemcitabine was given thrice weekly on days 1 and 8 in combination with carboplatin, which was given only on day 1 of every cycle. Gemcitabine amount in the body and area under the concentration-time curves of plasma gemcitabine, 2',2'-difluorodeoxyuridine, and intracellular gemcitabine triphosphate in white cells were compared to determine which best describes tumor shrinkage over time. Tumor growth kinetics were described using a Gompertz-like model. RESULTS: The apparent half-life for the effect of gemcitabine was 7.67 weeks. The tumor turnover time constant was 21.8 week.cm. Baseline tumor size and gemcitabine amount in the body to attain 50% of tumor shrinkage were estimated to be 6.66 cm and 10,600 mg. There was no evidence of relapse during treatment. CONCLUSIONS: Concentration-based exposure metrics for gemcitabine and its metabolites were no better than gemcitabine amount in predicting tumor shrinkage in primary lung cancer lesions. Gemcitabine dose-based models did marginally better than treatment-based models that ignored doses of drug administered to patients. Modeling tumor shrinkage in primary lesions can be used to quantify individual sensitivity and response to antitumor effects of anticancer drugs.

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.

Model
Publication ID: 18594002 Submission Date: 15 Nov 2009 18:46:45 UTC Last Modification Date: 17 Mar 2015 11:24:15 UTC Creation Date: 16 Nov 2009 12:37:34 UTC
Mathematical expressions
Rules
Rate Rule (variable: Ce) Rate Rule (variable: Size) Assignment Rule (variable: Exposure) Assignment Rule (variable: rem_time)
Assignment Rule (variable: Keq) Assignment Rule (variable: Effect) Assignment Rule (variable: RateIn) Assignment Rule (variable: Kover)
Physical entities
Compartments Species
COMpartment Ce    
Global parameters
rem_time Exposure Size Effect
Dose Dose_Int1 Dose_Int2 Dose_Length
Cycle_Int N_Cycle conversion_factor AE50
Keq Teq Size_0 RateIn
T_Turnover Kover    
Reactions (0)
Rules (8)
 
 Rate Rule (name: Ce) d [ Ce] / d t= Exposure/1-Ce*Keq
 
 Rate Rule (name: Size) d [ Size] / d t= (RateIn*Effect-Kover*Size)*Size
 
 Assignment Rule (name: Exposure) Exposure = piecewise(Dose, (time < Cycle_Int*N_Cycle) && (Dose_Int1 < rem_time) && (rem_time < Dose_Length), Dose, (time < Cycle_Int*N_Cycle) && (Dose_Int2 < rem_time) && (rem_time < Dose_Int2+Dose_Length), 0)
 
 Assignment Rule (name: rem_time) rem_time = (time*conversion_factor-floor(time*conversion_factor/(Cycle_Int*conversion_factor))*Cycle_Int*conversion_factor)/conversion_factor
 
 Assignment Rule (name: Keq) Keq = log(2)/Teq
 
 Assignment Rule (name: Effect) Effect = 1-Ce/(AE50+Ce)
 
 Assignment Rule (name: RateIn) RateIn = Size_0*Kover
 
 Assignment Rule (name: Kover) Kover = 1/T_Turnover
 
   Spatial dimensions: 3.0  Compartment size: 1.0
 
 Ce
Compartment: COMpartment
Initial concentration: 0.0
 
Global Parameters (18)
 
   rem_time
Value: NaN   (Units: week)
 
   Exposure
Value: NaN   (Units: mg)
 
   Size
Value: 6.66   (Units: cm)
 
   Effect
Value: NaN   (Units: dimensionless)
 
   Dose
Value: 5203.84   (Units: mg)
Constant
 
   Dose_Int1
Constant
 
   Dose_Int2
Value: 1.0   (Units: week)
Constant
 
   Dose_Length
Value: 0.44359   (Units: week)
Constant
 
   Cycle_Int
Value: 3.0   (Units: week)
Constant
 
   N_Cycle
Value: 6.0   (Units: dimensionless)
Constant
 
   conversion_factor
Value: 604800.0   (Units: sec_per_week)
Constant
 
   AE50
Value: 10600.0   (Units: mg)
Constant
 
   Keq
Value: NaN   (Units: per_week)
 
   Teq
Value: 7.67   (Units: week)
Constant
 
   Size_0
Value: 6.66   (Units: cm)
Constant
 
   RateIn
Value: NaN   (Units: per_week)
 
   T_Turnover
Value: 21.8   (Units: cm_week)
Constant
 
   Kover
Value: NaN   (Units: per_cm_per_week)
 
Representative curation result(s)
Representative curation result(s) of BIOMD0000000234

Curator's comment: (updated: 23 Nov 2009 15:49:57 GMT)

The model reproduces figure 1 of the reference publication. The simulation was done using SBML odeSolver.

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