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ASL_Prot

ASL_c > ASL_b

ASLoOH_Prot

ASLoOH_c > ASLoOH_b

ASLpOH_Prot

ASLpOH_c > ASLpOH_b

AS_Prot

AS_c > AS_b

ASoOH_Prot

ASoOH_c > ASoOH_b

ASpOH_Prot

ASpOH_c > ASpOH_b

CR_oOH

ASLoOH_c > ASoOH_c

CR_pOH

ASLpOH_c > ASpOH_c

CYP3A4_ASLoOH

ASL_c > ASLoOH_c

CYP3A4_ASLpOH

ASL_c > ASLpOH_c

CYP3A4_ASoOH

AS_c > ASoOH_c

CYP3A4_ASpOH

AS_c > ASpOH_c

Export_AS

AS_c > AS_m

Export_ASL

ASL_c > ASL_m

Export_ASLoOH

ASLoOH_c > ASLoOH_m

Export_ASLpOH

ASLpOH_c > ASLpOH_m

Export_ASoOH

ASoOH_c > ASoOH_m

Export_ASpOH

ASpOH_c > ASpOH_m

Import_AS

AS_m > AS_c

Import_ASL

ASL_m > ASL_c

Import_ASLoOH

ASLoOH_m > ASLoOH_c

Import_ASLpOH

ASLpOH_m > ASLpOH_c

Import_ASoOH

ASoOH_m > ASoOH_c

Import_ASpOH

ASpOH_m > ASpOH_c

R_ASASL_c

ASL_c > AS_c

R_ASASL_m

ASL_m > AS_m

R_oOH_m

ASLoOH_m > ASoOH_m

R_pOH_m

ASLpOH_m > ASpOH_m

UGT1A3_AS

AS_c > ASL_c

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Fixed species

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Constraints

Note that constraints are not enforced in simulations. It remains the responsibility of the user to verify that simulation results satisfy these constraints.


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A systems biology approach to dynamic modeling and inter-subject variability of statin pharmacokinetics in human hepatocytes.

  • Joachim Bucher
  • Stephan Riedmaier
  • Anke Schnabel
  • Katrin Marcus
  • Gabriele Vacun
  • Thomas S Weiss
  • Wolfgang E Thasler
  • Andreas K Nüssler
  • Ulrich M Zanger
  • Matthias Reuss
BMC Syst Biol 2011; 5 : 66
Abstract
BACKGROUND: The individual character of pharmacokinetics is of great importance in the risk assessment of new drug leads in pharmacological research. Amongst others, it is severely influenced by the properties and inter-individual variability of the enzymes and transporters of the drug detoxification system of the liver. Predicting individual drug biotransformation capacity requires quantitative and detailed models.
RESULTS: In this contribution we present the de novo deterministic modeling of atorvastatin biotransformation based on comprehensive published knowledge on involved metabolic and transport pathways as well as physicochemical properties. The model was evaluated on primary human hepatocytes and parameter identifiability analysis was performed under multiple experimental constraints. Dynamic simulations of atorvastatin biotransformation considering the inter-individual variability of the two major involved enzymes CYP3A4 and UGT1A3 based on quantitative protein expression data in a large human liver bank (n = 150) highlighted the variability in the individual biotransformation profiles and therefore also points to the individuality of pharmacokinetics.
CONCLUSIONS: A dynamic model for the biotransformation of atorvastatin has been developed using quantitative metabolite measurements in primary human hepatocytes. The model comprises kinetics for transport processes and metabolic enzymes as well as population liver expression data allowing us to assess the impact of inter-individual variability of concentrations of key proteins. Application of computational tools for parameter sensitivity analysis enabled us to considerably improve the validity of the model and to create a consistent framework for precise computer-aided simulations in toxicology.
The SBML for this model was obtained from the BioModels database (BioModels ID: BIOMD0000000328) Biomodels notes: Time courses as in figure 2 of the publication. Integration was performed using Copasi 4.6.33. JWS Online curation: This model was curated by reproducing the figures as described in the BioModels Notes. No additional changes were made.